chapter 1, version a - qut...september 2014, the santarém school of management and technology,...

INVESTIGATING THE ROLE OF

KNOWLEDGE MANAGEMENT AT VARIOUS

LEVELS OF PROJECT MANAGEMENT

OFFICE

SHAHRAM SOKHANVAR

MSc of Socio-Economic Systems Engineering (IRPD-Iran)

BSc of Economics (Shahid Beheshty University-Iran)

Certified Program and Portfolio Management (Microsoft-USA)

Project Management Professional (PMI- USA)

Microsoft Certified Technologies (Microsoft-USA)

Submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

Science and Engineering Faculty

Queensland University of Technology

2015

Investigating the Role of Knowledge Management at Various levels of Project Management Office i

ii Investigating the Role of Knowledge Management at Various levels of Project Management Office

To my beloved Mum, Akram

My dad, my Hero, who I sadly lost

My lovely family members, and

Without whom none of success would be possible.

Investigating the Role of Knowledge Management at Various levels of Project Management Office iii

iv Investigating the Role of Knowledge Management at Various levels of Project Management Office

KEYWORDS

Investigating the Role of Knowledge Management at Various levels of Project Management Office v

LIST OF PUBLICATION AND PAPERS

1) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), The Required

Types of Project Knowledge in Various Maturity Levels of Project Management

Office, The Journal of Project Management, Status : Submitted

2) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), The Challenges of

Project Management Office from Knowledge Management Perspective, The

International Journal of Project Management, Status : Submitted

3) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), Management of

Project Knowledge in a Project-based Organisation: A Theoretical Framework, The

2014 PMI® Research and Education Conference, 27th -29th July 2014, Portland

Marriott Waterfront, Portland, Oregon, USA.


Project Knowledge in a Project-based Organisation: a Case Study of Mining

Industry, The 2014 International Conference Knowledge Engineering- IKE14, 21st -

24th July 2014, Monte Carlo Resort, Las Vegas, Nevada, USA.

5) Shahram Sokhanvar, Bambang Trigunarsyah, Prasad Yarlagadda (2014), Project

Knowledge Management in PMOs, Book Chapter, Cambridge Scholar Publishing,

under publishing process.


Project Knowledge in a Project-based Organisation: a Case Study of Research

Enterprise, 15th European Conference on Knowledge Management, 4th -5th

September 2014, The Santarém School of Management and Technology, Santarém,

Portugal.

7) Shahram Sokhanvar, Judy Matthews, Prasad Yarlagadda (2014), The importance of

Knowledge Management Processes in a Project-based organization: a Case Study of

Research Enterprise, 12th Global Congress on Manufacturing And Management-

GCMM, 8th -10th December-2014, School of Mechanical and Building Sciences, VIT

University, in Association with Queensland University Of Technology, Tamil Nadu,

India.

8) Shahram Sokhanvar, Bambang Trigunarsyah, Prasad Yarlagadda (2011), The role of

knowledge in the project management office, 25th International Project Management

vi Investigating the Role of Knowledge Management at Various levels of Project Management Office

Association (IPMA) Proceeding Conference, 9th -13th October 2011, Brisbane

Convention and Exhibition Centre, Brisbane, QLD, Australia.

ABSTRACT

Organisations undertake projects to achieve diverse objectives such as operational efficiency,

technological enhancement, customer satisfaction, service improvement, and organisational

development. Project management (PM) is the application of knowledge, skills, tools, and

techniques to meet project objectives. Project management practices are essential to both ensure

the efficiency and effectiveness of projects, and also achieve quality outcomes. In addition,

project Knowledge Management (KM) is an important factor in improving the quality of a

project, and increasing its success rate. In other words, knowledge management practices not

only increase the quality of project outputs, but also, they resolve some of project management

challenges such as loss of knowledge and the need for rework.

Larger organisations often establish a Project Management Office or PMO, an organisational

department or unit, to both develop project management practices, and also oversee as well as

control organisational projects. The Project Management Maturity Model, or PMMM, addresses

the development of the project management office, from immature to mature levels, through the

recommendation of numbers of practices, and criteria in the various levels. Theoretically, the

project management office is responsible for providing and maintaining knowledge

management practices. Hence, project management maturity models should address the

development of knowledge management within the project management office. In other words,

the PM maturity models should guide how a project management office could be improved

from a knowledge management perspective. However, little research has been carried out to

indicate the relationship between a Project Management Maturity Model and Knowledge

Management. In other words, the absence of knowledge management practices in the current

PM maturity model is obvious in the existing literature.

This study aims to investigate Knowledge Management practices in the current Project

Management Maturity Models through: A) analysing the role of knowledge management

practices in various maturity levels of the PMO, B) exploring the contribution(s) of the PMO for

managing project knowledge, and C) developing a framework to address knowledge

management practices in various maturity levels of the PMO. In order to meet the research

objectives, three research questions have been defined: 1) To what extent are knowledge

management processes and practices employed in the PMOs, 2) How do knowledge

management practices contribute to maturity level of PMO, and 3) How can knowledge be

integrated in the PM Maturity Model. The ultimate objective of this research is to develop a

Investigating the Role of Knowledge Management at Various levels of Project Management Office vii

framework to address four knowledge management processes, i.e. capturing; creation;

transferring; and reusing, in five maturity levels of the Project Management Office.

An extensive literature review was undertaken to understand the current debates regarding

project management and its related methodology, project management office and project

management PM maturity models, and knowledge management in functional and project-based

organisations. This endeavour resulted in the development of the preliminary research

framework to determine the scope of the study. This developed framework comprises three

major elements: 1) knowledge management processes, sub processes and practices in the

project-based environments, 2) a project management maturity model to assist the development

of project management office, 3) a knowledge management maturity model to address the

development of knowledge management in the project management office.

Due to the exploratory and inductive nature of this research, a qualitative approach and

multiple case study methods were adopted. Cases were chosen on the basis of theoretical

sampling of large enterprises with a project management office in their structure and three

distinct organisations were chosen as the research case studies. Data collection using research

questions, derived from the proposed research framework, was carried out through interviews

with senior managers, project managers, and project and PMO staff. Further data from

workplace observations and document analysis were gathered. All data were analysed to both

examine the research framework, and develop number of emerging propositions and

recommendations. A range of analytical techniques, such as grounded theory and pattern

matching, were employed to work with the collected data, alongside the Nvivo for data

management.

The research findings concluded that there is a significant relation between the maturity level

of the project management office, and the utilised knowledge management practices. This

means that a project management office with higher maturity level has more effective project

knowledge management. In addition, knowledge capturing is the most important knowledge

management process, while knowledge reusing is the least important knowledge management

process in various maturity levels of the project management office. This means that the project

management office’s first priority is to capture project knowledge, then knowledge creation,

transferring, and finally reusing. For instance, the research findings revealed that for developing

knowledge capturing in a project management office with first level of maturity, two basic sub-

processes of knowledge storing and classification will be considered through addressing some

knowledge management practices, such as document management systems and databases.

Furthermore, the research findings revealed that the type of project management office is

another factor in determining the priority of knowledge management development. For instance,

in a PMO as the centre of excellence, knowledge transferring is the second most important KM

viii Investigating the Role of Knowledge Management at Various levels of Project Management Office

process, while in a practical PMO, knowledge creation is prioritised before knowledge

transferring. In addition, according to the current literature, only a knowledge capturing process

should be employed in the closing phase, however, the research findings have explored some

challenges in this regard. In other words, it was revealed that in the closing phase, some

knowledge transferring practices are used in PMO with higher maturity levels. So it could be

proposed that in a PMO with a higher maturity level, knowledge transferring practices should be

employed, accordingly.

Also, the research findings explored the level of maturity impacts on types of knowledge

management challenges. In a PMO with low maturity level, the majority of challenges related to

the existing knowledge management systems and applications, while in a PMO with higher

maturity level, the PMO is faced with more advanced challenges, such as absence of knowledge

management practices for knowledge reusing and transferring, and integration of the existing

applications with knowledge management practices.

This research contributes to literature in project management, specifically the Project

Management Office, through integrating Knowledge Management practices in Project

Management Maturity models. The developed framework addresses the recognised gap by

recommending appropriate knowledge management processes, and practices in various maturity

levels of the Project Management Office. In addition, the research outcomes propose numbers

of criteria to assess the maturity levels of the Project Management Office, from a knowledge

management point of view. This study is the first attempt to discuss the maturity of the Project

Management Office from a knowledge management perspective, and it develops a new direction

in the literature of Project Management Maturity Models.

Investigating the Role of Knowledge Management at Various levels of Project Management Office ix

TABLE OF CONTENTS

Keywords ............................................................................................................................................... iv List of Publication and Papers ................................................................................................................ v Abstract .................................................................................................................................................. vi Table of Contents ................................................................................................................................... ix List of Figures ....................................................................................................................................... xiv List of Tables ....................................................................................................................................... xvii List of Abbreviations ............................................................................................................................. xx Statement of Original Authorship ......................................................................................................... xxi Acknowledgements .............................................................................................................................. xxii

INTRODUCTION .................................................................................................. 1 CHAPTER 1

Research background ................................................................................................................... 1 1.1

Problem statement ....................................................................................................................... 3 1.2

Research Aim and Objective ....................................................................................................... 4 1.3

Research questions ...................................................................................................................... 4 1.4

Research approach ....................................................................................................................... 4 1.5

Thesis structure ............................................................................................................................ 5 1.6

LITERATURE REVIEW ....................................................................................... 7 CHAPTER 2

Introduction ................................................................................................................................. 7 2.1

The notion of knowledge and knowledge management............................................................... 7 2.2

Knowledge management frameworks .............................................................................. 8 2.2.1

The evolution of Project Management....................................................................................... 11 2.3

Project and Project Management .................................................................................... 11 2.3.1

Project In Controlled Environment (PRINCE2) ............................................................. 12 2.3.2

Project Management Body of Knowledge (PMBOK) .................................................... 14 2.3.3

The Project Management Office (PMO) ........................................................................ 15 2.3.4

Taxonomies of knowledge ............................................................................................. 18 2.3.5

The Project Management Maturity Models .................................................................... 20 2.3.6

Conclusion ...................................................................................................................... 22 2.3.7

Knowledge management in project-based organisations ........................................................... 23 2.4

Type of Knowledge and KM in Project-based Organisations ........................................ 24 2.4.1

A succinct summary of the existing KM discussion in PBO .......................................... 25 2.4.2

Challenges of knowledge management in project environments ................................... 28 2.4.3

The Research Problem ............................................................................................................... 29 2.5

Problem Definition ......................................................................................................... 29 2.5.1

The Research Aim .......................................................................................................... 31 2.5.2

The Significance of Research ......................................................................................... 32 2.5.3

The Research Questions ................................................................................................. 32 2.5.4

x Investigating the Role of Knowledge Management at Various levels of Project Management Office

The Research Objectives ................................................................................................ 33 2.5.5

The Research limitations ................................................................................................ 33 2.5.6

The Research Purposes ................................................................................................... 34 2.5.7

Conclusion ................................................................................................................................. 34 2.6

THE CONCEPTUAL FRAMEWORK ................................................................ 36 CHAPTER 3

Introduction................................................................................................................................ 36 3.1

Theoretical Background ............................................................................................................. 36 3.2

Knowledge management processes in project environments ......................................... 36 3.2.1

Knowledge management processes in project lifecycle ................................................. 37 3.2.2

Tacit and explicit dimensions of knowledge at project environment ............................. 38 3.2.3

PMBOK and knowledge management ........................................................................... 39 3.2.4

Methods of transforming Tacit to Explicit knowledge ................................................... 40 3.2.5

Project management maturity model .............................................................................. 41 3.2.6

Knowledge Management Maturity Model ...................................................................... 42 3.2.7

Conceptual Framework Premises .............................................................................................. 47 3.3

Types of the required knowledge ................................................................................... 47 3.3.1

Knowledge Management Processes in PMOs ................................................................ 48 3.3.2

Project management maturity model .............................................................................. 51 3.3.3

Knowledge management maturity model ....................................................................... 52 3.3.4

Conclusion ................................................................................................................................. 52 3.4

RESEARCH DESIGN .......................................................................................... 55 CHAPTER 4

Introduction................................................................................................................................ 55 4.1

A snapshot of research flow ....................................................................................................... 55 4.2

Epistemological and philosophical position of this research ..................................................... 55 4.3

Research Method ....................................................................................................................... 57 4.4

The Rationale for selection of case study ....................................................................... 57 4.4.1

Research Design ........................................................................................................................ 58 4.5

The structure of the research design ............................................................................... 59 4.5.1

Research method implementation .............................................................................................. 61 4.6

Selection of Case studies ................................................................................................ 61 4.6.1

Case study protocol ........................................................................................................ 62 4.6.2

Data collection implementation ................................................................................................. 62 4.7

Interviews ....................................................................................................................... 62 4.7.1

Survey questionnaire ...................................................................................................... 64 4.7.2

Direct observation .......................................................................................................... 64 4.7.3

Documentations analysis ................................................................................................ 64 4.7.4

Data analysis .............................................................................................................................. 65 4.8

Grounded theory as inductive theory building method ................................................... 65 4.8.1

Data analysis processes .................................................................................................. 66 4.8.2

Data organisation ............................................................................................................ 66 4.8.3

Data display .................................................................................................................... 67 4.8.4

Investigating the Role of Knowledge Management at Various levels of Project Management Office xi

Complementary analytical techniques ............................................................................ 68 4.8.5

The quality of research .............................................................................................................. 70 4.9

Internal validity .............................................................................................................. 71 4.9.2

External validity ............................................................................................................. 72 4.9.3

Reliability ....................................................................................................................... 72 4.9.4

Conclusion ................................................................................................................................. 72 4.10

CASE STUDY ANALYSIS: SCIENCO ............................................................... 74 CHAPTER 5

Introduction ............................................................................................................................... 74 5.1

SCIENCO’s background ........................................................................................................... 74 5.2

Research Objectives and Questions ........................................................................................... 75 5.3

Data collection procedures ........................................................................................................ 76 5.4

The data collection schedule .......................................................................................... 76 5.4.1

The data collection methods ........................................................................................... 77 5.4.2

The data analysis ....................................................................................................................... 78 5.5

The level of maturity for SCIENCO’s Project Management Office............................... 78 5.5.1

Knowledge management practices and processes in SCIENCO .................................... 95 5.5.2

Discussion and Implications .................................................................................................... 115 5.6

Knowledge capturing’s sub processes and practices in SCIENCO .............................. 115 5.6.1

Knowledge creation’s sub processes and practices in SCIENCO ................................ 117 5.6.2

Knowledge transferring’s sub processes and practices in SCIENCO .......................... 119 5.6.3

Knowledge reusing sub-processes and practices in SCIENCO .................................... 120 5.6.4

Conclusion ............................................................................................................................... 121 5.7

CASE STUDY ANALYSIS: GOVCO ................................................................ 124 CHAPTER 6

Introduction ............................................................................................................................. 124 6.1

GOVCO’s background ............................................................................................................ 124 6.2

Data collection procedures ...................................................................................................... 125 6.3

The data collection methods .................................................................................................... 126 6.4

The data analysis ..................................................................................................................... 126 6.5

The maturity level of GOVCO’s Project Management Office ..................................... 127 6.5.1

Knowledge management processes and practices in GOVCO ..................................... 142 6.5.2

The importance of knowledge management processes in GOVCO ............................. 157 6.5.3


Knowledge capturing’s sub processes and practices in GOVCO ................................. 162 6.6.1

Knowledge transferring’s sub processes and practices in GOVCO ............................. 164 6.6.2

Knowledge creation’s sub processes and practices in GOVCO ................................... 165 6.6.3

Knowledge reusing’s sub processes and practices in GOVCO .................................... 167 6.6.4

Conclusion ............................................................................................................................... 168 6.7

CASE STUDY ANALYSIS: MINCO ................................................................. 171 CHAPTER 7

Introduction ............................................................................................................................. 171 7.1

MINCO’s background ............................................................................................................. 171 7.2

Data collection procedures ...................................................................................................... 172 7.3

xii Investigating the Role of Knowledge Management at Various levels of Project Management Office

Data analysis ............................................................................................................................ 173 7.4

MINCO’s PMO maturity level ..................................................................................... 174 7.4.1

Knowledge management processes and practices in MINCO ...................................... 193 7.4.2

The importance of knowledge management processes in MINCO .............................. 207 7.4.3


Knowledge transferring’s sub-processes and practices in MINCO .............................. 211 7.5.1

Knowledge reusing’s sub processes and practices in MINCO ..................................... 212 7.5.2

Knowledge capturing’s sub processes and practices in MINCO .................................. 213 7.5.3

Knowledge creation’s sub processes and practices in MINCO .................................... 215 7.5.4

Conclusion ............................................................................................................................... 217 7.6

DISCUSSION AND RESULT ............................................................................ 220 CHAPTER 8

Introduction.............................................................................................................................. 220 8.1

The analysis procedure ............................................................................................................ 220 8.2

An overview of case studies .................................................................................................... 221 8.3

Organisational structure ........................................................................................................... 222 8.4

Project management maturity level in three case studies ......................................................... 226 8.5

Knowledge management practices in various levels of PMO .................................................. 228 8.6

The Challenges of PMO from knowledge management perspective ............................ 228 8.6.1

The required types of knowledge in Project Management Offices ............................... 230 8.6.2

KM processes and KM practices at various levels of maturity ................................................ 233 8.7

Knowledge Capturing ................................................................................................... 233 8.7.1

Knowledge creation ...................................................................................................... 236 8.7.2

Knowledge Transferring ............................................................................................... 238 8.7.3

Knowledge Reusing ...................................................................................................... 241 8.7.4

PMO’s contributions to knowledge management .................................................................... 242 8.8

The importance of KM processes in various levels of PMO ........................................ 242 8.8.1

How PMO can contribute for managing the project knowledge .................................. 244 8.8.2

Model Development ................................................................................................................ 259 8.9

Integration of KM practices at various level of maturity .............................................. 259 8.9.1

Conclusion ............................................................................................................................... 269 8.10

CONCLUSIONS ................................................................................................. 273 CHAPTER 9

Overview ................................................................................................................................. 273 9.1

Knowledge Management Challenges in the PMO ................................................................... 274 9.2

The required types of knowledge in various levels of maturity ............................................... 275 9.3

Utilisation of knowledge management practices in PMO ........................................................ 276 9.4

The importance of knowledge management processes in PMO .............................................. 277 9.5

PMO’s contributions to knowledge management .................................................................... 277 9.6

Knowledge management processes in five maturity levels ..................................................... 278 9.7

Research Contributions ............................................................................................................ 279 9.8

General Contributions................................................................................................... 279 9.8.1

Theoretical Contributions ............................................................................................. 280 9.8.2

Investigating the Role of Knowledge Management at Various levels of Project Management Office xiii

Research limitations ................................................................................................................ 280 9.9

Future research ........................................................................................................................ 281 9.10

BIBLIOGRAPHY ....................................................................................................................... 284 APPENDICES ............................................................................................................................. 294

Appendix A - The Case Study Protocol................................................................................... 294 Appendix B - The research questions and Survey-questionnaire ............................................ 298 Appendix C - Ethics Approval ................................................................................................ 302 Appendix D - Samples of interview transcription in SCIENCO ............................................. 304

xiv Investigating the Role of Knowledge Management at Various levels of Project Management Office

LIST OF FIGURES

Figure 2-1 Modes of Knowledge Creation (Nonaka and Takeuchi 1995) .............................................. 8

Figure 2-2 PRINCE2's project lifecycle(adapted from (Bentley 2009)) ............................................... 13

Figure 2-3 PRINCE2’s components (adapted from (Bentley 2009)) .................................................... 13

Figure 2-4 OPM3 framework (Project Management Institute 2008b) .................................................. 21

Figure 2-5 The development of PM and KM (developed for this research) ......................................... 30

Figure 2-6 The significance of this Research (developed for this research) ......................................... 32

Figure 3-1 KM process at project-based organisation (Owen, et al. 2004) ........................................... 37

Figure 3-2 Kerzners’ Maturity Level (2005) ......................................................................................... 41

Figure 3-3 The research KM processes model (developed for this study) ............................................ 48

Figure 3-4 KM process and practices model (developed for this research) .......................................... 49

Figure 4-1 Research methods and data inquiry techniques (developed for this research)..................... 57

Figure 4-2 Research Design (developed for this research) ................................................................... 60

Figure 4-3 Interview and survey questions tree (developed for this research) ...................................... 63

Figure 4-4 Data analysis processes (developed for this research) ......................................................... 66

Figure 4-5 Sample of Coding (developed for this research) ................................................................. 69

Figure 5-1 A snapshot of SCIENCO's structure (from SCIENCO’s organisational chart) ................... 75

Figure 5-2 PMO’s ML from PMBOK's knowledge areas perceptive (developed for this study) ......... 80

Figure 5-3 SCIENCO’s Maturity level from PLC perceptive (developed for this research) ................ 81

Figure 5-4 PM Methodologies in SCIENCO (developed for this study) ............................................. 84

Figure 5-5 The exsisting KM challenges in SCIENCO’s PMO (developed for this study) .................. 89

Figure 5-6 Types of required knowledge in SCIENCO (developed for this research).......................... 92

Figure 5-7 The required types of knowledge in SCIENCO (developed for this research) .................... 94

Figure 5-8 A snapshot of KM process categories in the Nvivo (developed for this research) .............. 97

Figure 5-9 KM processes at project lifecycle (developed for this research) ......................................... 99

Figure 5-10 Knowledge capturing in SCIENCO’s PMO (developed for this research) ..................... 101

Figure 5-11 Knowledge Creation practices in SCIENCO (developed for this research) .................... 105

Figure 5-12 Knowledge Transferring at project lifecycle (developed for this research) ..................... 108

Figure 5-13 Knowledge reusing in SCIENCO’s PMO (developed for this research) ......................... 110

Figure 5-14 The importance of KM processes in SCIENCO (developed for this research) ............... 113

Figure 5-15 The general ranking of KM processes in SCIENCO (developed for this research) ........ 114

Figure 5-16 The SECI Model at SCIENCO (Nonaka and Teece 2001) .............................................. 118

Investigating the Role of Knowledge Management at Various levels of Project Management Office xv

Figure 6-1 A snapshot of GOVCO’s structure (from GOVCO’s organisational chart) ...................... 125

Figure 6-2 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study) ...... 128

Figure 6-3 The ML of GOVCO’ PMO: project lifecycle (developed for this research) ..................... 129

Figure 6-4 The exsisting KM challenges of GOVCO’s PMO (developed for this study) .................. 138

Figure 6-5 Types of required knowledge in GOVCO (developed for this research) .......................... 140

Figure 6-6 A snapshot of KM process categories in the Nvivo (developed for this research) ............ 143

Figure 6-7 KM processes at project lifecycle: GOVCO (developed for this research) ....................... 145

Figure 6-8 Knowledge Capturing in project lifecycle: GOVCO (developed for this research) .......... 148

Figure 6-9 Knowledge Transferring practices in GOVCO (developed for this research) ................... 151

Figure 6-10 Knowledge Creation in GOVCO (developed for this research) ...................................... 154

Figure 6-11 Knowledge reusing in GOVCO (developed for this research) ....................................... 156

Figure 6-12 Importance of KM process in project lifecycle: GOVCO (developed for this study) ..... 159

Figure 6-13 The general ranking of KM processes in GOVCO (developed for this research) ........... 160

Figure 6-14 The SECI model in GOVCO’s PMO (Nonaka and Teece 2001) .................................... 167

Figure 7-1 Snapshot of MINCO’s structure ((extracted from MINCO’s organisational chart) .......... 171

Figure 7-2 ML of MINCO’s PMO’s from knowledge areas perceptive (developed for this study) ... 175

Figure 7-3 MINCO’s Maturity level from project lifecycle perceptive (developed for this research) 176

Figure 7-4 MINCO's project life cycle (adopted from MINCO’s PM framework) ............................ 179

Figure 7-5 Selection &definition phase (adopted from MINCO’s PM framework) ........................... 180

Figure 7-6 The current KM challenges in MINCO’s PMO (developed for this study) ...................... 187

Figure 7-7 Types of required knowledge at MINCO’s PMO (developed for this research) ............... 191

Figure 7-8 KM processes at project lifecycle in MINCO (developed for this research) ..................... 195

Figure 7-9 Knowledge Capturing in MINCO’s PMO (developed for this research) .......................... 198

Figure 7-10 Knowledge Creation in MINCO (developed for this research) ....................................... 200

Figure 7-11 Knowledge transferring in MINCO (developed for this research) .................................. 204

Figure 7-12 Knowledge reusing at project lifecycle: MINCO (developed for this research) ............. 206

Figure 7-13 The importance of KM processes in MINCO (developed for this research) ................... 208

Figure 7-14 The general ranking of KM processes: MINCO (developed for this research) ............... 209

Figure 7-15 The SECI in MINCO’s PMO (Nonaka and Teece 2001) ................................................ 216

Figure 8-1 PMO level of maturity and project managers authorities (developed for this research) ... 223

Figure 8-2 Maturity of PMOs from project lifecycle perspective (developed for this study) ............. 226

Figure 8-3 Maturity of PMOs from knowledge area perspective (developed for this research) ......... 227

Figure 8-4 Challenges of KM at different maturity levels (developed for this study) ........................ 229

Figure 8-5 Importance of knowledge types in various maturity level (developed for this research) .. 230

xvi Investigating the Role of Knowledge Management at Various levels of Project Management Office

Figure 8-6 Numbers of the coded comments for KM processes (developed for this study) ............... 233

Figure 8-7 Knowledge capturing in various levels of maturity (developed for this study) ................. 234

Figure 8-8 Knowledge creation at various levels of maturity (developed for this study) ................... 237

Figure 8-9 Knowledge transferring at various levels of maturity (developed for this study) .............. 239

Figure 8-10 Knowledge reusing at various levels of maturity (developed for this study) .................. 241

Figure 8-11 Importance of KM processes in project lifecycle: All cases (developed for this study) .. 243

Figure 8-12 Knowledge caprtuing's sub-processes (developed for this study) ................................... 246

Figure 8-13 K. capturing’s sub processes in various level of maturity (developed for this study) ..... 247

Figure 8-14 Knowledge creation's sub-processes in three case studies( developed for this study) ..... 249

Figure 8-15 K. creation’s sub processes in various levels of maturity (developed for this study) ...... 251

Figure 8-16 Knowledge transferring's sub-processes case studies (developed for this study) ............ 253

Figure 8-17 K. transferring’s sub-processes in various levels of maturity (developed for this study) 254

Figure 8-18 Knowledge reusing’s sub-processes in three case studies (developed for this study) ..... 256

Figure 8-19 K. reusing’s sub processes in various level of maturity (developed for this study) ......... 257

Figure 8-20 KM sub processes in the first level of maturity (developed for this study) ..................... 261

Figure 8-21 KM sub processes in the second level of maturity (developed for this study) ................ 264

Figure 8-22 KM sub processes in the third level of maturity (developed for this study) .................... 267

Figure 8-23 KM processes in the fourth and fifith level of maturity (developed for this study) ......... 269

Figure 8-24 Summary of the research findings (developed for this study) ......................................... 270

Figure 8-25 KM challenges in PMOs (developed for this research) ................................................... 271

Investigating the Role of Knowledge Management at Various levels of Project Management Office xvii

LIST OF TABLES

Table 2-1 Knowledge perspectives and their definitions (Alavi and Leidner 2001) ............................... 9

Table 2-2 KM processes frameworks (developed for this study) ........................................................... 9

Table 2-3 Knowledge areas and Phases in PMBOK (developed for this research) .............................. 14

Table 2-4 Characteristics of tacit and explicit Knowledge (developed for this research) ..................... 18

Table 2-5 The comparison of PMMMs (developed for this study) ....................................................... 22

Table 2-6 Knowledge types in Projects (developed for this research) .................................................. 24

Table 2-7 KM initiatives and barriers in PMO (developed for this research) ....................................... 27

Table 2-8 The benefits of study findings (developed for this research) ................................................ 34

Table 3-1 Project phases and KM Processes Adapted from (Owen and Burstein 2005) ...................... 38

Table 3-2 KM objects of PMBOK (Reich and Wee 2006) ................................................................... 39

Table 3-3 Knowledge types in project context (Srikantaiah, et al. 2010) ............................................. 40

Table 3-4 KM maturity model, proposed by Feng (F-KMMM) (Feng 2006) ....................................... 44

Table 3-5 General KMMM (Kankanhalli and Pee 2009) ..................................................................... 47

Table 3-6 Types of knowledge in research framework (developed for this research) .......................... 48

Table 3-7 Knwoledge Creation pratices in project enviroments (developed for this research) ............ 49

Table 3-8 Knowledge capturing practices in project environment (developed for this research) ......... 50

Table 3-9 Knowledge transferring pratcices in project enviroment (developed for this research) ....... 50

Table 3-10 Knowledge reusing practices in project environment (developed for this research) .......... 51

Table 3-11 The customised KM Maturity Model or R-KMMM (developed for this research) ............ 53

Table 4-1 Different methods with their relevant situation (Yin , 2009, p. 8) ........................................ 58

Table 4-2 The proposed quality tactics (Yin 2009) .............................................................................. 71

Table 5-1 The Research Questions (developed for this research) ......................................................... 76

Table 5-2 Interviewees’ list and schedule in SCIENCO (developed for this research) ........................ 77

Table 5-3 The Data collection methods (developed for this research) .................................................. 78

Table 5-4 PMO’ ML from PM knowledge perspective (developed for this research) .......................... 79

Table 5-5 PMO’ ML from project lifecycle perspective (developed for this research) ........................ 80

Table 5-6 Participants’ quotes in SCIENCO’s PMO (developed for this research) ............................. 82

Table 5-7 The current systems and tools in SCIENCO’s PMO (developed for this research) ............. 85

Table 5-8 Example of using Axial &Open coding in SCIENCO (developed for this study) ................ 88

Table 5-9 Types of required knowledge in SCIENCO (developed for this research) ........................... 93

Table 5-10 KM processes and PLC (adopted from Owen and Burstein (2005)) .................................. 95

xviii Investigating the Role of Knowledge Management at Various levels of Project Management Office

Table 5-11 KM processes and their associated KM practices (developed for this research) ................ 96

Table 5-12 The usage of KM processes in SCIENCO (developed for this research) ........................... 98

Table 5-13 Knowledge capturing’s categories and practices (developed for this research)................ 102

Table 5-14 Knowledge creation’s categories and pratices (developed for this research).................... 104

Table 5-15 Knowledge transferring categories and pratices (developed for this research) ................. 107

Table 5-16 Knowledge Resing in SCIENCO’s PMO (developed for this research) ........................... 109

Table 5-17 Knowledge capturing sub-processes in SCIENCO (developed for this research) ............ 116

Table 5-18 Knowledge creation sub procesess in SCIENCO (developed for this research) ............... 117

Table 5-19 Knowledge transferring sub processes in SCIENCO (developed for this research) ......... 119

Table 5-20 Knowledge reusing sub-processes in SCIENCO (developed for this research)................ 120

Table 6-1 Interviewees’ list and schedule in GOVCO (developed for this research) ......................... 126

Table 6-2 Data collection methods (developed for this research) ....................................................... 126

Table 6-3 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study) ....... 127

Table 6-4 The ML of GOVCO’ PMO: project lifecycle (developed for this research) ...................... 128

Table 6-5 Participants’ quotes in regards to GOVCO’s PMO matuirty (developed for this research) 130

Table 6-6 The current system and tools in GOVCO’s PMO (developed for this research) ................ 133

Table 6-7 Example of using Axial &Open coding in GOVCO’s PMO (developed for this study) .... 137

Table 6-8 Types of knowledge and their rank at GOVCO (developed for this research) ................... 141


Table 6-10 The usage of KM processes in GOVCO (developed for this research) ............................ 144

Table 6-11 Knowledge capturing’s practices: GOVCO (developed for this research) ....................... 147

Table 6-12 Knowledge Transferring categories and pratices: GOVCO (developed for this research)149

Table 6-13 Knowledge creation’s categories in GOVCO (developed for this research) .................... 152

Table 6-14 Knowledge Reusing in GOVCO (developed for this research) ........................................ 155

Table 6-15 Knowledge capturing sub-processes in GOVCO (developed for this research) ............... 162

Table 6-16 Knowledge transferring sub processes in GOVCO (developed for this research) ............ 164

Table 6-17 Knowledge creation sub procesess in GOVCO (developed for this research) .................. 165

Table 6-18 Knowledge reusing sub-processes in GOVCO (developed for this research) .................. 167

Table 7-1 Interviewees’ list and schedule in MINCO (developed for this research) .......................... 173

Table 7-2 The Data collection methods (developed for this research) ................................................ 173

Table 7-3 PMO’ ML from PM knowledge perspective (developed for this research) ........................ 174

Table 7-4 MINCO’s PMO ML from project lifecycle perspective (developed for this research)....... 175

Table 7-5 Participants’ quotes in regards to MINCO’s PMO matuirty (developed for this research) 178

Table 7-6 The current systems and tools in MINCO’s PMO (developed for this research) ............... 181

Investigating the Role of Knowledge Management at Various levels of Project Management Office xix

Table 7-7 Example of Axial and Open coding in MINCO’s PMO (developed for this study) ........... 185

Table 7-8 Types of required knowledge in MINCO (developed for this research .............................. 192


Table 7-10 The usage of KM processes in MINCO (developed for this research) ............................. 194

Table 7-11 Knowledge capturing categories and practices: MINCO (developed for this research) ... 197

Table 7-12 Knowledge creation categories and pratices: MINCO (developed for this research) ....... 199

Table 7-13 Knowledge transferring pratices in MINCO (developed for this research) ...................... 202

Table 7-14 Knowledge Resing practices in MINCO (developed for this research) ............................ 205

Table 7-15 Knowledge transferring sub processes in MINCO (developed for this research) ............. 211

Table 7-16 Knowledge reusing sub-processes in MINCO (developed for this research) ................... 212

Table 7-17 Knowledge capturing sub-processes in MINCO (developed for this research) ................ 214

Table 7-18 Knowledge creation sub procesess in MINCO (developed for this research) .................. 215

Table 8-1 The research questions (developed for this study) .............................................................. 220

Table 8-2 A snapshot of three case studies (developed for this research) .......................................... 224

Table 8-3 A snapshot of three case stuides (continued ) ..................................................................... 225

Table 8-4 Knowledge capturing's sub-processes in various PMOs (developed for this study) .......... 244

Table 8-5 Knowledge creation’s sub-processes in various PMOs (developed for this study) ............ 248

Table 8-6 Knowledge transferring’s sub-processes in various PMOs (developed for this study) ...... 252

Table 8-7 Knowledge reusing’s sub-processes in various PMOs (developed for this study) ............. 255

xx Investigating the Role of Knowledge Management at Various levels of Project Management Office

LIST OF ABBREVIATIONS

PM

KM

KMS

PMO

PMMM

KMMM

GKM

ML

PBO

PMBOK

PRINCE2

PMI

AHP

OGC

DB

DMS

CoP

MIS

DSS

FMS

FAQ

ES

FIE

Project Management

Knowledge Management

Knowledge Management System

Project Management Office

Project Management Maturity Model

Knowledge Management Maturity Model

General Knowledge Model

Maturity Level

Project-Based Organisation

Project Management Body of Knowledge

Project In Controlled Environment

Project Management Institute

Analytic Hierarchy Process

Office of Government Commerce

Data base

Document Management System

Community of Practice

Management Information System

Decision Support System

File Management System

Frequently Asked Questions

Expert System

Formal and Informal Event

Investigating the Role of Knowledge Management at Various levels of Project Management Office xxi

STATEMENT OF ORIGINAL AUTHORSHIP

The work contained in this thesis has not been previously submitted to meet requirements for

an award at this or any other higher education institution. To the best of my knowledge and

belief, the thesis contains no material previously published or written by another person except

where due reference is made.

Signature: QUT Verified Signature

Date: May 2015

xxii Investigating the Role of Knowledge Management at Various levels of Project Management Office

ACKNOWLEDGEMENTS

I would like to express my deep and sincere appreciation to my principal supervisor,

Professor Prasad Yarlagadda, for his unconditional support, friendly concern, professional

guidance, and encouragement over the past four years. Also I would like to deeply thank my

associate supervisor, Dr Judy Matthews, for her support and constructive guidance during the

course of this research project. In addition, I would like to cordially thank my external

supervisor, Associate Professor Bambang Trigunarsyah, for his friendly support for this

research.

QUT’s research office and SEF’s HDR staff, specifically Ms Elaine Reyes, have been very

helpful during this journey and I would like to appreciate their contribution. Also, I would like

to thank Professor Acram Taji for her kind support and friendly consideration. In addition, I like

to appreciate Ms Diane Kolomeitz’s professional services for proofreading and editing this

thesis.

I also would like to thank all the organisations and individuals who took part in this research,

for their cooperation and being helpful to me in accessing the required information. Due to

confidentiality, I am not able to mention their names, but this PhD would have not been

accomplished without their help and support. Also, I would like to thank my friends in Australia

who have been like family to me during this journey.

Last but certainly not least, I am forever indebted to my lovely parents and beloved family.

Thank you all.

Chapter 1 | INTRODUCTION 1

Chapter 1

INTRODUCTION

RESEARCH BACKGROUND 1.1

Knowledge is an organisational asset that comes from an individual’s mind, belief or values

and it creates value for improving competitive advantages (Drucker 1993; Drucker 2013).

According to Davenport and Prusak (2000) knowledge is "a fluid mix of experiences, values,

contextual information, and expert insights that provides a framework for evaluation and

incorporating new experiences and information." Hence, knowledge entails the subsequent

characteristics: 1) it is in people’s mind so cannot be easily transferred, 2) knowledge is a

judgement based on individual beliefs therefore it can be different from one person to another,

3) it is a vital element for creating new knowledge, 4) knowledge can be lost if it’s not properly

transferred or captured, and 5) it is an important asset for organisations and their competitive

advantages (Alavi and Leidner 2001; Davenport 1997; Davenport 2013). People, technology

and process are three core components of knowledge management in both functional and

project-based organisation (Davenport and Prusak 2000). From a process point of view,

knowledge management is defined as “a systemic and organisationally specified process for

acquiring, organising and communicating both tacit and explicit knowledge of employees so

that other employees may make use of it to be more effective and productive in their work”

(Alavi and Leidner 1999).

Project management is a relatively new approach to improve organisational competitive

advantages (Kerzner 2013). Project is defined as a temporary set of activities to obtain

predetermined objectives (Project Management Institute 2013). Project management is the

application of skill, tools, knowledge, and experience to achieve project objectives (Project

Management Institute 2013). It is generally accepted that the employment of appropriate PM

practices significantly impacts on delivering successful projects (Anbari 2005).

An investigation by the Standish Group (1995) in 1994 revealed that only 16% out of 175

000 Information Technology (IT) projects were successfully completed in the United States,

while 31% failed and the remaining 53% struggled with about 190% overrun costs. According

to Anbari (2005) the rate of unsuccessful project implementation and project failure has been

significantly increased since early 2000. A study by KPMG international claims that the lack of

project management methodology is the major cause of project failure (Whittaker 1999). In

other words, projects will most likely fail or be faced with numbers of issues and challenges, if

appropriate PM practices are not utilised (Anbari 2005; The Standish Group 1995). Due to the

2 Chapter 1 | INTRODUCTION

increasing importance of PM practices, numbers of project management methodologies and

standards have been developed since late 1990, by which organisations could improve their

project performance. The Project Management Body of Knowledge (PMBOK) has been

developed by the Project Management Institute (PMI) in late 1990 (Project Management

Institute 2013). In addition, the Office of Government Commerce (OGC) in the UK has

developed PRINCE2 (PRoject IN Controlled Environment) since early 2000 as another PM

methodology (Office of Government Commerce 2005). Both PMBOK and PRINCE2 are being

revised every four years in order to both improve current practices and introduce new best

practices.

After employing project management practices by organisations, studies show that the

numbers of unsuccessful and failed projects have significantly dropped. For instance, the

Standish Group conducted a similar study in 2002 in the same industry to investigate whether

utilising project management practices impacted project performance or not. The study revealed

that the project success rate has been significantly raised to 34 % (from 16% in 1994) while the

failure rate dropped to 16 % (from 31% in 1994) in which both rates indicate more than 100%

improvement (The Standish Group 2003). In other words, the appropriate employment of

project management practices significantly impact on delivering successful projects (Anbari

2005; The Standish Group 2003).

Management of project knowledge has been recognised as an important factor for project

success (Ajmal, et al. 2010). Due to the importance of knowledge management, many studies

have been conducted since the early 1990s, however, few research studies have discussed

knowledge management processes in project environments (Koskinen 2010; Koskinen and

Pihlanto 2008). Since project teams are disbanded or members leave after project completion,

knowledge management in a project-based environment is not similar to functional organisation

(Kasvi, et al. 2003). The temporary nature of projects imposes numbers of issues such as

“reparative activities”, “leaking of project knowledge”, and “reworks” for projects and project-

based organisations (Ajmal, et al. 2010; Koskinen and Pihlanto 2008; Love, et al. 2003).

A Project Management Office (PMO) is a unit or department within an organisation to

centrally facilitate, manage and control organisational projects through developing and

maintaining suitable processes and practices for PM (Kerzner 2009; Ward and Daniel 2013).

According to Santosus (2003) a PMO has a significant role in improving the rate of project

success, which means that it contributes to dropping the rate of project failure through both

establishing appropriate PM practices and, then, assisting project team members with applying

them (Artto, et al. 2011; Ward and Daniel 2013). In other words, the PMO is a unit within

modern organisations to institutionalise PM practices and processes to improve their


organisational competencies (Dai and Wells 2004; Desouza and Evaristo 2006; Hurt and

Thomas 2009; Müller, et al. 2013).

Project Management Maturity Models (PMMM) have been proposed to address the

development of PMO in organisations through addressing appropriate project management

practices (Andersen and Jessen 2003; Aubry, et al. 2013; Crawford 2012; Yazici 2009). PM

maturity models contribute to the evolvement of PMO from an immature to a mature level

(Kerzner 2005; Kerzner 2013; PRINCE2 Foundation 2008; Project Management Institute

2008b). Despite the usefulness of current PMMMs, there are some challenges yet to be

addressed, which will be discussed in the next section.

PROBLEM STATEMENT 1.2

According to Liu and Yetton (2007), organisations have shown meaningful interest in

establishing and developing PMOs since the early 2000s. By the end of 2003 more than 50 000

US organisations have launched their PMOs and it has been estimated that a considerable

number of companies will establish their PMOs later (Liu and Yetton 2007). It is advisable to

adopt an appropriate PM maturity model to develop a PMO in an organisation (Kerzner 2005;

Project Management Institute 2008b). PM Maturity Models have been developed based upon: 1)

the existing PM methodologies such as PMBOK and PRINCE2, which address PM practices,

and 2) a process management approach that addresses minimum requirements to achieve

various levels of maturity (Kerzner 2005; Kulpa and Johnson 2008). The Organisational Project

Management Maturity Model (OPM3) has been proposed by the PMI to address the

development of PMOs, while OCG has developed a Portfolio, Program, Project Management

Maturity Model (P3M3) for the same reason (PRINCE2 Foundation 2008; Project Management

Institute 2008b). Both OPM3 and P3M3 address the development of a PMO through

progressively implementing and customising PM practices.

Despite the usefulness of current PMMMs, there are some challenges in developing a PMO

such as maturity levels, and type of organisations (Aubry, et al. 2008; Gajic and Riboni 2010).

According to Singh, et al. (2009) there are more than 30 challenges that PMOs deal with during

both their establishment and development stages. This means that the current PMMMs need to

be developed from some aspects to resolve the current challenges.

According to the findings of this study, knowledge management is one of the main

challenges that is yet to be addressed in the current PMMMs. Despite the number of studies that

have been conducted to investigate issues of KM in projects, few studies have considered KM

issues in PMOs. In other words, there is a significant gap in the existing literature to address

knowledge management practices in various maturity levels of PMO. The existing PMMMs

not only do not contribute to assessing the maturity of a PMO from a KM point of view,

4 Chapter 1 | INTRODUCTION

but also they do not address suitable KM processes, procedures or practices for various

maturity levels of a PMO.

With regards to the above mentioned explanation, developing an appropriate framework to

address suitable KM practices at different levels of a PMO, will significantly contribute to both

developing PMMMs from a KM point of view, and also improving the PMOs competencies. In

addition, increasing tendencies among organisations to implement and develop their PMOs,

corroborate the importance of this study, by which some of the challenges of current PMMMs

will be addressed.

RESEARCH AIM AND OBJECTIVE 1.3

The research aim is:

“To investigate KM practices in Project Management Maturity Models”

This research proposes a comprehensive framework to collaborate KM practices in each

level of PMMMs. Moreover, the proposed framework contributes to the existing PMMMs

through both addressing appropriate KM practices for various levels of maturity and assessing

maturity levels of PMO from a KM point of view. In addition, the proposed framework

comprises: 1) appropriate KM practices for each maturity level of PMO, 2) criteria and indices

to assess levels of maturity from a KM perspective, and 3) a suitable roadmap to address the

development of KM in PMOs.

The three following research objectives have been proposed to meet the above mentioned

research aim: 1) to analyse the role of KM practices in various maturity levels of PMO, 2) to

explore the contribution(s) of PMO for managing project knowledge, and 3) to develop a

framework to address KM in various maturity levels of PMO. The achievement of objectives

contributes to develop a theory(s) and/or frameworks to address the recognised research gap.

RESEARCH QUESTIONS 1.4

In order to achieve the research aim and the above-mentioned objectives, three main

questions have been defined as following: 1) to what extent are KM processes and practices

employed in the PMOs, 2) How do KM practices contribute to the maturity level of the PMO,

and 3) How can knowledge be integrated in the PM Maturity Model. The first and second

questions have been answered through case study methods, while the third question was

discussed through both cross-case analysis and developing a comprehensive framework.

RESEARCH APPROACH 1.5

This research is “Exploratory” in nature, and also it is an “Inductive” study since it aims to

propose a theory(s) or hypothesis to address the recognised gap (Gray 2009). Moreover, the

type of the proposed research questions indicate that it is a qualitative research instead of


quantitative one (Creswell 2009; Gray 2009; Yin 2009). Furthermore, a Constructivism

worldview has been identified as the suitable paradigm for this research because: 1) there is no

theory behind this research; 2) it is an exploratory study ; and 3) it has been aimed to develop a

framework and theory to address the recognised gap(Gray 2009; Guba and Lincoln 1994). Case

Study has been chosen as the research methodology, alongside the four data collection methods;

interview, observation, questionnaire-survey and document analysis. Also, Grounded Theory,

together with the other analytical methods, have been utilised as the analysis techniques

(Creswell 2009; Yin 2009).

THESIS STRUCTURE 1.6

In this research, nine subsequent chapters have been provided to present the study outcomes.

Chapter One discusses the research introduction and the need for the management of project

knowledge in PBOs. In addition, the research questions, objectives, aims and designs have been

succinctly presented in this chapter.

Chapter Two presents a comprehensive literature review in three areas: Project

Management, Knowledge Management, and Knowledge Management in a Project Environment.

The research problems, the significance of the research, the research questions and objectives

have been presented in this chapter. At the end, the benefits of the research for various groups

and organisations have been illustrated.

Chapter Three presents the preliminary research framework which has been derived from

the literature. Also it discusses how research questions have been planned to be answered

through employing the proposed framework.

Chapter Four illustrates the research methodology and design. The data collection methods

have been illustrated to explain how data has been gathered and organised. Also, the data

analysis methods have been discussed, accordingly.

Chapters Five to Seven discuss three case studies outcomes, individually. For each case, one

chapter has been assigned to present them thoroughly; the result of each case has been

presented, in a consistent manner to give clear and insightful information about management of

project knowledge in various levels of maturity.

Chapter Eight presents the cross-case analysis through synthesising the findings from case

studies, and discussing the research findings to refine the preliminary research framework,

proposed in Chapter Four.

Chapter Nine discusses the conclusion of this thesis through discussing the findings against

the research question, and also presenting the research contributions, implications, limitations

and significance. At the end of this chapter, recommendations for future research have been

outlined.

7 Chapter 2 | LITERATURE REVIEW

Chapter 2

LITERATURE REVIEW

INTRODUCTION 2.1

This chapter discusses both Knowledge Management (KM) and Project Management

(PM) from different points of view. Management of human knowledge has been

epistemologically investigated since the classical Greek era (Alavi and Leidner 2001; Aubry,

et al. 2011). In contrast, PM has been recently considered as a modern approach to improve

organisational competencies (Jugdev and Thomas 2002; Stretton 1994). Due to the

importance of both KM and PM, in the last twenty years a plethora of studies have focused

on addressing them in both functional and project-based organisation (Brown and Duguid

1998; Nonaka and Takeuchi 1995; Nonaka and Takeuchi 2011; Peltola, et al. 2002; Wiig

1997b).

This chapter aims to critically investigate current discussions, methodologies, theories

and the substantial findings of both KM and PM, in order to formulate the research problem.

To do so, the four following sections have been provided: first, knowledge management and

its associated literature are presented; second, project management and project-based

organisations are discussed; third, the current discussions of KM in project based

environments are explained; and fourth, the recognised gap and research problem are

formulated.

THE NOTION OF KNOWLEDGE AND KNOWLEDGE MANAGEMENT 2.2

Drucker (1993) believes that “Intellectual property” or “individuals’ knowledge” refers to

the nonphysical and intangible asset of organisations by which competitive advantages could

be significantly improved. Since late 1980s, organisations have changed their strategies from

product-oriented to knowledge-driven, after realisation of knowledge impacts on

organisational performance (Wiig 1997a). It is generally accepted that individuals’

knowledge significantly contributes to the quality of products and, consequently, competitive

advantages (Drucker 2013; Porter 1985; Wiig 1997a).

Knowledge is defined as "a fluid mix of experiences, values, contextual information, and

expert insights that provides a framework for evaluation and incorporating new experiences

and information" (Davenport 2013; Davenport and Prusak 2000). According to Knight and

Howes (2003) knowledge is valuable information which comes from an individual’s mind.

Data and information are two main constituents of knowledge in which "Data is simple


observation of states of the world" and "Information is data endowed with relevance and

purpose" (Knight and Howes 2003).

According to (Nonaka and Takeuchi (1995); Nonaka and Takeuchi (2011)), knowledge is

subjective, process-relational, and aesthetic, and is created through human being interactions.

Knowledge is an important asset for both individuals and organisations and entails the

following characteristics (Alavi and Leidner 1999; Arora, et al. 2010; Davenport and Prusak

2000; Nonaka 1994):

• Knowledge comes from individual’s mind, belief or values;

• Knowledge is an individual’s ability to generate new knowledge or information from existing information, experience, insight or knowledge; and

• Knowledge creates value for organisations to develop competitive advantages

Knowledge management frameworks 2.2.1

From a process point of view, Nonaka and Teece (2001) define KM as the process to

transform tacit knowledge to explicit knowledge. In order to elaborate the mentioned

transformation, a spiral model was developed which comprises four processes: Socialisation,

Externalisation, Combination, and Internalisation (Nonaka 1994). According Nonaka and

Takeuchi (1995), in SECI model knowledge is created through interacting four processes, as

shown at Figure 2-1. Tacit Knowledge TO Explicit Knowledge

Tacit Knowledge

From Socialisation

Externalization

Explicit Knowledge Internalization Combination

Figure 2-1 Modes of Knowledge Creation (Nonaka and Takeuchi 1995)

Socialisation is the process of converting tacit to tacit knowledge through socialising

between owner of knowledge and learner, while Externalisation is the process of converting

tacit to explicit knowledge through articulation and codification (Nonaka and Takeuchi

1995; von Krogh, et al. 2012). In addition, Combination is the process of converting less

complex explicit knowledge to more complicated, through adding new features to an existing

articulated system or such; in contrast, Internalisation is the process of converting explicit

knowledge to tacit knowledge through utilising explicit knowledge to solve problems and

obtain new experiences i.e. learning by doing.

According to Walker and Christenson (2005) the SECI model both discusses individuals’

interactions to create new tacit knowledge, and addresses similar conversions in different

levels; individuals, groups, organisations and their inter-organisations. This model has been

examined in a number of contexts and it is known as one of the significant frameworks with

which to address knowledge management; however, many factors have not been considered

in this model (Walker and Christenson 2005). For instance, the role of individuals has not

Chapter 2 | LITERATURE REVIEW 9

appropriately discussed, particularly from a social science aspect. This means that some

influential factors such as culture and motivation, which directly impact on individuals’

behaviours, have not been addressed. The SECI model has been proposed in functional

organisations and it has not been properly investigated in the project context (Owen, et al.

2004; Owen and Linger 2011).

Table 2-1 Knowledge perspectives and their definitions (Alavi and Leidner 2001)

View of Knowledge Knowledge Management Definition is to

State of mind (Knowledge is state of knowing and understating )

Enhance individual’s learning and understanding through provision of information

Object (Knowledge is an object to be stored and manipulated) Build and manage knowledge stocks

Process (Knowledge is a process of applying expertise)

Create, share, and distribute knowledge through managing knowledge flows

Access to Information (Knowledge is a condition of access to information)

Organize appropriate access to and retrieval of content

Capability (Knowledge is the potential to influence action)

Build core competencies and understanding strategic know-how

According to Alavi and Leidner (2001), perspectives of knowledge are important factors to

define knowledge management. Five perspectives of knowledge have been proposed : 1) a

state of mind; 2) an object; 3) a process; 4) a condition of having access to proper

information; and 5) a capability by which KM could be defined in various ways (Alavi and

Leidner 2001). As shown at Table 2-2, if knowledge is a process, then KM is defined as

process of creation, sharing, and distribution of knowledge, while if knowledge is a

capability then KM is considered as building of core competencies and understanding

organisational strategic know-how (Alavi and Leidner 2001). In general, the knowledge

management has been defined as “ a systemic and organizationally specified process for

acquiring, organizing and communicating both tacit and explicit knowledge of employees so

that other employees may make use of it to be more effective and productive in their work.”

(Alavi and Leidner 1999) .

Table 2-2 KM processes frameworks (developed for this study)

Proposed Context Authors

Processes and their underpinnings

Phase 1 Phase 2 Phase 3 Phase 4 Phase 5 Phase 6

Functional Organizations

Nissen et al (2000) Create Organise Formalise Distribute Apply Evolve

Lytras et al. (2002)

Relate/value (Identify, Verify , Filter

&Select )

Acquire (Formalize,

Codify, Represent,

Format &Map)

Organise (Store,

Transform, Classify)

Enable Reuse (Adapt

&Create)

Transfer (Share,

Distribute, forward&

Line to ppl)

Use (Apply,

Integrate & learn)

Project –based Organisation

Owen & Burstein (2005)

Create Capture Transfer Reuse **** ****

Kasvi et al. (2003) Creation Administration Retrieval Utilization **** ****

Davidson Identify Assess Select Execute Operate Conversion


and Rowe (2009)

define

From a process point of view, Nissen, et al. (2000) conducted a comprehensive study to

investigate the current studies of KM, and eventually, an “amalgamated KM process

framework” was developed to address the KM lifecycle. As depicted in Table 2-3, five

processes were proposed to address KM: create, organise, formalise, distribute, apply and

evolve (Nissen, et al. 2000). Further, a complementary research was undertaken by Lytras et

al. (2002) to examine the mentioned model for developing an applicable and generic KM

process framework for functional organisations, as shown in Table 2-2.

In contrast, one of the first attempts to address KM processes in PBOs was conducted by

Owen and Burstein (2005) where KM processes were defined as: create, capture, transfer,

and reuse. As can be seen in Table 2-2, KM processes for both functional and project based

organisations have been presented to elaborate similarities and differences of KM processes

at the two mentioned contexts. The model proposed by Lytras et al. (2002) has been

employed in a number of research studies and it comprises of underpinning KM processes,

which covers the majority of KM processes. Due to the integrity and validity of this

framework, i.e. Lytras et al. (2002)’s model, it will be adopted to develop the research

framework. Also, the KM process model in Project-based Organisations (PBO), proposed by

Owen and Burstein (2005), will be employed as another premise for this study.

To sum up the above mentioned discussions, following can be mentioned as

characteristics of knowledge management (Alavi and Leidner 2001; Arora, et al. 2010;

Davenport and Prusak 2000; Kasvi, et al. 2003; Koskinen and Pihlanto 2008; Liebowitz and

Megbolugbe 2003; Nonaka and Takeuchi 1995; Wiig 1997b):

• KM is combinations of processes, procedures, practices, applications, and tools to increase organisational competitive advantages,

• KM creates value from organisational intangible assets through engaging individuals in appropriate practices,

• KM is an integrated cycle of knowledge creating, organising, transferring/sharing and using/reusing, and

• KM is the strategy to get right knowledge to the right person in the right time to improve the organisational performance.

In summary, data and information are main constituents of knowledge by which

knowledge is expanded or improved. Knowledge is the state of the mind that is created

through utilising data or information, so it needs to be managed through processes and

procedures. Contemporary organisations keen to manage individual’s knowledge in order to

improve their knowledge-bases and, eventually their competitive advantage.


THE EVOLUTION OF PROJECT MANAGEMENT 2.3

Today's competitive environment compels organisations to be innovative, knowledge

driven and project oriented (Brown and Duguid 1998; Kerzner 2009; Project Management

Institute 2008a). The need for timely response to market changes, customer needs and

technology improvements leads organisations to develop their competencies (Kotnour 2011;

Kotnour 2000). To do so, a project-oriented approach is being adopted by companies for

improving their agility, efficiency, and eventually competitive advantage (Jugdev and

Thomas 2002; Kloppenborg 2014). PM is defined as the application of knowledge, skills,

tools, and techniques to meet project requirements as well as objectives through employing

appropriate processes as well as methods (Project Management Institute 2008a). There are

five phases in the project lifecycle: initiating; planning; executing; controlling; and closing in

which each stage comprises of methods, procedures and processes to be utilised by project

team members for delivering a quality product or service (Project Management Institute

2013).

There are numbers of PM methodologies or guidelines that exist in the current literature.

The Project Management Body of Knowledge (PMBOK), developed by the Project

Management Institute (PMI), and Project In Controlled Environment (PRINCE2), proposed

by the Office of Government Commerce (OCG) in the UK, are the traditional PM

methodologies which have been established and improved based since 1990 (Office of

Government Commerce 2005; Project Management Institute 2013). In this section of the

literature review, projects, PM and their associated concepts will be discussed, followed by

presentation of numbers of PM methodologies. Then, the project management office (PMO)

will be reviewed, and at the end, PM Maturity Models (PMMM) will be discussed.

Project and Project Management 2.3.1

According to the Project Management Institute (2008a) a project is a temporary

endeavour to create a unique product or service in given periods of time with a determined

budget. In other words, a project is an activity that could not be implemented through

organisational procedures (Kerzner 2009). Project Management (PM) is the application of

knowledge, skills, tools, and techniques to meet project objectives (Project Management

Institute 2008a). PM is integration of skills and experiences to achieve a defined scope

within the given time and budget through utilising appropriate processes, practices and tools

(Office of Government Commerce 2005). A project is successful when it : 1) has met

objectives and project scope, 2) has been finished in planned time, 3) has been managed on

or below the planned budget and cost, and 4) has met the expected quality (Office of

Government Commerce 2005; Project Management Institute 2013).


Both knowledge and experience of the project manager are crucial factors for project

success (Koskinen 2010; Koskinen 2000; Peltola, et al. 2002). This means that a way of

managing knowledge within in a project was recognised as an important competency for

both project manager and project team members (Ajmal, et al. 2010; Bresnen, et al. 2003;

Kasvi, et al. 2003). Moreover, project success and quality of project are strongly dependent

on project managers’ knowledge of both PM methodologies and associated technical

knowledge (Kotnour 2000). According to Love et al. (2003), KM has a strong influence on

the efficiency of PM, in which poor utilisation of KM practices not only negatively impacts

on project success, but also causes some inefficiency such as overrun cost. As discussed

earlier, there are a number of types of knowledge related to project environment: knowledge

of project management, knowledge of application area, knowledge of other management

science especially human behaviour, knowledge of related tools and applications, and

knowledge of project context (Project Management Institute 2008a). The knowledge of PM

is addressed through appropriate standards and methodologies, such as PMBOK and

PRINCE2. Due to popularity of the mentioned frameworks, they will be succinctly explained

in the next section.

Project In Controlled Environment (PRINCE2) 2.3.2

PRINCE2 has been developed by the British’s Office of Government Commerce, since

1989 (Bentley 2009). The PRINCE2 addresses a generic PM standard, which comprises

numbers of PM practices to be employed in various types of projects (Office of Government

Commerce 2005). The last version of PRINCE2, fifth edition, was published in 2009, and it

consists of three major categories: project processes, project components, and required

techniques, which have been depicted in Figure 2-3 (Bentley 2009). From a project lifecycle

point of view, eight distinctive management processes are proposed in PRINCE2: 1) starting

up a project or SU, 2) directing a project or DP, 3) initiating a project or IP, 4) managing

stage boundaries or SB, 5) controlling a stage or CS, 6) managing product delivery or MP, 7)

closing a Project or CP, and 8) planning or PL (Bentley 2009; PRINCE2 Foundation 2008).

It is advised that the mentioned processes should be implemented in accordance to the

proposed processes detailed in Figure 2-1.


Figure 2-2 PRINCE2's project lifecycle(adapted from (Bentley 2009))

In addition, there are eight subsequent components in PRINCE2: 1) business case, 2)

organisations, 3) plan, 4) controls, 5) management risk, 6) quality, 7) configuration, and 8)

change control, in which each component entails the required knowledge, which should be

employed during a project lifecycle (PRINCE2 Foundation 2008). As presented in

Figure 2-3, the above mentioned components should be used at various stages of a project,

by which the quality of project management is met (Bentley 2009).

Figure 2-3 PRINCE2’s components (adapted from (Bentley 2009))

Also, three major techniques are advised in PRINCE2: 1) product based planning

techniques, 2) quality review techniques, and 3) change control techniques, which should be


employed in the whole project lifecycle (Bentley 2009). These techniques and their usages

have been properly addressed in the PRINCE2 as a means to undertake project activities.

Project Management Body of Knowledge (PMBOK) 2.3.3

PMBOK has been developed by the Project Management Institute (PMI) since 1996 as

the main reference for project management in the US (Guide 2004; Project Management

Institute 2008a). As the most influential PM guideline in the globe, PMBOK has been

revised based upon the latest successful best practices in order to both strengthen the method,

and broadly communicate the latest findings of project management (Project Management

Institute 2008a; Project Management Institute 2013). PMBOK proposes five phases for the

project life cycle: 1) initiation, 2) planning, 3) execution, 4) monitoring and controlling, and

5) closing (Project Management Institute 2013). In addition, ten following knowledge areas:

1) integration management 2) scope management, 3) time management, 4) cost management,

5) quality management, 6) human resource management, 7) communications management,

8) risk management, 9) procurement management, 10) stakeholders management, and 9) are

advised to be employed during five project phases (Project Management Institute 2013).

As presented at Table 2-4, each knowledge area has an appropriate correlation and

interactions with five Project Phases. This means that PMBOK addresses what sort of

knowledge areas and their associated practices should be employed at project lifecycle

(Project Management Institute 2013). In other words, knowledge areas were divided into a

number of sub-categories and processes in which forty-eight processes are addressed during

five phases of project lifecycle. These guide project managers to appropriately follow

suitable processes to undertake project activities.

Table 2-3 Knowledge areas and Phases in PMBOK (developed for this research) Project Phase

Initiation Planning Execution Monitoring & Control Closing Knowledge Area

1 Project Integration Management √ √ √ √ √ 2 Project Scope Management √ √ 3 Project Time Management √ √ 4 Project Cost Management √ √ 5 Project Quality Management √ √ √ 6 Project Human Resources Management √ √ 7 Project Communications Management √ √ √ 8 Project Risk Management √ √ 9 Project Procurement Management √ √ √ √ 10 Project Stakeholders Management √ √ √ √

Given the process-based structure of PMBOK, the ten knowledge areas have been made

inter-correlated, by which the output of one knowledge area is used as an input for another

knowledge area. This means that inaccurate or less quality outcomes of a predecessor

knowledge area, in various project phases especially in the initiation and planning stages,

significantly impact on the quality of a successor knowledge area, and ultimately, quality of


a whole project (Project Management Institute 2013). According to PMI (2008a),

appropriate usage of knowledge areas in each phase is a crucial key to manage a project

successfully. In other words, this methodology gives an applicable roadmap to address

proper tools and applications in order to assist project team members; however, there are

number of factors which should be considered during the employment of this standard. This

framework has been adopted as the research PM methodology and it will be discussed in the

future.

The Project Management Office (PMO) 2.3.4

The Project Management Office (PMO) is a unit or department in matrix and project-

based organisations to institutionalise PM practices through developing and customising PM

methodologies (Kerzner 2009; PRINCE2 Foundation 2008; Project Management Institute

2008b). According to Desouza and Evaristo (2006), PMO is an exercise to customise and

sustain PM practices, methods, techniques and tools in companies. The notion of PMO has

being developed since the 1950s, and it has been continuously improved, especially in the

last ten years, through proposing PMO as an important part of organisational structure in

modern enterprises (Kerzner 2005). In the early 1950s, PMO was considered as an optional

organisational unit to delegate some ordinary tasks and authorities, while since the early

2000s it has become a strategic unit or department in project-based and matrix organisations

to contribute to achieving organisational goals as well as project objectives (Kerzner 2005;

Walker and Christenson 2005).

In order to establish and develop a PMO, numbers of changes should be undertaken in

structure, processes, procedures as well as organisational culture (Kerzner 2005; PRINCE2

Foundation 2008; Project Management Institute 2008a). In other words, PMO not only

should take responsibility of existing PM activities, but also it is accountable to continuously

improve organisational competencies, from a PM point of view (Kerzner 2013). However,

PMO development is not an overnight activity and it needs to be appropriately prepared for

such a mission (Crawford 2006). This means that PMO should be gradually established and

developed in a way that not only its position and responsibility are being accepted by other

organisational units, but also robust and reliable interactions are being developed among

PMO and the whole organisation (Kerzner 2005; Project Management Institute 2008b).

A Project Management Maturity Model (PMMM) has been proposed to address step-by-

step development of a PMO from an immature level to a mature level (Project Management

Institute 2008b). In other words, PMMM is a method to guide the establishment of PMO

through addressing suitable approaches, processes, criteria, and practices for both

institutionalising of a PMO unit within an organisation, and also developing organisational

competencies, from a PM point of view (Kerzner 2005). In addition, PMMM contributes to


improve organisational readiness as well as a culture for adopting project management as an

approach for enhancing competitive advantages (Crawford 2012; Crawford 2006; Jugdev

and Thomas 2002).

The development of PMO through employing PMMM, is recommended as the best

solution for improving PM practices in organisations (Jugdev and Thomas 2002). Hence,

PMO could possess different levels of maturity in which the higher levels mean a better

PMO performance. According to the current literature, numbers of the following

responsibilities have been mentioned for PMOs, regardless of level of maturity (Artto, et al.

2011; Crawford 2012; Desouza and Evaristo 2006; Hurt and Thomas 2009).

• Aligning projects with organisational strategies,

• developing standards, processes, and methods of PM and improving organisational capacities to employ them,

• Managing all requirements for a project such as staffing, equipment and space in order to optimise organisational resource usage,

• Assessing viability and feasibility of project and its contribution to the business value of organisation,

• Defining and monitoring project success/failure measures,

• Monitoring and controlling organisational project,

• Training project stakeholders especially project team members and project manager,

• Quality assurance of the project,

• Managing organisational projects risks,

• Coordinating communication management across projects, a mentoring platform for project managers,

• Project portfolio management: Multiple project management (simultaneously or

historically) to conduct and manage similar issues in order to compare and

manage them appropriately, and

• One of the main responsibilities of the PMOs could be categorised as: managing

project and team members' knowledge, capturing and utilising lessons learned

and linking project knowledge to organisational knowledge.

There are numbers of PMMMs to address the development and responsibilities of PMO,

which will be discussed in the next section. The Organisational Project Management

Maturity Model (OPM3) is a well-known PMMM which is proposed by PMI to address the

development of PMO as well and PMBOK in organisations (Project Management Institute

2008b). In addition, the Portfolio Program Project Management Maturity Model (P3M3) is

another PMMM published by OCG to develop the PMO from a PRINCE2 perspective

(PRINCE2 Foundation 2008). The above mentioned responsibilities of PMO have been

emphasised by both mentioned PMMMs in a way that not only does PMO not intervene with


the responsibilities of project managers but also it aims to offer appropriate services and

advice to them (PRINCE2 Foundation 2008). The following have been made by PMI to

clarify the significant role of PMO (Project Management Institute 2008a):

• Project managers pursue specific project’s observations, in contrast the PMO

follows corporate level strategies;

• Responsibility of a project manager is limited to a specific project while the PMO

is responsible for all an enterprises’ projects;

• The focus of a project manager is only on specified project objectives, but the

PMO conducts scope management in the high level of an enterprises’ projects.

• Optimising the use of shared organisational resources across the project is the

responsibility of the PMO but project managers just focus on one project; and

• The project manager manages the scope, schedule, cost and quality of the

products of the work packages, while the PMO manages overall risk, overall

opportunity and all project interdependencies.

According to the existing literature there is a strong agreement among academics and

practitioners about the significant contribution of a PMO for delivering a successful project

(Santosus 2003). In addition, anecdotal evidence reports that organisations have shown

meaningful interest in launching and improving the PMO within their structures. According

to Liu and Yetton (2007), a considerable number of companies established their PMOs in

2003 and it was estimated that another 50 000 US organisations will launch their PMO by

the end of 2003. This means that organisations believe that establishing and developing the

PMO through standard processes enhances the quality of the project management and it is

known as an appropriate resolution for tackling project failure (Andersen, et al. 2007; Dai

and Wells 2004; Desouza and Evaristo 2006).

Given the increasing interests of launching and enhancing a PMO, there are numbers of

challenges during PMO development which need to be looked into. (Kerzner 2005; Kotnour

2011). More than 30 challenges have been discussed by Singh, et al. (2009) through

undertaking the Delphi method, by which some issues such as lack of PMMMs and

knowledge management have been discussed. Despite the usefulness of this study, the

recognised challenges have not clearly been discussed in terms of their rank and importance.

According to researcher investigations, the majority of them could be tackled through

following appropriate implementation of PMO maturity models, however, some of them

need other solutions. However, KM in the PMO is one of the recognised challenges, which

will be investigated as the subject of this research.


In summary, PMO is a unit in organisation which is responsible for PM activities. The

development of PMO is not the overnight decision and it necessitates an undertaking through

appropriate methods (Kerzner 2005). Since early 2000s, numbers of organisations have

started to establish and develop their PMO through employing in accordance with existing

PMMMs, however, there are some challenges that are yet to be addressed (Aubry, et al.

2008; Grant and Pennypacker 2006; Jugdev and Thomas 2002; Liu and Yetton 2007). Due to

the significant impacts of PMO in an organisational structure, it is preferred to employ

reliable methods that are developed based upon best practices. PMMMs are considered as

valid methodology to address the development of PMO (PRINCE2 Foundation 2008). In the

next section, numerous current PMMMs will be discussed to gain insightful knowledge in

this regard.

Taxonomies of knowledge 2.3.5

Knowledge is a multidimensional phenomenon that could be investigated from different

point of views (Ein-Dor 2008). There are a number of types of knowledge in the literature,

by which knowledge management is defined (Alavi and Leidner 2001). This means that

definition of knowledge management is related to the adopted taxonomy of knowledge. The

first and the most important taxonomy of knowledge is tacit and explicit dimension which

was recognised by Polanyi in the 1970s (Ein-Dor 2008; Polanyi 1983).

According to Polanyi (1983) human beings could not articulate, elaborate or tell

everything he/she knows. In other words, tacit knowledge exists in the individual’s mind,

while explicit knowledge is the articulated knowledge (Anand, et al. 2010; Ein-Dor 2008;

Polanyi 1983). However, how individuals’ implicit knowledge could be transformed to

explicit knowledge has become an important subject for numbers of studies (Davenport and

Prusak 2000; Nonaka and Takeuchi 1995).

Table 2-4 Characteristics of tacit and explicit Knowledge (developed for this research)

Explicit Knowledge Tacit Knowledge

Can be codified or articulated. Difficult to codify or articulate.

Found in documents, forms and inductions. Embedded in individual intuitions and expertise.

Can be explained or elaborated. Difficult to explain or elaborate. Can be exploitable. Difficult to exploit.

Can be schematic and easy to understand. Complex to be understood. Can be sharable, transferable and teachable. Difficult to share, transfer, and teach.

Known as “Know-why”. Known as “Know-how”. Independent from individual’s mind. Dependent to individual’s mind.

The mentioned taxonomy of knowledge was been developed by Nonaka (1994) through

proposing a “knowledge spiral“ model. According to Nonaka (1994) tacit knowledge is the

root of human knowledge and it is embedded in an individual’s mind, beliefs and thoughts,

which cannot be easily codified. In other words, tacit knowledge is the hidden side of


individual knowledge, deeply rooted in his/her actions, ideals, and commitments (Nonaka

1994). While explicit knowledge is articulated and codified in organisational documents,

forms and instructions, so it is not complex to share, transfer and disseminate through

appropriate and formal systems, processes or procedures (Nonaka 1994). Table 2-1

summarises the characteristics of tacit and explicit knowledge, in the current literature

(Ajmal and Koskinen 2008; Alavi and Leidner 1999; Arora, et al. 2010; Christensen and

Bang 2003; Davenport and Prusak 2000; Kasvi, et al. 2003; Knight and Howes 2003;

Koskinen 2000; Nonaka and Takeuchi 1995).

Tacit knowledge is a critical source to develop organisational competencies (Goffin, et al.

2010; Teerajetgul and Chareonngam 2008). Individuals are owners of tacit knowledge

therefore, organisations should focus on articulating this type of knowledge in order to

enrich the knowledge-bases (Nonaka and Takeuchi 1995). Tacit knowledge can be

transformed to explicit knowledge through articulating and/or documenting methods, which

is a significance challenge (Nonaka and Takeuchi 1995). Tacit knowledge has two

dimensions: cognitive; and technical, where the cognitive dimension relates to the mental

model of an individual, while technical dimension refers to an individual’s concrete know-

how and skills (Nonaka and Takeuchi 2011; von Krogh, et al. 2012). This typology

emphasises the importance of psychology by which a human being’s mental model could be

analysed. In other words, management of tacit knowledge is dependent on individuals’

mental model, and consequently, management of human behaviours as well as organisational

culture (Koskinen and Pihlanto 2008).

To transform the tacit knowledge to explicit knowledge, understanding of both human

behaviour and organisational culture plays a significant role (Koskinen and Pihlanto 2008).

However, the existing solutions have mainly focused on technical or mechanical aspects

rather than individuals’ behaviours (Koskinen 2000). In other words, considering social and

behavioural aspects of a human being is mandatory to encourage individuals to transfer their

knowledge. A study by Walker and Christenson (2005) has discussed social science and

physiology to understand both employees’ behaviour within organisations and their

interactions with co-workers, an organisation and external environments. Similar research

has been conducted to examine the tacit dimension of knowledge against a number of

behaviour factors in order to investigate the social aspect of tacit knowledge within Project-

Based Organisations (Koskinen and Pihlanto 2008). These studies have recognised numbers

of factors such as organisational culture, individual mental mode, and trust, to facilitate

transforming tacit knowledge to explicit knowledge (Ajmal and Koskinen 2008; Koskinen

and Pihlanto 2008; Wiewiora, et al. 2010).


The context of this study, i.e. Project Management Office (PMO), necessitates focus on

the existing taxonomies of knowledge in project environments. In the current literature, a

few attempts have been undertaken to discuss types of knowledge in PBOs, however, the

taxonomy of knowledge has not been discussed extensively. In other words, there is no

accepted or generic typology of knowledge in PBOs, however, some evidence claims that

this subject is being evolved (Kasvi, et al. 2003; Wiewiora, et al. 2009b). Kasvi et al. (2003)

introduce three types of knowledge in project environments: 1) Technical knowledge which

is related to products, their parts and technologies; 2) Procedural knowledge which concerns

how product should be produced in a project through appropriate procedures; and 3)

Organisational knowledge which is related to communication and collaboration of project.

These types of knowledge will be discussed further in section 2.4. From a tacit and explicit

perspective, it could be concluded that “technical knowledge” could be more of a tacit

knowledge, while procedural and organisational knowledge could be considered as an

explicit type of knowledge. This typology was adopted and developed by some studies in

PBOs. For instance, Wiewiora et al. (2010) have accepted two first types i.e. technical &

procedural knowledge, but they modified the last one, organisational knowledge, to be

“about customer requirement”. This change has been undertaken in accordance to PMBOK

(2008a).

The Project Management Maturity Models 2.3.6

The basic idea of a maturity model is that “you must learn to crawl before you can learn

to walk” (Andersen, et al. 2007). As discussed previously, PMMM is a framework to

construct PMO in an organisation through improving from an immature level, i.e. initial or

ad hoc, to mature level, i.e. optimised or centre of excellence (Jugdev and Thomas 2002;

Kerzner 2005; PRINCE2 Foundation 2008; Project Management Institute 2008b). This

means that PMO should be systematically developed by adopting appropriate PMMM to: 1)

assess and measure the current maturity level, 2) benchmark the current status, 3) plan to

achieve the higher maturity level. According to Andersen, et al. (2007) a process-oriented

approach is the common strategy among the existing PMMM by which PMOs could follow

certain process to achieve their objectives.

Both PMBOK and PRINCE2 address PM through numbers of processes in various

phases. In other words, both PRINCE2 and PMBOK are considered as process-base

methodologies (Bentley 2009; Kerzner 2013). In addition, both PM methods have their

associated PMMMs, OPM3 and P3M3, to address the development of PMO. This means that

OPM3 is a suitable PMMM for those organisations that adopted PMBOK, and similarly,

P3M3 is recommended by PRINCE2 followers to be adopted (Bentley 2009; Kerzner 2013).

Despite some differences from the PM point of view, OPM3 and P3M3 have been developed


based upon the Capability Maturity Model Integration (CMMI), developed by Carnegie

Mellon University as the valid method to create a mature process model (Grant and

Pennypacker 2006; Jugdev and Thomas 2002; Kulpa and Johnson 2008).

Figure 2-4 OPM3 framework (Project Management Institute 2008b)

OPM3 addresses the development of PMBOK in organisations, through developing PMO

in three categories: project, program, and portfolio at four levels of maturity: 1) standardise;

2) measure, 3) control, and 4) continuously improve (Project Management Institute 2008b).

As shown at Figure 2-4, maturity level of PMO could be improved by following certain steps

(Project Management Institute 2008b).

In a similar manner, P3M3 is a step-by-step framework to address the customisation of

PRINCE2 in three following categories: portfolio, program, and project, at five levels of

maturity: awareness, repeatable, defined, managed, and optimised (PRINCE2 Foundation

2008). As shown in Table 2-5, P3M3 has one more level, in comparison to OPM3 and, also

it follows the CMMI methodology, from a process point-of-view.

As presented in Table 2-5, there are four popular mentioned PMMMs in the current

literature: OPM3, P3M3, Kerzner’s PMMM, and CMMMI-based PMMM. According to this

table, all four PMMMs follow a process-based approach and the majority of them have

adopted CMMI in this regard. It could be concluded that there is no significant difference


among the mentioned PMMMS except the adopted PM methodology. Hence, adopting

appropriate method is dependent on some factors. For instance, OPM3 is recommended if

the adopted PM methodology is PMBOK, and similarly, P3M3 is suitable for organisations

that choose PRINCE2.

Table 2-5 The comparison of PMMMs (developed for this study) Maturity Level

Level 1 Level 2 Level 3 Level 4 Level 5 Maturity Model

OPM3 Standardize Measure Control Continuously improve ******

P3M3 Awareness Repeatable Defined Managed Optimized

Kerzner’s PMMM Common Language

Common Process

Singular Methodology Benchmarking Continues

Improvement

CMMI- based PMMM Initial Repeatable Refined Managed Optimized

According to Gasik (2011) eight elements should be considered, before choosing a

maturity model: 1) method independency: degree to which a maturity model is aligned to a

PM methodology, 2) public domain: the degree to which a maturity model and maturity

assessment can be applied by anyone besides its owners, 3) publication: the degree to which

a maturity model is issued in publications, 4) industry independency: the degree to which the

application of a maturity model is limited to particular industry sectors, 5) transparency: the

traceability of the calculation of the maturity scores, 6) toolset independency: the degree to

which the usage of a maturity model is bound to a toolset, 7) years of existence: how many

years a maturity model has existed, and 8) ease of use: the degree to which a maturity model

is easy to use in practice. These factors were investigated in more than twenty maturity

models, and eventually, the following have been recommended as the most suitable maturity

models (Gasik 2011):

• Organizational Project Management Maturity Model (OPM3)

• Capability Maturity Model Integration (CMMI-DEV)

• Kerzner Project Management Maturity Model (PMMM)

• Project, Program, Portfolio Management Maturity Model (P3M3)

Since Kerzner’s PMMM has been developed based on PMBOK, and also it has been

adopted by numbers of organisations, it has been adopted as the research PMMM and will be

discussed thoroughly, in the section 3.3.3.

Conclusion 2.3.7

Project management is an important factor to improve organisational competitive

advantage (Aubry, et al. 2011; Grant and Pennypacker 2006). The dramatic increasing

attention to PM necessitates addressing appropriate PM methodologies and structures

(Jugdev and Thomas 2002; Kotnour 2000). The realisation of PM importance, has led


number of organisations to develop various types of PM methodologies, standards and

solutions such as PMBOK and PRINCE2 (Kerzner 2013; PRINCE2 Foundation 2008;

Project Management Institute 2013). The PMO has been defined as a unit or department to

establish and develop PM methodologies (Kerzner 2013; Project Management Institute

2013). The development of PMOs has been addressed by proposing PM maturity models

(PMMM) (Kerzner 2005). PMMM contributes to both the development of PMOs from

immature levels to a mature level, and enhancement of organisational capabilities from a PM

perspective (PRINCE2 Foundation 2008). According to the current literature, there are

numbers of PMMM such as OPM3, P3M3 and Kerzner’s PMMM. The selection of an

appropriate method depends upon a number of factors that should be considered before any

practical steps (Gasik 2011).

KNOWLEDGE MANAGEMENT IN PROJECT-BASED ORGANISATIONS 2.4

The management of project knowledge is a critical activity for project success (Ajmal, et

al. 2010; Davidson and Jillian 2009; Koskinen and Pihlanto 2008), and managing a

successful project is significantly dependant on project knowledge management (Kotnour

2011; Kotnour 2000). In other words, the ability to identify and utilise appropriate

knowledge contributes to both delivering quality products, and achieving project objectives.

In other words, KM processes and practices play significant roles in delivery of a successful

project.

As discussed earlier, KM has been extensively discussed in functional organisations since

the 1990s, however, it is claimed that current KM practices for those types of enterprise are

not necessarily appropriate for project-based organisations (Polyaninova 2010). According to

Bresnen, et al. (2003), the three following issues are the main constituents of KM challenges

in PBOs: 1) projects are finite and their personnel disband or leave after project termination,

therefore created knowledge might not be utilised in similar projects, 2) there are difficulties

in developing and disseminating knowledge within and between projects -inter and intra

project-, and 3) fragmentation of project team members into different groups, makes the flow

of knowledge difficult among groups.

The temporary nature of projects is recognised as the main reason to emphasise the

importance of necessitating customised KM practices to tackle KM issues in PBOs (Bresnen,

et al. 2003; Newell, et al. 2006; Pemsel and Müller 2012). According to Ajmal and Koskinen

(2008), the temporary nature of projects creates a number of challenges from a KM point of

view, and the diversity of project team members’ expertise for cooperating in a short time

period, also cause KM challenges in PBOs. Given the existence of broad discussions of KM

in the literature, however, a few of them have focused on addressing KM in project

environments (Koskinen, et al. 2003; Ribeiro and Ferreira 2010; Söderlund 2010).


According to Kasvi et al. (2003) the existing solutions of KM practices in the literature are

not suitable for project contexts and KM is yet be properly addressed. It is generally

accepted that the current KM studies could not cover the recognised challenges of KM in

PBOs such as leaking knowledge, lack of mentoring and timely limited activities (Landaeta

2008; Leseure and Brookes 2003; Wiewiora, et al. 2009b).

According to Desouza and Evaristo (2006) management of project knowledge is one of

the most critical roles of the PMO. Given the importance of KM in the PMO, limited studies

have been undertaken to address this phenomena. Particularly, there is a significant gap in

which to address the KM practices in PMMM. In other words, PMMM have addressed

number of practices for improving the maturity of the PMO from a PM point-of-view,

however, the KM perspective has not been discussed by these models. In this section, major

discussions of KM in PBOs will be presented, in order to have a better understanding of the

current discussions of KM to formulate the research problem.

Type of Knowledge and KM in Project-based Organisations 2.4.1

Project knowledge can be categorised as tacit and explicit, in which tacit knowledge is

critical for project success (Koskinen 2010; Koskinen 2000). According to Koskinen (2000)

transforming tacit knowledge to explicit should be undertaken through consideration of the

social and behavioural aspects of human characteristics. Some behavioural elements of tacit

knowledge such as trust, social influence and culture have been examined in PBOs, and they

are considered as significant factors to managing tacit knowledge (Wiewiora, et al. 2010).

Given the tacit and explicit dimensions of project knowledge, Damm and Schindler (2002)

have discussed the following three types of knowledge: 1) knowledge about project, which is

required before and during the project implementation such as PM methods, 2) knowledge in

project which presents KM during project execution such as KM processes, and 3)

knowledge from project, which deals with KM after the closing phase, for instance lesson

learned, as presented in Table 2-6.

Table 2-6 Knowledge types in Projects (developed for this research)

Authors Type of knowledge in PBOs

Koskinen (Koskinen 2010; 2000)

• Explicit Knowledge • Tacit Knowledge

Kotnour (Kotnour 2011; 2000)

• Intra-project Knowledge • Inter-project knowledge

Damm and Schindler (2002)

• Knowledge about project • Knowledge in project • Knowledge from project

Kasvi et al. (2003) • Technical knowledge • Procedural knowledge • Organizational knowledge


Wiewiora (2010) • Technical knowledge • Procedural knowledge • Knowledge about customers’ needs

A succinct summary of the existing KM discussion in PBO 2.4.2

From a practical point-of-view, Kasvi, et al. (2003) propose three types of project

knowledge: 1) technical knowledge, which is about technical aspects of project product, 2)

procedural knowledge that focuses on processes of producing product, and 3) organisational

knowledge that focuses on collaborating and integrating knowledge within an organisation.

Similar to the above mentioned type of knowledge, these three types of knowledge could be

investigated from both tacit and explicit perspectives, however, it seems the first and the last

ones are more tacit rather than explicit, while the procedural knowledge is likely of an

explicit nature. A study by Wiewiora et al. (2009a) has adopted accept the first two types of

knowledge, and changed the third one to "knowledge about customer requirements”, in

accordance with PMBOK. Table 2-6 exhibits some of taxonomies of knowledge in the

PBOs.

The importance of tacit knowledge on project success has been initially investigated by

Koskinen and Pihlanto (2008); Koskinen, et al. (2003); Ward and Daniel (2013). Since,

individuals are owners of tacit knowledge, hence, individuals’ behaviours and the social

science aspect of knowledge management were considered (Koskinen, et al. 2003).

According to Koskinen, et al. (2003) three types of competencies are required for managing

individual knowledge in PBOs: 1) explicit knowledge, which could be easily shared and

communicated, 2) tacit knowledge, which hardly can be shared, and 3) personal

characteristics such as stress management and tolerance. In other words, these competencies

are influential factors in transforming tacit knowledge into explicit knowledge (Koskinen

and Pihlanto 2008; Koskinen, et al. 2003).

Apart from the above-mentioned competencies, five types of communication: 1) face to

face, 2) telephone, 3) written personal, 4) written formal, 5) numeric formal have been

adopted as possible connection media among individuals in a project context (Koskinen, et

al. 2003). According to Koskinen, et al. (2003), face-to-face is the best method to transform

tacit knowledge into explicit knowledge, by which knowledge could be codified for transfer

and reuse purposes. A further investigation by Wiewiora et al. (2010), which will be

discussed later, not only confirms the importance of face-to-face communication for

knowledge transfer, but also it claims that informal face-to-face communication is an

effective method for knowledge transfer.

The role of social science is another subject which was considered by Koskinen, et al.

(2003). The numbers of non-technical factors, such as personal characteristics, intuition,


individual’s mental model, and commitment have been investigated to examine their impact

on managing project knowledge (Koskinen, et al. 2003). All mentioned factors, which are

called Holistic Concepts of Man, could be significantly influential for transforming tacit

knowledge to explicit knowledge, hence, appropriate methods could facilitate the processes

of articulating tacit knowledge (Koskinen and Pihlanto 2008; Koskinen, et al. 2003).

According to Kotnour (2000) the quality of projects could be improved through adopting

the following cycle: Plan-Do-Study-Act or PDSA in which knowledge management and

organisational learning play an important role. In other words, knowledge is created during

“study and plan” phases and should be utilised at “do and act” stages. This means that

quality of projects increases when organisations learn from previous projects and apply this

knowledge accordingly (Kotnour 2000). The PDSA is a customised form of PDCA (Plan-

Do- Check-Act) which was developed by Edward Deming to address the development of a

quality management system (Scherkenbach 1986). The PDSA cycle discusses both inter- and

intra- project knowledge to address how creating and sharing knowledge within a project, i.e.

intra-project, and combining and sharing lessons learned across other projects, i.e. inter-

project, will contribute to the quality of the projects (Kotnour 2000). The significance of

Kotnour’s research is to introduce the relation between project performance and appropriate

knowledge management as well as organisational learning. The PDSA cycle and its

associated processes have been adopted, and then developed later on, for addressing

knowledge flow in project lifecycle (Owen, et al. 2004; Wiewiora, et al. 2010).

From a processes point-of-view, Kasvi, et al. (2003) propose four KM processes to

address KM activities in PBOs: 1) knowledge creation, 2) administration, 3) dissemination,

and 4) utilisation. As discussed earlier, numbers of models have been proposed to address

KM processes in functional organisations, as presented at Table 2-3. A comparison between

those models and the above mentioned KM processes reveals that they have some

similarities, however, “knowledge transfer” is the missing process which has not been

properly discussed by Kasvi, et al. (2003). In fact, knowledge transfer/share has been argued

as the most critical process of KM in functional organisations and, in particular, it is

recognised as the most important challenges in PBOs (Koskinen, et al. 2003; Owen, et al.

2004; Wiewiora, et al. 2010).

Due to the importance of knowledge transferring, the above mentioned KM processes

were developed by Owen, et al. (2004), in which four KM processes were proposed: 1)

creation, 2) capture, 3) transferring, and 4) reusing. In addition, these processes were

examined through employing Kotnour’s PDSA cycle in which PDSA was modified to PDSO

(Plan-Do-Study-Orient) and OODA (Observe-Orient-Decide-Act) (Owen, et al. 2004).

According to Owen, et al. (2004) the PDSO cycle addresses KM creation within a project,


while OODA cycle discusses knowledge integration at the organisational level. In other

words, PDSO deals with capture and creation of knowledge at operational level, i.e. projects;

in contrast, OODA discusses knowledge transfer from project to organisational level, i.e.

PMO or Project-base structure (Owen, et al. 2004). This model has been examined in

numbers of cases, and it has been adopted as one of the research premises, as discussed in

section 3.2.2 (Owen and Burstein 2005; Owen, et al. 2004).

From a KM practice point of view, knowledge transferring was investigated by

Wiewiora, et al. (2010) in which numbers of techniques and practices were examined, intra-

and inter- projects. According to Wiewiora, et al. (2010) informal face-to-face interactions

are the first KM practices to share knowledge in PBOs. The second and third KM practices

for knowledge transferring, are formal face-to-face interactions, and email (Wiewiora, et al.

2010). This study is the one of the latest studies that has considered project-based

organisations instead of functional organisation. However, knowledge transfer was the main

focus of their study and other KM processes have not been discussed by Wiewiora, et al.

(2010). This PhD project aims to cover this gap through discussing other KM practices, i.e.

creation, capturing, and reusing.

From a system point-of-view, a system theory approach has been discussed to address

the KM in a project environment (Davidson and Jillian 2009). According to Davidson and

Jillian (2009) the three following levels: operational, tactical, and strategic, should be

considered to develop appropriate KM processes and practices. It is obvious that processes

are not necessarily similar at each level, which indicates that various processes could be

developed at each level (Davidson and Jillian 2009). At an operational level, KM processes

should manage issues such as lessons learned, while in other levels, specifically the strategic

level, knowledge management most likely deals with integration of lower levels through

systematic interactions (Davidson and Jillian 2009). According to Davidson and Jillian

(2009) system theory has a significant role to facilitate the enrichment of knowledge

management within PBOs.

Table 2-7 KM initiatives and barriers in PMO (developed for this research)

Enablers of KM in the Project –base organizations

Barriers of KM in the Project –base organizations

Familiarity with KM Inappropriate Technology Appropriate Coordination Less management support

Incentives for knowledge efforts Weak contents of knowledge Appropriate systems for handling KM Project Management

Cultural support Cultural issues

As depicted in Table 2-7, there are numbers of initiatives and barriers of knowledge

management in PBO, which have been discussed in the current literature (Ajmal, et al.


2010). According to Ajmal, et al. (2010) knowledge management is an influential factor for

developing organisational competitive advantage, hence, it is important to recognise KM

initiatives, enablers and barriers in PBOs. This contributes to develop a reliable KM system,

by which PBOs could manage their project knowledge, and eventually improve their

competitive advantages.

According to Ajmal, et al. (2010) “incentives” and “appropriate KM system” have been

proposed as the most significant enablers of KM in PBOs, while “lack of proper

coordination” and “cultural issues” are known as the most important barriers. This means

that an appropriate KM system, which comprises processes, procedures, and technology,

significantly improves the management of project knowledge. In addition, improving

organisational culture and developing incentives, alongside management support, contribute

to the enhancement of project knowledge management (Ajmal, et al. 2010; Ajmal and

Koskinen 2008).

Challenges of knowledge management in project environments 2.4.3

As discussed earlier, KM in functional organisations is not similar to project-based

organisations (Koskinen and Pihlanto 2008). Hence, KM in PBOs should be investigated to

address appropriate practices to resolve the current challenges of KM projects (Bresnen, et

al. 2003; Koskinen and Pihlanto 2008; Owen, et al. 2004). In order to investigate KM in

project environments, initial attempts have focused on studying KM in single project, but

later on project environments and PBOs have chosen as the main context (Koskinen and

Pihlanto 2008; Kotnour 2000). The majority of the prior studies have strongly emphasised on

challenges of PBOs and projects from KM perspectives. Given the importance of knowledge

for project success, it is generally accepted that KM should be the major subject for research,

in order to address the current challenges of managing project knowledge (Koskinen and

Pihlanto 2008; Srikantaiah, et al. 2010). Following are some of recognised challenges and

issues of KM in project based organisations, which have been recognised in the current

literature:

• Knowledge leakiness & stickiness in projects (Brown and Duguid 1998), • Lack of KM initiatives in projects (Liebowitz and Megbolugbe 2003), • Difficulties of articulating individual knowledge (Koskinen, et al. 2003), • Lack of appropriate knowledge sharing and acquisition systems (Koskinen, et al.

2003), • Repetitive works or rework because of lack of effective knowledge reuse and

transferring system (Desouza and Evaristo 2006; Love, et al. 2003; Owen, et al. 2004),

• Lack of knowledge social networks as knowledge transfer initiatives (Walker and Christenson 2005),


• Lack of wisdom in projects because of inappropriate knowledge management systems in the project environment (Walker and Christenson 2005),

• Lack of learning and organisational learning in project environment (Kotnour 2000; Newell, et al. 2006),

• Poor system of collecting and assimilating lessons learned between and within projects (Goffin, et al. 2010; Newell, et al. 2006), and

• Lack of collaboration because of unsystematic KM in the project environment (Davidson and Jillian 2009).

As is can be inferred from the mentioned KM issues, there are numbers of recognised

gaps in the existing literature, from a KM point-of-view. As discussed earlier, PM maturity

models address the development of PBOs, however, KM has not been addressed in this

framework. In other words, PMMMs, as methodology for developing PBOs and PMOs,

should provide appropriate practices for developing PMOs from a KM point of view. In fact,

not only the existing PMMMs do not discuss the maturity from KM perspectives, but also,

they have just focused on development of PM practices. This gap will be discussed in the

next section to formulate the research problem.

THE RESEARCH PROBLEM 2.5

Problem Definition 2.5.1

According to Love et al. (2003) the cost of rework in Australian construction projects has

been about 35% of total cost, and 50% of total overrun cost. Poor knowledge management

has been recognised as one of the major causes for project inefficiency and/or failure (Love,

et al. 2003). This means that KM is an influential factor, which contributes to both reduce

project costs and improve project performance (Love, et al. 2003). In a consistent manner,

Owen, et al. (2004) emphasise the importance of project KM in project environments as the

critical factor to successfully fulfil the project’ objectives.


Figure 2-5 The development of PM and KM (developed for this research)

Both KM and PM were developed separately until 2000s. Since the late 1950s,

knowledge management studies have concentrated on addressing issues of managing

knowledge in functional organisations (Alavi and Leidner 1999; Schacht and Mädche 2013;

von Krogh, et al. 2012), while PM has been considered as an important approach in the last

three decades. Figure 2-5 presents a glimpse of PM and KM development in the last 50

years, and also it describes the recognised gap in the literature. As shown in the mentioned

figure, since the late 1990s the evolution of the PMO has been considered as one of the latest

developments of PM by which organisation could improve their competencies. According to

Liu and Yetton (2007), more than 50,000 organisations in the US have established or

developed their PMO since 2002 and they predict that in the near future the PMO will be an

inevitable part of organisational structure. PM Maturity Models (PMMM) have been recently

proposed to address both the development of PMO and, also, some of existing challenges

during PMO establishment (Kerzner 2013). In other words, PM maturity models contribute

to improve the maturity levels of PMO through recommending proper PM processes and

practices (Kerzner 2013; PRINCE2 Foundation 2008; Project Management Institute 2013).

KM has been broadly discussed, in functional organisations, to address appropriate

practices for developing organisational competencies. According to (Julian (2008); Kidwell,

et al. (2000); Pemsel and Müller 2012) there is a significant interest in applying knowledge

practices in the project environment, by which enterprise project management could be

developed, however, Leseure and Brookes (2003) believe that KM systems are a critical

1950s

1990s

2000s

1970s


challenge for the development of project environments. This has been discussed by a number

of authors to address various aspects of project knowledge management (Bakker, et al. 2011;

Julian 2008; Lindner and Wald 2011; Pemsel and Wiewiora 2013; Rose 2013; Schacht and

Mädche 2013). Anecdotal data indicates that since 2003, numbers of studies have been

conducted to discuss the management of project knowledge to both discuss the crucial role

of KM in projects, and accentuate addressing KM in the project environment (Arora, et al.

2010; Aubry, et al. 2007; Bresnen, et al. 2003; Koskinen and Pihlanto 2008; Liu and Yetton

2007).

As mentioned is section 2.3.4, the PMO is responsible for coordinating all project

activities within organisations, specifically managing the inter/intra project activities

(Kerzner 2009). Despite the fact that some of the PMO’s issues have been discussed in the

literature, however, there is still some obvious lack of studies to address gaps in PMOs

(Aubry, et al. 2011; Aubry, et al. 2010). In other words, the PMO and proposed maturity

models (PMMM) have not been critically investigated to address the current challenges in

the existing literature. On the other hand, knowledge is an important factor for project

success (Koskinen and Pihlanto 2008). This means that addressing project knowledge

management is an inevitable part of the PMO’s responsibility. In other words, PMO should

address “the integration and management of project knowledge during five phases of

project life cycle: Initiation; Planning; Executing; Controlling & Monitoring; and

Closing”. However, the current PM maturity models are yet to address project KM in

various levels of maturity.

To the best of this researcher’s knowledge, few studies have investigated the role of KM

practices in the PMO. Particularly, the existing PMMMs have not addressed the maturity of

the PMO from a KM point of view. In addition, there appears to be no criterion or measure

to examine the maturity level of PMO from KM perspectives. The research problem is:

“The absence of knowledge management processes and practices in various

maturity levels of the PMO”

The Research Aim 2.5.2

The aim of this study is “To Integrate KM practices in each maturity level of the

Project Management Office”. This aim will be fulfilled through developing and proposing

a comprehensive framework by which KM processes and practices are addressed in various

maturity levels of PMO. This framework will address appropriate KM practices to assist

project stakeholders during the project lifecycle. In addition, this framework will expedite

knowledge flows between project and organisation in order to enrich organisational

knowledge-bases. Moreover, the proposed framework will address some of the current issues

in the PMO, such as lessons learned and knowledge leak.


The Significance of Research 2.5.3

As discussed, the existing PM maturity models do not address the maturity of PMO from

KM point of view. This research aims to address this gap through developing a

comprehensive KM framework. It is anticipated that this framework will address the

required KM practices/processes for each level of the PMO and integrate the KM in the

various levels of PMO. In addition, this framework shall propose numbers of criteria for

assessing the PMO maturity from a KM point of view, as shown at Figure 2-6. The research

contributions are:

• Developing a framework to address KM practices in the current PMMM, and

• Proposing new criteria to assess the maturity of the PMO from a KM point of

view.

Previous attempts to develop the PMO maturity

model

The research contributions

Figure 2-6 The significance of this Research (developed for this research)

The findings of this research shall contribute to improving the efficiency of organisational

project management, and ultimately the organisations’ competitive advantage. Also, this

research shall provide original insights about the role of KM in the PMO to improve

performance and the Project Management Office (PMO).

The Research Questions 2.5.4

According to Yin (2003), defining the research question(s) is one of the most important

steps in the research projects. In fact, the research questions determine the research

objectives, the research design, and also data collection methods (Yin 2009). In order to

The PMO Maturity

Model

Organizational Structures

Project Management

Methods

Maturity Model Approach

Process-based model

Lack of KM Practices

Proposing new Criteria to assess the maturity of the

PMO from KM point of view

Developing a framework to address KM practices for each maturity level of the

PMO


achieve the research aim, and the above-mentioned contributions, three main questions have

been defined, alongside their associated sub-questions as follows:

1) To what extent are KM processes and practices employed in the PMOs? 1.1. What are the current challenges of the PMO from a KM perspective?

1.2. What types of knowledge are required at each phase of project lifecycle?

1.3. What kinds of KM practices are utilised in each maturity level of PMO?

2) How do KM practices contribute to maturity level of the PMO? 2.1. What is the importance of knowledge processes at each phase of project?

2.2. How PMO can contribute to managing the project Knowledge?

3) How can knowledge be integrated in the PM Maturity Model? 3.1. How is knowledge created, captured, transferred and reused in PMOs?

3.2. How can KM practices be employed in each maturity level of the PMO?

The first and second questions will be answered through a case study method, while the

third question will be responded to through both cross-case analysis and development of a

comprehensive framework.

The Research Objectives 2.5.5

Three research objectives have been proposed to make appropriate links between research

questions and the research aim, as follows:

• To analyse the role of KM practices in various maturity levels of PMO To explore challenges of KM in project base organisations (PBOs)

To recognise the required types of knowledge at each level of maturity

To analyse the utilisation of KM practices in the PMO

• To explore the contribution(s) of PMO for managing project knowledge To understand the characteristics of utilised KM practices in various levels of the PMO

To explore the importance of KM processes and practices in the PMO

To analyse the contribution of the PMO from a KM perspective

• To develop a framework to address KM in various maturity levels of PMO To define the required KM practices for each level of the PMO maturity

To integrate KM processes/practices in each level of the PMO maturity

To develop a theory(s) and framework for addressing KM practices in PMMM

To propose appropriate criteria for each level of the PMO from a KM perspective

It is anticipated that achievement of the above-mentioned objectives will contribute to the

development of a theoretical framework.

The Research limitations 2.5.6

The focus of this research is to investigate KM in PMOs where the PMO is considered as

a unit or department in the organisational structure. However, the interactions of PMO with


other business units, in terms of KM activities, will not be considered during the course of

this investigation. In addition, PMBOK has been adopted as the PM methodology in this

study, alongside Kerzner’s model as a PMO maturity model. This means that the findings of

this research might be useful for those selected frameworks mentioned. Furthermore, the

outcomes of this research will address KM practices in PMOs, however, they could be more

likely applicable for other project environments such as single project or Project Based

Organisations (PBO). Also, this research aims to study KM activities from a process point-

of-view rather than from technical and IT perspectives. This means that the IT aspect of KM

will not be discussed in this study and it could be considered for further research.

The Research Purposes 2.5.7

The research will investigate KM practices for each level of PMO maturity, and identify

multiple criteria to assess the PMO maturity from a KM perspective. The research findings

will be useful for a numbers of organisations and individuals, as shown in Table 2-8:

Table 2-8 The benefits of study findings (developed for this research) Targets for research

benefits Contributions from research

Functional Organizations that

intend to establish their PMO

Understanding the role of KM in their PMO development; Implementing and developing the PMO by considering new KM practices;

and Utilising proposed KM practices for each level of the PMO maturity.

Project-based Organisations

Employing appropriate KM practices for their organisations; Understanding the role of KM in their environment; and

Developing their PMO and customising proposed KM practices.

The established/developed

PMOs that seek improvement

Assessing the existing level of PMO from a KM perceptive; Improving the maturity level of PMO and employing appropriate KM

practices for each level; Developing performance of PMO by integrating and collaborating KM

practices.

The PMO and PM consultants

Developing and Assessing the existing level of PMO from a KM perspective,

Employing appropriate KM practices to respond the gap of poor KM practices in PMO; and

Understanding the role of KM in the PMO to develop the road map from a Km point-of-view.

The proposed framework will contribute to improve knowledge management in PBOs at

all levels of PMO maturity.

CONCLUSION 2.6

Both knowledge management and project management are recognised as crucial factors

for developing organisational competitive advantages (Alavi and Leidner 2001; Kerzner

2009). These two disciplines were separately developed until knowledge management was

recognised as a promoter of project success (Koskinen 2000). The convergence of PM and

KM has become more important, when both were identified as critical organisational

competencies. In addition, the evolution of PMO, as a reliable approach for institutionalising


PM methodologies within an organization, has led to the development of maturity models to

address PMO’s improvement. This research recognised that current PM maturity models are

yet to be addressed from KM perspectives, and this important gap was chosen as the subject

of this study.

In order to find solutions for the recognised gap, research problem, questions and

objectives, alongside the contribution and significance of this study, have been defined

accordingly. To fulfil the proposed objectives, a framework is required to support the process

of exploring KM in PMOs. In other words, this framework should create a scaffold for the

investigation, by which the collected data should be analysed. In the next chapter, the

proposed framework will be discussed in detail.

36 Chapter 3 | The Conceptual Framework

Chapter 3

THE CONCEPTUAL FRAMEWORK

INTRODUCTION 3.1

This chapter presents the proposed research framework through a discussion of underlying

premises, components, and ultimately, the rationale for developing this framework. The

preliminary framework will be utilised as a guide for gathering and organising data then it shall

be refined and revised after analysing the collected data.

First, a succinct presentation of current discussions will be followed by a theoretical

foundation of the preliminary framework. Second, the framework’s premises, key terms, and

definitions will be presented. Third, the developed framework will be discussed through

elaborating the theoretical and/or empirical underpinning of the proposed relationships among

its components. Finally, concluding remarks will be presented.

THEORETICAL BACKGROUND 3.2

Knowledge management processes in project environments 3.2.1

People, technology and process are three core components of KM at both functional and

project-based organisations (Davenport 2013; Davenport and Prusak 2000). From a process

point of view, KM is defined as “a systemic and organizationally specified process for

acquiring, organizing and communicating both tacit and explicit knowledge of employees so

that other employees may make use of it to be more effective and productive in their work”

(Alavi and Leidner 1999). Knowledge Management (KM) has been recognised as a critical

factor for both organisational performance and project success (Bakker, et al. 2011; Koskinen

and Pihlanto 2008; Kotnour 2011; Kotnour 2000; Nonaka and Takeuchi 2011). KM in

functional organisations is not similar to project-based organisations since projects are

temporary and teams are disbanded or members leave after project completion (Eriksson 2013;

Gasik 2011; Kasvi, et al. 2003; Schacht and Mädche 2013). In other words, the temporary

nature of projects imposes some issues such as “reparative activities”, “leaking of project

knowledge”, and “reworks” for projects and project-based organisations (Ajmal, et al. 2010;

Desouza and Evaristo 2006; Koskinen and Pihlanto 2008; Love, et al. 2003).

From a process point-of-view, KM is defined as a systematic process of acquiring, capturing,

communicating, and transferring the knowledge of employees to increase their productivity and

organisational competencies (Alavi and Leidner 2001; Gajic and Riboni 2010; Kasten 2010). A

model proposed by Newman and Conrad (2000) introduces four major processes for KM as

Chapter 3 | The Conceptual Framework 37

knowledge creation; retention; transfer; and utilisation, and called this model the “General

Knowledge Model (GKM)”. This model was adopted and developed by Owen and Burstein

(2005) in the project environment context through four KM processes: Creating; Capturing;

Transfer/Sharing; and Reusing (Owen and Burstein 2005). In their study, knowledge

“Retention” and “Utilisation” have been changed, respectively, to knowledge “Capturing” and

“Reusing” and they have kept both “Creation” and “Transferring” in their proposed KM

framework, as depicted at Figure 3-1 (Owen and Burstein 2005). This knowledge process model

has been examined in a number of studies at various project management contexts and it is

claimed that it is valid enough to be considered in any project environments (Morales-Arroyo, et

al. 2010).

Figure 3-1 KM process at project-based organisation (Owen, et al. 2004)

The mentioned framework comprises four KM processes that are interconnected to one

another (Owen and Burstein 2005). According to this model, knowledge is created through

knowledge transferring, while knowledge is transferred by utilising the captured knowledge. In

addition, knowledge is captured from two processes: reusing and creation. This means that after

creating knowledge, a robust system is required to capture that knowledge in order to transfer it.

Moreover, this model addresses the fact that knowledge reusing is dependent on knowledge

transferring and, ultimately, knowledge capturing. In other words, if the knowledge capturing is

not robust, then, knowledge cannot be properly transferred and reused. Also, transferring

knowledge directly impacts on knowledge creation. This knowledge process model has been

examined in a number of studies in various project management contexts and it is claimed that it

is valid enough to be considered in any project environments (Morales-Arroyo, et al. 2010).

Also, this model is the only KM process model that has been developed and examined in a

project environment. Due to the validity of this model, it was adopted as one of the research

premises.

Knowledge management processes in project lifecycle 3.2.2

Project knowledge should be managed during project phases (Eriksson 2013; Owen and

Burstein 2005; Wiewiora, et al. 2009b). According to Owen and Burstein (2005) the most

important knowledge management activities should be undertaken at initiation, planning, and

execution and monitoring phases, while at the closing phase only knowledge capturing is


required. In other words, in the three mentioned phases, i.e. initiation; planning; and execution

& monitoring, all KM processes should be utilised, however, at the closing phase only the

knowledge capturing process should be managed. Table 2-4 illustrates the mentioned discussion

to clarify where KM resides in various phases of project. This model has been employed and

validated by numbers of studies in project management contexts, so it has been adopted as

another premise of the research framework.

Table 3-1 Project phases and KM Processes Adapted from (Owen and Burstein 2005)

Initiation Planning Execution & monitoring Closing

Knowledge Creation √ √ √ Knowledge Capturing √ √ √ √

Knowledge Transferring √ √ √ Knowledge Reuse √ √ √

Tacit and explicit dimensions of knowledge at project environment 3.2.3

Tacit knowledge is a crucial factor for project success and resides in a project’s stakeholders’

minds, while explicit knowledge refers to the codified and articulated knowledge that exists in

project documents and databases (Goffin, et al. 2010; Koskinen and Pihlanto 2008; Srikantaiah,

et al. 2010; Teerajetgul and Chareonngam 2008). Knowledge is created in projects but the

challenge is to capture it, and then make it reusable for various purposes, such as applying to

similar projects and transferring to project team members (Kasvi, et al. 2003). One of the aims

of KM is to provide a comprehensive system for transforming tacit knowledge to the explicit in

which it could be transferred and then utilised for various purposes (Alavi and Leidner 2001;

Nonaka and Takeuchi 1995; von Krogh, et al. 2012). Since tacit knowledge exists in

individuals’ mind, organisations try to employ appropriate KM systems for transforming it to

explicit knowledge. In order to cope with individuals’ resistance, organisations manage this

issue through numbers of ways, such as improving organisational culture and developing proper

systems to change human behaviour (Kasvi, et al. 2003).

In the project context, tacit and explicit knowledge exist in numbers of formats or states such

as; technical knowledge, costing knowledge, and knowledge about clients (Anand, et al. 2010;

Anbari 2005; Arora, et al. 2010; Christensen and Bang 2003). These types of knowledge are

mainly owned by project team members, who rarely aim to share with others, therefore such

knowledge could be lost when project teams are disbanded (Koskinen and Pihlanto 2008).

“Knowledge leakiness and stickiness” has been recognised as one of the major challenges for

PBOs (Love, et al. 2005). According to Love et al. (2005; 2003) poor KM is the main cause of

more than fifty percent of the “cost of rework”, in selected Australian major projects. According

to the current literature, lack of appropriate KM practices to transform tacit knowledge to

explicit knowledge is a major challenge for PBOs (Ajmal and Koskinen 2008; Koskinen and


Pihlanto 2008). The development of a KM system in a project environment could contribute to

the address of some of the current issues, such as reworks.

PMBOK and knowledge management 3.2.4

From a PM point of view, there are two types of knowledge in project-based environments:

1) project management knowledge of (KPM) and 2) knowledge of application area or domain

DM) knowledge (Kasvi, et al. 2003; Project Management Institute 2013). According to

PMBOK (2013) PM practices address the required knowledge to manage projects activities,

while the domain knowledge pertains to the required technical knowledge necessary for

carrying out the project. The PM knowledge is addressed by PM standards and methodologies

such as PMBOK, and PRINCE2, by which numbers of practices and processes are advised to be

utilised during the project life cycle. Domain knowledge is the incorporation of specific

technical knowledge to accomplish project activities (Kasvi, et al. 2003). The knowledge and/or

experience of the integrating of both PMK and DK are important factors in delivering a

successful project (Kasvi, et al. 2003; Koskinen and Pihlanto 2008; Project Management

Institute 2013). In fact, project managers are responsible for the integration of PMK and KM,

through which the success of project is increased (PRINCE2 Foundation 2008; Project

Management Institute 2013).

Table 3-2 KM objects of PMBOK (Reich and Wee 2006)

Type Count Explanation

Total processes 44 The 4th edition of PMBOK comprises of 44 processes which

contains 70 unique inputs and outputs.(Recently in the 5th edition 4 more processes have been included)

Knowledge objects 48 48 Out of 70 input/outputs deal with knowledge management

Explicit/Tacit knowledge 47/1 Majority of knowledge objects are explicit There is only one

object, Enterprise Environmental Factor, contain tacit knowledge

Processes deal with Tacit KM 19 19 out of 44 processes are related to tacit KM and they are

mainly referring to “expert judgment”

As discussed in section 2.3.3, PMBOK is the adopted PM methodology for this research and

it is reviewed and developed every four years. In the latest version of PMBOK 5th five phases

and 10 knowledge areas have been addressed, as shown in Table 2-3. In fact, it guides what

processes should be used at what project phase. For instance, at the initiation phase, PMBOK

recommends two processes: 1) developing the project charter, and 2) Identifying stakeholders.

In PMBOK, knowledge is created from the initial steps of the project to the closing phase

(Reich & Wee, 2006). From a KM point of view, a study was conducted to investigate all

processes and practices in PMBOK 3rd, in order to examine tacit and explicit dimensions of the

existing knowledge objects (Reich & Wee, 2006). According to Reich and Wee (2006) in

PMBOK 47 out of 48 knowledge objects deal with explicit knowledge, while only one object

discusses management of tacit knowledge, as depicted in Table 3-2. This means that PMBOK


has a strong bias toward explicit knowledge through some recommendations for documentation

of project knowledge. In other words, KM practices and specifically, the management of tacit

knowledge, are yet to be addressed in PMBOK (Reich and Wee 2006).

Methods of transforming Tacit to Explicit knowledge 3.2.5

Appropriate utilisation of tacit knowledge is the key for project success (Goffin, et al. 2010;

Koskinen and Pihlanto 2008; Teerajetgul and Chareonngam 2008). Therefore, the

transformation of tacit knowledge to explicit knowledge is a crucial process during a project

lifecycle. In order to develop a system to manage the mentioned transformation, both PM and

organisational cultures play an important role (Ajmal and Koskinen 2008; Davidson and Jillian

2009). This means that two major factors should be considered to develop a KM system: 1) The

maturity PM maturity level organisations, and 2) the culture of organisation from a KM

perspective. Understanding the characteristics of tacit and explicit knowledge is an important

factor for establishing effective practices to transform tacit knowledge to explicit knowledge

(Goffin, et al. 2010). According to Srikantaiah, et al. (2010), various formats and states of both

tacit and explicit knowledge in PBOs, could be categorised as shown in Table 3-3.

Table 3-3 Knowledge types in project context (Srikantaiah, et al. 2010) Tacit knowledge

exists in Explicit knowledge

resides in Methods of transforming Tacit

knowledge to explicit • Face to face

communication - formal and/or informal

• Telephone Conversation - formal and/or informal

• Virtual communication& meetings

• Presentations& video conferences

• Mentoring and Coaching • Study tours • Training • Client knowledge • Best Practices

• Publications and books

• Internal records • Sound/video

recording • Map &graphical

material • Data Warehouses • E-mails • Internet • Intranet • Self-study materials • Newsletters • Groupware

• Formal & informal meetings, networking

• Developing community of practices • Interviews and videotaping • Subject matter experts directories

and/or yellow page • Knowledge /information

repositories • After action review/ project

milestone review • Mentoring programs • Knowledge maps • Requiring strategies • Retention strategies

In order to implement and develop these practices, different levels of capability are required

(Srikantaiah, et al. 2010). In other words, the development of proposed KM practices depends

on a number of factors such as organisational culture, individuals’ behaviour, the existing

systems and processes, and existing information technology infrastructure (Christensen and

Bang 2003; Desouza 2006; Diakoulakis, et al. 2004; Leidner, et al. 2008). This means that

organisational readiness is a critical factor for successfully implementing such a KM system

(Davidson and Jillian 2009). These practices will be used to develop the KM process models, as

discussed in section 3.5.2.


Project management maturity model 3.2.6

Project Management (PM) is an application of knowledge, skills, tools, and techniques to

meet project objectives (Project Management Institute 2008a). The Project Management Office

(PMO) is a relatively new function in organisations, to develop, oversee and maintain project

management activities (Project Management Institute 2013; Spalek 2012). PM Maturity Models

(PMMM) have been proposed to address the development of PMOs (Hsieh, et al. 2009;

Kankanhalli and Pee 2009; Kerzner 2005). A number of PMMMs have been developed to

address associated practices to establish the PMO, such as, Organizational Project Management

Maturity Model (OPM3), Portfolio Program Project Management Maturity Model (P3M3), and

3) Kerzner’s PMMM, as discussed in the section 2.3.5. The Kerzner’s PMMM has been utilised

by many organisations and it’s known as one of the more reliable PMMMs, which could be

used with most of the PM methodologies. As explained, Kerzner’s PMMM has been adopted as

other premises of this research, and it will be discussed in the next section.

Kerzner’s Maturity Model 3.2.6.1

The Kerzner’s PMMM (K-PMMM) proposes a step-by-step methodology to address the

specific processes and procedure at each level of maturity. It addresses the development of

PMBOK in PBOs in five levels of maturity: 1) common language, 2) common process, 3)

singular methodology, 4) benchmarking, and 5) continuous improvement (Kerzner 2005;

Kerzner 2013). As shown at Figure 3-2, the first level of maturity, which is called “common

language”, the importance of PM has been raised and, also, the need for developing a common

language for PM among project team members is becoming apparent. In other words, not only

do project team members not use the same jargon, so as to be understood by others, but also

there is no PM methodology in place to address basic processes of managing projects. This

means that projects: 1) are hero driven, 2) do not follow a certain method, and 3) are faced with

numbers of challenges (Kerzner 2013)

Figure 3-2 Kerzners’ Maturity Level (2005)

After implementing and developing basic PM processes, which are utilised by project team

members as a common language, the maturity of PBO is elevated to level two or “Common

Continuous Improvement

Common processes

Singular methodology

Benchmarking

Common Language

Level of Maturity

Com

petitive advantages

Level 5

Level 4

Level 3

Level 2

Level 1


Process”. At this level, there are some basic processes to address fundamental PM practices,

such as time and cost management, for managing project activities. Also, senior managers have

realized the importance of PM so they support the development of the PMO to reach the upper

levels of maturity (Kerzner 2005).

At the third maturity level, a comprehensive PM methodology should be utilised as the

“Singular Methodology” among all project team members. This means that the PMO has

developed the previous PM standard to the level at which both basic and some of the advanced

PM practices have been properly addressed. In other words, PBOs has gone to the level that: 1)

all utilised PM practices have been integrated at one PM standard, 2) all various PM

methodologies have been combined in one organisational-wide PM methodology, 3) Project

team members actively adhere to the developed PM standard (Kerzner 2005).

At the “Benchmarking” stage, the fourth level, the focus is to both improve the current PM

processes and, ultimately, address all knowledge areas of PMBOK. This means that PBOs have

been achieved to a level in which all PM processes have been integrated at an organisational

level and, therefore, projects could be interrelated to organisational strategies (Kerzner, 2005).

And eventually, the fifth level is called “Continuous Improvement” in which the PM

methodology is continuously improved through “benchmarking information” and the main

focus of this is to enhance the organisational competitive advantages (Kerzner 2005).

In summary, K-PMMM addresses various PM practices at different levels of maturity by

which PBOs could both develop the basic requirements for the specific level, and prepare

prerequisites to achieve the next level of maturity. It also comprises a number of criteria to

dynamically assess the quality of PM. The aim of utilising the K-PMMM is to develop the

organisational capabilities and culture in order to incorporate PM practices in organisational

processes and procedures (Kerzner 2005). In addition, it is a road map to address practices,

based upon the status of PM functionality, for enhancing organisational competencies from a

project management point of view. However, this framework, similar to other PMMMs, is yet to

be addressed from a KM perceptive.

Knowledge Management Maturity Model 3.2.7

Similar to PMMM, a KM Maturity Model (KMMM) is an accepted framework to

progressively develop a KM system in organisation (Feng 2006; Kankanhalli and Pee 2009).

KMMM contributes to the improvement of KM activities through both formulating the

development of a KM system, and assessing the effectiveness of the existing KM activities

(Feng 2006). There are numbers of proposed KMMMs in the existing literature to adopt and

follow for undertaking the journey of KM system development (Desouza 2006; Feng 2006;

Hsieh, et al. 2009). A study was conducted by Feng (2006) to investigate the current KMMMs

and then develop a comprehensive KMMM. At its conclusion, this study advised the three


following criteria to select appropriate KMMMs:1) objectives to be attained at each maturity

level, 2) KM practices and processes, and 3) KM enablers. This means that there are three

practices that are recommended to be considered before adopting any KMMM. At first, the

objective of developing such as KM system, should be defined as the ultimate aim to be reached

at each level of maturity. Second, a set of processes and practices are required for satisfying

determined criteria. KM processes comprise a number of practices by which inputs, such as tacit

or explicit knowledge, create some outputs, such as explicit knowledge, through utilising some

tools and techniques. Third, the enablers are those tools, technologies or systems which both

facilitate the KM processes and contribute to objective satisfaction.

In addition, an integrated KMMM was developed by Feng (2006) to address the

development of a KM system in five levels of maturity, as shown in Table 3-4. In the proposed

framework, four KM processes: Creation, Storage, Sharing and Application, have been

discussed at five levels of maturity. This model discusses the improvement of this KM system

through: 1) defining the objective for each level of maturity and expectations from a KM point

of view, 2) proposing appropriate KM practices that should satisfy associated processes, 3)

addressing proper tools and enablers that support each of the KM processes, 4) illustrating the

required structure at each level of maturity, 5) proposing criteria to assess the maturity level

(Feng 2006).

In the mentioned model, two types of enablers are discussed, i.e. structure, and science and

technology. Organisational structure plays an important role for managing knowledge, hence,

certain requirements should be met to achieve each level of maturity. For instance, at the third

level of maturity it is recommended to develop a KM unit within the organisational structure for

taking on the responsibilities of KM. Also science and technology are introduced as crucial

enablers for KM systems, specifically at upper levels, by which KM is facilitated and elevated

(Feng 2006). In this framework, the first three levels of maturity are the most important stages

for preparing a robust KM system, while the fourth and fifth levels focus on both improving and

maintaining previous levels’ achievements through developing some systems and practices for

auditing and measuring the performance of the KM system.


Table 3-4 KM maturity model, proposed by Feng (F-KMMM) (Feng 2006)

KK Maturity

KM Processes Creation Storage Sharing Application

First level • At this stage required preparation works are undertaken and KM processes and practices should be defined and planned

Initial activities

• SWOT analysis, Feasibility study and requirements analysis • KM concepts definition, Challenges against KM, KM evaluation for organisation

Second level

• Valuing knowledge creation

• Respecting to the originality of K.

• Developing K. documentation

• Developing repository systems

• Facilitating informal communication

• Developing process to reuse existing knowledge

Enablers and tools

• Learning tool • Plot assistant design • Simulation Software • Brain and thinking

support systems

• Electronic notice board

• Document edit S/W

• Database

• Electronic notice board • Video Conference

meeting • Email and Chat room

• Interface design S/W

Common initiatives and

tools

• Defining the concept of KM in practice • Developing Internet, Intranet and any types of networks in organisation • Developing community of practices

Third level

• Developing K. creation strategies

• Establishing formal K. creation

• Developing processes for refining K.

• K. conformity check

• Storing K. in suitable place

• Establishing and developing formal channels for sharing K.

• Education and Training • Enhancing the security

of K. sharing

• Developing systems to support K. application

• Dividing the work areas to related functions

Enablers and tools

• Data mining • Documentation

Search • Knowledge detection

tools • Idea implement

assistant tools • Case-based reasoning

systems • Pattern simulation • Concurrence

filtration systems

• Data Repository • Data storage • File management

systems • Case-based

reasoning systems • FAQ • Work process

systems • Expert systems

• Search engine • Knowledge list • Knowledge map • Content-based original

search • Online learning systems • Expert yellow page • Expert training systems • Regular seminar and

workshops

• Expert systems • Work process

systems • Online prompt

analysis • Decision support

systems


tools

• Establishing a unit to take the responsibility and accountability of KM • Systematically Supporting KM • Establishing and developing standard for KM • Developing KM sub processes

Fourth level of KMM

• Developing the K. creating sub-processes

• Developing the K. storage sub-processes

• Developing the K. sharing sub-processes

• Developing K. app. sub-processes

Enablers and tools

• Measuring the K. creating success

• Measuring the K. storage success

• Measuring the K. sharing success

• Measuring K. application success


tools

• Measuring the success of KM through indexes and Critical success factor (CSF) • Measuring the success of KM sub-processes • Putting control in place for all KM processes and activities • Developing an Audit unit for measuring the KM

Fifth level of KMM

• Continuously improving the KM processes and procedures • Developing the KM control and audit systems and unit • Integrating the KM processes and procedures

Enablers and tools

• Developing and research Unit in the KM department • Developing a Decision making unit in the KM department


The F-KMMM has been examined and then refined by Feng (2006) in a couple of

organisations, such as a commercial bank and a governmental organisation. It is believed that

this model could be utilised as a reliable benchmark for developing an organisational KM

system (Feng 2006). However, to the best of this researcher’s knowledge, F-KMMM has not

been investigated in any PBOs, specifically in the PMO. Since F-KMMM has not been

examined in the PBOs, in the next step it is compared to other existing KMMMs to make sure

that it is valid enough to be utilised in the research framework. One of the latest KMMMs,

which is valid enough to use at all types of organisations, is General KMMM or G-KMMM

(Kankanhalli and Pee 2009). According to Kankanhalli and Pee (2009), G-KMMM could be

adopted by both functional and PBOs to improve KM through the following level of maturity:

1) Initial, 2) Aware, 3) Defined, 4) Managed, and 5) Optimising, as illustrated in Table 3-5. The

G-KMMM comprises three KM players: People, Process, and Technology to address the

following:

• What are the expectations at each level of maturity,

• How should process and technology be implemented at each level of maturity,

• How should organisations prepare the people side of KM at each level,

• How should KM processes be integrated with organisational processes, and

• How should KM players be collaborated?

Despite the fact G-KMMM does not discusses proper KM practices at each level of maturity,

it provides useful indications to address expectations from each level. Also, it covers the people

side of KM, which is not the scope of this study. This means that this research aims to focus on

“Process” and to some extent “Technology” sides of KM players, therefore, “People” will not

be covered in this research.

According to Kankanhalli and Pee (2009) their proposed framework, G-KMMM, has been

examined in a number of organisations and they have concluded that it could be adopted by any

types of organisations in order to develop the KM system. In addition, an assessment method

has been developed in this framework to evaluate both the existing KM system and the

effectiveness of implementing KM practices. In general, it is claimed that G-KMMM is robust

and comprehensive enough to be employed by any organisations in improving their KM

practices (Kankanhalli and Pee 2009).

Generally speaking, G-KMMM is more comprehensive since it addresses all KM players,

but F-KMMM mainly focuses on the processes of KM in various levels of maturity. Also,

research findings confirm that not only there is no major difference between these two

frameworks, but also, they could be utilised as complementary methods. For instance, it was

realised that G-KMMM KM practices have not been specifically addressed, while in F-KMMM


it is the opposite. Therefore, the amalgamation of both models could create a comprehensive

KMMM.


Table 3-5 General KMMM (Kankanhalli and Pee 2009)

Maturity Level

General Description

KM Players People Process Technology

Initial

• Little/ no intention to formally manage Organizational K.

• Organization and employees are not aware of the need to formally manage knowledge

• No formal processes to manage organizational knowledge(K)

• No specific KM technology or infrastructure in place

Aware

• Organization has the intention to manage its organizational knowledge

• Management is aware of the need for formal KM

• K. is indispensable for performing routine task is documented

• Pilot KM projects are initiated, but not necessarily by Management (Mgmt.)

Defined

• A basic Infrastructure to support KM has been put in place

• Mgmt. is aware of its role in encouraging KM

• Providing training on KM • Developing KM strategy • Defining Individual KM

roles • Developing incentive

system

• Formalising processes of content info. Mgmt.

• Measuring the KM utilisation on organisational productivity

• Basic KM Infrastructure in place (e.g. single point of access)

• Some enterprise-level KM projects are put in place

Managed

• KM initiatives are well established in the organization

• Common strategy & standardised approaches towards KM

• Incorporating KM into organizational strategy

• More advanced KM training

• Quantitative measurement of KM processes (i.e., use of metrics)

• Enterprise-wide KM systems are in place

• Usage of KM systems is at a reasonable level

• Seamless integration of tech. architecture

Optimizing

• KM is integrated into organization & is continually improving

• It is an automatic component in any organizational processes

• Culture of sharing is institutionalized

• KM processes are constantly improved

• Existing KM processes are adapted to meet new business req.

• KM procedures are an integral part of the organization

• Existing KM infrastructure is continually improved

To the best of this researcher’s knowledge both G-KMMM and F-KMMM have not been

examined in any PBOs and, consequently not in PMOs. In other words, incorporation of KM

maturity models in PBOs is yet to be discussed in the current literature. Hence, KM is the

missing part in project environments and needs to be appropriately discussed.

CONCEPTUAL FRAMEWORK PREMISES 3.3

This section aims to clearly present the research domains, theories and assumptions to build

up the research framework. This framework was developed based on the above mentioned

discussions and comprises some adopted models or assumptions.

Types of the required knowledge 3.3.1

After thoroughly studying the current literature, eight types of knowledge have been chosen

in the research framework, as depicted in Table 3-6. This classification of knowledge is part of

the theoretical framework, which is being examined in selected case studies in order to analyse

the importance of each type of knowledge at various maturity levels of PMOs. In addition, it


was assumed that all forms of knowledge could have tacit or explicit dimensions. Table 3-6

depicts this classification and illustrates them from tacit and explicit points of view.

Table 3-6 Types of knowledge in research framework (developed for this research)

Types of knowledge Tacit or Explicit knowledge Project Management

Knowledge PMK are addressed in standard (explicit) also, exist in PM’s experience

(tacit ) so It could be both tacit and explicit Knowledge about

Processes/procedures Procedures and processes generally are addressed through instructions

and manual, so, it is more explicit than tacit

Technical Knowledge Technical knowledge could explicit , however, their application is

important which reside in people’s mind, so it is assumed that it is more tacit knowledge

Knowledge about Clients This type of knowledge is more tacit since it is not easy to codify all of relations with clients.

Costing Knowledge Costing happens through documents but this type of knowledge is more explicit.

Legal and Statutory Knowledge

Documentation of laws and regulation is essential, therefore, this knowledge is more explicit knowledge and obtained through

documents. Knowledge about Supplier Similar to knowledge about client, it has a tacit nature of knowledge

Knowledge of Who Knows What

If organization has a good system to recognize and capture address knowledge owners it could be explicit, otherwise it is tacit

Knowledge Management Processes in PMOs 3.3.2

From a process point-of-view, the proposed KM processes by Owen et al. (2004) have been

adopted in the research framework. As shown at Figure 3-3, it is assumed that there are four

processes for managing knowledge: 1) creation; 2) capturing; 3) transferring; and 4) reusing. In

addition, it is assumed that knowledge is generally created in PMOs but the first priority is to

capture the current knowledge. This means that without proper knowledge capturing,

knowledge reusing and transferring will be problematic. Also, it is assumed that there is a strong

relationship between knowledge transferring and reusing. In the research framework, knowledge

reusing will not properly conducted without appropriate knowledge transferring. And finally,

new knowledge is created through proper knowledge transferring.

Figure 3-3 The research KM processes model (developed for this study)

KM practices are defined as methods, tools or activities to support and facilitate the KM

processes (Ajmal, et al. 2010; Alavi and Leidner 2001; Bredillet 2008). Since KM practices

have various functionalities, KM sub-processes were defined to inter-relate KM practices to KM


process, as shown in Figure 3-3 and Figure 3-4. In other words, the KM sub process connects

similar KM practices to KM processes. Consequently, for each KM process, specific practices

were adopted, through which KM is facilitated and applied accordingly.

Figure 3-4 KM process and practices model (developed for this research)

In the research framework, each KM process entails some sub-processes by which KM

practices are correlated to the KM process. For instance, knowledge capturing comprises four

sub processes: Identification, Storing, Classification and Selection. In addition, knowledge

identification has numbers of practices such as expert locator, as shown in following tables. As

could be seen, the similar functionality of the mentioned three KM practices convinced us to put

them in the same sub-process. It should be mentioned that development of this classification has

been initiated through scrutinising some of the proposed models by (Kasten (2010); Lytras and

Pouloudi (2003); Ribeiro and Ferreira (2010)); (Barclay and Osei-Bryson (2010); Newell, et al.

(2006); Nissen, et al. (2000)). In the following sections each of the four processes and their

associated sub- processes will be correlated to proposed KM practices.

According to Nonaka and Takeuchi (1995; Nonaka and Takeuchi 2011), knowledge is

created through four processes, Socialisation, Externalization, Combination and Internalization,

which are called SECI. In order to develop the knowledge creation framework, the SECI model

was employed alongside the proposed KM practices by Feng (2006) and Kankanhalli & Pee

(2009). In total, more thirteen KM practices, which could be utilised for knowledge creation

purposes, were recognised in the literature, as shown in Table 3-7 (Carrillo 2005; Love, et al.

2003; Newell, et al. 2006; Nonaka and Takeuchi 2011).

Table 3-7 Knwoledge Creation pratices in project enviroments (developed for this research)

Knowledge Creation Sub Processes

Practices for Knowledge Creation

Socialisation • Formal and informal event • Workshops & seminar • Community of practices

Externalization • Workshops & seminar • Deductive & Inductive

thinking

• Experts system • Experience Report • Community of practices

Combination • Community of practices • Best Practice Cases

• Knowledge Broker • Data mining • Documentation search

Internalization • Research services • Simulation

• Experimentation

KM Process

KM Sub-process

KM Practices


For instance, externalisation is a sub-process to transform tacit to explicit knowledge. As

Table 3-7 depicts, in total, five practices have been proposed to support the externalisation sub

process. These practices are practical methods or tools to elicit an individual’s mind (Alavi and

Leidner 2001; Caniëls and Bakens 2012; Hoegl and Schulze 2005; Kasvi, et al. 2003;

Kloppenborg 2014; Owen and Linger 2011). The proposed practices are being examined in the

selected case studies to explore: 1) what KM practices are utilised at PMOs, 2) how they have

been employed and developed, and 3) what are challenges of utilising them.

Table 3-8 Knowledge capturing practices in project environment (developed for this research)

Knowledge Capturing Sub Processes

Practices for Knowledge Capturing

Knowledge Identification

• Expert locator • Knowledge repositories

• Knowledge detection tools • Formal and informal event

Knowledge Storing • Data base • Formal and informal event

• Document Management System (DMS)

Knowledge Classification

• DMS • Frequently ask questions

(FAQ) • File management system

• Management information system (MIS)

• Intranet

Knowledge Selection • Knowledge inquiry system • Data base • Frequently ask questions (FAQ)

According to the research framework, knowledge capturing comprises four sub-processes,

as presented in Table 3-8. The recognised practices to support knowledge capturing were

classified in four sub- processes: identification, storing, classification and sec lection (Alavi and

Leidner 2001; Barclay and Osei-Bryson 2010; Caniëls and Bakens 2012; Lytras, et al. 2002;

Owen and Burstein 2005; Tan, et al. 2007). As presented in Table 3-8, in total, eleven practices

were adopted to support knowledge capturing, and its associated sub processes. These practices

could be used for both measuring the maturity of PMO from a KM point of view, and also,

could be a guide to employing the appropriate process, with regards to level of maturity.

Table 3-9 Knowledge transferring pratcices in project enviroment (developed for this research) Knowledge Transferring

Sub Processes

Practices for Knowledge Transferring

Knowledge Distribution and

forwarding

• Project bulletin and reports

• Communication channels • Knowledge list

• Video and Tele Conference meeting • Yellow page • Intranet • Data base

Knowledge Sharing • Knowledge map • Formal and informal

events

• Training • Mentoring

In the research framework, two main sub processes i.e. knowledge distribution &

forwarding, and knowledge sharing, have been defined for knowledge transferring. In total,

eleven practices have been adopted as practices to facilitate both the mentioned sub-processes

and, ultimately, knowledge transfer, as shown in Table 3-9 (Ajmal and Koskinen 2008; Bakker,


et al. 2011; Feng 2006; Kankanhalli and Pee 2009; Kasvi, et al. 2003; Landaeta 2008; Lytras

and Pouloudi 2003; Wiewiora, et al. 2010).

For the knowledge reusing process, three sub-processes have been defined: Adapting,

Applying and Integrating, in which each one comprises numbers of practices. In total, eleven

practices have been adopted in the research framework by which knowledge reusing is

facilitated (Bell 2010; Feng 2006; Kamara, et al. 2003; Lytras and Pouloudi 2003; Morales-

Arroyo, et al. 2010; Tan, et al. 2007). As could be seen in Table 3-10, some of the practices are

similar to the practices that exist in knowledge transferring or capturing processes. This means

that some of the recognised practices could contribute to more than one knowledge process,

such as data bases, and Intranet.

Table 3-10 Knowledge reusing practices in project environment (developed for this research) Knowledge Reusing

Sub Processes Practices for

Knowledge Reusing

Knowledge Adapting

• Electronic notice board • Documents management

system (DMS) • Intranet

• Data base • Yellow page • Knowledge detection tools • Formal or informal events

Knowledge Applying • Expert systems • DMS

Knowledge Integrating • Knowledge map • Data mining

In summary, the KM framework comprises four KM processes that have been classified to

thirteen sub-processes, in which they are supported by numbers of KM practices. This

framework, as shown at Figure 3-3, represents assumed relationships among KM practices, sub-

processes and processes. All mentioned processes, sub processes and their associated practices

have been defined in a tree format and, then, it has been used to fit in with Nvivo’s requirement

for nodes and categories.

Project management maturity model 3.3.3

As discussed, the developed research framework will be examined in various maturity levels

of PMOs. The level of maturity should be determined through current PM maturity models

(PMMMs). To do so, the Kerzner’s PMMM (2005; Kerzner 2013) has been adopted to assess

the maturity level of selected cases. As discussed is section 3.2.6.1, K-PMMM has been

proposed based upon the PMBOK, and it comprises of five levels of maturity (Kerzner 2005).

K-PMMM has been adopted to fulfil following purposes:

1) To determine the maturity level of case studies, from a PM point of view,

2) To develop the research framework based upon research findings.

To do so, firstly the maturity of case studies is assessed by K-PMMM, then a research KM

framework will be utilised to collect data from selected cases. Ultimately, it is expected that the

research framework shall be developed alongside a number of propositions aimed at addressing

original research questions.


Knowledge management maturity model 3.3.4

As discussed earlier there are numbers of KMMMs in the literature. In this investigation, the

two following KMMMs were discussed: F-KMMM and G-KMMM. The research KM

framework (R-KMMM) has been developed through amalgamating these frameworks, as shown

in Table 3-11. The developed R-KMMM has two major contributions in this research: 1) It was

used to develop the KM framework, and 2) It will be employed to investigate the selected case

studies from a KM point of view. This preliminary framework will be refined through analysing

the research findings.

CONCLUSION 3.4

In this chapter, after a succinct review of associated literature, the research framework was

developed under the following premises: 1) KM processes, sub processes, and practices, 2)

PMMM as a method to both assess the maturity level of PMO and develop the research

framework, 3) PMBOK as project management methodology, and 4) R-KMMM as the method

to address proper KM practices at various maturity levels of PMO. In the next step this

framework should be examined by utilising the collected data from cases. This means that an

appropriate research methodology is required to facilitate both collecting accurate and reliable

data, and analysing the gathered information in order to test the preliminary research

framework. The next chapter has been assigned to thoroughly discuss the research design and

methodology.


Table 3-11 The customised KM Maturity Model or R-KMMM (developed for this research)

Level of Maturity Conditions

KM Processes

Knowledge Creation Knowledge Capturing Knowledge Transferring Knowledge Reusing

First Level, Initiating KM in

PMO

In general • There is little or no intention to formally manage project knowledge. • PMO and projects team members are not properly aware of the need to formally manage knowledge.

• There is no specific KM technology or infrastructure in place. • There is no formal process to manage project knowledge.

Initial activities

and/or enablers

• Firstly, SWOT analysis, Feasibility study and requirements analysis should be undertaken to initiate developing KM system at the PMO. • Initial definition of KM concepts as well as undertaking current KM challenges in the PMO, are required at this level. • At this stage both required preparation works and planning for KM processes and practices should be undertaken. • Some of basic practices might be conducted to manage knowledge capturing and creation. • There is no or limited practices support knowledge reusing and transferring.

Second level, Increasing KM awareness and

developing basic PM

processes in the PMO

In general • PMO management and top managers have realised the importance of project KM. • Management is aware of the need for formal KM system. • The concept of KM and has been defined and understood by projects team members. • Knowledge capturing improves through developing documentation and repository systems • There is no one or unit for being responsible of KM

• Knowledge capturing and creation should be improved in compare to previous. • There are some practices in place to support knowledge transferring and reusing. • Internet, Intranet and any types of networks in PMO contribute to KM • Informal communications are facilitated to help knowledge creation and transferring

Knowledge

management

practices

• More practices in place in comparison to previous level

• Integration with other KM practices has not been undertaken yet

• More practices in place in comparison to previous level

• Integration with other KM practices has not been undertaken yet

• Proper KM practices have been developed to support knowledge transferring

• At least one practice, specifically , is in place to support knowledge reusing

Third level, Developing proper KM

system in the PMO

In general

• There is a basic Infrastructure in place to support KM. • PMO and top managers are aware of their role in encouraging KM. • There is a unit or person to take the responsibility and accountability of KM. • KM is systematically supported through proper systems and established standards. • There are some training courses to instruct KM in the PMO. • KM strategies have been developed in line with PMO and, ultimately organisational strategies.

• There are numbers of integrated processes and procedures to be followed. • Basic KM Infrastructures have put in place and are being utilised. • There are some incentive systems to encourage project team members to follow KM procedures • Some KM practices are integrated at enterprise-level KM. • Individual roles for managing knowledge have been defined.

Knowledge

management

practices

• Knowledge creation strategies have been developed and translated into KM practices.

• Formal knowledge creation system should be established.

• Proper KM practices have been developed to create knowledge through transferring

• The integration with other KM processes has been undertaken.

• Knowledge capturing strategies have been developed and translated into KM practices.

• Proper KM practices to support knowledge selection and classification have been developed.

• Proper systems to capturing knowledge have been developed and collaborated.


• Knowledge transferring strategies have been developed and translated into KM practices.

• Proper KM practices have been developed to prepare formal channels for sharing Knowledge

• Education and Training are been conducted properly • Robust system should be in place to ensure the security of

Knowledge transferring. • The integration with other KM processes has been

undertaken.

• Knowledge reusing strategies have been developed and translated into KM practices.

• Robust systems and practices are in place to support applying Knowledge.

• Decision support systems and expert systems should be developed.


Fourth level, Managing projects’

knowledge in the PMO and

integrating project KM

with organisational

KM

In general

• Project KM and organisational strategies have been collaborated. • The role of project KM to improve organisational competitive advantages has been realised. • PMO KM practices and processes have been integrated with organisational KM activities. • KM initiatives have been properly established in the PMO. • PMO KM standards have been integrated with PM standards • Advance trainings and workshops to improve the KM are being conducted

• Existing KM unit in PMO have been integrated with organisational KM department • All KM systems have been integrated • Measuring the KM utilisation on project productivity is being conducted • Everybody is responsible for managing project knowledge. • Numbers of quantitative index, critical success factors (CSF), and metrics have been developed to measure

the effectiveness of KM processes.

Knowledge

management

practices

• Knowledge is properly created through all sub-processes(SECI): Socialisation, Externalisation, Combination and internalisation

• The integration with other KM processes has been conducted at organisational level.

• Success of Knowledge creation processes is being measured.

• Knowledge is properly captured through its sub-processes: Identification, Storing, Classification, and Selection.


• Success of Knowledge capturing processes is being measured.

• Knowledge is properly transferred through its sub-processes: Sharing, and Distributing & Forwarding


• Success of Knowledge transferring processes is being measured.

• Knowledge is properly reused through its sub-processes: Adapting, Applying and Integrating


• Reusing through transferring is well-managed. • Success of Knowledge reusing processes is

being measured.

Fifth level, Optimising the KM system in

the PMO

In general • Culture of sharing and knowledge transferring has been institutionalized. • Both organisation and PMO utilises an integrated KM system. • An audit unit should be developed for measuring the KM. • KM is integrated into organisation and it is continually improving.

• KM procedures are an integral part of the PM methodology as well as organisational process asset. • The existing KM infrastructure is continually improved to support all KM improvements • All KM processes have an automatic component in place. • Project KM and competitive advantages have been collaborated to support organisational strategies

Advance

Improvements • A research unit should be developed in KM department for supporting the optimization of the KM in both PMO and organisation. • Development of a decision making unit in the KM department will contribute to enhancing organisational competitive advantages

Chapter 4 | Research Design 55

Chapter 4

RESEARCH DESIGN

INTRODUCTION 4.1

This chapter aims to present the research design, data collection methods, and analysis

approaches in order to illuminate the proposed research questions. This approach allows the

researcher to investigate the phenomena and, also, examine a preliminary framework in order to

explore the current activities of PMOs from a KM point of view. It is expected that the preliminary

framework shall be refined through research findings and, ultimately, numbers of propositions and

recommendations will be developed to answer research questions and propose the final framework.

Chapter four comprises the following sections. First, the research flow has been presented in

section 4.2 to review the research questions, followed by section 4.3 to discuss the epistemological

and philosophical position of this research. Second, in sections 4.4 and 4.4 4.5, the research design

and selection of research methodology will be discussed to explain the appropriateness of employing

a case study. Third, the research implementation method and data collection techniques have been

discussed in 4.6 and 4.7. In sections 4.8, and 4.9, data analysis and the research quality have been

explained, followed by the conclusion in section 4.10.

A SNAPSHOT OF RESEARCH FLOW 4.2

The lack of addressing KM practices in the various maturity levels of PMO has been recognised

as the main research gap. This research was conducted to address the recognised gap through

answering following research questions:

1) To what extent are KM processes and practices employed in the PMOs?

2) How do KM practices contribute to the maturity level of the PMO?

3) How can knowledge be integrated in the PM Maturity Model?

As presented in Chapters 2 and 3, the current literature does not address the above mentioned

questions. In Chapter 4, a preliminary framework was developed based upon current literature. This

framework will be examined through appropriate research methods. As will be discussed later, 1)

this research follows the constructivism paradigm, 2) it is inductive and has an exploratory nature,

and 3) case study is the best research method with which to achieve the research objectives.

EPISTEMOLOGICAL AND PHILOSOPHICAL POSITION OF THIS RESEARCH 4.3

It is necessary to have a good understating of the philosophical and epistemological position of

research before conducting any further steps or actions (Creswell 2009; Gray 2009; Guba and

56 Chapter 4 | Research Design

Lincoln 1994). The research paradigm is “A basic set of beliefs that guide actions”, by which the

steps of research could be properly defined through adopting a suitable worldview (Creswell 2009).

According to Guba and Lincoln (1994) there are four paradigms or worldviews for designing a

research study: Positivism, Post-Positivism, Critical Theory, and Constructivism. Positivism and

post-positivism paradigms assume that the reality exists and it could be critically measured through

quantitative research methodologies; in contrast, constructivist perspective resides where there are

many realities with no single truth in the existing complex world (Guba and Lincoln 1994).

According to Creswell (2009) a constructivism paradigm has an inductive approach by which

numbers of theories could be developed through investigating the phenomena. In addition, a

constructivism worldview is a suitable approach for both exploratory and qualitative research

(Creswell 2009). In other words, this paradigm follows the inductive approach to comprehend the

existing reality of the subject under study, through exploring views/thoughts of multiple participants.

This researcher believes this study: 1) has an exploratory nature, 2) is an inductive research, 3) aims

to develop a number of propositions and hypotheses to address research questions, 4) deals with

participants’ thoughts and follows the qualitative approach for data inquiry to explore under-study

phenomena, 5) does not aim to verify of falsify the existing theory, 6) aims to construct and propose

a framework through qualitative methods in order to address knowledge management practices in the

project management office, and therefore 7) follows the constructivism paradigm.

Research design is “a logical plan for getting from here to there”, in which “here” refers to

research questions and “there” directs the research results (Yin 2009). According to Creswell (2009)

research design is a combination of plans and procedures to explain how research questions are

answered through spanning broad decisions to methods of data collection and analysis. There are

three popular research designs or methodologies: Qualitative, Quantitative, and Mixed method in

which qualitative design entails open-ended question(s) with an inductive approach and uses

“words”, while, quantitative research involves closed-ended question(s) with a deductive approach

and uses “numbers”, and mixed method is the combination of both (Creswell 2009).

This research follows a qualitative approach because of the following reasons:

• The research aims to answer questions through using “words” rather than “numbers”,

• The nature of research is exploratory and aims to understand the existing phenomena,

• The main aim is to develop a theory and framework, hence it follows inductive approach

rather than deductive (see section 4.3), and

• This research will be undertaken in the real world, through conducting case studies.

With regards to inductive approach and the explorative nature of this research, appropriate data

collection methods as well as analysis techniques should be employed to achieve research objectives.

Accurate data and information is crucial to undertake proper analysis for providing quality outcomes


(Corbin and Strauss 2008; Gray 2009; Yin 2009). The triangulation approach is the highly

recommended strategy to obtain reliable data to understand what happens in reality (Creswell 2009;

Yin 2009). It contributes to provide credible and quality data by which phenomena are being

investigated from various perspectives (Yin 2009).

RESEARCH METHOD 4.4

The case study method has been selected as the main methodology. This method has been

recommended as one of the popular approaches to investigate under-study phenomena in the fields

of social science, management and information systems (Creswell 2009; Gray 2009; Yin 2009).

According to Yin (2009), a case study is an in-depth study of a subject in a real life context, by

which researchers have the opportunity of observing phenomenon, where the phenomenon is

influenced by or impacts on other entities and components.

Figure 4-1 Research methods and data inquiry techniques (developed for this research)

In order to gather proper data and information from the selected case studies, four data collection

methods and techniques, Interview, Direct observation, Questionnaire, and Document analysis, have

been employed, as shown at Figure 4-1. Also, Grounded theory was chosen as the research analysis

method. In the next sections, the reasons for choosing case study have been discussed.

The Rationale for selection of case study 4.4.1

According to Yin (2009), there are four major research methods: Experiment; Case study;

Survey; and Archival analysis. One of the most important factors to adopt an appropriate research

method is the “type of research question”. Table 4-1 illustrates the type of research questions and

their suitable research method. According to Yin (2009) if the research questions contain “how and

why” statements, then “case study” and “experiment” are recommended as suitable research

methods. In a consistent manner, Creswell (2009), advocates the suitability of case study for

qualitative research, especially, where it deals with “why and how” questions.

With regards to existing discussions in the literature, experiment is mainly utilised for

quantitative studies, while case study is advised for qualitative research during the specific time

without considering their frequencies (Creswell 2009; Yin 2009). In addition, experiment is

appropriate in which a researcher needs to control the under-study subject; in contrast, the aim of

Research Method

Case Study

Interview Observation Questionnaire Document Analysis


employing case study is to study the subject as it is, without having any control over them (Yin

2009).

Table 4-1 Different methods with their relevant situation (Yin , 2009, p. 8)

Method Form of research question Requires control of behavioral events?

Focuses on contemporary events

Experiment How, Why Yes Yes

Survey Who, What, Where, How many , How much No Yes

Case study How, Why No Yes

Archival analysis

Who, What, Where, How many, How much No Yes/ No

This research question mainly contains “how”, which indicates that experiment or case study are

more suitable for this research, however, there are two main reasons to choose case study as the

research method: 1) case study is employed when researchers prefer to see the real operation without

having control on “behavioural events” but if a researcher needs to have control on “behavioural

events” then the experiment should be used, and 2) case study is suitable for qualitative research,

while experiment is used for quantitative studies (Creswell 2009; Yin 2009).

RESEARCH DESIGN 4.5

According to Yin (2009) research design is a systematic plan to investigate an understudy

problem through consideration of the four following components: 1) Research question, 2) Research

proposition, 3) The unit of research, 4) the logic linking of data to proposition. Given the qualitative,

inductive, constructivist, and exploratory nature of this research, the mentioned components have

been illustrated as following:

1) The research questions, which are discussed in section 4.2

2) The research proposition

The exploratory research does not need to have a proposition (Creswell 2009; Gray

2009; Yin 2009). This is consistent with the qualitative and constructivism nature of this

research, in which there is no aim to accept or reject a proposition; instead, numbers of

propositions will be developed at the end of this study.

3) The unit(s) of analysis

The unit of analysis is the level to which collected data is aggregated and analysed and

it could be individuals, groups of people, divisions, departments, organisations, industries

or even countries (Aita and McIlvain 1999; Yin 2009). Since this study aims to explore

the KM practices in the PMO, thus the unit of analysis is the Project Management Office.

4) The logic linking of data to proposition


As discussed, Grounded theory, as a powerful approach to create theory from collected

data, has been selected to create logic links between data, research questions, proposed

theories, and framework.

The structure of the research design 4.5.1

As discussed, a research plan is one of the important components of research design by which

logical steps of study are presented. This research comprises of three major phases: 1)

Comprehension phase, 2) Exploration phase, 3) Framework development and Write up phase. As

Figure 4-2 illustrates, the followings stages have been conducted in this study:

• Comprehension Phase

An extensive literature review has been undertaken during comprehension phases in order

to meet the following objectives:

To deeply understand the current associated literature of PM and KM,

To formulate the research gap and propose research questions, and

To develop the research framework.

• Exploration Phase

Three cases have been selected to be studied and investigated to meet the following

objectives:

To identify and analyse the existing KM practices, and

To answer the first and second research questions.

• Framework Development and Write up Phase

At this phase Grounded theory and other appropriate analysis techniques has been utilised

to achieve the ultimate aims of this research, “To Integrate KM practices into Project

Management Office maturity levels”:

To analyse obtained data,

To propose propositions and frameworks based, and

To develop a framework to address KM practices in the PMO maturity model for

answering the third question.

60 Chapter Chapter 4 | Research Design

Figure 4-2 Research Design (developed for this research)


RESEARCH METHOD IMPLEMENTATION 4.6

Case study is used as “an empirical inquiry that investigates a contemporary phenomenon in

depth and within its real-life context especially when the boundaries between phenomenon and

context are not clearly evident” (Yin, 2009, p. 18). A single case study contributes to provision

of in-depth understanding of the subject under study, while multiple case studies provide a

robust and reliable base to build and develop theories (Eisenhardt & Graebner, 2007; Perry,

1998; Yin, 2009). In other words, choosing multiple case studies strongly contributes to theory

development in which is more accurate, generalisable, and reliable, in comparison to a single

case study outcome (Eisenhardt & Graebner, 2007). In total, three cases have been selected for

this study. Both exploratory and explanatory approaches have been considered during the

implementation of three case studies, in which from an exploratory perspective, all relationships

between research framework and associated entities have been examined, while through an

explanatory approach, relationships among entities and components have been explained.

Selection of Case studies 4.6.1

Replication logic “refers to two or more cases in the same study where the investigator is

looking for congruence that indicates increased confidence in the overall findings” (Aita &

McIlvain, 1999, p. 258). According to Yin (2003, 2009), following the “replication logic

approach” contributes to the external validity of research. As discussed, project management

office has been adopted as the “unit of analysis” in which a multiple case studies approach will

be followed to strengthen the result of this study (Yin, 2009, p. 50).

In order to identify and select suitable case studies, four conditions have been defined:

1) The organisation should have an office, centre or unit to manage projects,

2) The organisation should have a project management methodology in place for

managing projects which could be an abstract or comprehensive,

3) The PMO maturity model for improving the quality of PMO functionality should be

adopted or followed, If there is none, assessment will be implemented, and

4) The PM unit or office is supported by top managers.

Theoretically, five PMOs are required to address the research gap in five levels of maturity,

however, three cases have been investigated due to subsequent limitations: 1) The PMO and

PMO maturity models are relatively new therefore, finding the PMO with the maturity levels of

four or five in Australia was difficult, and 2) the time limitation of this research was another

barrier. Three case studies were selected with PMOs at various levels of maturity. The selected

cases are well-known organisations from different industries. Since QUT’s ethical agreement

has been followed, there is obligation to not disclose the names of the selected organisations for


confidentiality purposes. Therefore, the organisations have given a title to indicate their context

as followings:

• SCIENCO is a research organisation,

• GOVCO is a governmental organisation, and

• MINCO is a mining organisation.

Case study protocol 4.6.2

The case study protocol increases reliability and quality of the case study through providing

a suitable ground to establish appropriate communications (Yin, 2009). This protocol comprises

the required instrument and procedure to undertake the case studies and four data collection

methods. As could be seen in Appendix A, a case study protocol was developed in this research

and it was used as the main protocol between researcher and organisations under study. A copy

of the provided case study protocol, which has been approved by QUT’s Ethics office, was

given to the nominated liaison person from each case study. This contributes to the development

of a reliable relationship between researcher and participants.

DATA COLLECTION IMPLEMENTATION 4.7

Prior to conducting data collection, appropriate arrangements such as negotiation

communication were being made with participants and the liaison person. A consent form as

part of Ethical clearance (Ethic Number: 1100001424), which was approved by QUT’s Ethic

office, has been signed by participants to get their formal agreement to take part in our

investigation. The Appendices B depicts a sample of the issued consent form. In the first step, a

questionnaire was given to every individual to assess the maturity of the PMO. After collecting

all responses, the questionnaires were analysed to determine the maturity level of PMO. It

should be mentioned that some of selected case studies have already assessed their maturity,

however, a common method was required to assess them with the same approach.

Interviews 4.7.1

Interviews are one the most important sources of the case study’s evidence (Yin 2009).

There are three types of interview: structured, semi-structured, and unstructured interview. The

structured interview is a set of structured questions with the same stimulus, while an

unstructured interview is the opposite (Berg 2004). This means that unstructured interviews do

not comprise standard questions in which questions could be evolved during the course of

interview. A semi structured interview is comprised of predetermined questions that

respondents are being asked in a systematic manner, however, it gives the interviewer the

flexibility to ask unstructured questions, if required (Berg 2004).

The semi-structured interview questions were selected for this research because on the one

hand, there are numbers of pre-determined questions based on the research questions, on the


other hand, researchers are keen to ask other questions if it is required during the interview

courses. Through following the recommended advice for providing reliable interview questions,

the numbers of questions as well as survey-questionnaires were developed, as shown in

Figure 4-3 and Appendix B (Leedy and Ormrod 2001; Yin 2009).

Interviews were conducted through the following case study protocol, in which at the

beginning of every interview, an introduction was provided after getting the participant’s

consent. Then, a succinct definition of terms and concepts was provided to prepare the

respondent for answering the questions. Afterward, briefly the interviewee’s background was

presented to initiate the demographic section in which interviewees’ background was

questioned. When the interviewer realised the interviewee was ready, then the main research

questions were asked accordingly. Eventually, at the end, four survey questions were answered

by each participant.

According to Yin (2009) and Creswell (2009), interviews should be continued until the

researcher is encountered with repetitive and redundant answers. In other words, when an

investigator feels that saturation of data has happened, this means that the investigation either

could be finished or another data collection should be employed. In SCIENCO and GOVCO,

the redundancy of data was realised after six interviews, while in MINCO redundancy occurred

after five interviews.

Figure 4-3 Interview and survey questions tree (developed for this research)


Survey questionnaire 4.7.2

In the current literature, two types of questionnaire have been discussed: Self-Administered;

and Interviewer-Administrated (Gray 2009). With regards to the inductive and exploratory

nature of this research, the researcher aims to explore the opinions of respondents about the KM

practices in the PMO. In addition, triangulation of the data was another reason for conducting a

questionnaire in this case study (Yin, 2009). Two survey-questionnaires were developed for this

research and the same target. One was for assessing the PMO maturity level, and another for

ranking the importance of knowledge processes as well as knowledge types. In fact, the second

questionnaire was investigated at the end of the interview, as depicted in Figure 4-3

In order to analyse the outcomes of the survey, AHP (Analytic Hierarchy Process) was

employed by which the obtained data were weighted properly for analysis purposes. According

to Stam and Silva (1997), AHP is a popular structured technique for ranking and analysing

under study phenomena or decision making through utilising mathematics.

Direct observation 4.7.3

This is another data collection method, which is recommended to conduct during the case

study implementation to observe and record the existing activities of a case study, related to a

research problem (Creswell 2009; Gray 2009; Yin 2009). Direct observation, also contributes to

quality of collected data through the following triangulation strategy. At least three days were

arranged for each case, to observe the current PM related activities, processes, procedures and

applications. Direct observation sessions were conducted before and after interviews in order to

understand interviewees’ explanations when they were talking about an application or process.

Participating in the project meetings, and formal and informal discussion among projects was

also part of direct observation to observe the existing activities related to project knowledge

management.

Documentations analysis 4.7.4

Organisational documents such as procedures, standards, forms and manuals contribute to

provide specific details for supporting data and evidence from other data collection methods

(Yin 2009). Also, this is the only codified source of evidence which contains explicit knowledge

within the PMO, by which researchers could obtain insightful information about under-study

subjects. The main reasons to employ this source of evidence during the investigation are to

gain:

• Insightful information about organisations’ goals, objectives, strategic plan,

structure, and, also a road map for developing the PMOs,

• Information about current PM methodologies and processes, and

• Information about current instructions to understand the developed PM practices.


DATA ANALYSIS 4.8

According to Yin (2003), qualitative data analysis comprises of examining, categorising,

tabulating, testing, and/or recombining qualitative and quantitative evidence to both address the

initial inquiries of the study and, also, identify new relationships or concepts. The importance of

data analysis in the research project necessitates developing the appropriate strategy(s).

According to Yin (2009) the four following strategies contribute to both analysing the collected

data and quality of research: 1) Relying on theoretical proposition; 2) Developing a case

description; 3) Using both qualitative and quantitative data; and 4) Examining rival

explanations. With regards to research questions, which are “how” and “what” types of

question, the first strategy and second strategies have been suitable since they led researchers to

provide a data collection plan in order to find related data and ignore the information which is

not associated with the scope of this research. The third and fourth strategies, also, were

followed by those robust and reliable outcomes that were developed through data analysis (Yin

2009). Both the research framework (R-KMMM) and research questions have been very helpful

during the data collection and analysis stages. During the data analysis, all of the framework

components as well as elements were investigated against the collected evidence, also including

rival analysis. In addition, both qualitative and quantitative data assisted to make strong and

robust analysis.

Grounded theory as inductive theory building method 4.8.1

According to Corbin and Strauss (2008) the aim of exploratory studies is to obtain clearer

understanding of under-investigated problems or questions in order to both collect data and

make appropriate relations among them through building theories or hypotheses. Eisenhardt and

Graebner (2007) advocate that Grounded Theory is one of the best methods to develop theory(s)

based upon obtained data from case studies. Grounded theory has been extensively used in both

organizational and management studies since late 2000, which shows the increasing importance

of this method (Gray 2009).

Technically, “analysis” is the process of breaking down a subject to have better

understanding of it (Lindner and Wald 2011). Also, data analysis is defined as the examination

and investigation of the subject and its associated data through appropriate techniques or tools

for revealing their functionality, characteristics and properties in order to make new knowledge

and inferences (Corbin and Strauss 2008). This means that information analysis gives meaning

to data and provides a vehicle to transform data to knowledge.

Given the exploratory, inductive and constructivism nature of this study, Grounded theory

has been adopted as the main analytical approach in order to develop numbers of propositions

for addressing the research problem. Having said that, this approach has been selected for the

following purposes: 1) To analysis and classify the collected data, 2) To discover and identify


relationships among the obtained data; 3) To propose theory(s) to answer research questions in

order to develop the preliminary framework for addressing the KM practices in the PMO

maturity levels.

Data analysis processes 4.8.2

According to Lindner and Wald (2011) data analysis comprises of the following three stages:

1) reducing the amount of data in a way that could be understandable, 2) displaying the

processed data through developing groups/categories and as such, and 3) drawing conclusions

by which the under-study phenomena are addressed. This approach was adopted and then

customised by defining three stages for this research: 1) data organisations, 2) data display, and

3) conclusion and theory development, in which each stage consists of numbers of processes.

Figure 4-4 Data analysis processes (developed for this research) depict the proposed analysis

stages and processes.

Figure 4-4 Data analysis processes (developed for this research)

Data organisation 4.8.3

At this stage, four processes were conducted in order to make data ready for the next stage.

After conducting interviews and surveys, the provided notes and comments were integrated with

each interview. Then, recorded interviews were transcribed into MS Word documents and at the

same time, associated comments and notes were attached to and integrated with each one. At the

end, all interviews had the same format with the same order of contents to be entered into our

analysis application. In addition, for organising the server results, they were collected, and then

entered into MS Excel sheets in an organised manner, to be used by the adopted analysis tools.


Data display 4.8.4

In this stage, all organised interviews were uploaded to Nvivo 10, as the main application for

data analysis and coding purposes. According to Lindner and Wald (2011) “Coding” in Nvivo

is the process of storing passages of information or comments in various nodes and tree nodes,

in which sources always remain intact. This means that coding consists of assigning passages to

specific terms which is shorter in a way that the main resource still remains unchanged.

As discussed earlier, grounded theory was employed as our main analytical method, by

which coding in the Nvivo was conducted. According to Corbin and Strauss (1990), processes’

grounded theory should be designed to develop a “well integrated concept” by which the

phenomena under study have been thoroughly investigated by proposing a theoretical

framework. Coding is the critical part of constructing and employing grounded theory, by which

an analytic process is facilitated (Corbin and Strauss 1990; Corbin and Strauss 2008; Gray

2009). In other words, the bones of analysis processes are made by coding and theoretical

integration constructs a skeleton by assembling the bones (Charmaz 2014). In doing so, the

following three stages have been designed to undertake this analytical technique. Figure 4-5

depicts a sample of coding used for this research.

Open Coding 4.8.4.1

The interpretive process of analytically breaking down and disaggregating the data into units

is known as Open coding (Charmaz 2014). Since this research aimed to explore the KM

practices in the PMOs, hence, KM Practices and associated processes were used as a base for

open coding, in conjunction with preliminary research framework, for developing appropriate

codes, concepts and categories. The preliminary coding is managed through Nvivo and a

manual coding technique. In addition, the conceptual framework and additional nodes were

created when the concepts emerged from the data. At the end of the open coding process,

numbers of codes were developed but they were broad, in which no proper and reliable

inference was possible. Therefore, appropriate integration among the created nodes and

categories was required to give more meaning for analysis purposes.

Axial coding 4.8.4.2

Once codes were defined, the next step was undertaken to examine the relationship among

categories and sub-categories. In other words, Axial coding is the process of scrutinising the

validity of codes and relations of the categories in order to build a skeleton of the categories

through making appropriate links among them (Corbin and Strauss 1990; Corbin and Strauss

2008). To do so, firstly hypotheses were developed through testing codes and categories by

collected data, then, possible propositions were developed to construct relations between

categories. This means that categories of KM practices in the PMO were examined through the

obtained data. Then, categories were refined through examining codes and their relations, in


which weak categories were edited or removed. In this step, well-grounded hypotheses as well

as categories were recognised to make researchers ready for the next step.

Complementary analytical techniques 4.8.5

According to Yin (2009) there are numbers of analytical techniques such as pattern

matching, explanation bundling, and numerical count analysis. Pattern matching is used to

compare findings of the empirical study to predict one in which, if they confirm each other, then

internal validity of study findings is reliable (Yin 2009). This method was employed in both

within-case and cross-case analysis by which the research findings were compared to both the

research KM maturity model (discussed in chapter 3), and to each other. In addition,

explanation building is another form of pattern matching by which an appropriate pattern is

developed through analysing obtained data (Yin 2009). This means that, based on gathered data

in each case, a pattern might be developed to address common behaviour among research

components. This technique was used in the course of this research specifically during the

“cross-case analysis”.

The importance and frequency of understudy components could be estimated through a

“numerical counts analysis” technique in which the importance of an issue is determined

through counting either numbers of occurrences or raised by participants and people (Lindner

and Wald 2011). This technique was frequently used in this research for assessing the

importance of KM practices as well as processes. Also, it was employed during the survey

outcomes analysis.


Figure 4-5 Sample of Coding (developed for this research)

Within-case analysis 4.8.5.1

According to Yin (2009) “within-case” analysis aims to scrutinise each case as a standalone

entity, by which a researcher could be intimately familiar with case study and its current

operations and activities. In addition, this process contributes to properly interpret rich as well

as complex data in the way that research objectives could be met (Creswell 2009; Yin 2009). At

this stage, each case was thoroughly scrutinised by employing related components of the

research framework in order to address the research gap in every case. The explanations and

outcomes of employing analysis techniques, tools, and applications such as Grounded theory,

Pattern matching and Nvivo have been presented in each case study report, which can be found

in Chapters 5, 6, and 7.


Cross-case analysis 4.8.5.2

The aim of “Cross-case analysis” is to strengthen the research findings from a previous stage

i.e. “within case analysis”, to develop robust propositions and theories (Yin 2003). One of the

aims of undertaking such a method was to compare and analyse the similarities and differences

of research framework’s components in three different case studies. Tables were developed by

which each component was analysed in different contexts. For instance, knowledge creation and

its associated practices were examined in three maturity levels of PMO to find in what levels

creation of knowledge was stronger, therefore, some propositions were developed based on

findings for addressing research questions. Also Nvivo, alongside the other analytical

techniques such as pattern matching and explanation building, is employed to enrich the

developed theories of this research. In Chapter 8, cross-case analysis is presented.

THE QUALITY OF RESEARCH 4.9

According to Yin (2009), the quality and validity of qualitative research depends on four

factors: construct validity, internal validity, external validity, and reliability. For quality

purposes, this approach was adapted alongside the process-oriented quality tactic. In other

words, numbers of processes and procedures were developed in order to make sure that all four

above-mentioned quality factors were followed and satisfied. Table 4-2 illustrates the

mentioned quality factors and their associated tactics.

Construct Validity 4.9.1.1

The process of establishing suitable operational measures to ensure the constructs of data

collection and analysis, is called construct validity (Yin 2009). According to Yin (2009) three

factors should be considered to improve “construct validity” of qualitative research: 1) using

multiple sources of evidences, 2) establishing a suitable chain of evidence, and 3) developing

an appropriate data base for obtained data.

Using multiple sources of evidences 4.9.1.2

One of the most recommended and popular techniques for using multiple sources of

evidence is “triangulation”, by which a researcher uses more than one source of data to

improve the data collection and construct validity (Lindner and Wald 2011; Yin 2009). In other

words, this approach contributes to rigours and integration of study by which outcomes of

research are more reliable and generalisable (Yin 2009). Two types of triangulation have been

mentioned in the literature: data and methodology triangulation in which data triangulation

addresses using multiple sources of data such as project manager or PMO staff, while

methodology triangulation deals with the way the data is collected, such as interview and direct

observation (Yin 2003). In this research, both types of triangulation were employed through

choosing different roles in the project management office, and also four data collection


methods: interview, survey questionnaire, documents analysis, and observation. In addition, in

the case study protocol, general processes and procedure were defined to ensure the quality of

data collection.

Table 4-2 The proposed quality tactics (Yin 2009) Quality Factor Appropriate Tactics

Construct Validity

• Developing a conceptual model for KM practice • Followings data triangulation approach by using multiple sources of evidence

Following methodological triangulation through employing multiple techniques such as interview, observation and document analysis

• Establishing the appropriate chains among the sources and techniques • Developing proper database for collected data through using Nvivo and Ms Excel

Internal Validity

• Employing analytical analysis techniques such as pattern modelling and explanation building alongside the Grounded theory

• Utilizing logic models for analysis such as program level logic model External validity • Choosing replicable logic for multiple case studies and Grounded theory

Reliability • Preparing and employing an appropriate case study protocol • Developing an appropriate data base

Establishing suitable chain of evidence 4.9.1.3

The chain of evidence is developed to follow any change in evidence from the initial

research questions to the final conclusion, by which the researcher is able to study the

phenomenon in different situations (Yin 2009). In this study, the three following tactics were

implemented to create a chain of evidences: 1) a data base was created to help researchers

collecting related data, 2) the sequence of each case was narratively provided to clearly

represent the structure of events and their associated sequences, and 3) the case study protocol

was developed for systematic data collection and data analysis purposes.

Developing appropriate database for obtained data 4.9.1.4

The Nvivo 10 was used as the main database, alongside the MS Excel, to record and capture

obtained data from interviews and surveys. Also, Nvivo was employed for analysis purposes in

which all created queries, relationships and memos have been recorded accordingly. Three types

of queries were run during the course of research: Matrix, Text search, and Annotation, by

which data analysis was conducted. Also, all created nodes and categories as well as models

were developed and recorded in the Nvivo for analysis proposes as well as improving the

construct validity of research data.

Internal validity 4.9.2

Internal validity is maximised when researchers aim to explain and justify reasons of

relationships among various components (Yin 2009). In other words, justification and

explanation of the research components such as KM practices and processes should follow a

logical way in order to be internally valid. Yin (2003) recommends a careful use of proper


analytical methods, such as pattern matching or explanation building, to ensure the internal

validity of this research.

External validity 4.9.3

Generalisability of research findings confirms the external validity of case study research

(Yin 2009). Since theory development is one of the research’s aims, so generalisability was an

important factor to improve the quality of research outcomes. To do so, replication logic was

conducted, by which findings of the first case study were replicated in second and third case

studies to ensure that validity of relationships among research components is emerged (Yin

2009). In other words, during cross-case analysis, the “replication logic” was used to confirm

that research findings are valid and generalisable. According to Corbin and Strauss (2008)

grounded theory provides appropriate processes to develop a theory that could be valid to be

generalised. In other words, embedded processes of this theory develop a reliable and valid

theory.

Reliability 4.9.4

Reliability discusses the credibility and consistency of research outcomes in which biases

and errors of research have been removed or minimised; therefore, the same outcomes will be

obtained if the research is conducted again (Yin 2009). Among existing recommended

approaches to obtain reliable outcomes, four were employed in this study. 1) A case study

protocol was developed to address the unique method of data collection as well as analysis, 2)

an appropriate database was provided to collect and record data from the beginning in order to

minimise any loss of data, 3) data and methodology triangulation tactics were followed to make

sure that both data and their sources are more than one, and 4) the same questions, which were

derived from research questions, were asked during the course of study to prevent any bias from

the researcher side (Aita and McIlvain 1999; Berg 2004; Creswell 2009; Yin 2009).

CONCLUSION 4.10

This research follows an inductive, exploratory and constructive approach. The case study

method has been chosen as the research methodology, alongside the Grounded theory as the

data analysis methods. A number of strategies and tactics were presented to be used for

improving the quality of the research. In addition, triangulation of data was used to collect the

quality and rigorous data. Moreover, a case study protocol was developed to both make

effective communication with organisations, and increases the quality of research. Also,

appropriate applications, namely Nvivo 10, will be utilised for data analysis purposes.

In the following chapters, i.e. 5, 6, 7, the within-case study analysis for three case studies

will be presented through use of the research methodology and design. In Chapter 8, the cross


case analysis will be discussed to compare the selected cases, and also to develop the

preliminary research framework.

74 Chapter 5 | Case Study Analysis: SCIENCO

Chapter 5

CASE STUDY ANALYSIS: SCIENCO

INTRODUCTION 5.1

In the previous chapter, the research methodology presented the selected methods for

gathering the research information, analysing, and interpreting the collected data. As discussed,

the case study method was chosen as the research methodology, and the grounded theory

alongside the other analytic techniques, such as pattern matching, was adopted as the research

data analysis method.

In the next three chapters, i.e. 5, 6, and 7, the three selected case studies will be examined

against the research framework, in order to answer the research questions. To do so, the

research methodology was employed from data collection stage to data analysis phase, and each

stage has been thoroughly followed and presented accordingly. In this chapter, SCIENCO’s

PMO was investigated to explore the project knowledge management in a research organisation

in order to discuss the two first research questions (RQ1. How are KM practices and processes

employed in the PMOs, and RQ2. How do KM practices contribute to improve maturity level of

the PMO?). First, the organisation’s background will be explained, followed by data collection

procedures. Second, the PMO’s maturity level will be discussed alongside the current PM

systems. Third, data analysis will be undertaken to discuss the current status of SCIENCO’s

PMO from a KM perspective. Finally, concluding remarks and the research findings will be

summarised.

SCIENCO’S BACKGROUND 5.2

SCIENCO was formed in the early 1920s as an organisation to carry out scientific research

to develop three major industries: mining, farming, and manufacturing. Since then, SCIENCO

has expanded its research activities to various fields such as environment, human nutrition,

urban and rural planning, water, and astronomy, to become one of the largest and most diverse

research agencies in the world (Müller, et al. 2013). As an internationally known organization,

SCIENCO defined its mission as: “to deliver innovative solutions for industry, society and the

environment”. In addition, SCIENCO’s stated vision is: “using science to make a profound and

positive impact for the future of humanity” (Müller, et al. 2013).

In order to manage more than 6500 employees, SCIENCO has adopted the matrix structure

approach, in which thirteen divisions have been developed as business units to manage all

research areas (nationally or internationally), and ten flagships has been defined to focus on

Chapter 5 | Case Study Analysis: SCIENCO 75

current national challenges. The majority of SCIENCO’s divisions and flagships undertake a

number of projects, programs or portfolios. Projects are research based, in which they are either

sponsored by clients or undertaken for strategic and technological advancement purposes.

Figure 5-1 A snapshot of SCIENCO's structure (from SCIENCO’s organisational chart)

As shown in Figure 5-1, division and/or flagship managers have the ultimate responsibility

for project success/failure and they are accountable for initiating, planning, implementing and

closing assigned projects. In addition, there is an enterprise supportive function, Program and

Performance Department (PPD), which is responsible to provide processes, procedures, and

methodology to unify and integrate all project-related activities within SCIENCO. Functionality

of PPD is similar to a classic PMO, which has been developed in the last three years.

As a research organisation, SCIENCO uses various approaches to develop appropriate

solutions for diverse industries. Applicability and novelty of solutions are the most significant

contributions of SCIENCO to the body of knowledge. This entails either creating knowledge

that is new to the world or the industry, or developing current knowledge to propose a new

solution for addressing the recognised challenge. In other words, SCIENCO is a company that

creates knowledge through both operational activities and project implementation. Since this

study aims to focus on KM in projects, SCIENCO is an interesting case study to be investigated.

On one hand, knowledge creation is embedded in research and operational activities which

should be captured and reused. On the other hand, SCIENCO’s PMO facilitates organisational

projects so it has the responsibility of managing projects’ knowledge. This means that in

scientific projects with the aim of creating new knowledge, different KM practices may be used,

in comparison to other types of organisations. Therefore, the outcomes of this investigation may

generate some new light on revealing new aspects of project KM in research organisations.

RESEARCH OBJECTIVES AND QUESTIONS 5.3

As discussed in Chapters 1 and 2, this research aims to explore the management of project

knowledge in the PMOs. To do so, three objectives have been defined for this study: Research

Objective (RO) 1) to analyse the role of KM practices in various maturity levels of PMO, RO2)

to explore the contribution(s) of PMO for managing project knowledge, and RO3) to develop a

CEO/Board

Executive Team Member

Flagships Divison

Enterprise Functional Support

Program and Performance


framework to address KM in various maturity levels of the PMO. In order to achieve the

mentioned research objectives, a case study method was adopted with the following in which

each case should: 1) manage projects in organisations, 2) have a PM methodology, and 3) have

a PMO in place.

Table 5-1 The Research Questions (developed for this research)

1. To what extent are KM processes and practices employed in the PMOs? 1.1. What are the current challenges of the PMO from KM perspective?



2. How do KM practices contribute to maturity level of the PMO? 2.1. What is the importance of knowledge processes at each phase of project? 2.2. How can PMO contribute to managing the project Knowledge?

3. How can knowledge be integrated in the PM maturity model? 3.1. How is knowledge created, captured, transferred and reused in PMOs?

3.2. How can KM practices be employed in each maturity level of PMO?

In order to satisfy the mentioned research objectives, three research questions were defined:

RQ1) to what extent are KM processes and practices employed in the PMO, RQ2) how do KM

practices contribute to maturity level of the PMO, and RQ3) how can knowledge be integrated

in the PM Maturity Model, in which each research question entails some sub-questions, as

presented in Table 5-1. These questions were examined in SCIENCO through following the

research methodology, and are discussed in the next sections.

DATA COLLECTION PROCEDURES 5.4

According to the research methodology, case study protocol should be followed to

communicate with the selected case study, as shown in Appendix A. The case study protocol

was used to facilitate the following: 1) initiating contacts with authorities, 2) planning for data

collection methods, 3) assessing the maturity of organisation from a PM point of view, 4)

conducting the interviews and survey, 5) undertaking complementary interviews, 6) analysing

the data, 7) preparing the case study report. In addition, the proposed research methodology was

followed for data collection and analysis purposes, as depicted Figure 4-4

The data collection schedule 5.4.1

The PPD division in SCIENCO was selected to undertake three data collection methods, i.e.

interview, document analysis and direct observation. To do so, a liaison person was appointed

from SCIENCO to assist with arranging suitable dates for conducting interviews, as well as

direct observation. In addition, she facilitated the access to organisational documents and the


current PM applications and tools. As shown in Table 5-2, seven interviewees were chosen in

SCIENCO: PPD’s senior manager, PMO manager or coordinator, one program manager, two

project managers, and two project team members. In some cases, interviews were conducted

two times, as researchers needed more clarifications. For confidentiality purposes, interviewees’

names were replaced by a selected code as can be seen in the following Table.

Table 5-2 Interviewees’ list and schedule in SCIENCO (developed for this research)

Interviewee Position Location 1st interview 2nd interview

Researcher’s Comments

In.Sc.1 Senior Manager in Brisbane

28/03/2012 (face to face)

20/04/2012 (on the phone)

Attached in Appendix D

In.Sc.2 Business Development

manager ( project Manager)


19/04/2012 (face to face) NA

In.Sc.3 PPD reps in Sydney 5/04/2012 (on the phone)

25/04/2012 (on the phone) NA

In.Sc.4 Program Manager Brisbane



In.Sc.5 Project Manager Brisbane 30/03/2012 (face to face)

(31/05/2012 (face to face) NA

In.Sc.6 Project team member in Brisbane



In.Sc.7 PM coordinator in Brisbane

28/03/2012 (face to face) NA NA

All interviews were electronically recorded and the majority of data collection activities

were undertaken at SCIENCO’s site in Brisbane, from late March 2012 to late May 2012. Also,

five days were spent to directly observe the current PM activities in SCIENCO. In addition, it

took two days to study the utilised software and systems in the SCIENCO’s PMO. After

finishing the data collection phase, the collected interviews were fully transcribed into the MS

Word format in order to prepare them for uploading in Nvivo, as the analysis applications. In

total, this process took three months, and more than 160 pages of interviews transcriptions were

provided to be used in Nvivo.

The data collection methods 5.4.2

According to the research methodology, three forms of data collection were employed: 1)

semi-structured interviews alongside the two types of questionnaires, one for assessing the PMO

maturity level and another for assessing the importance of KM processes, 2) direct observation,

and 3) document analysis. The first questionnaire was developed to assess the maturity level of

project management activities and was given before interview questions. The second

questionnaire asked about KM practices, after finishing the interview questions. In addition,

direct observation and document analysis were employed for gathering complementary

information from this case. Both mentioned methods were used to investigate SCIENCO’s

activities from a PM as well as a KM point of view. The data collection activities were


conducted in accordance with the case study protocol, also by getting assistance from an

assigned employee, as SCIENCO’s liaison. Table 5-3 represents the utilised data collection

methods in SCIENCO.

Table 5-3 The Data collection methods (developed for this research)

Data Collection Method Location Facilitator Date

Interviews and Questionnaires

SCIENCO’s Site in Brisbane Researcher

Mentioned in the Table 5-2

Documents Review SCIENCO’S site in Brisbane and QUT

Researcher and SCIENCO’s liaison

person

12/04/2012 till 31/05/2012

Direct Observation SCIENCO Site in Brisbane

Researcher and SCIENCO’s liaison

person

16/04/2012 and 23/04/2012

In addition, the triangulation of data collection methods was adopted in order to ensure the

quality of gathered data (Singh, et al. 2009).

THE DATA ANALYSIS 5.5

After data collection, the process of data analysis was conducted to investigate SCIENCO’s

PMO from a PM and KM point of view, and to ultimately answer the research questions. At the

first step, the maturity level of the PMO was assessed, and then KM challenges were discussed,

and followed by analysing the required types of knowledge during project lifecycle. At the end,

the importance of four KM processes: Creation, Capturing, Transferring, and Reusing were

analysed, and then examined against the explored KM challenges to investigate the relation

between KM process and KM issues in the SCIENCO’s PMO. In fact, the first and second

research questions (RQ1- How are KM practices and processes employed in the PMOs, RQ2) How

do KM practices contribute to improve maturity level of the PMO) will be answered at the end of

this section.

The level of maturity for SCIENCO’s Project Management Office 5.5.1

According to the research methodology, the assessment of a PMO’s maturity level is the

initial step to manage the process of data analysis. The designed assessment model is a

questionnaire survey which comprises 13 questions to cover the examination of nine PMBOK’s

knowledge areas during the project life cycle. This assessment model is the customised form of

PM assessment method, suggested by Kerzner (2013) which has been simplified to meet the

research scope and objectives.

This questionnaire was distributed among numbers of employees in SCIENCO, by which

participants were asked to rate each question from 0 (lowest) to 10 (highest) in which they

should choose “0-1” for poor, “2-3” for weak, and eventually “8-10” for world standard

quality. Ten questionnaires were distributed among respondents and, eventually seven of them

were returned and all the answers entered in MS Excel 2010.


According to the research framework and (Kerzner (2005); Kerzner (2013)), the level of

maturity for a PMO could be any number from 1 to 5, in which number 1 represents the lowest

level of maturity (ML), while number 5 claims the optimum maturity level (OL). In other

words, maturity level is defined at five levels in which the lowest maturity level, i.e. ML=1,

indicates that PMO is in its initial steps to improve the quality of project management, in

contrast the highest maturity level, i.e. ML=5, means that PMO has developed and customised a

robust and advanced project management system to support organisational projects (Project

Management Institute 2008b).

Table 5-4 PMO’ ML from PM knowledge perspective (developed for this research)

PMBOK’s Knowledge area Maturity level Average ML Project Scope management 0.58

1.47

Project Cost management 2.57 Project Time management 1.64

Human Resource management 1.36 Project Quality Management 0.93

Project Risk management 2.43 Project Communication management 1.00

Project Procurement management 1.50 Project Integration management 1.29

At first, the maturity level (ML) for nine knowledge areas of PMBOK was analysed, and as

Table 5-4 as well as Figure 5-2 illustrate, project risk and cost management received the highest

ranking PM practices, while the other seven knowledge areas were rated less than 2. This means

that current respondents have given low numbers to these practices, which means that the

current PM practices for supporting those seven areas have not met the expected quality from

respondents’ point of view (Project Management Institute 2008b). In other words, from

participants’ perspective only risk and cost management, to some extent, are supported through

the current PM practices, while other knowledge areas are yet to be improved. The research

analysis revealed that the weighted average maturity level for SCIECNO’s PMO is 1.47. From

PMBOK’s knowledge perspective, this means that SCIENCO’s PMO should be classified as the

PMO with first level of maturity (Desouza 2006; Kerzner 2005; Project Management Institute

2008b).


Figure 5-2 PMO’s ML from PMBOK's knowledge areas perceptive (developed for this study)

In the next step, maturity level was analysed from a project lifecycle point of view, so as

Figure 5-3, and Table 5-4 depicts, respondents have rated the “Planning Phase” at more than 2,

while the other three phases were rated less than 2. This means respondents are more satisfied

with the planning phase in SCIENCO in comparison to other project phases (Kerzner 2005;

Project Management Institute 2008b). As will be discussed later, respondents mentioned that the

current PM processes do not significantly help them during the project lifecycle so projects are

faced with number of issues in this regard. This is consistent with the assessed level of maturity,

i.e. ML=1, which means that the PMO has not developed the required PM practices to facilitate

organisational project management (Kerzner 2013).

Table 5-5 PMO’ ML from project lifecycle perspective (developed for this research) Project Phases Maturity level(ML) Average ML

Initiation 0.64

1.43 Planning 2.14

Execution and monitoring 1.71 Closing 1.21

As Table 5-5 represents, the average maturity level (AML) for a project life cycle has been

assessed as 1.43. This result supports previous evidence and it both strengthens the quality of

data collection method and shows that respondents answered questions. As shown at Figure 5-2

and Figure 5-3, PMO’s ML from two different points-of-view has been analysed and assessed,

in which both determined the first level of maturity for SCIENCO’ PMO (ML= Maturity Level,

OL=Optimum Level).

0.58

2.57

1.64

1.36 0.93

2.43

1.00

1.50

1.29

0.000.501.001.502.002.503.003.504.004.505.00

Project Scope

Project Cost

Project Time

HR management

Project QualityProject Risk

ProjectCommunication

Project Procurement

Project Integration

ML OL


Figure 5-3 SCIENCO’s Maturity level from PLC perceptive (developed for this research)

The research analysis revealed that SCIENCO’s PMO has ML=1.47 from a project

knowledge point-of-view, and ML=1.43 from a project lifecycle perceptive. According to the

current literature and the research framework, SCIENCO’s PMO could be technically

categorised as a PMO with first level of maturity (Grant and Pennypacker 2006; Kerzner 2005;

Project Management Institute 2008b). This means that the PMO has developed some basic

practices of project management, however, the majority of required PM practices are yet to be

addressed at this level of maturity, as presented in Table 5-4. In other words, at the first level of

maturity, the awareness for project management has been raised in the organisation in which

the PMO is responsible for developing PM competencies by addressing reliable and practical

PM practices (Project Management Institute 2008b)

According to (Kerzner (2005); Kerzner (2013)) the first level of maturity is called common

language, which means that the need for project management in an organisation as well as a PM

framework as a common language among project team members has been raised at this level of

maturity. The current literature has defined the following characteristics for the PMO with the

first level of maturity which means that they could be generally recognised in any PMO with a

low level of maturity (Crawford 2006; Kerzner 2005; Kerzner 2013; Project Management

Institute 2008b):

• In the PMO with a first level of maturity, there is no unique project management framework, however, attempts to develop it have been initiated,

• There is an observed lack of addressing project management tool/techniques in place,

• There are limited services to assist project managers, and they have to manage with different methods,

0.64

2.14

1.71

1.21 0.000.501.001.502.002.503.003.504.004.505.00Initiation

Planning

Execution&monitoring

Closing

ML OL


• In PMOs with a low level of maturity, the self-interest of project managers comes before organisational best interest, and

• There is an observed lack of investment for conducting PM trainings in the organisation. Table 5-6 Participants’ quotes in SCIENCO’s PMO (developed for this research)

Subject Associated participants’ comments

Current PM methodologies

“…I don’t think that.. there is any particular methodologies across our organisation…” quoted by In.Sc.1

“...in general there’s not a formal methodology that’s been outlined…” quoted by In.Sc.2 “…Not really. No. there is some kind of risk assessment in place but it’s not I’m not aware of

any formal project management process…” quoted by In.Sc.5 “…In terms of an organisational arrangement there isn’t anything specific that we follow but

we are planning to develop such a thing …” quoted by In.Sc.3

Lack of service

to project manager

“…So once you get to this point it really does become more about the project leader managing that in a you know in a more personal way, sort of an ad hoc way…” quoted by In.Sc.4 “… apart from that there’s not really a structured approach to providing support for the

ongoing project management…” quoted by In.Sc.4 “…I’m not aware of anything in terms of time management, skills, no just general advice. But

as I said project support officer doesn’t get involved in…” quoted by In.Sc.5

According to the research findings, the mentioned criteria have been observed in the

SCIENCO’s PMO, which will discussed later. This means that both the maturity assessment

method and the existing situation of SCIENCO have consistently revealed that the selected

PMO has the first level of maturity in which: 1) the current PM methodology is still under

development, so project managers have to use their own methods to manage their project, and 2)

PM trainings need to be improved to increase the knowledge or project management as well as

PM competencies. In addition, the collected data from interviews confirm that the above

mentioned criteria for first level of maturity have been pointed out by participants, of which

some of their most common were presented in Table 5-6.

According to the current literature, the importance of PM methodology for managing

projects is raised at the first level of maturity (Kerzner 2005; Project Management Institute

2008b). In other words, at this level of maturity the existence of a common language among

employees and project managers becomes an important priority for organisations (Kulpa and

Johnson 2008). Therefore the initial steps should be undertaken at the first level of maturity, in

order to address the major issues of PM through developing a reliable PM framework (Crawford

2002; Kerzner 2013; Project Management Institute 2008b). During the process of document

analysis, a PM framework was in the SCIENCO. In the next section, this framework has been

analysed in order to shed more light on the current PM methodology in SCIENCO.

Project Management methodology in SCIENCO 5.5.1.1

As discussed earlier, the majority of SCIENCO’s participants believe that there is not any

PM methodology in place, however, there is a document which has been developed by PPD

(herein after it will be called PMO) and it is a single set of “One-SCIENCO” project

methodology to be used by project managers. From a respondent point-of-view, the existing PM


methodology has not been appropriately announced or trained. The current PM framework

consists of nine pages, by which the PM life cycle has been addressed in the five following

phases, and it is advised that is be followed across the whole enterprise:

• Identification phase: to identify problem, issue or request,

• Selection phase: to analyse alternative solutions and initiate primary steps,

• Definition phase: to plan all required activities, resource and requirements,

• Execution phase: to implement the proposed plan,

• Transition & Close out phase: to hand over the developed product/service These five phases are similar to the current PM methodologies, especially the waterfall

method, and it follows logical steps from initiating to terminating a project (Larmer and

Mergendoller 2010; Project Management Institute 2013). However, the existing PM standard is

not comprehensive, as it just addresses the management of a project in less than 10 pages with

limited supporting documents. Further analysis revealed the following about this framework: 1)

It is an abstract document in which just three out of nine pages discusses whole PM

methodology, and other pages explain some basic definition of PM, 2) the recognised three

pages just succinctly discuss high level steps of project management, while there are many

activities that are yet to be addressed by this framework, 3) there are limited supporting

documents, workflows, templates, forms and systems in order to facilitate the project

management, 4) There is a significant lack of clear explanation of using proper tools,

application or methods to support project managers, and 5) this abstract framework not only has

not been collaborated with the current processes and procedures, but also it has not been

appropriately trained or communicated to SCIENCO’s employees; the majority of them are

unaware of such a framework existing in SCIENCO.

In the next level of investigation, participants’ comments in regards to their thoughts about

the current PM methodology were analysed. The research findings revealed that the majority of

participants not only have not been trained or taught to use this standard but also are not familiar

with it at all. In addition, during the interviews, participants were asked that “what kind of PM

methodology is used at SCIENCO”. The outcomes of analysis for this question have been

represented in Figure 5-4 and it shows that the majority of respondents believe that there is “no

specific PM methodology” in place, which means that the current PM framework has not been

recognised by most of the participants, as for instance one of them explains that “…I don’t think

that. There is any particular methodologies across our organisation…” quoted by In.Sc.1. In

addition, participants believe that since there is limited PM framework in place, project

managers mostly use their own ways to manage organisational projects. In fact both of these

findings confirm that SCIENCO’s PMO has the first level of maturity (Kerzner 2005; Project

Management Institute 2008b).


After discussing these findings with the SCIENCO PMO coordinator, In.Sc.3, she explained

that they have commenced a project to both improve the current PM framework, and also

develop a comprehensive PM methodology to be used across the organisation. This statement

confirms another criterion of PMO with first level of maturity, in which the PM awareness is

raised at this level (Kerzner 2013). Also, it reveals that the need for a common language among

project team members across the SCIENCO has been accepted by an organisational senior

manager. Therefore the current PM standard could be considered as a tool to make common

language among SCIENCO’S project team members before introducing the new one.

Figure 5-4 PM Methodologies in SCIENCO (developed for this study)

As discussed, participants believe that there is lack of existence of a reliable PM standard in

SCIENCO. This is one of the reasons that SCIENCO’s managers use different methods or their

own ways to undertake their projects. This is another criterion of PMO with first level of

maturity in which project managers do not have access to any specific PM method, so they have

to use their own method (Kerzner 2013). In other words, the success of a project is very

dependent on project managers and how he/she leads the project to the end, as In.Sc.2 asserts

“…in SCIENCO that I’m aware of which basically means that a project will run on an

individual basis…”. This means that projects are more “hero driven” instead of “system driven”

which is expectable because of PMO’s low level of maturity (Kerzner 2005).

In summary, the research findings indicate that SCIENCO has initiated the development of

its PMO as well as an organisational-wide PM framework. The PMO assessment model and

data analysis consistently confirm PMO has the first level of maturity in which: 1) the

importance of PM has been raised, 2) however, there is no unique PM framework, 3) project

managers utilise their own method to manage a project, and 4) PM training courses are not

SCIENCO’s priority. According to Kerzner (2013) at the first level of maturity, PM systems

and tools have not been appropriately developed, so they need to be considered at a higher

maturity level. In the next section, the current PM systems and application will be investigated

to examine against Kerzner (2013)’s statement.

Current SCIENCO PM standard

No Specific PM methodology

PMBOK

PRINCE2

Project Manager do their own way to manageproject

0 2 4 6 8 10

Frequency, 4


Project management systems and tools in SCIENCO’s PMO 5.5.1.2

In order to obtain adequate information in SCIENCO, the combination of all three data

collection methods, i.e. triangulation, was utilised (Yin 2009). On one hand, interviews have

disclosed both participants’ thoughts about the current PM systems, and how they have been

utilised. On the other hand, direct observation and document review technique have provided

insightful and practical information about the current PM tools. These findings are in line with a

similar study, undertaken in SCIENCO’s PMO, in which both confirm the usage of the same

tools and application for project management in SCIENCO (Wiewiora, et al. 2009a). Table 5-7

depicts the research findings in this regard and shows the current systems and tools which are

employed by project stakeholders during the project lifecycle.

As shown in Table 5-7, numbers of systems were recognised in SCIENCO which are used

during the project lifecycle. For instance, SCIENCO utilises SAP as the total system to

collaborate all organisational and project costs and revenue information. According to Kerzner

(2013) at the highest level of maturity for PMO a fully integrated project management system is

expected in which all project information and data across the organisation are coordinated

through this system. The research analysis shows that SAP is just used for integrating project

cost and revenue in SCIENCO, so it does not integrate all project activities. This is consistent

with the research framework, since SCIENCO’s PMO has first level of maturity, so it is not

logical expect to find a fully integrated PM system in SCIENCO.

Table 5-7 The current systems and tools in SCIENCO’s PMO (developed for this research)

Application Propose of use

SAP To integrate cost and revenue of projects across SCIENCO Enterprise Opportunity

Pipeline (EOP) A system for managing new business leads and proposals, tracking

progress of contracts from draft to the end Wiki A system to find a person, information, solution or other required data Trim Document repository to capture the project activities

Gemma A system to spread information among groups and project team members

MS SharePoint Server To manage project information, report and activities as well as activity collaboration.

Off System Tools Suits Used the entire Project Life Cycle Process from Brief to Closing as

common tools for dialogue with clients, customers and all stakeholders

Common Costing Framework (CCF)

To manage, control and integrate all projects costs, individually and/or comprehensively.

Numerous systems such as Trim, Wiki, and the intranet are employed during the project

lifecycle, as depicted in Table 5-7, however, these systems have not just been developed for

project management purposes. Further investigations have disclosed that employees have been

faced with some issues in this regard and following are their comments:

“…I understand that there are tools available that can be used, but I haven’t actively

used them myself yet...”, quoted by In.Sc.4


“…It’s not an enforced system and then the thing is it is not necessarily public

available so the access to certain areas and regions can be restricted to a number of

people...”, quoted by In.Sc.3

“…We do have that…the Wikipedia system or we have folder structure where we can

put stuff in there. I think the trouble is that it is A. not used. Coherence through the entire

organisation and B. most of the time the access is restricted…”, quoted by In.Sc.4

As it could be inferred, these comments show that despite the existence of numbers of

systems in SCIENCO, participants believe that they face some issues, which need to be

addressed. In some comments, respondents directly have mentioned their challenges, as In.Sc.3

explained the issue of system integration in SCIENCO “…at the moment is that we’re doing

this trying to develop our PMO but their current systems are not integrated…”. This means that

the current systems need to be collaborated as participants complain about lack of integration.

Access to the current information is another issue that respondents are faced with. In other

words they believe that current systems do not provide appropriate access for them to capture

their required knowledge, For instance In.Sc.2 has commented: “…Sometimes you go back to it

when you really need to, somebody who was working on the project let’s say five years ago is

still here and there are people that are here for a long time. But there are some people there

you know that have never left. So if you want to you have to go back into like the Trim system

and so on and try to find some reports and you know some interactions and sometimes that’s

very difficult…”. This means that the current systems such as Trim need to be improved from an

accessing point-of-view.

From a knowledge management point of view, the majority of participants have mentioned

that the current system does not significantly support project knowledge management. In other

words, when respondents were asked to explain their thoughts about the contribution of current

tools as systems to support KM, they have not positively responded in this regard. For instance,

In.Sc.3 and In.Sc.4 have quoted followings to explain their thoughts in this regard: “…So when

you look at the system I don’t think we have a very good system implementation of capturing

this type of knowledge…”, “…But there is no such a thing to manage project knowledge from

beginning to closing…”.

In summary, there are numbers of systems and tools in place to facilitate project

management in SCIENCO, as shown at Table 5.7. The research findings revealed there are

some issues with the current systems, such as lack of integration and inappropriate access. In

addition, SCIENCO’s employees believe that the current systems should be improved in order

to significantly contribute to management of project knowledge. These findings are consistent

with a similar study at SCIENCO as it was revealed that the current systems do not significantly

facilitate the process of knowledge transferring (Wiewiora, et al. 2010). In the next section, the


issues of SCIENCO’s PMO will be discussed from a KM point-of-view to get insightful

information about the existing KM challenges of PMO with first level of maturity.

Knowledge Management challenges in SCIENCO 5.5.1.3

In order to recognise the issues of PMO from KM perspective interview, data was used as

the main source of research information for data analysis. To do so, the research framework was

followed in which interviews’ transcriptions were uploaded to the Nvivo, as data analysis

software. Then, the process of coding, both open coding and axial coding, was managed as is

advised by similar qualitative research (Charmaz 2014; Corbin and Strauss 2008; Wiewiora, et

al. 2010). In the first stage of the open coding process, more than 60 nodes were developed in

the Nvivo. These codes or comments have directly or indirectly mentioned the current

challenges from a KM point of view. Following are some of the examples of the coded

comments:

“…Just the PMO itself I’d say really it doesn’t really do it at all in terms of the identifying,

even re-identifying sort of stage of the knowledge as…”, quoted by In.Sc.4.

“… KM it is a huge challenge and actually I think it’s in general one of the biggest

challenges nowadays and the challenge is actually growth in a non-linear way with the size

of the organisation…”, quoted by In.Sc.1.

In the next level of analysis some of the Nvivo’s functions, such as queries and

classification, were utilised to find the relation among the current coded information.

Eventually, after running numbers of model five categories, the research axial codes were

developed as the major challenges of SCIENCO’s PMO. In other words, all sixty coded

comments, in regards to KM challenges, have been classified in five major categories through

following research methodology (Corbin and Strauss 2008). This means that each category, or

axial code, represents a number of associated issues of KM in the SCIENCO’s PMO. In other

words, the following KM challenges have been recognised through employing both “theory

making” and “Grounded theory” techniques, advised by qualitative research experts as methods

to make theory from similar data (Charmaz 2014; Corbin and Strauss 2008; Eisenhardt and

Graebner 2007):

1) Lack of KM practices and processes during project life cycle

2) Lack of appropriate systems to support project KM

3) Issue of locating and accessing right information and/or right expert

4) Difficulties of searching and detecting required knowledge

5) Issue of appropriate access to the existing systems

Table 5-8 is an example to present how participants’ quotes were related to open codes, and

also, how axial codes were developed accordingly.


Table 5-8 Example of using Axial &Open coding in SCIENCO (developed for this study)

Axial coding Open coding Quote’s samples

Difficulties of searching and detecting required

knowledge

Detecting proper knowledge "...Interestingly Google is the first place that if I want to look for something about SCIENCO…" "...However for finding knowledge we should, informally, find the right person. For instance, I know person X

is working here for twenty years so I can ask him but there is certainly not a system..." "...In a big organisation like this it is very hard to get the information across from one group to another or to

another site and to learn from the experience that the other people had..." "...So if a group sets up a project for a client X and they think oh that might be confidential it might be that only people within this group get access to that area in this Wikipedia system. And say two years later there’s another

group talking to client X again they won't have any knowledge about that previous history..."

Difficulties of searching in current DB Difficulty of locating right information

Searching outside DBs to find information Issue of filtering required knowledge

Lack of best practices What knowledge works what doesn't Where to find what I’m looking for

Issue of locating and accessing right information

and/or right expert

Difficulties to find an expert within organisation "...might know vaguely that this person has experience. But it would be a lot easier if I knew that there are three people who have had specific experience with this type of technology ..."

"...But it’s still umm there is still a specific need I think to be able to search through a PMO to identify or individuals or identify the particular individuals that have worked with a particular type of technology..."

"...I found it very difficult when I came in, on board to the SCIENCO because I was trying to actually find in the system what people’s capabilities were but I couldn’t find it..."

Finding right person to obtain knowledge Finding who works on what

knowledge about employees capabilities Researchers are protective on their knowledge

Lack of KM practices and processes during project life

cycle

Knowledge is getting accessible through managers "...But the new people don’t have access to knowledge and it’s difficult to go and ask questions constantly…"

"...if I need some knowledge/information, I would talk to stream leader or the team manager…" "...So it would be very difficult for me to follow what they have written in the lab book unless they were guiding

me through So again I would have to ask this particular person what is the knowledge..."

No integrity among current system to access knowledge No proper access of knowledge for new team members

Person's network is more important The more people you know the more access you have

Issue of appropriate access to the existing systems

Current system does not properly support KM "...At the moment we are learning a lot during the project, the team is learning a lot during the project. There is no formal requirement or any requirements to do reflections of what the project, what they learn and so on…"

"...So there is no system, there is just person that’s right, Or somebody else knows that I go to and asks that person, so it’s not really a system..."

"...So there are forms and I suppose the post project review would be a process but as I say it’s not one that’s

Lack of complementary proper systems Lack of incentive to use current systems

They are not generally user friendly They are not properly integrated with organisational tools

Lack of appropriate systems to support project

knowledge management

Capturing is more about to publishing "...You might have to do something again several times and it might take longer than what you’d planned to do…"

"... often we find ourselves working on thing, then finding out these guys have done something similar..." "...there are no formal mechanisms for it at all. In fact it’s probably one of our the greatest challenges ..." "...it would be important to make the system so that people could put the information in without having to

rewrite their publications or do you know do things along those line..." "...Capturing that is the purpose of the post project review and as I said we traditionally although there is a form

and structure for doing some kind of post project review, that hasn’t typically been used a lot..." "...the challenge certainly is as you know umm distributing that generated knowledge within the group and later

on passing it on to other people..." "...I don’t think there is high level of trust between them [to share knowledge]..."

Challenges of capturing lesson learnt Project meeting Challenges with Post Project review

Current knowledge are not properly reused Informality of KM activities

Knowledge is not logged or organised No reflection of previous knowledge on current project

Transferring is a significant challenge Capturing intangible knowledge is challenge

KM is undervalued and needs to get more attention


Figure 5-5 The exsisting KM challenges in SCIENCO’s PMO (developed for this study)

According to research methodology, the frequency of each phenomenon should be used to

analyse its importance. After running numbers of matrix queries in Nvivo, the obtained data was

transferred to Ms Excel for further analysis. As presented at Figure 5-5, the “lack of KM

practices and process during project life cycle” was recognised as the most frequent-mentioned

KM challenge, 34%, in SCIENCO’S PMO. In other words, more than thirty percent of the

existing issues are related to the lack of processes or procedures to address KM practices. Also,

participants believe the current PM practices need to be improved. Since SCIENCO’s PMO has

the first level of maturity, it faces the undeveloped PM practices. On the other hand, it could be

expected that in SCIENCO, as a research organisation, there are numbers of KM practices in

place by which research activities could be appropriately managed. However, participants

believe that the existing current KM practices do not meet their expectations, as they have

mentioned numbers of issues in this regard, which will be discussed later. For instance

Wiewiora, et al. (2009a) have investigated the knowledge transferring process in SCIENCO and

they found that this process is yet to be appropriately developed.

The second most frequent-mentioned challenge with 27 %, relates to the current systems in

the SCIENCO. The research findings revealed that participants believe the systems’

contribution to management of project knowledge needs to be improved. In other words, despite

the existence of some systems and tools in place, these are not adequate enough to satisfy

current requirements. According to Alavi and Leidner (2001) KM has three main components:

people, process, and technology. The KM system is the combination of processes and

technology to address how people should employ a system for managing knowledge

(Davenport, 1997). The issue with the current system implies that integration between KM

processes and existing technology as well as applications is an issue in SCIENCO. This means

that SCIENCO should not only develop new tools and applications, but also it needs to integrate

all systems, in order to address the lack of appropriate systems.

8%

27%

34%

17%

14% Issue of appropriate access to the existingsystems

Lack of appropriate systems to supportproject knowledge management

Lack of KM practices and processes duringproject life cycle

Issue of locating and accessing rightinformation and/or right expert

Difficulties of searching and detectingrequired knowledge


The third most frequent challenge is the way of locating or finding right expert or

information. As could be logically inferred, creating knowledge is the main objective of a

research organisation (Byounggu and Heeseok 2002; Nonaka 1994). SCIENCO as a research

organisation with numbers of branches and offices around Australia and Globe, manages a wide

range of activities to create knowledge for various purposes. In addition, SCIENCO’S experts

and scientists have been located in different places to undertake their projects. This might create

some issues such as parallel works in which employees are not appropriately informed of

similar works conducted by another, as following comments describes their concerns:

"... too often we find ourselves looking at or working on things and then finding out

you know these guys have done something similar...", quoted by In.Sc.4

"...I found it very difficult when I came in, on board to the SCIENCO because I was

trying to actually find in the system what people’s capabilities were but I couldn’t find

it...", In.Sc.1

The issue of locating information or person impact on managing organisational knowledge,

specifically, knowledge reusing and transferring (Goffin, et al. 2010; Nonaka and Takeuchi

1995; Wiewiora, et al. 2009a). As will be discussed later, both the areas of knowledge reusing

and transferring are not satisfactory. This means that addressing the above mentioned challenge

will contribute to improve knowledge transferring and reusing, and eventually project

knowledge management.

The fourth most-frequent challenge is the issue of searching and detecting required

information. According to the collected data, all of participants have mentioned some problems

to explain their concerns about searching and finding current knowledge. They have pointed out

numbers of concerns such as: filtering current information; lack of best practices; and detecting

proper knowledge. For instance, one of the SCIENCO’s senior managers interestingly quoted

that: "...Google is the first place that if I want to look for something about SCIENCO…".

According to the current literature, access to right information impacts on KM in general,

specifically knowledge capturing and reusing (Koskinen and Pihlanto 2008; Senaratne and

Sexton 2009; Yuan and Yang 2009). This means that difficulties of finding the required

information impact on capturing and reusing project knowledge, therefore this issue needs to be

addressed to improve the status of KM in the SCIENCO.

Access to current systems and knowledge is the fifth most frequent mentioned issue in the

SCIENCO’s PMO. According to respondents’ comments, people’s networks play an important

factor to access to the current information in the SCIENCO. In addition, they believe that

knowledge is normally accessible through their managers, as one of the interviewees quotes:

"...if I need some knowledge or information, I would talk to stream leader or the team

manager…". According to existing literature, appropriate access to knowledge plays a strong


role in creating and reusing knowledge (Alavi and Leidner 2001; Nonaka and Teece 2001). This

means that SCIENCO could face some issues in regards to knowledge creation and reusing. As

it has been discussed, knowledge reusing is the less developed KM process among other KM

processes. In other words, addressing the above mentioned issue will improve both knowledge

reusing, and eventually quality of project knowledge management.

In summary, five challenges have been recognised in SCIENCO’s PMO, from a KM point of

view. As discussed, the mentioned challenges were examined through employing the research

framework as well as the current literature, in order to investigate their relations with four KM

processes. It was revealed that all KM processes have been impacted by these issues, especially

knowledge reusing. This means that the current status of project knowledge management needs

to be developed. In this section, the primary parts of first question (RQ1- How are KM practices

and processes employed in the PMOs?) have been discussed to explore KM issues in

SCIENCO. In the next section, the second part of the first research question, the required types

of knowledge at project lifecycle, will be discussed to find the importance of knowledge types

during the project life cycle.

The required types of knowledge at project life cycle 5.5.1.4

The main reason for investigating required knowledge is to understand the importance of

each type of knowledge for, ultimately, answering another part of the first research question.

According to the research framework, eight types of knowledge are critical in project

environments: Project Management Knowledge; Knowledge about Procedures; Technical

Knowledge; Knowledge about Clients, Costing Knowledge; Legal and Statutory Knowledge;

Knowledge about suppliers; and Knowledge of who knows what. In order to rate the importance

of each knowledge type, survey forms were distributed among the eight participants and,

eventually, seven completed forms were returned (about 85 % response rate). In the survey,

respondents were asked to rank the above mentioned types of knowledge from 1, the least, to 8,

the most important knowledge during four phases of a project life cycle.

After collecting data and entering to MS Excel sheets, an Analytical Hierarchy Process

(AHP) was employed to analyse survey responses. This technique is a process that uses

hierarchical decomposition through a weighted matrix to analyse complex information in multi-

criterion decision (Ghodsypour and O'brien 1998). It is a highly recommended technique for

ranking the importance of competing factors in operational management (Lindner and Wald

2011; Stam and Silva 1997). This technique was employed and the advised processes were

followed to rank the importance of types of knowledge in SCIENCO’s PMO, as shown at

Figure 5-6.


Figure 5-6 Types of required knowledge in SCIENCO (developed for this research)

The research analysis revealed that “knowledge about customers” and “costing knowledge”

are the most important types of required knowledge at the initiation phase. According to

PMBOK (2012) the client’s expectations and their related costs are very important to initiate

projects, which is consistent with this finding. In contrary, “Technical knowledge” and

“Knowledge about procedures” have been mentioned as less important types of knowledge at

initiation phase. The main objective of the initiation phase is to conduct high level activity for

preparing projects, therefore, technical knowledge and/or procedural knowledge, which are

mostly used for planning purposes, do not have high priority at this stage (Kerzner, 2013).

The main aim of the planning stage is obtain details of client expectations in order to plan

for meeting all of them (Project Management Institute, 2012). Interestingly, research findings

are in line with mentioned theory in which “knowledge of who knows what” and “Knowledge

about client” were indicated as the most important types of knowledge, while respondents state

that “legal knowledge” and “procedural knowledge” are less likely to be required at this stage.

Moreover, “technical knowledge” has become more important at this stage, compared to the

initiation phase, which is quite logical since it is used to provide project plans and resource

allocation.

4

2

1

8 7

4

5

6 Initation

4

2

5

7

6

1

4

8 Planning

7

1

6

8

4

5

3 3

Execution 7

8

1

5

3 3

4

6

Closing


“Knowledge about client” has still remained as the most important required knowledge at

the execution phase. The second most important knowledge at this stage is “Project

Management Knowledge”, which climbed from 4th level to 7th. At this stage the project

manager and the team play a crucial role to put everything together to follow the project plan

and, ultimately, meet client’s expectations (Project Management Institute, 2012). On the other

hand, existence of an appropriate “technical knowledge” is major requirement to undertake the

assigned activities, and has been ranked as the third most important knowledge. The fifth place

has been assigned by respondents to “Legal knowledge”, which was the least important at

planning stage. It is generally accepted that all legal and standard requirements should be mostly

followed and met at execution phase that is wisely pointed out by participants.

The purpose of the closing phase is to confirm the completion of project deliverables to

satisfy project stakeholders’ expectations (Project Management Institute, 2012). Participants

mentioned “knowledge of project management” and “knowledge about client” as the most

important types of knowledge among others at closing phase, while they believe that “technical

knowledge” and “legal knowledge” are not very important at this stage. According to project

management best practices, a project could not be properly closed without meeting the client’s

expectation, and, this could not be appropriately undertaken without good understanding of

project management tools and techniques. In addition, “technical knowledge” and “knowledge

about suppliers” are mainly used during planning and execution phase, since closing is all about

handing out the deliverable.

After analysing the rank of each type of knowledge at various phases, another level of

investigation was carried out to determine the overall rank of eight types of knowledge,

regardless of project lifecycle phases. Similarly, the AHP technique was used to assign

appropriate weights for each entity, then, their weighted percentages were calculated and

ranked, as depicted in Table 5-8.

Table 5-9 Types of required knowledge in SCIENCO (developed for this research)

Types of Knowledge \ Project Phase

Individual Rank Total weighted Rank

Initiation Planning Execution Closing Rank Percentage Project Management Knowledge 4 4 7 7 6 14.86%

Knowledge about Procedures 2 2 1 8 3 8.78% Technical Knowledge 1 5 6 1 3 8.78%

Knowledge about Clients 8 7 8 5 8 18.92% Costing Knowledge 7 6 4 3 5 13.51%

Legal and statutory Knowledge 4 1 5 3 3 8.78% Knowledge about suppliers 5 4 3 4 4 10.81%

Knowledge of who knows what 6 8 3 6 7 15.54%

The research analysis revealed that, from SCIENCO’s employees’ point of view,

“knowledge about client”, “Knowledge of who knows what”, and “project management

knowledge” are the most critical types of knowledge, while “technical knowledge” and “Legal


knowledge” are the less important ones. There might be a number of reasons for this ranking: 1)

those types of knowledge with lowest levels, could indicate that employees are happy with

them, and it is reasonable because SCIENCO is research company and its employees possess

good technical knowledge as well as legal knowledge, 2) while higher ranked knowledge might

be the indication of employees’ expectation to improve the provision of them.

These findings could be a useful indication for PMO with the low level of maturity, in order

to improve their KM system. In other words, it could be inferred that the first three types of

knowledge are the most important ones to be improved if the PMO has low maturity levels.

Figure 5-7 The required types of knowledge in SCIENCO (developed for this research)

From the PM point of view, interestingly, the first three types of knowledge are very

important knowledge to initiate and undertake the project (Project Management Institute, 2012).

The maturity level for SCIENCO’s PMO is one which means that there are numbers of

challenges to be solved at PMO, one of which is KM. Previously, challenges of KM at PMO

were discussed and, then, it was concluded that not only current systems need to be improved

but also there are limited systems or procedures in place to support project knowledge

management. Therefore, the provided ranking could be a significant implication of required

types of knowledge when a PMO has the first level of maturity. In other words, PMOs with

similar level maturity could focus on improving their system through using the above mentioned

ranking as a practical best practice.

In summary, eight types of knowledge were examined in SCIENCO to explore the

importance of them during project lifecycle. In addition, the general ranking has been analysed

to find the importance of knowledge types at first level maturity, in which the following ranking

was revealed: 1) Knowledge about Clients, 2) Knowledge of who knows what, 3) Project

Management Knowledge, 4) Costing Knowledge, 5) Knowledge about suppliers, 6) Knowledge

about Procedures, 7) Technical Knowledge, 8) Legal and statutory Knowledge. So far, the first

two sub-questions have been discussed to answer the first research question (RQ1- How are KM

Initation Planning Execution Closing

4 4

7 7

2 2

1

8

1

5

6

1

8

7

8

5

7

6

4

3

4

1

5

3

5

4

3

4

6

8

3

6

Project Management Knowledge Knowledge about Procedures Technical KnowledgeKnowledge about Clients Costing Knowledge Legal and statutory KnowledgeKnowledge about suppliers Knowledge of who knows what


practices and processes employed in the PMOs?). The next section aims to completely answer

the first research question as well as the second research question (RQ2- How do KM practices

contribute to improve maturity level of the PMO?), through discussing four knowledge

management processes and their subsequent KM practices.

Knowledge management practices and processes in SCIENCO 5.5.2

As discussed in the Chapter 3, the research framework, four KM processes were adopted in

which each process has numbers of KM practices. Also, it was assumed that all four KM

processes are employed throughout the project lifecycle (PLC) except the closing phase, as

depicted in Table 5-10. This means that all KM processes should be utilised during the PLC,

however, knowledge capturing is the only KM process which should be used at closing phase.

This assumption will be examined during the case study analysis.

Table 5-10 KM processes and PLC (adopted from Owen and Burstein (2005))

Initiation Planning Execution

& monitoring

Closing



In this section, the second research question (RQ2- How do KM practices contribute to

improve maturity levels of the PMO?) and its two sub-questions will be discussed. To do so the

following steps will be carried out: 1) investigating the utilisation of KM practices and KM

processes at four phase of PLC, 2) examining the above-mentioned assumption about KM

processes at project lifecycle, and 3) ranking the importance of four KM practices at each phase

of the project lifecycle.

All collected data through interviews, questionnaires, direct observation, and document

analysis were used to improve the quality and accuracy of research outcomes (Creswell 2009;

Yin 2009). Nvivo and MS Excel and other appropriate tools have been employed to analyse the

collected data, as they have been advised to be used for qualitative research (Bakker, et al. 2011;

Lindner and Wald 2011). According to the research framework, numbers of practices have been

assigned to each KM process by which knowledge management is supported in a project, as

shown in Table 5-11. These KM practices were used to develop numbers of nodes in the Nvivo

through employing open and axial coding techniques (Bakker, et al. 2011; Corbin and Strauss

2008). In addition, the advised procedures to code interviews’ data have been followed to

develop associated codes in this regard, as depicted at Figure 5-8. At the final stage of analysis,

the research framework was employed to integrate all codes for developing final axial codes.

These steps will be followed in this section to discuss the utilisation of KM practices in the

SCIENCO, and ultimately answer the second research question.


In the first stage, analysing KM practices during the project lifecycle has been carried out

through examining the collected data from interviews and direct observation. The open coding

technique was utilised to understand and, then, categorise respondent’s quotes. During this

stage, a regular activity was undertaken to compare the coded commonest and the research

framework in order to improve the quality of the developed categories (Julian 2008). Therefore,

all of interviews’ comments and quotes, related to KM, were associated to one or more KM

practices and consequently, KM processes. In other words, for each KM process and practice, a

number was obtained which shows the frequency of an associated phenomenon. This frequency

number was created through using the matrix query function in the Nvivo and it has been

utilised as one of the research data to analyse KM in the SCIENCO (Lindner and Wald 2011).

Figure 5-8 presents a snapshot of Nvivo as an example of how KM processes are related to KM

practices in this study.

Table 5-11 KM processes and their associated KM practices (developed for this research) Practices for

Knowledge Capturing • Expert locator • Frequently ask questions

(FAQ) • Knowledge repositories • Data base • Document Management

System (DMS)

• File management system • Management information

system(MIS) • Knowledge detection tools • Formal and informal event • Intranet • Knowledge inquiry system

Practices for Knowledge Creation

• Formal and informal event • Workshops & seminar • Community of practices • Best Practice Cases • Research services • Expert system

• Experience Report • Knowledge Broker • Data mining • Documentation search • Deductive & Inductive

thinking



• Communication channel • Knowledge list • Training &Mentoring • Discussion forums • Data Base

• Video and Tele Conference meeting

• Yellow page • Intranet • Knowledge directories • Formal and informal events

Practices for Knowledge Reusing

• Electronic notice board • Document Management

System (DMS) • Intranet • Expert systems • Data base • Knowledge map

• Yellow page • Knowledge detection too • Lessons learnt • Data mining • Formal or informal event

In order to analyse the collected data, frequency was used as the main criteria to explore the

current status of knowledge management in this case. During the process of coding interviews,

more than one hundred and seventy (170) comments and quotes, which have been directly

mentioned to explain the usage of KM practices, were recognised and then coded accordingly.

After analysing SCIENCO’S employees’ comments, it was revealed that more than forty-four

percent of KM practices are employed at execution and monitoring phase, while only less than

fourteen percent of them are utilised at closing stage, as depicted in Table 5-12. This means that

usage of KM practices at the execution phase is more than for the closing phase. These findings

revealed that the majority of KM practices are managed at execution phase in comparison to

three other phases. This is consistent with the nature of SCIENCO’s business as a research

organisation. In other words, the execution phase at research projects is more about creating and


developing a new technology and knowledge, therefore, numbers of KM practices should be

used to contribute for managing project knowledge (Argote et al., 2003).

Figure 5-8 A snapshot of KM process categories in the Nvivo (developed for this research)

From a KM process perspective, more than fifty percent of KM practices are utilised for

knowledge capturing, while only less than three percent are employed for reusing, as shown in

Table 5-12. This means that not only is knowledge capturing fairly stronger than the other KM

processes, but also participants believe the current KM practices mostly support the knowledge

capturing and then knowledge creation. In addition, knowledge reusing is not appropriately

supported by existing KM practices, which is line with the previous research findings in the KM


challenges in SCIENCO. In other words, reusing of the knowledge could be of the biggest

challenges from a KM point of view but more evidence is required to make proper conclusions

in this regard, which will be discussed later.

Table 5-12 The usage of KM processes in SCIENCO (developed for this research)

Initiation Planning Execution &

monitoring Closing

26.4% 15.3% 44.4% 13.9% Knowledge Creation 34.2%

Percentage of KM processes Knowledge Capturing 51.3%

Knowledge Transferring 11.8% Knowledge Reuse 2.6%

According to the above mentioned findings, the associated practices to knowledge capturing

and creation have been mentioned as more than eighty percent, while knowledge transferring

and reusing have less than 15 percent all together. As a matter of fact, knowledge reusing and

transferring has been respectively quoted just two and nine times, which means that participants

believe there are limited KM practices to support both transferring and reusing knowledge in

SCIENCO. These findings are in accordance with another study that was undertaken two years

ago at SCIENCO’s PMO to investigate the knowledge transfer in which authors have realised

the current challenges of knowledge transfer (Liang, et al. 2009).

From a project lifecycle point of view, the usage of KM practices at each project phase has

been analysed to examine how KM processes are used during a project life cycle. As Figure 5-9

presents, at initiation phase there are numbers of KM practices in place to support knowledge

capturing and creation processes, while knowledge transferring and reusing are yet to be

improved in this phase. This means that the lack of KM practices to support knowledge reusing

at this stage is significant. According to PMBOK (Project Management Institute 2013) both

initiation and planning are most important phases in which to utilise previous experience and

similar projects’ knowledge, however, knowledge reusing in SCIENCO not only in initiation

but also in other project phases has not been appropriately addressed.

At planning and execution phase, as Figure 5-9 depicts, all KM processes are supported

through numbers of KM practices, however, similar to the initiation phase, respondents believe

that most of the current KM practices facilitate the process of knowledge creation and capturing.

In other words, limited numbers of KM practices have been developed to support knowledge

reusing and transferring. According to the existing PM methodologies, knowledge creation at

planning phase is an important activity as all the project plans should be created at this phase

(Bentley 2009; Project Management Institute 2013; Reich and Wee 2006). The research

findings confirm this expectation in which planning is an important phase to create knowledge,

as shown at Figure 5-9.


Figure 5-9 KM processes at project lifecycle (developed for this research)

All KM processes should be employed at execution phase (Arora, et al. 2010; Owen and

Burstein 2005). The research findings explored that knowledge capturing and creation are fairly

supported through current practices, while knowledge reusing and transferring are to be

improved in this phase. According to the current literature, knowledge reusing at execution

phase is very helpful to improve the productivity and efficiency through benchmarking and

looking at similar projects (Polyaninova 2010). In addition, reusing previous knowledge helps

to monitor and control through defining proper criteria and measures (Project Management

Institute 2013). Also, training, mentoring and other simular activities to share and transfer

knowledge should be undertaken at execution phase, but little evidence was found in this

regard. Therefore, it could be initially concluded that KM practices to support knowledge

reusing and transferring at execution phase, are yet to be addressed in SCIENCO.

According to the research framework it has been assumed that only knowledge capturing

should be employed at closing phase (Owen and Burstein 2005). As shown at Figure 5-9, this

assumption has been confirmed since respondents believe that at closing phase the current KM

practices only support knowledge capturing, while there are few KM practices to facilitate other

KM processes. This means that the closing phase is all about delivering project outcomes and

capturing the knowledge activities such as lessons learnt and post project review (Kerzner 2009;

Project Management Institute 2013). In other words, from participants’ point of view, the

existing KM practices contribute to capture knowledge, which is consistent with the research

framework.

In summary, it could be concluded that all KM processes are supported, to some extent, by

associated KM practices at three project phases, and only knowledge capturing is managed at

closing phase, in SCIENCO. The research findings revealed that knowledge creation and

0

2

4

6

8

10

12

14

16

Capturing

Creation

Transferring

ResuingReusing


capturing are supported, to some degree, by numbers of KM practices, while knowledge reusing

and transferring are yet to be developed. In addition, knowledge reusing is rarely supported

through current KM practices. As discussed earlier, the current maturity level of SCIENCO’s

PMO is one which means that PM is yet to be addressed in this organisation (Kerzner 2013).

This means that there are limited PM practices to support project management, and

consequently project knowledge management. Therefore, lack of KM practices could be

expected at this level of maturity, however, there are some bases for KM which need to be

improved. In the next sections each knowledge process will be individually discussed to answer

the second research question (RQ2. How do KM practices contribute to improve maturity level of

the PMO?).

Knowledge Capturing in SCIENCO’s Project Management Office 5.5.2.1

According to current literature, knowledge capturing is the only KM process that should be

employed from the beginning to the end of a project lifecycle (Owen and Burstein 2005). This

assumption was examined through investigation of obtained data, specifically from interviews

and survey-questionnaires. As discussed earlier, the research findings are in accordance with the

above-mentioned theory which means that SCIENCO’s employees believe that at closing phase

they have only employed knowledge capturing practices. In addition, further analysis

determined that more than 84 quotes, out of 160 in total, are related to utilisation of knowledge

capturing practices at four project phases: 25 at Initiation; 9 at planning; 34 at execution &

monitoring; and 16 at closing. In addition, Figure 5-10 indicates the frequency of obtained data

related to KM practices and it shows the utilisation of knowledge capturing practices at various

project phases. As this figure depicts, a documents management system (DMS) database is the

most frequent KM practice to support knowledge capturing, which has been mentioned by

participants.

In the next level of analysis, open coding and axial coding techniques were employed to

investigate the associated comments and quotes (Miles & Huberman, 1994). At depicted in

Table 5 13, there are eleven categories to support knowledge capturing. These categories were

used alongside the outcomes of the open coding process and, eventually, it was revealed that 7

out of 11 categories of knowledge capturing practices have mentioned by SCIENCO’s

employees. In other words, participants believe that seven types of knowledge capturing

practices are facilitated through the current developed practices, however, some of them are yet

to be improved. For instance, respondents believe that while the existing documents

management system and databases are fairly developed, the file management system and

management information system need to be enhanced. In addition, the research findings

explored that four KM practices, knowledge detection tools, knowledge inquiry systems,

frequently asked questions, and expert locater, are yet to be addressed in the SCIENCO’s PMO.


Figure 5-10 Knowledge capturing in SCIENCO’s PMO (developed for this research)

As Table 5-13 illustrates, there are three columns to discuss the status of knowledge

capturing practices in SCIENCO. The first column is the axial code, which is based on the

research framework. The second column represents the name of system, tools or practice, and is

used to support the associated knowledge capturing practice, or first column. And the third

column illustrates the frequency of KM practices, which were obtained through Nvivo analysis

functions.

From a project lifecycle point of view, these practices are employed mostly at execution and

initiation phases, while at planning and closing phase only 11, and 9 comments were

recognised. This means that, from the participants’ perspective, more than seventy percent of

knowledge capturing activities take places at initiation and execution phase. In other words,

participants believe that at both planning and closing phases the current KM practices are as

strong as initiation and execution phases. The lack of instruction and procedures has been

mentioned as the main reason of such as difference. Therefore, this is the PMO’s responsibility

to develop practices for addressing appropriate tools and processes in this regard.

As it could be found in Table 5-13, the documents management system (DMS) is the most

frequently mentioned KM practice. This means that DMS satisfactorily supports knowledge

capturing process from the respondents’ point of view. In addition, participants believe that the

current databases (DB) such as Trim and Wikis, contribute to the process of capturing project

knowledge. Also, SCIENCO has a unique way to capture some of the knowledge through a

publishing and e-publishing system (EPS), by which employees are advised to provide papers

for representing their tacit knowledge.

0

2

4

6

8

10

12

Initiation Planning Execution andMonitoring

Closing

Data base

Document Management System (DMS)

Hand Notebooks

Expert locator

File Management System(FMS)

Formal or Informal events

Frequently Ask Questions (FAQ)

Intranet

Knowledge detection tools

Knowledge inquiry system

Knowledge repositories

Management Information System(MIS)


The above mentioned KM practices are the most frequent KM practices to support

knowledge capturing in SCIENCO’s PMO. In other words, from participants’ point-of-view, the

current DMS, DBs and EPS contribute to the process of knowledge capturing, and KM in the

SCIENCO. However, further analysis through using the relationship function in Nvivo revealed

that there are correlations between these KM practices and the recognised KM challenges in

SCIENCO. For instance, despite the existence of DBs in SCIENCO, participants believe that

they have an issue of accessing to current DBs, as In.Sc.1 comments: “…sometimes I use

Google to search for accessing our published papers…“. This means that despite the existence

of some KM practices to support knowledge capturing, they are still faced with numbers of

issues, such as lack of accessibility and search-ability, which need to be addressed. According

to Alavi and Leidner (2001), appropriate systems such as DBs and DMS significantly contribute

to knowledge capturing in organisations, therefor SCIENCO’s PMO should improve the quality

of these KM practices through addressing the recognised challenges.

Table 5-13 Knowledge capturing’s categories and practices (developed for this research)

Knowledge capturing category Associated System/Practices in SCIENCO Frequency

Data base • Enterprise Opportunity Pipeline(EOP) • Trim • Wikis

18


• Hand Notebooks • Intellectual Property (IP) documentation • Lessons learned • Meeting minutes • Off system and assistant Tools • Post project review • Project Briefing • Project Debriefing • Project Reports

35

Expert locator • None 0 File Management System (FMS) • Windows base system 4

Formal or Informal events • Regular meeting 3 Frequently Ask Questions (FAQ) • None 0

Intranet • MS SharePoint 6 Knowledge detection tools • None 0 Knowledge inquiry system • None 0

Knowledge repositories • Publishing and E-publishing system 13 Management Information System

(MIS) • SAP 4

In addition, the research findings recognised that some practices such as file management

system (FMS), management information system (MIS) and formal and informal event are being

used in SCIENCO to facilitate knowledge capturing. Since their frequency is not significant, so

it means that respondents do not frequently utilise them for knowledge capturing purposes. In

other words, these KM practices have not been recognised by SCIENCO’s employees for

managing KM activities. This is consistent with one of the recognised challenges, i.e. lack of

strong KM practices in the SCIENCO. In other words, there are some KM practices in place


which need to be appropriately communicated and trained to be effectively employed for

capturing project knowledge.

On the other hand, four out of eleven KM practices for knowledge capturing have not been

recognised in the SCIENCO’s PMO, i.e. Expert locator, knowledge detection tools, knowledge

enquiry system, and FAQ. This means that SCIENCO’s PMO should address these practices as

they significantly contribute to project knowledge management (Kamara, et al. 2003; Tan, et al.

2007). In addition, further analysis through using Nvivo revealed that the absence of these

practices has been mentioned by some participants. For instance, participants explained some

concerns in regards to finding the right expert to get right information, and consistently Expert

locater is a KM practice that could address their concerns. In other words, most of the current

KM challenges in the SCIENCO could be addressed through developing an appropriate KM

system, in accordance with the research framework.

According to the current KM literature, at first level of maturity, organisations are advised to

prepare an appropriate environment for both developing a common language for PM and, also,

realising the importance of KM (Desouza 2006; Kankanhalli and Pee 2009). According to the

research finding, all respondents have realised the importance of KM for improving project

success rate, as all of them have directly mentioned some concerns from a KM point-of-view.

This means that they have at least basic knowledge of project management, which is consistent

with the findings of a similar study in SCIENCO (Julian 2008). In other words, the recognised

awareness of importance of KM for project success in SCIENCO has met the basic requirement

for the first level of maturity, from a KM point-of-view. However, according to the research

framework, SCIENCO’s PMO should initiate an appropriate plan to address the recognised

challenges, in order to achieve the next level of maturity.

In summary, knowledge capturing is the most frequently mentioned phenomena among all

four KM processes, in which more than 50% of comments were found this regard (see table 5-

12). More than 40% of current KM practices support knowledge capturing, however, there are

still numbers of challenges in this regard. At the first level of maturity, it was found that the

subsequent practices which are utilised for capturing knowledge are databases; MIS; DMS;

knowledge repositories; and formal and informal events. In addition, some other practices such

as knowledge detection tools, expert locators, knowledge inquiry system and FAQ are yet to be

addressed in the SCIENCO PMO. The research findings have not revealed any inconsistency

against the research framework, as the SCIENCO PMO has the first level of maturity.

Knowledge Creation in SCIENCO’s Project Management Office 5.5.2.2

SCIENCO, as a research organisation, has significantly contributed to a body of knowledge

in many areas such as agriculture, oil and gas and mining, therefore, it could be inferred that

“creating knowledge” is one of SCIENCO’s missions (Julian 2008). In fact, most projects in


SCIENCO are defined to propose both a solution for current challenges in various industries or

to develop a technology or new knowledge. According to Nonaka (2001), knowledge creation

has four stages: Socialisation, Externalisation, Combination; and Internalisation or SECI.

According to the research framework, SECI could be supported through numbers of KM

practices, which have been illustrated and defined in the research framework (see Table 5-11 &

Figure 5-11). In order to investigate the current KM practices of knowledge creation, numbers

of questions were designed by using the KM framework. These questions were developed to

elicit participants’ thoughts about those practices that support creation of knowledge within

SCIENCO. These practices were classified to eleven categories and associated practices as

shown in Table 5-14.

Table 5-14 Knowledge creation’s categories and pratices (developed for this research)

Knowledge Creation categories Associated System/Practices in SCIENCO Frequency

Best Practice Cases • None 0 Community of practices • None 4

Data mining • None 0 Decision support system (DSS) • None 0

Deductive & Inductive thinking • Brainstorming, • Think tank 10

Documentation search • None 1 Experience Report • None 1

Expert systems (ES) • Expert Interview • Expert Judgment 6

Informal and formal Event • Formal face to face meeting • Workshops & seminar 28

Knowledge Broker • None 0

Research services • Experimentation • Simulation • Use of Metaphors

12

The initial investigation shows that more than fifty-three percent of knowledge creation

activities are undertaken at the execution phase, as shown in Figure 5-11. This outcome is in

line with the previous discussed assumption in which SCIENCO, as a research organisation,

undertakes projects to create knowledge. In other words, in SCIENCO the majority of

knowledge creation activities are well-conducted in the execution phase, where some KM

practices such as experiments and simulations are managed to create knowledge. In addition, the

research findings revealed that there are few knowledge creation activities at closing phase,

which is consistent with the research framework, as depicted at Figure 5-11. In other words, as

the research framework assumes, little activity has been recognised to facilitate knowledge

creation.

As illustrated in Table 5-14 and Figure 5-11, “formal and informal events” are the most

frequent KM practices for knowledge creation purposes, from participants’ points-of-view. In

other words, SCIENCO’S employees believe that most of the knowledge that they have created


so far, have been through face-to-face conversations, meetings (formal or informal),

participating in seminars, workshops or conferences. According to KM theories, “formal and

informal event” is a practice to support both socialisation and externalisation process for

creating knowledge (Nonaka and Takeuchi 1995). The following is an example of one of the

quotes to explain how formal and informal events contribute to create knowledge in the

SCIENCO.

“…more often will typically be one researcher who will spend a lot of time

developing the concept themselves and fleshing it out and then they will communicate

that idea…”, quoted by In.SC.4

Figure 5-11 Knowledge Creation practices in SCIENCO (developed for this research)

The second most frequent KM practice for facilitating knowledge creation is “research

services”. Three sub-practices are used to support research services: simulation, use of metaphor

and experimentation. According to Nonaka and Teece (2001) the research services support

“internalisation” to support the knowledge creation process. Since SCIENCO is a research

organisation, there are numbers of tools in place to manage knowledge creation. Following is

one of the comments which is mentioned to explain the experimentation: “… will work together

and they’ll do a little trial of something and then produce a model …”, quoted by In.Sc.3

The third most frequent knowledge creation practice is “deductive and inductive thinking”

such as brainstorming and think-tank. These types of KM practices support both

“externalisation” and, also extent “socialisation” processes of knowledge creation (Nonaka and

Teece 2001). Similarly, “expert system” and “community of practices” are the fourth and fifth

most frequent KM practices in the SCIENCO’s PMO. As shown in Figure 5-11, the research

findings revealed that these KM practices are used mostly at execution and monitoring phase. In

other words, both KM practices facilitate the socialisation part of SECI in which experts from

0

2

4

6

8

10

12

14

16

18


Closing

Best Practice Cases

Community of practices

Data mining

Decision support system

Deductive & InductivethinkingDocumentation search

Experience Report

Expert system

Informal and formal Event


various areas could get together and discuss a subject from different perspectives, in order to

create a new knowledge (Hsieh, et al. 2009; Peltola, et al. 2002; Wiig 1997b). This means that

these two practices have been fairly developed in the SCIENCO to contribute to the process of

knowledge creation.

On the other hand, the research analysis revealed that 6 out of 11 KM practices for

facilitating knowledge creation have not been appropriately addressed in the SCIENCO. In

other words, limited evidence has been explored to support utilisation of some of the KM

practices, i.e. knowledge broker, data mining, decision support system, and documentation

research. These types of practices mostly support the “combination” process of SECI model for

facilitating knowledge creation (Nonaka and Takeuchi 1995). This means that in SCIENCO’s

PMO, the “combination” process needs to be addressed, as numbers of practices to support

“socialisation”, “externalisation”, and ”internalisation” have been fairly developed and are in

place.

In summary, knowledge creation is the second most frequent KM process mentioned by

SCIENCO’s employees. In fact, research findings revealed that more than thirty percent of

current KM practices support knowledge creation in SCIENCO’s PMO. According to Nonaka

and Takeuchi (1995) four sub-processes or SECI are the main constituents of the knowledge

creation process. The research outcomes explored that there are some KM practices to fairly

support “socialisation”, “externalisation” and “internalisation”, however ”combination” is yet to

be addressed in the SCIENCO. As discussed earlier, SCIENCO’s PMO has the lowest level of

maturity, therefore, it is plausible to both explore some incomplete systems and recognise some

gaps from a KM point-of-view. According to the research framework, at this first level of

maturity, the awareness of knowledge creation should be raised alongside some basic KM

practices. Therefore, the SCIENCO’S PMO has met the minimum requirements in accordance

with the research framework.

Knowledge Transferring in SCIENCO’s Project Management Office 5.5.2.3

Similar to other KM processes, the research framework was employed to explore the current

knowledge transferring status at SCIENCO. After coding interviews, eleven categories were

developed in which some of them have some sub-categories, as depicted in Table 5-15.

According to the research findings, knowledge transfer is the third most frequent-mentioned KM

process. In fact, less than 12 percent of quotes and comments have discussed SCIENCO’S KM

activities from a knowledge transferring point-of-view. This means that from respondents’

point-of-view, the knowledge transferring process has not been well-developed as well as the

other two KM practices, i.e. knowledge creation and knowledge capturing. In other words, the

current KM practices for supporting knowledge transferring need to be improved, from a

respondents’ point of view. This is consistent with the outcomes of similar research in


SCIENCO by which Julian (2008) has focused on studying knowledge transferring in

SCIENCO.

As shown in Table 5-15, “formal and informal events” is the most frequently mentioned KM

practice for supporting a knowledge transferring process in SCIENCOS’ PMO. This means that

participants believe that the current knowledge is mainly transferred through formal and

informal events. For instance, following is a participant’s comment to explain workshops and

seminars, as one of associated practice for formal and informal events:

“…On the other hand in our group we have seminars every afternoon on the Wednesday

and during the seminars there will be one person talking to others you know let’s say

they’ve captured…that they really are into it scientifically...”, quoted by In.Sc.4.

Table 5-15 Knowledge transferring categories and pratices (developed for this research)

KM transferring categories Associated System/Practices in SCIENCO Frequency

Communication channels • Chat rooms • Email 5

Database • Wikis 5 Discussion forums • None 0

Electronic bulletin board • Project bulletin and reports 2 Formal and informal events • Seminar and workshops 11

Intranet • None 4 Knowledge directories • None 2

Knowledge list • None 0

Training & mentoring • Induction • Mentoring • Online learning systems

8

Video and Tele Conference meeting • None 2

Yellow page • None 0

Training and mentoring is the second most frequently mentioned practice to facilitate the

knowledge transferring process. According to research findings, some new KM practices for

knowledge transferring, such as Induction, have been fairly developed to improve the project

knowledge management, as one of the participants [In.Sc.3] explains:“… Also there is an

induction where you start, everyone has to go to a two day course. But no, I mean when I

started it was very difficult because there was nothing…”. In addition, direct observation

recognised numbers of mentoring programs for juniors, which are managed by senior staff,

consistent with one of the interviewee’s comments : “… a project that I was mentioning before

we did establish and …”, quoted by In.SC.5. In other words, from participants’ point-of-view

training and mentoring practices contribute to a process of knowledge transferring in the

SCIENCO’s PMO.

Communication channels and database are the third and fourth most frequently mentioned

KM practices to support the process of knowledge transferring. According to the research

findings, email was found as an important means for transferring knowledge since it is used


across the organisation, as In.Sc.4 comments; “…transfer again mostly done through documents

and email…”. Also, Wiki as the one of current DBs is the most reusable data base that

contributes to transfer project knowledge across the SCIENCO (Wiewiora, et al. 2010). On the

other hand, there are some challenges in regards to current DBs as well as communication

channels. In fact, accessibility and search-ability are the significant issues in this regard, which

need to be addressed by the PMO in the next level of maturity.

Figure 5-12 Knowledge Transferring at project lifecycle (developed for this research)

On the other hand, seven out of eleven KM practices to support knowledge transferring are

yet to be appropriately developed in SCIENCO’s PMO. In fact, the limited evidences have been

recognised to support the utilisation of numbers of KM practices in SCIENCO, i.e. Video Tele

conference, Intranet, Discussion forums, yellow pages, intranet, knowledge list, and “bulletin

board”. This means that a few KM practices are there to significantly support knowledge

transferring process. In other words, SCIENCO should focus on providing an appropriate plan

to address these KM practices in order to improve the quality of knowledge management, and

eventually increase the project success rate.

In summary, knowledge transferring is the third frequent KM process from participants’

point-of-view in the SCIENCO. In fact, the research outcomes revealed that respondents believe

the four following KM practices: formal and informal events; communication channels;

database; and training and mentoring, contribute to knowledge transferring in the SCIENCO’s

PMO, while the other associated practices, such as yellow pages and knowledge list, are yet to

be addressed. These findings are consistent with a similar study, undertaken by Wiewiora, et al.

(2010). According to Wiewiora, et al. (2010) the three major following practices: formal and

informal events; email; and Wiki, are used in SCIENCO for supporting knowledge transferring,

however, some factors such as lack of trust and appropriate culture make numbers of challenges

for transferring project knowledge. In fact, the lack of culture and trust in the project

0

1

2

3

4

5

6


Closing

Communication channels

Database

Discussion forums

Electronic bulletin board

Formal and informal events

Intranet

Knowledge directories

Knowledge list

Training& mentoring

Video and Tele Conference meeting

Yellow page


environment could be improved through the following maturity models (Kerzner 2005; Project

Management Institute 2008b). In other words, SCIENCO’s PMO could address some of the

existing issues of knowledge transferring in the next level of maturity.

Knowledge Reusing in SCIENCO’s Project Management Office 5.5.2.4

The process of knowledge reusing has been recognised as the least frequently mentioned of

the KM processes in SCIENCO. In fact, only less than three percent of comments have been

discussed as knowledge reusing, as shown in Table 5-12. According to the research framework

there are 11 KM practices to support knowledge reusing. In order to investigate these KM

practices in the SCIENCO, the similar process of coding was managed, as presented in

Table 5-16. As it could be inferred from this table, there are a few practices to support

knowledge reusing in the SCIENCO. In other words, the existing KM practices do not

significantly support the process of knowledge reusing in this case study, in which only less

than 10 quotes have been found to support project knowledge reusing.

From participants’ point-of-view, the majority of knowledge reusing practices have not been

addressed in the SCIENCO, from respondents’ point-of-view. In addition, only less than six

comments have been mentioned to support the following KM practices: formal and informal

events, database, electronic notice board, internet and lesson learnt. However, their frequencies

are not significant enough to be considered as reliable KM practices to support knowledge

reusing. This means that either interviewee does not believe that there are some practices for

reusing knowledge in place, or the current practices have not been appropriately designed for

this purpose. Both scenarios indicate that the current KM practices are yet to be developed in

order to improve the quality of knowledge reusing in the SCIENCO’s PMO. According to

PMBOK (2013) the previous or similar project’s knowledge should be used at initiation,

planning, execution and monitoring phases, however, the research outcomes explored that there

are limited practices to facilitate reusing of the existing knowledge SCIENCO’s PMO.

Table 5-16 Knowledge Resing in SCIENCO’s PMO (developed for this research)

KM reusing categories Associated System/Practices at SCIENCO Frequency

Data base • Wiki 1 Data mining • None 0

Document Management System • After action review • Post project reports

0

Electronic notice board • None 1

Expert systems • None 0

Formal or informal meetings • None 2

Intranet • None 1

Knowledge detection tools • None 0

Knowledge map • None 0

Lesson learnt • None 1



Furthermore, the next level of analysis focuses on knowledge reusing at project life cycle. As

depicted at Figure 5-13, knowledge reusing is inadequately used at three project life cycle

except closing phase. This is consistent with the research framework, as it has been assumed

that only knowledge capturing should be employed at closing phase. In addition, the lack of

knowledge reusing practices is quite obvious in Figure 5-13.

Figure 5-13 Knowledge reusing in SCIENCO’s PMO (developed for this research)

In summary, knowledge reusing is the least used KM process in the SCIENCO, from

respondents’ point of view. As the research findings revealed, there are a few comments in this

regard, which means that knowledge reusing is not satisfactory from participants’ perspective.

In other words, knowledge reusing is yet to be addressed in the SCIENCO’s PMO. According to

Love, et al. (2003) lack of knowledge reusing practices causes the “rework”, which has been

mentioned as one of the significant challenges for projects in Australian companies. Therefore,

this knowledge process should be addressed, as it impacts on improving quality of project

outcomes. On the other hand, according to the research framework, knowledge reusing is

dependent on quality of knowledge capturing and transferring (Owen and Burstein 2005).

Consequently, if PMO focuses on improving knowledge capturing and transferring, then it will

impact on quality of the knowledge reusing process. This means that PMO as first level of

maturity SCIENCO should focus on improving three KM processes, i.e. knowledge capturing,

creating and transferring, however, the development of knowledge reusing should be considered

for achieving the next level of maturity.

Summary 5.5.2.5

In conclusion, the first research question (RQ1- How are KM practices and processes

employed in the PMOs?) and its sub-questions have been discussed in this section. In order to

answer the third sub-question (RQ 1.3 What kinds of KM practices are utilised in each maturity

level of PMO?), it was realised that more than 50 percent of the coded comments support

0

1


Closing

Data base

Data mining


Electronic notice board

Expert systems

Formal or informal meetings

Intranet


Knowledge map

Lesson learnt

Yellow page


knowledge capturing, more than 30 percent knowledge creation, less than 13 percent knowledge

transferring, and less than 3 percent knowledge reusing process. This means that knowledge

capturing and creation are significantly supported by the research findings while knowledge

transferring and reusing are not as robust as other two KM processes.

Also, according to the research framework, it has been assumed that only knowledge

capturing should be employed at closing phase. To examine this assumption, numbers of

techniques were employed and, eventually, the research findings confirm that this assumption is

valid in the SCIENCO’s PMO. In addition, the research analysis explored that the majority of

KM activities are undertaken at Execution and Planning phase, while numbers of KM practices

in are at initiation and closing are significantly two other phases. This finding is in line with PM

literature, since PMBOK explicitly addresses numbers of PM processes to support KM at

planning and execution phase (Project Management Institute 2013).

Based on the case study findings, some propositions could be made to address the KM at

first at the first level of maturity: 1) Knowledge capturing and creation are the most important

processes to be improved at the first level of maturity. This means that PMO at this level should

firstly focus on improving current practices for capturing knowledge and then creation, 2)

Knowledge transferring has the third priority but the existence of some practices to support the

basics is necessary, 3) Knowledge reusing is the least important KM process at this level, and it

is dependent on quality of the knowledge capturing and transferring process. This means the

quality improvement of knowledge capturing and transferring directly impacts on quality of

knowledge reusing process.

The importance of knowledge processes in SCIENCO 5.5.2.6

In order to answer the second research question (RQ2-How do KM practices contribute to

improve maturity level of the PMO) a survey–questionnaire was distributed among participants

and seven of them were returned. In this survey, SCIENCO’ participants were asked to rank the

importance of four KM processes: Creation; Capturing; Transferring and Reusing at project

life cycle, i.e. Initiation; Planning; Execution & monitoring; and Closing. After collecting the

respondents’ answers, MS Excel was used to analyse the collected data. As discussed earlier,

the AHP technique is a suitable and accurate method for ranking the priority of competing

phenomena (Lindner and Wald 2011; Stam and Silva 1997), therefore, this technique was used

to rank KM processes in SCIENCO’s PMO.

According to the research findings, at the initiation phase respondents believe that

knowledge capturing and then transferring are the most important processes, while knowledge

reusing is not as important as other KM processes. The current PM standards advise that two

major PM processes: developing project charter; and identifying project stakeholders, should be

employed at the initiation phase (Kamara, et al. 2003; Project Management Institute 2013; Tan,


et al. 2007). As could be inferred, these two mentioned processes contribute to create required

knowledge for the next phase, i.e. planning, therefore the created knowledge needs to be

captured and transferred. In addition, according to the existing PM methodologies, the

utilisation of knowledge of similar projects plays a significant role at initiation phase.

However, participants rank knowledge reusing as the last important KM process, as shown at

Figure 5-14. As discussed in the previous section, knowledge reusing has limited numbers of

KM practices in SCIENCO. Also, the level of PMO’s maturity is one which means that

SCIENCO’s PMO is at its initial steps of development. Therefore, it could be justified that the

importance of knowledge reusing in the initiation phase has not be appropriately realised. This

means that the current research findings support previous evidence and clarify that knowledge

reusing is the last important KM process, when the level of maturity at PMO is one. So it could

be concluded that despite the importance of the knowledge reusing planning and initiation

phase, a PMO with first level of maturity should focus on other KM processes.

According to PMBOK, at the planning phase knowledge creation is the most important KM

process (Reich and Wee 2006). This research finding is consistent with the mentioned theory, in

which participants believe that knowledge creation has the first priority at planning phase, as

depicted at Figure 5-14. Also, they asserted that knowledge reusing is the second important KM

process at the planning phase. As discussed earlier, the interview analysis revealed that

knowledge reusing has the lowest KM practices in the SCIENCO, especially at planning phase.

This means that the importance of knowledge reusing at the planning phase has been realised by

participants, however, the current practices do not appropriately support the knowledge reusing

process.

Initiation Phase

Planning Phase

0

1

2

3

4

CapturingCreatingTransferringReusing

0

1

2

3

4


Execution and Monitoring phase

Closing Phase

Figure 5-14 The importance of KM processes in SCIENCO (developed for this research)

According to PM methodologies and the research framework, all of the KM processes

should be properly employed at the execution and monitoring phase (Kerzner 2013; Project

Management Institute 2013). The research findings explored that respondents have indicated

knowledge creation as the most important KM process, and knowledge capturing as the second

most important , while knowledge reusing has the lowest importance at this phase.

According to Reich and Wee (2006), at the execution and monitoring phase, the majority of

KM practices should managed the process knowledge capturing and transferring, so the

knowledge creation and reusing should have the next priorities, however, the research findings

do not support the above mentioned assumption. As explained earlier, SCIENCO is a research

organisation so the nature of its activities is different from other industries such as construction

or mining. In other words, SCIENCO undertakes project to create and deliver knowledge or

knowledge-driven deliverables, while a construction company conducts a project to deliver

products such as buildings or bridges. Therefore, knowledge creation is the most important

activities at execution phase for research projects in SCIENCO, while knowledge capturing and

transferring are the most important KM processes in other types of project bases organisations.

As discussed earlier, according to the research framework, knowledge capturing should be

the only KM process to be used at closing phase (Owen and Burstein 2005). This means that

knowledge capturing should be the most important KM process during the closing phase of a

project. As Figure 5-14 depicts, knowledge capturing has been ranked by SCIENCO’s

employee, as the most important KM process at closing phase, which is line with the research

assumption. This means that both interview findings and survey consistently confirm the

importance of the knowledge capturing process at closing phase.

0

1

2

3

4

0

1

2

3

4


Figure 5-15 The general ranking of KM processes in SCIENCO (developed for this research)

At the next level of analysis, the importance of KM processes has been analysed through

considering the project lifecycle. In other words, it was aimed at determining the general

ranking of KM process, regardless of the project life cycle. To do so, the AHP method was

employed through assigning appropriate weight to each project phase. This weighted model

enables a researcher to analyse the overall rank of the KM process regardless of various phases

(Lindner and Wald 2011). The research findings explored the following ranking of KM

processes: 1) Capturing, 2) Creation, 3) Transferring, and 4) Reusing, which are depicted in

Figure 5-15.

According to the research findings, in general, knowledge capturing is the most important

KM process in SCIENCO from participants’ points-of-view. This means that SCIENCO’s

employees believe that, in the current situation, the first priority is to develop a KM system to

support knowledge capturing, and then creation. In addition, knowledge transferring and reusing

have the third and fourth level of importance. This means that SCIENCO’s employees have

realised the importance of these two KM processes, however, their first priority is to focus on

knowledge capturing and creation process. According to the literature and the research

framework, a robust knowledge capturing system provides a reliable ground for other KM

processes, specifically KM transferring and reusing (Arora, et al. 2010; Owen, et al. 2004).

Therefore, it should be reminded that this ranking has been obtained through conducting the

survey, therefore, for validation purposes, it needs to be compared to previous findings.

In summary, the research findings from the survey, interview analysis, documents analysis,

and observation have consistently agreed on the importance of knowledge capturing and

creation processes as the first priority from participants’ points of-view, while knowledge

transferring and reusing have not been found to be as important as the other two KM processes.

So it could be concluded that current KM practices mainly support knowledge management

processes in the following order: Capturing, Creating, Transferring and Reusing. In addition,

by considering the maturity level of SCIENCO’s PMO, it could be summarised that at the first

Capturing

Creating

Transferring

Reusing

0

1

2

3

4

Capturing

Creating

Transferring

Reusing


level of maturity PMO should focus on developing appropriate KM practices for facilitating

project knowledge capturing and creation, however, basic practices for knowledge transferring

and reusing will contribute to the equality of project knowledge management. At this section,

the first sub question of the second research (RQ2-How do KM practices contribute to improve

maturity level of the PMO) was answered. The next section aims to discuss the remaining part

of the second question.

DISCUSSION AND IMPLICATIONS 5.6

In the previous sections, the first question, and initial part of the second research question

have been discussed. At first, the existing challenges of project KM in SCIENCO have been

explored at the early sections of this chapter, then the importance of the four KM processes have

been analysed through using both interview, and questionnaire methods. As discussed, the

research outcomes from both mentioned methods are consistent, which contributes to the quality

of research findings (Yin 2009). In this section, another level of research analysis will be

discussed to explore the potential relation between the recognised challenges and four KM

processes as well as their associated sub-processes.

Knowledge capturing’s sub processes and practices in SCIENCO 5.6.1

As discussed earlier, the initial analysis has shown that most of challenges are related to

knowledge capturing. However, according to the research findings, knowledge capturing not

only has been ranked as the most important KM process, but also most of the current KM

practices in the SCIENCO facilitate the knowledge capturing process. In order to examine this

phenomenon, further analysis was undertaken through employing the research framework.

According to the research framework, knowledge capturing has been classified into four sub-

processes: Identification, Storing, Classification, and Selection, as shown at Table 5-17 (Lytras

and Pouloudi 2003; Nissen, et al. 2000). As discussed earlier, five KM challenges have been

recognised in SCIENCO’s PMO: 1) Difficulties of searching and detecting required knowledge,

2) Issue of locating and accessing right information and/or right expert, 3) Lack of KM practices

and processes during project life cycle, 4) Lack of appropriate systems to support project KM,

and 5) Issue of appropriate access to the existing systems.

The collected data was entered to Nvivo as well as the research framework, and then

numbers of Nvivo’s functions such as queries and relationship were employed to analysis the

relation between challenges and knowledge capturing sub-processes. The analysis outcomes

revealed that “knowledge storing” is the most satisfactory process among other knowledge

capturing sub-processes, in which its related KM practices are appropriately used in the

SCIENCO, as depicted at Table 5-17. In addition, the only challenge against the knowledge

storing process is the issue of access to the associated applications. This means that knowledge


storing is the strongest KM sub-process to support knowledge capturing. Similar analysis was

managed for the other three sub-processes and their results have been presented in Table 5-17.

Table 5-17 Knowledge capturing sub-processes in SCIENCO (developed for this research)

K. Capturing Sub

Processes


Associated Challenges Current Status


• Expert locator • Formal and informal

event

• Knowledge detection tools • Knowledge repositories 1, 3 and 5

A few practices in place, however, it is yet to be developed

Knowledge Storing

• Data base • Formal and informal

event

• Document Management System (DMS) 5

Most of the current system support this

process


• DMS • Frequently ask

questions (FAQ) • Intranet


system (MIS) 4,5

After knowledge storing this process

has the most KM practices to be

supported

Knowledge Selection

• Knowledge inquiry system (KIS)

• Data base • Frequently ask questions

(FAQ) 1,4,5

A few practices in place, however, it is yet to be developed

The knowledge classification process has been fairly developed in SCIENCO, and the

research findings confirm that some of the associated KM practices to knowledge classification,

such as MIS and DMS, are used in this case, but some practices such as frequently asked

question (FAQ) are MIS are yet to be developed to improve knowledge classification, and

ultimately knowledge capturing. In addition, from the respondent point-of-view, two of five

recognised issues, i.e. 4 and 5, impact on the quality of knowledge classification, as depicted in

Table 5-17. This means that knowledge classification needs to be improved, since some of its

associated practices are yet to be addressed.

Knowledge selection is another sub-process of knowledge creation with three practices, as

shown in Table 5-17. According to the research findings only the database has been addressed

to support knowledge selection, while KIS and FAQ are yet to be improved in SCIENCO. In

addition, further investigation through using revealed that three recognised challenges are

directly related to lack of knowledge selection practices, i.e. 1, 4, and 5. This means that the

current practices do not appropriately support the knowledge selection process and it needs to

be improved accordingly.

According to the research framework there are four KM practices to facilitate knowledge

identification: Expert locator, Knowledge detection tools, Knowledge repositories, Formal and

Informal event. The research findings explored that except for formal and informal event, the

other mentioned practices are yet to be addressed in SCIENCO. In addition, three out of five

recognised challenges are directly related to lack of practices for supporting knowledge

identification. This means that knowledge identification faces three mentioned challenges and

they are yet to be addressed in the SCIENCO.


In summary, knowledge storing and classification have been fairly addressed in SCIENCO,

while knowledge selection and identification are yet to be appropriately addressed in this case.

This means that knowledge selection and identification are supported with a few practices, but

there are numbers of KM practices to support knowledge storing and classification. However,

all four mentioned sub-processes are faced with numbers of challenges, as shown in Table 5-17.

This means that knowledge capturing has been developed in some aspect but it still needs to be

improved and there are some issues related to the knowledge capturing process. In other words,

despite the fact that the majority of current KM practices support the knowledge capturing

process, they have not addressed all the current KM challenges in SCIENCO. The research

findings explored that SCIENCO should focus on improving knowledge identification and

selection in order to both develop knowledge capturing and address the current KM issues.

According to the research framework, this shall contribute to improve the quality of knowledge

transferring and knowledge capturing, and ultimately the level of PMO maturity.

Knowledge creation’s sub processes and practices in SCIENCO 5.6.2

As discussed earlier, knowledge creation is the second important KM process in

SCIENCO’S PMO, and also has the most KM practices after knowledge capturing. Knowledge

creation is part of daily activity in SCIENCO, as a research organisation. According to Nonaka

and Takeuchi (1995) knowledge is created through four processes: Socialisation,

Externalisation; Combination; and Internalisation which is called SECI. The SECI model was

adopted in the research framework by which knowledge creation has been classified to four KM

sub processes and their associated KM practices, as presented in Table 5-18.

According to the research framework, Socialisation is the process of creating tacit

knowledge through various types of communicating (Nonaka & Teece, 2001) in which it is

facilitated through any type of formal and informal events, as shown in Table 5-18. Hoegl and

Schulze (2005) discuss that informal events are the best practices for supporting socialisation by

which tacit knowledge is discussed and sometimes transferred among individuals. As discussed

earlier, formal and informal events are the most mentioned KM practice to support knowledge

creation practices, as illustrated in Table 5-14. This means that socialisation is appropriately

supported in SCIENCO through a number of practices such as workshop & seminar, community

of practice, and formal and informal events.

Table 5-18 Knowledge creation sub procesess in SCIENCO (developed for this research) K. Creation


Knowledge Creation Current Situation

Socialisation • Formal and informal event

• Workshops & seminar • Community of practices

Most of them have been put in place and utilised

Externalisation

• Workshops & seminar

• Deductive & Inductive thinking


Most of them have been put in place and utilised but some of them such as expert system should be


improved

Combination • Community of

practices • Best Practice Cases


Except the community of practices, other are yet to

be addressed

Internalisation • Research services • Simulation

• Experimentation Most of them are utilised

The Externalisation is the processes of transforming tacit to explicit knowledge (Nonaka and

Teece 2001). According to the research framework there are numbers of practices to facilitate

Externalisation such as community of practice and expert systems. The research findings

revealed that most of the mentioned KM practices are used to some extent, however, some of

them are yet to be improved. For instance SCIENCO’s employees participate in numbers of

seminars and workshops, but they believe that a community of practice is yet to be improved

upon in SCIENCO. Also, they mentioned that the current expert system faces some issues as

one of participants explains [In.Sc.3]“…most of our researchers are protective about their

knowledge ...”. In fact, externalisation has been fairly developed in SCIENCO, however, it

needs to be improved to address some of the mentioned issues.

The process of transforming the explicit knowledge to more complicated explicit knowledge

is called Combination (Nonaka and Teece 2001), which is supported through numbers of

practices as shown in Table 5-18. According to the research findings, respondents believe that

community of practice is the only KM practice, among other combination practices, which is

used in SCIENCO to support a combination process. This means that there are four KM

practices to facilitate combination which are yet to be addressed in SCIENCO: knowledge

Broker, Data mining, Documentation search, and Best Practice Cases. In other words, the

majority of KM practices for Combination process need to be improved in SCIENCO’s PMO.

According to Nonaka (1994) Internalisation is another way of creating knowledge through

developing new tacit knowledge from existing explicit knowledge. According to the research

framework there are three KM practices to support Interrelation: research services, simulation,

and experimentation, as depicted in Table 5-18. The research findings explored that from

respondents’ perspectives, all of the mentioned practices are used in SCIENCO. In other words,

SCIENCO as a research organisation has provided adequate tools for knowledge creation

through Internalisation process.

Tacit Knowledge TO Explicit Knowledge

Tacit Knowledge

From

Socialization (has been addressed in

SCIENCO)

Externalization (has been addressed in

SCIENCO)

Explicit Knowledge

Internalization (has been addressed in

SCIENCO)

Combination (yet to be properly

addressed)

Figure 5-16 The SECI Model at SCIENCO (Nonaka and Teece 2001)


In summary, knowledge creation has been significantly addressed in SCIENCO, however,

there are some issues that are yet to be addressed. As discussed, three out of four knowledge

creation sub-processes have been addressed, but the Combination sub-process is faced with lack

of KM practices such as data mining and documentation search. According to Nonaka (2001;

2011) the SECI model follows a spiral method in which all four sub-processes should be

interconnected as illustrated at Figure 5-16. This means that the process of knowledge creation

is fully supported when all four sub-processes are being appropriately utilised. As shown at

Figure 5-16, three out of four knowledge creation wings, Socialisation, Externalisation, and

Internalisation, have been developed to some extent, but Combination needs to be addressed

accordingly. In other words, the SECI model does not completely work in the SCIENCO’S

PMO and it needs to be improved through addressing the mentioned issue.

Knowledge transferring’s sub processes and practices in SCIENCO 5.6.3

According to the research framework there are two sub-processes for knowledge

transferring: Distribution & Forwarding; and Sharing, as depicted at Table 5-19 (Lytras and

Pouloudi 2003; Newell, et al. 2006; Nissen, et al. 2000). The communication channels (Email,

chat), and intranet are an example of “knowledge distribution”, and, training, discussion forums

and mentoring are instances of “knowledge sharing”. In fact, distribution process technologies

are more influential, while for knowledge sharing procedures, people play an influential role

(Hurt and Thomas 2009; Nonaka and Takeuchi 2011; Wiewiora, et al. 2010). As shown in

Table 5-15, the research findings revealed that both sub-processes are employed, to some

extent, during project lifecycle for knowledge transferring purposes, however, they need to be

improved since some of their associated practices have not been appropriately developed. In

other words, it was explored that all three out of four practices for knowledge sharing (formal

and informal events, training, and mentoring) are used in SCIENCO. In addition, some of the

KM practices for supporting knowledge distribution, such as knowledge list and yellow pages,

have not been mentioned by SCIENCO’s participants. This means that from the respondents’

point of view, both knowledge sharing and distribution needs to be improved in SCIENCO.

As discussed earlier, a similar study was conducted by Wiewiora (2011) to investigate

knowledge transferring in SCIENCO. In that research, numbers of factors such as “trust” and

“culture” have been discussed to investigate the challenges of knowledge transferring in

SCIENCO (Wiewiora, et al. 2009a). According to Wiewiora (2011) lack of “trust”, and

appropriate culture, impacts on transferring knowledge among SCIENCO’s employees. This

means that SCIENCO should address appropriate practices to improve both trust and

organisational culture for motivating employees in order to share their knowledge.

Table 5-19 Knowledge transferring sub processes in SCIENCO (developed for this research) K. Transferring Sub Processes

Practices for Knowledge Transferring Current Situation



Forwarding


• Communication channels

• Knowledge list


• Yellow page • Intranet • Data base

Some practices need to be improved such as yellow

pages, intranet, and knowledge list

Knowledge Sharing • Discussion forums • Formal and

informal events

• Mentoring • Training

Some practices need to be improved such as mentoring

and discussion forums

In addition, according to the research framework, transferring knowledge is dependent on the

quality of knowledge capturing (Arora, et al. 2010; Owen and Burstein 2005). As discussed

earlier, SCIENCO faces a number of challenges to capture project knowledge. The research

findings revealed that the lack of appropriate systems is one of the mentioned challenges which

hinder knowledge capturing. Therefore, SCIENCO has been advised to developed new systems

to improve the quality of knowledge capture. According to the research framework some of the

KM systems, such as DMS and DBs, are used both for knowledge capturing and transferring

purposes. In other words, developing a KM capturing system directly contributes to improve

knowledge transferring.

In summary, transferring knowledge in SCIENCO’S PMO is not as strong as the other two

mentioned KM processes, i.e. capturing and creation. According to the research framework,

knowledge transferring comprises two sub-processes: distribution and sharing, in which

distribution relies more on systems and application, while human factors, such as trust and

culture, impact on knowledge sharing. The research findings revealed that SCIENCO not only

needs to improve the associated systems for knowledge distribution purposes such as DMS and

DBs, but also it is advised to develop appropriate practices such as incentives and rewards for

addressing the current issues, i.e. trust and culture. This will contribute to enhance the quality of

project knowledge management, ultimately to improve the maturity level of SCIENCO’s PMO.

Knowledge reusing sub-processes and practices in SCIENCO 5.6.4

As discussed earlier, knowledge reusing is the least important of the KM processes in

SCIENCO, from participants’ points-of-view. According to the research framework, knowledge

reusing comprises three sub-processes: Adapting, Applying, and integrating, as depicted in

Table 5-20 (Lytras and Pouloudi 2003; Nissen, et al. 2000). In addition, in the research

framework, knowledge reusing has strong coloration with knowledge capturing and transferring

(Owen and Burstein 2005). This means that robust knowledge capturing and transferring plays a

significant role, in order to implement a reliable knowledge reusing system. As mentioned

previously, less than three percent of the coded comments have discussed KM from a

knowledge reusing point-of-view. This means that participants believe that the current practices

are not strong enough to support knowledge reusing in SCIENCO’S PMO. In other words, all

three sub-process of knowledge reusing needs are yet to be improved.

Table 5-20 Knowledge reusing sub-processes in SCIENCO (developed for this research)


K. Reusing Sub Processes

Practices for Knowledge Reusing Comments

Knowledge Adapting




Majority of the mentioned KM practices are

yet to be addressed for

knowledge reusing

purposes



In summary, SCIENCO’s PMO with first level of maturity has developed limited practices

to support the knowledge reusing process. The research findings revealed that all three sub-

processes of knowledge reusing are yet to be addressed in SCIENCO’s PMO. According to the

research framework, knowledge reusing is improved through developing knowledge capturing

and transferring. Therefore, SCIENCO’s PMO is advised to address the recognised issues of

knowledge capturing and transferring, which ultimately contribute to improve knowledge

reusing. In other words, SCIENOC at this level of maturity is advised to prioritise KM in

accordance to the recognised importance of knowledge processes.

CONCLUSION 5.7

This chapter aims to answer the first and second research questions (RQ1. How are KM

practices and processes employed in the PMOs, and RQ2. How do KM practices contribute to

improve maturity level of the PMO), and their associated sub-questions (what are the current

challenges of the PMO from KM perspective, What types of knowledge are required at each of

following project phases, What kinds of KM practices are utilised in each maturity level of

PMO, What is the importance of knowledge processes at each phase of project, How PMO

should contribute for managing the project Knowledge). The selected case study, SCIENCO, is

a research organisation which has a PMO with first level of maturity. In order to investigate the

above mentioned questions in SCIENCO, the research framework (Chapter 3) has been

employed by following the research methodology (Chapter 4). In that section, a summary of the

research findings has been explained accordingly.

According to the research findings, SCIENCO deals with the following challenges from a

KM point-of-view: Difficulties of searching and detecting required knowledge, Issue of locating

and accessing right information and/or right expert, Lack of KM practices KM processes during

project life cycle, Issue of appropriate access to the existing systems, Lack of appropriate

systems to support project KM. This means that project knowledge management is yet to be

developed in SCIENCO, since the PMO deals with the five basic issues of KM.

The research findings revealed the following order, from participants’ points-of-view, for the

required types of knowledge: 1) Knowledge about Clients, 2) Knowledge of who knows what,

3) Project Management Knowledge, 4) Costing Knowledge, 5) Knowledge about suppliers, 6)


Knowledge about Procedures, 7) Technical Knowledge, 8) Legal and statutory Knowledge. This

is a clear indication for SCIENCO, or PMOs with a similar maturity level, to prioritise the

importance of their required knowledge.

Moreover, the importance of KM processes has been discussed through analysing both

interviews and survey, and consistently both revealed the following order: 1) Knowledge

Capturing 2) Knowledge Creation 3) Knowledge Transferring, and 4) Knowledge Reusing. This

means that knowledge capturing and creation are the most important KM practices, while

transferring and reusing are not as important as the other two. In addition, informal and formal

events are the most utilised KM practices, which contribute to all four KM processes. These are

valuable findings for the PMO to improve this practice, as they play a significant role for project


In the last section of this chapter, i.e. 5.6, the relation between KM challenges and KM

processes, as well as sub-processes, have been discussed. These findings will contribute to

prioritise the development of KM processes, sub-processes and practices. In other words, the

research findings address appropriate KM practices and processes with regards to their

associated challenges and issues. This will assist PMOs to improve the quality of project

knowledge management, and consequently the maturity level of PMO.

In the end, the following have been summarised in SCIENCO’s PMO, with first level of

maturity:

• At the first level of maturity the awareness of KM has been raised and considered,

• The first and second priority are knowledge capturing and knowledge creation, which need to be improved through providing associated KM practices,

• Knowledge transfer has the third level of importance in which basic KM practices should be put in place,

• At this level of maturity, the current PM methodology is abstract, so it is recommended to integrate both PM and KM practices to improve the quality of project knowledge management ,

• The PMO should provide appropriate practices to assist project team members with assessing the three most important types of knowledge:

o Knowledge of project management through providing PM methodology, o Knowledge about clients through developing proper KM practices, and o Knowledge of who know what through addressing appropriate KM practices

• The PMO at this level should focus on understanding the current PM systems in order to appropriately integrate them for PM and KM purposes.

124 Chapter 6 | Case Study Analysis: GOVCO

Chapter 6

CASE STUDY ANALYSIS: GOVCO

INTRODUCTION 6.1

In Chapter 5, the first case study, i.e. SCIENCO, was investigated through following both

research framework (Chapter 3) and methodology (Chapter 4). In this chapter, similar

procedures will be followed to scrutinise a second case study, GOVCO, from a KM point-of-

view. In this chapter, GOVCO’s PMO will be investigated to explore project knowledge

management in a governmental organisation in order to discuss the two first research questions

(RQ1. How are KM practices and processes employed in the PMOs, and RQ2. How do KM

practices contribute to improve maturity level of the PMO?). To do so, first the organisation’s

background will be explained, followed by data collection procedures. Second, the PMO’s

maturity level will be discussed alongside the current PM systems. Third, the data analysis will

be undertaken to discuss the current status of GOVCO’s PMO from a KM perspective. And

finally, concluding remarks and the research findings will be summarised.

GOVCO’S BACKGROUND 6.2

GOVCO is an Australian state governmental department which delivers a range of housing,

building and construction services to other governmental or non-governmental agencies. It also

provides appropriate policies, advice, and consultancy services in the areas of construction,

asset management and procurement for the state government. In addition, GOVCO in the main

body that manages government projects in the fields of construction and building. In fact,

GOVCO with more than 5500 employees deals with significant numbers of small and large

projects undertaken to improve the quality of public services. To do so, a PMO has been

developed within GOVCO’s structure in order to facilitate project management, ultimately to

contribute to project success rate, as shown at Figure 6-1.

The GOVCO’s PMO is responsible for developing appropriate and practical processes and

procedures to improve the quality of project management. In addition, this PMO is not in charge

of project implementation during project implementation. This means that GOVCO’s PMO has

been designed to provide PM services, so it is not involved in a project implementation. This

type of functionality of PMO is close to the definition of PMO as a “Centre of Excellence”.

According to the current literature, the PMO is the centre of excellence in which it has limited

involvement in project implementation, except providing services for improving the quality of

project management (Kerzner, 2005; Project Management Institute, 2008b). In other words, the

Chapter 6 | Case Study Analysis: GOVCO 125

centre of excellence develops services, processes and procedures to project managers for

assisting them with providing quality outcomes. This definition is compatible with the

expectations of GOVCO’s senior managers from their PMO.

Figure 6-1 A snapshot of GOVCO’s structure (from GOVCO’s organisational chart)

The GOVCO’s PMO provides numbers of services to project managers as well as other

project stakeholders. It has developed numbers of processes and procedures to facilitate project

management within GOVCO, and also offers numbers of training courses and workshops to

project managers in order to improve the knowledge of project management within the

organisation. In this chapter, GOVCO’s PMO will be discussed to not only assess the maturity

level of PMO, but also, to investigate “how project knowledge is managed” in this case study.

To do so, the reliable data will significantly contribute to the quality of this research, so in the

next section the process of data collection has been explained, accordingly.


Similar to the previous case study, the research methodology alongside the case study

protocol were followed to arrange the data collection in the field. In addition, the appointed

liaison person assisted with providing a schedule to conduct the research data collection. In

total, seven interviewees were selected: GOVCO’s senior manager, PMO manager and

coordinator, a program manager, two project managers, and one project team member, as shown

at Table 6-1. In some cases, interviews were conducted two times as the researcher needed more

clarification. For confidentiality purposes, interviewees’ names were replaced by a selected

code as can be seen in Table 6-1.

All interviews and the majority of data collection activities were undertaken at GOVCO’s

site, from late March 2012 to early June 2012. In addition, four days were spent to directly

observe the current PM activities in GOVCO. Also, it took three days to study the utilised

software and systems in GOVCO’s PMO. After the data collection stage, the collected

interviews were transcribed into the MS Word format in order to prepare them for uploading in

Nvivo, as the selected software for analysis purposes. In total, this process took two months, and

more than 140 pages of interviews transcriptions were provided to be used in Nvivo.

State Government

Other govermental departments GOVCO

Program management office


Table 6-1 Interviewees’ list and schedule in GOVCO (developed for this research)

Interviewee Position 1st interview 2nd interview

In.Gd.1 GOVCO senior Manager 30/05/2012 (face to face)


In.Gd.2 PMO manager 11/05/2012 (face to face)


In.Gd.3 PMO Coordinator 24/05/2012 (face to face)


In.Gd.4 Program Manager 25/05/2012 (face to face)


In.Gd.5 Project Manager 25/05/2012 (face to face)

(30/05/2012 (face to face)

In.Gd.6 Project Manager 29/03/2012 (face to face)


In.Gd.7 Project team member 29/03/2012 (face to face)


THE DATA COLLECTION METHODS 6.4

According to the research methodology, three forms of data collection were employed: 1)

semi-structured interviews alongside the two types of questionnaires, one for assessing the PMO

maturity level and another for assessing the importance of KM processes, 2) direct observation,

and 3) document analysis. The first questionnaire was developed to assess the maturity level of

project management activities, and was given before the interview questions, and the second

questionnaire was asked after finishing the interview questions.

Table 6-2 Data collection methods (developed for this research)


Interviews and Questionnaires

GOVCO building Researcher

Mentioned in Table 6-1

Documents Review GOVCO

building and QUT

Researcher and GOVCO’s liaison

person

12/05/2012 till 31/06/2012

Direct Observation GOVCO building

Researcher and GOVCO’s liaison

person

16/06/2012 to 20/06/2012

Both direct observation and document analysis have assisted the researcher, not only for

gathering complementary information from this case, but also for investigating GOVCO’s

activities from a PM as well as KM point-of-view. The data collection activities were conducted

in accordance with the case study protocol, also by getting assistance from the assigned

employee, as GOVCO’s liaison, as depicted in Table 6-2. In addition, the triangulation of data

collection methods was adopted in order to ensure the quality of gathered data (Singh, et al.

2009; Yin 2009).

THE DATA ANALYSIS 6.5

After data collection, the process of data analysis was conducted to investigate GOVCO’s

PMO from PM and KM points-of-view, and to ultimately answer the research questions. At the


first step, the maturity level of the PMO was assessed, then PM and KM challenges were

discussed, followed by analysing the required types of knowledge during the project lifecycle.

At the end, the importance of four KM processes, Creation, Capturing, Transferring, and

Reusing were analysed, and then they have been examined against the explored KM challenges

to explore the relationship between KM process and KM issues in GOVCO’s PMO.

The maturity level of GOVCO’s Project Management Office 6.5.1

According to the research methodology, the assessment of the PMO’s maturity level is the

initial step to commencing the process of data analysis. The designed assessment model was a

questionnaire survey, which comprises 13 questions to cover the examination of nine PMBOK’s

knowledge areas during the project life cycle. This assessment model is the customised form of

PM assessment method, suggested by Kerzner (2013) which has been simplified to meet the

research scope and objectives.

Table 6-3 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study)

PMBOK’s Knowledge area Maturity level Average ML

Project Scope management 1.93

2.32

Project Cost management 2.57 Project Time management 2.14

Human Resource management 1.93 Project Quality Management 2.79

Project Risk management 2.79 Project Communication management 2.00

Project Procurement management 2.29 Project Integration management 2.43

The questionnaires were distributed among numbers of employees in GOVCO, by which

participants were asked to rate each question from 0 (lowest) to 10 (highest) in which they

should choose “0-1” for poor, “2-3” for weak, and eventually “8-10” for world standard

quality. In total, 12 questionnaires were distributed among respondents and, eventually, eight of

them were returned and all the answers entered in MS Excel 2010. According to the research

framework and (Kerzner (2005); Kerzner (2013)), the level of maturity for a PMO could be any

number from 1 to 5, in which number 1 represents the lowest level of maturity, while number 5

claims the highest maturity level (ML). In other words, a maturity level is defined at five levels

in which the lowest maturity level, i.e. ML=1, indicates that the PMO is in its initial steps to

improve the quality of project management, in contrast the highest maturity level, i.e. ML=5,

means that the PMO has developed and customised a robust and advanced project management

system to support organisational projects (Project Management Institute 2008b).

At the first step, the maturity level (ML) for nine knowledge areas of PMBOK was

investigated, as depicted in Table 6-3 and Figure 6-2. The research findings revealed that the

average maturity level for GOVCO’s PMO is 2.32 out of 5. According to the research

framework and the current literature, ML=2.32 is classified as the second level of maturity


(Kerzner 2005; Project Management Institute 2008b). In addition, as Table 6-3 illustrates the

cost, risk and quality management are ranked at top levels in GOVCO, while HR,

communication, and scope management are yet to be developed in this case. In fact, participants

believe that PM practices have been fairly developed to support project cost, quality, and risk

management, while project scope, human resource, and communication are yet to be addressed

through developing appropriate practices. These findings have been confirmed during document

analysis, when numbers of processes were found to facilitate project risk and quality

management, while a few forms have been recognised to support cost, and communications.

Figure 6-2 The ML of GOVCO’s PMO: PMBOK's knowledge areas (developed for this study)

In the next step, maturity level was analysed from a project lifecycle point-of-view, as the

result depicted at Table 6-4 and Figure 6-3. According to the research findings the average

maturity level is 2.39, which should be ranked at second level of maturity (Kerzner 2005).

Table 6-4 The ML of GOVCO’ PMO: project lifecycle (developed for this research)

Project Phases Maturity level (ML) Average ML

Initiation 2.50

2.39 Planning 2.79


From a process point-of-view, planning and initiation are more satisfactory in comparison to

execution and closing. This means that from participants’ perspectives, the current PM practices

are fairly developed to facilitate initiation and planning phases, while a few practices support

execution and closing phases. Consistently, the interview analysis revealed that participants

have mentioned the lack of PM practices at execution phase, as In.Gd.2 explains “…I think we

actually do the least amount at execution. Because of what we do about the only thing that

would support them would be the training capability you know when they’re executing it…”. As

discussed earlier, GOVCO’s PMO has been designed to be the centre of excellence, therefore it

1.93 2.57

2.14

1.93

2.79 2.79

2.00

2.29

2.43

Project Scope

Project Cost

Project Time

HR management


ProjectCommunication

ProjectProcurement

Project Integration

ML OL


should have less involvement in the execution phase. In other words, the GOVCO’s PMO

should significantly contribute to project initiation, planning, and closing, however, the basic

PM practices to support execution phase, are helpful.

Figure 6-3 The ML of GOVCO’ PMO: project lifecycle (developed for this research)

The research findings revealed that maturity level assessment from both PMBOK’s

knowledge areas, and project lifecycle, have consistently determined that GOVCO’s PMO has

the second level of maturity. In addition, an internal assessment had been previously done by

GOVCO, and consistently they came up with a similar maturity level, as PMO’s manager

[In.Gd.2] explains “… we are probably 2 on a 5 scale the standard…”. In fact, the outcomes

from both methods of maturity assessment are consistent with the internal maturity assessment,

which means that the various methods of data collection have reliable as well as quality results

in this regard.

According to (Kerzner (2005); Kerzner (2013)) and the research framework, the second level

of maturity is called “common process”, which means that there some numbers of common

processes in place to facilitate project management. In addition, at this level of maturity the

benefits of project management have been recognised by organisational employees as well as

senior managers. Also, there is at least one project management framework in place to be

employed by project stakeholders. In other words, the PMO has passed the first level of

maturity, i.e. common language, where the existence of basic PM practices was essential. This

means that the PMO has been developed to address the basic requirements for the first level of

maturity. As discussed in the research framework (Chapter 3) the main characteristics of the

second level of maturity are (Kerzner 2005; Kerzner 2013):

• In the second level of maturity benefits of Project management were recognised and

emphasised,

2.50

2.79

2.00

2.29 0.00

1.00

2.00

3.00

4.00

5.00Initiation

Planning

Execution&monitoring

Closing

ML OL


• The need for processes and methodologies were recognised and supported at all

levels of organisation,

• The importance of cost, scope and quality were acknowledged by senior managers,

and projects stakeholders, and

• Project management training courses have become an important prerequisite for all

levels of project stakeholders, specifically project managers.

Table 6-5 Participants’ quotes in regards to GOVCO’s PMO matuirty (developed for this research) Subject Associated participants’ comments

PM Training

In.Gd.3 : “…We also offer training to new people once they’ve joined Project Services if they haven’t used our programs and software before we run the training for that…”

In.Gd.2: “…We’ve got someone who actually just works on training and all they do is actually coordinate training for project managers in the organisation…”

In.Gd.3:”…We do offer training to the people who haven’t done Prince 2 training or haven’t done SAP training and we run that to help them deliver their projects and things…”

PM Methodology

In.Gd.2:”… We have developed our methodology. We actually have taken a number of the international standards. So we’ve looked at PMBOK, we’ve looked at the ICB from IPMA,

there’s a Japanese one which goes from project to program management, Prince 2…” In.Gd.4:”…they [PMO] were basing it on PMBOK but I think more recently they’re moving

towards Prince 2...” In.Gd.5:”…I think well the real push for Prince 2 at the moment in learning the methodology. I

don’t think it’s all being applied or it’s being applied but in different terminology. But I think it’s more of a patchwork of some of PMBOK, some of Prince 2…”

Since it was revealed that GOVCO’s PMO has the second level of maturity, therefore the

above mentioned characteristics should be consistent with the current activities of PMO from a

PM point-of-view. In order to investigate the consistency of the above mentioned criteria, the

collected data, such as interview and direct observation, were utilised. The research findings

from interview analysis have confirmed the majority of mentioned criteria, and Table 6-5 covers

two subjects: PM methodology and PM training. This means that participants’ thoughts about

the current situation of PMO are consistent with the PMO at a second level of maturity. In other

words, both interview analysis and PMO assessment confirm the same level of maturity for

GOVCO’s PMO.

As shown in Table 6-5, participants have mentioned that PMO provides PM training courses

project stakeholders. This also has been confirmed during the direct observation stage, as this

researcher participated in one of the PM courses. In addition, respondents believe that there is a

PM methodology, as illustrated in Table 6-5. After conducting the document analysis stage, a

PM framework has been recognised in the GOVCO’s PMO, which will be the subject of next

section. In fact, these findings show that the obtained information from various data collected

methods is consistent and this contributes to the research quality.

The GOVCO’s project management methodology 6.5.1.1

As discussed earlier at the second level of maturity, at least one PM methodology should be

in place to be used by project stakeholders (Kerzner 2005). A PM framework was found in the

GOVCO’s PMO, during the documents analysis stage. In addition, the interview analysis


revealed that all participants were aware of the existence of a methodology, and the majority of

them have been trained in this regard. According to the PMO manager, the existing PM standard

has been customised through combining of PMBOK and PRINCE2: “…We actually have taken

a number of the international standards. So we’ve looked at PMBOK, we’ve looked at the ICB

from IPMA, there’s a Japanese one which goes from project to program management, Prince 2

but it’s amalgamation of both…” quoted by In.Gd.2 .

The existing PM standard has been developed through customising both PMBOK and

PRINCE2 [In.Gd.2]. According to the research findings, participants believe that the current

PM methodology significantly contributes to PM, through addressing the required processes,

procedures and actions that need to be done during project lifecycle. In addition, the existing

PM standard has been reasonably collaborated with the current processes and forms. Also, an

internal developed tool for project managers, i.e. The PMMate, has been integrated with PM

methodology to improve the quality of project outcomes in GOVCO.

On the other hand, the research findings revealed the following in regard to the current PM

methodology: 1) some of the participants have not clearly realised the importance of it in their

daily work; 2) this framework has not been completely endorsed by senior managers, so project

managers are not obliged to follow it, during project lifecycle; 3) Some of the current systems

and tools, such as SAP and risk management tools, have not been integrated with the PM

methodology. These issues show that GOVCO’s PMO should develop the current PM

methodology to address the existing concerns in this regards.

In summary, despite the usefulness of the existence of PM methodology, there are some

issues that are yet to be addressed, such as integrating with the current systems such as PMMate

and SAP. Also, there are some processes in place, for instance risk management, which have not

completely collaborated the existing PM standard. However, the current PM methodology is

consistent with the minimum requirements for the second level of maturity, therefore GOVCO’s

PMO could improve the level maturity through addressing above mentioned issues. In other

words, to achieve the next level of maturity a unique PM framework is required, by which the

majority of current systems have been collaborated (Kerzner 2005).

GOVCO’s Project Management Office as a Centre of Excellence 6.5.1.2

According to GOVCO’s senior managers, the PMO has been designed to be centre of

excellence [In.Gd.1]. A centre of excellence refers to an entity that provides support for a

focused area, without being involved in the undertaken activities (Raymond, et al. 2010).

Therefore, a PMO as a centre of excellence should support projects through providing PM

services and tools such as process, applications, research, and best practices in order to improve

the quality of project management (Dai and Wells 2004). This means that when a PMO is


developed as a centre of excellence, then it should not have any involvement in project

implementation.

The research findings explored that GOVCO’s PMO has been developed to help project

managers as well as team members, through providing various services such as, forms and

templates, training and workshop, monitoring and control, and sending alerts and reminders. In

other words, GOVCO’s PMO does not undertake any activities in the project, specifically at

execution, but it provides services for the project from initiation to closing phase.

“…The PMO is not …and the people in the PMO are not to be considered as additional

resources for the project manager…” quoted by In.Gd.1, the GOVCO’s senior manager

From a KM point-of-view, a centre of excellence should provide practical practices to

facilitate management to project knowledge (Crawford 2002; Walker and Christenson 2005).

According to the research framework (Chapter 3) the following criteria should be found at the

second level of maturity: 1) awareness of KM at this level should be realised by the senior

manager, 2) project team members should be familiar with the basics of KM, and 3) knowledge

capturing should be improved through practical practices for documentation and a repository

system. According to both the collected data and also the conducted observations, all above

mentioned criteria have been met, so following are some quotes in this regard:

“…I guess …is in increasing the awareness of the PSO so people are happy to contact

us…”, In.Gd.5.

“… We lose this big opportunity of gathering information progressively through a

project so we got involved up the front…”, In.Gd.3.

“…but it’s those others lessons that we learn or don’t learn during the project that

we’re not capturing so well…”, In.Gd.4.

“…I think that is a gap in capturing the reason for the changes type of thing more so

than the change itself often gets captured if that makes sense…”, In.Gd.4.

In summary, the level of maturity for GOVCO’s PMO is two, which means that there should

a PM methodology, some PM processes and also a training course in place (Kerzner 2005;

Kerzner 2013). These conditions have been confirmed through analysing PMO documents,

interview data and direct observation, in which all data collection methods confirmed the

required characteristics for a second level of maturity. In other words, the provided data from

different methods and sources, triangulation, are consistent, by which they improve the quality

research outcomes. In addition, it was revealed that GOVCO’s PMO has been designed as a

centre of excellence, which means that it does not intervene in project implementation. Since

the existing PMO’s systems significantly contribute to the quality of PM (Alavi and Leidner

2001; Davidson and Jillian 2009), they will be discussed in the next section.


Project management systems and tools in the GOVCO 6.5.1.3

According to the research findings, GOVCO’s PMO has number of systems and tools in

place, as depicted at Table 6-6. From a process point-of-view, more than 60 forms were

recognised, which are used to facilitate PM activities alongside the current PM methodology.

Also, there are numbers of tools such as MS project, MS excel, and email-based helpdesk,

which are used for facilitating PM. As shown at Table 6-6, there are five main tools: Internet;

SAP; PMMate; Risk Management System; and AConnect, in GOVCO, which significantly

contribute to management of GOVCO’s projects.

Table 6-6 The current system and tools in GOVCO’s PMO (developed for this research)


SAP To integrate cost and revenue of projects across GOVCO

PMMate It’s a customised processes program to maintain quality of project management activities

Intranet To capture and transfer project information Risk Management system It’s an excel base system to create estimation for project risk

AConnect It’s a web based software for contract administration

SAP is a total system which deals with project facts and figures, such as cost and revenue.

This software is a total solution for organisations to capture and transfer the costing knowledge

of projects, however, it is not a complete application for project management purposes

(Crawford 2012). This means that SAP has not been designed managing organisational projects,

but the integration of SAP and project management software could make a reliable collaboration

for both PM and organisational KM. This could be one of the future steps for GOVCO’s PMO

to improve the quality of PM. In addition, participants have mentioned a number of SAP’s

issues which need to be addressed:

“…The problem is that we have a program in SAP in our computer system, our business

system but it’s not particularly user friendly or flexible so we all tend to use MS

Project…” quoted by In.Gd.4.

“…The programming ability of SAP is very poor. I don’t think that there’ll be any way

that they can change SAP, I don’t think the IT people can rewrite SAP to make the way it

does a Gant chart easier and more flexible and less clunky…” quoted by In.Gd.4

PMMate is another PM application that comprises numbers of processes and procedures to

assist project managers with addressing appropriate PM processes. It is also used for quality

assurance purposes by which project team members undertake suitable actions, during project

life cycles. In addition, PMMate helps project team members by automatically populating letter

and forms when it is required. According to respondents, this application is quite useful to

capture and transfer the knowledge of a project. As In.Gd.3 explains “…PMMate is basically a


QA procedure and the templates embedded in sort of like…it automatically populates you know

letters and stuff like that …”.

Another system which is utilised during project lifecycle is the “intranet”. The internal

network has been designed to facilitate access to the required information across the

organisation. Also, it contributes to both capturing and transferring the project information. In

addition, there are some forms and templates as well as procedures which are available through

the intranet. Also, basic notice board has been developed on the intranet, which is used for

knowledge transferring.

An Ms Excel-based risk management system is used to facilitate the process of risk

management in GOVCO’s PMO. This application is currently considered as the main tool to

assess and manage the project risks, and then record all the collected information in order to use

for future projects. From one of the respondent’s point-of-view this system”… redeveloped that

whole process in Excel to enable people to go through and actually do both preliminary and

detailed risk assessments…”,[quoted by In.Gd.3]. However, it is fairly new to the department

and it needs to be trained appropriately, to be utilised by project team members.

AConnect is a web-based contract administration system in GOVCO, which is used both

internally and externally. This tool gives GOVCO’s clients and suppliers an environment in

which to access their required information. As one of the participants explains, “…it’s not an

internal thing, it’s external AConnect is a company a worldwide company that come up with a

very expensive, a good program that lots of people are using on bigger projects now…”, quoted

by In.Gd.4.

In summary, GOVCO’s PMO has numbers of systems in place to support the PM. These

systems and applications are used for various purposes and they contribute to the quality of

project management in GOVCO. In addition, more than 60 forms were recognised in GOVCO,

which are used to facilitate PM activities alongside the customised PM methodology. Also,

there are some tools such as MS project and MS excel, monkey server, and an email-based

helpdesk which are used for managing project. However, the lack of integration among the

current systems has been recognised as one of the major challenges in the GOVCO’s PMO. In

the next section, major issues of GOVCO’s PMO from a KM perspective will shed more light

on the issues in GOVCO.

Knowledge management challenges in GOVCO 6.5.1.4

As discussed in the previous chapter, to recognise the issues of PMO from a KM perspective,

interview data was used as the main source of research information. In addition the research

framework was followed, in which interviews’ transcriptions were uploaded to the Nvivo, as the

data analysis software. Then, the process of coding, both open coding and axial coding, was

managed as it is advised by similar qualitative research (Charmaz 2014; Corbin and Strauss


2008; Wiewiora, et al. 2010). In the first stage of the open coding process, more than 85 nodes

were developed in the Nvivo. These codes or comments have directly or indirectly mentioned

the current challenges from a KM point of view. Following are some of the examples of the

coded comments:

“…The reality is that SAP is an office wide program that all our admin staff use,

all the billing and everything as well, it’s not a program that’s been designed for

project managers…”, In.Gd.4.

“…The knowledge transfer when you are changing personnel or something like

that, handing over a project or something like that …is not particularly fantastic…”,

quoted by In.Gd.4.

“…I should say that there is information on processes, on how project services

wants those processes to work, but I wouldn’t say that it’s ….easily accessible or

made easily available to new people…”, quoted by In.Gd.5.

In the next level of analysis some of the Nvivo’s functions, such as queries and

classification, were utilised to find the relationships among the current coded information.

Eventually, after running numbers of models, four categories, as the research axial codes, were

developed as the major challenges of GOVCO’s PMO. In other words, all 85 coded comments,

in regards to KM challenges, have been classified in five major categories by following research

methodology (Corbin and Strauss 2008). This means that each category, or axial code,

represents a number of associated issues of KM in the GOVCO’s PMO. In other words, the

following KM challenges of GOVCO’s PMO have been recognised through following both

“theory making” and “Grounded theory” techniques, advised by qualitative research experts as

methods to make theory from similar data (Charmaz 2014; Corbin and Strauss 2008; Eisenhardt

and Graebner 2007):

1) Lack of integration among current processes and systems


3) Lack of KM practices and KM processes during project life cycle


Table 6-7 is an example of presenting how participants’ quotes were related to open codes,

and also, how axial codes were developed accordingly.

In the next step of data analysis, the importance of each challenge has been investigated to

get insightful information about their significance. According to research methodology, the

frequency of each phenomenon should be used to analyse the importance of each phenomenon.

To do so, after running numbers of matrix queries in Nvivo, the obtained data was transferred to

Ms Excel for further analysis. As shown in Figure 6-4, the research findings revealed that 44


percent of the coded comments have indicated the “lack of KM practices and KM processes

during project life cycle” as the most frequently mentioned challenges. This means that

participants believe that the current KM practices are not enough to support their expectations

from a KM point-of-view.

For instance, the majority of participants have mentioned their issues with managing project

lessons learned as well as project review processes, as In.Gd.3 quotes “…The defect, the lessons

learned might be started earlier and updated but it wouldn’t actually be finished and emailed to

the PMO until the very end…”. This means that participants are already aware of importance of

KM practices to improve the quality of project management. In other words, the lack of KM

processes is a recognised issue, and it needs to be addressed accordingly.


Table 6-7 Example of using Axial &Open coding in GOVCO’s PMO (developed for this study)


Lack of integration among current processes and

systems

Project information and SAP are not synchronised “…The reality is that SAP is an office wide program that all our admin staff use, all the billing and everything as well, it’s not a program that’s been designed for project managers…”, In.Gd.4.

“…kind of just haphazardly getting four or five different things together, then seeking approval, If it was possible to design a one size fits all this is what you need to move forward that would be quite useful…”, quoted by In.Gd.3

“…I think the one thing that we’ve yet to do is actually upgrade our high level process overflow which actually says you know pictorially this is the process flow and these are all the various components in the planning that you get to do…”,

quoted by In.Gd.2.

Processed need to be Improved

Poor change management system

Current processes are not quite practical

Challenges with SAP

Issue of locating and accessing right information and/or

right expert

PMO staffs are multi-tasking “…The knowledge transfer when you are changing personnel or something like that, handing over a project or something

like that …is not particularly fantastic…”, quoted by In.Gd.4. “…We wanted some experienced project managers in there as well as other staff who could act in the…more of a support

role…”, quoted by In.Gd.1. “…I think the biggest difficulty is the staff change. Because we’ve got staff coming in and going out , you don’t get the

level of efficiency within PMO to be able to start actually like real time affecting things…”, quoted by In.Gd.2. “…If I had someone who was skilled on change management, this is what we’re going to roll out, they can actually come

up with a detailed plan and communication…”, quoted by In.Gd.2

Main issue is to get right person

Issues with transferring knowledge to new person

Staffs are changed regularly

Lack of KM practices KM

processes during project life cycle

Project reviews should be undertake properly “…if there was a way of accessing information about a similar project for a similar budget and similar contract type I would have gone and had a look at it to try and find out some information about you know what they recommend you do.

But I didn’t really get anything specific…”, quoted by In.Gd.4. “…We ask for it and it’s something that they should be doing but yes whether they actually do it and send it to us is where

we’re finding the difficulty…”, quoted by In.Gd.3. “…I think that is a gap in capturing the reason for the changes type of thing more so than the change itself often gets

captured if that makes sense…”, quoted by In.Gd.5 “…we lose this big opportunity of gathering information progressively through a project so we got involved up the front,

we get involved sort of in the planning and at the end…”, In.Gd.2.

Knowledge of previous projects is not available

Issues with capturing lesson learned

Knowledge transferring and reusing should be improved

Internal & external communications are not satisfactory Challenges with knowledge capturing practices

Issue of appropriate access to the

existing systems

Proper access to information resources is a challenge “…I should say that there is information on processes, on how project services wants those processes to work, but I wouldn’t say that it’s ….easily accessible or made easily available to new people…”, quoted by In.Gd.5.

“…I think to help out the whole closing of the whole project it would be helpful to have more information throughout. The project reviews I also think like I’ve filled them in and sent them to the PMO and I don’t know where they go type of

thing…”, quoted by In.Gd.4. “…you need to make it easy because people are busy , people are lazy so in order to try to make it easy for them to be able

to see it up front I think that would be helpful…”, quoted by In.Gd.4. “Internally we do have project reviews that are fairly new, they’ve just redone it all over the past year or so through the

PSO and you know I haven’t, none of my projects have been at the stage of finishing like in the last six months or so…”, quoted by In.Gd.2.

PMO does not offer any practical assistance throughout the project

PMO does not help to find external consultant The current data base for project reviews are not easy

accessible

Challenges of access to Intranet

Chapter 6 Case Study Analysis: GOVCO 138

Figure 6-4 The exsisting KM challenges of GOVCO’s PMO (developed for this study)

The second and third most frequently mentioned challenges, with 22 %, and 21 %, are “lack

of integration in the current systems” and “issues of access to the existing systems”. According

to Alavi and Leidner (2001) KM has three main players; people, process, and technology, in

which a KM system is the combination of processes and technology to address how people

should employ a system for KM purposes. The research findings revealed that the current

systems have been faced with issues not only from integration, but also from access points-of-

view. This means that GOVCO’s participants believe the existing systems should be developed

in order to improve their contribution to management of project knowledge. For instance, the

following are some of the participants’ concerns in this regard:

“…there’s no way of getting whatever file that those are all stored in, if you come along

on a new project I don’t think you can easily find out what someone might have said on a

particular project about lessons learnt…”, quoted but In.Gd.4.

“…so again PMO doesn’t help you to find this kind of expertise…”, quoted by In.Gd.5

According to the research framework, access to knowledge is part of the knowledge

capturing process. This means that knowledge capturing should be problematic, as there are

some issues in regards to access to the current system. However, more evidence is required to

confirm that issues of access to the current systems impact on knowledge capturing in the

GOVCO’s PMO.

The fourth concern, with 13 percent, is the lack of processes or systems to facilitate locating

and/or finding right expert or information. Since the PMO at GOVCO is a centre of excellence,

therefore, it is expected to recognise some processes or practices to facilitate finding the right

expert or information, however, the majority of respondents believe that current systems are yet

to be developed to address this issue. Followings are some of the interviewees’ comments in

this regard:

“…the main issue has been trying to get the right people into the PSO…” , quoted by

In.Gd.1

21%

44%

13%

22% Lack of integration among current processesand systems

Lack of KM practices KM processes duringproject life cycle

Issue of locating and accessing rightinformation and/or right expert

Issue of appropriate access to the existingsystems


“…I think the biggest difficulty we’ve got is the staff changed. Because we’ve got staff

coming in and going out it’s, you don’t get the level of efficiency within the PSO to be able to

start actually like real time affecting things…” quoted by In.Gd.2

According to the research framework, inappropriate access to the right person impacts on

both Knowledge Reusing and Knowledge Capturing. Therefore, it is expected to see some

inefficiency in knowledge capturing and reusing in the GOVCO’s PMO. The relation between

KM process and the recognised KM knowledge will be discussed in section 6.6.

In summary, four challenges have been explored in GOVCO’s PMO, from a KM point of

view. As discussed, the mentioned challenges were examined through employing the research

framework as well as the current literature, in order to investigate their relationship with four

KM processes. It was revealed that all KM processes have been impacted by these issues,

especially knowledge reusing. This means that there are numbers of issues that are yet to be

addressed in the GOVCO. In this section, the primary parts of the first question (RQ1- How are

KM practices and processes employed in the PMOs?) have been discussed to explore KM

issues in GOVCO. In the next section, the second part of the first research question will be

discussed to find the importance of knowledge types during the project life cycle.

The required types of knowledge at project life cycle in GOVCO 6.5.1.5

According to the research framework, there are eight types of knowledge in project

environments: Project Management Knowledge; Knowledge about Procedures; Technical

Knowledge; Knowledge about Clients; Costing Knowledge; Legal and statutory Knowledge;

Knowledge about suppliers; and Knowledge of who knows what. In this stage of data analysis,

it was aimed to understand the importance of each type of knowledge for answering another part

of the first research question. To rate the importance of each knowledge type, survey forms

were distributed among the 10 participants and, eventually, eight completed forms were

returned. In the survey, respondents were asked to rank various types of knowledge from 1, the

least, to 8, the most important ones.

After collecting data and entering these to MS Excel sheets, an Analytical Hierarchy Process

(AHP) was employed to analyse survey responses. This technique is a process that uses

hierarchical decomposition through a weighted matrix to analyse complex information in multi-

criterion decision (Ghodsypour and O'brien 1998). It is a highly recommended technique for

ranking the importance of competing factors in operational management (Lindner and Wald

2011; Stam and Silva 1997). This technique was employed and the advised processes were

followed to rank the importance of types of knowledge in GOVCO’s PMO, as shown at

Figure 6-5.

In the initiation phase, the research findings revealed that the “knowledge about client” and

“project management knowledge” are the most important types of knowledge, while “legal


knowledge” and “knowledge about supplier” are the less important types of knowledge.

According to PMBOK (2013) client expectations and knowledge of PM are important to initiate

projects, therefore, the research findings are in line with PMBOK, as the adopted PM standard.

As depicted in Figure 6-5 and Table 6-8, the research outcomes explored that at initiation phase,

knowledge about supplier and legal knowledge are considered as important as other types of

knowledge. As defined in the current PM standard, the aim of the initiation phase is to conduct

high level activity for preparing projects (Project Management Institute 2013; Wideman 2002).

This means that the PMO’s priority should be on providing the “knowledge about client” and

“PM knowledge”, instead of preparing “knowledge about supplier” or “legal knowledge”.

Figure 6-5 Types of required knowledge in GOVCO (developed for this research)

At the planning phase, two types of knowledge have been ranked as the most important

knowledge: PM knowledge and knowledge of organisational procedures, in contrary,

knowledge about supplier and legal knowledge have been categorised as the less important

ones. Project management methodologies emphasise the importance of knowledge of PM for

planning, more than other types of knowledge, because it helps to integrate all related

information for providing a realistic and reliable project plan (Bentley 2009; Project

7

6

4

8

3

2 1

5

0

1

2

3

4

5

6

7

8Initiation 8

7

4

6

3

2

1

5

Planning

8

6 7

2

5 5

3

1

Execution 8 7

2

6

4

3

1

5

Closing


Management Institute 2013). This means that participants expect from PMO to develop various

types of training and workshops for improving the knowledge of PM among project team

members. Also, it indicates that PMO should consider developing the PM processes and

procedures in order to collaborate with the current organisational systems.

Table 6-8 Types of knowledge and their rank at GOVCO (developed for this research)


Individual Rank Total weighted Rank Initiation Planning Execution Closing Rank Percentage

Project Management Knowledge 7 8 8 8 8 19.8%

Knowledge about Procedures 6 7 6 7 7 14.7%

Technical Knowledge 4 4 7 2 5 11.8%

Knowledge about Clients 8 6 2 6 6 14.5%

Costing Knowledge 3 3 5 4 3 11.2%

Legal and statutory Knowledge 2 2 5 3 2 9.6%

Knowledge about suppliers 1 1 3 1 1 6.5%


At the execution phase, respondents have punctuated the importance of “PM knowledge” but

“technical knowledge” has been ranked as the second most important knowledge at this stage.

This means that technical knowledge has become an important type of knowledge at execution

phase. Need for technical knowledge is an obvious requirement at this phase and it is mandatory

to execute all project activities (Project Management Institute 2013; Reich and Wee 2006). This

analysis confirms the consistency of participants’ answers with both common sense and project

management practices. In addition, “knowledge of who knows what” and “knowledge about

client” were ranked as the less important knowledge at execution. This means that at execution

phase, the process of project planning has been conducted, so both knowledge about client, and

finding the right person are not as important as other types of knowledge (Project Management

Institute 2013).

At the closing phase, “knowledge of PM” and “knowledge about organisational procedure”

are the most important knowledge, from respondents’ points-of-view, while, “knowledge about

supplier” and “legal knowledge” are not as important as other types of knowledge. According to

PM standards, at closing, the project should be formally finished through verifying the project

deliverables and terminating the contract (Project Management Institute 2013). Therefore,

knowledge of PM is mandatory to professionally follow the closing steps, and also, it is very

important to have a good knowledge of organisational procedures to formally finish projects in

accordance with organisational policies. On the other hand, since project deliverables have been

already submitted and they are ready to verify, then knowledge about suppliers and legal

knowledge are not going to be very helpful at this stage (Project Management Institute 2013).

After analysing the rank of each type of knowledge at various phases, another level of

investigation was carried out to determine the overall rank of eight types of knowledge,


regardless of project lifecycle phases. Similarly, the AHP technique was used to assign correct

weights for each entity, then, their weighted percentages were calculated and ranked, as

depicted in Table 6-8. According to research findings, “project management knowledge”,

“knowledge about procedures”, and “Knowledge about client” are the most important types of

knowledge required during the project lifecycle, while, ”knowledge about suppliers”, “legal and

statutory knowledge”, and “costing knowledge” are not as important as the other types of

knowledge.

In summary, eight types of knowledge were examined in the GOVCO to explore the

importance of them during project lifecycle. In addition, the total rank has been analysed to find

the importance of knowledge types at first level maturity, in which the following ranking was

revealed: 1) Project Management Knowledge, 2) Knowledge about Procedures, 3) Knowledge

about Clients, 4) Technical Knowledge, 5) Knowledge of who knows what, 6) Costing

Knowledge, 7) Legal and statutory Knowledge, and 8) Knowledge about suppliers.

Consistently, the first three types of knowledge are very important knowledge to initiate and

undertake the project (Project Management Institute, 2012). This could be insightful

information for those PMOs which have a similar level of maturity. So far, the first two sub-

questions have answered the first research question (RQ1- How are KM practices and processes

employed in the PMOs?). The next section aims to completely answer the first research question

as well as second research question (RQ2- How do KM practices contribute to improve maturity

level of the PMO?), through discussing four knowledge management processes and their

subsequent KM practices.

Knowledge management processes and practices in GOVCO 6.5.2

As discussed in the previous chapter, four KM processes were adopted in which each process

has numbers of KM practices. Also, it was assumed that all four KM processes are employed

throughout the project lifecycle (PLC) except for the closing phase, as depicted in Table 6-9.

This means that all KM processes should be utilised during PLC, however, knowledge capturing

is the only KM process which should be used at closing phase. This assumption will be

examined during the case study analysis.



& monitoring

Closing



In this section, the second research question (RQ2- How do KM practices contribute to

improve maturity levels of the PMO?) and its two sub-questions will be discussed. To do so, the


following steps have be carried out: 1) investigating the utilisation of KM practices and KM

processes at four phases of PLC, 2) examining the above-mentioned assumption about KM


of the project lifecycle. To do so, the research framework and research methodology were

followed thoroughly, as explained in the previous chapter, i.e. section 5.5.2. After following all

required processes, the obtained information was entered into Nvivo and eventually the

following categories have been developed, as depicted at Figure 6-6.

Figure 6-6 A snapshot of KM process categories in the Nvivo (developed for this research)

In order to analyse the collected data, frequency was used as the main criteria to explore the

current status of knowledge management in this case. During the process of coding interviews,

more than two hundred and fifty (250) comments and quotes, which have been directly


After analysing GOVCO’S employees’ comments, it was revealed that more thirty one percent

of KM practices are employed at execution and monitoring phase, while only less than nineteen

percent are utilised at closing stage, as shown at Table 6-10. This is an indication of using

more KM practices during the execution and monitoring phase in comparison to closing phase.

This finding is consistent with KM and PM literature, since the majority of project activities

should be undertaken at execution and monitoring phase (Project Management Institute 2013).


In addition, initiation phase and then planning are the second and third phase in terms of

frequency.

From KM process perspective, it was found that more sixty percent of current practices are

utilised for knowledge capturing, while only less than 1.5 percent are employed for facilitating

project knowledge reusing. This finding shows that the majority of current KM practices have

been developed to support the knowledge capturing process, while few practices contribute to

knowledge reusing. This is consistent with previous findings in which participants were

complaining about poor access to previous project information as well as lessons learned.

Despite the significant number of KM practices for capturing project knowledge, there are still

some challenges in this regard. For instance, finding the right person or having proper access to

the existence information have been mentioned as current issues of GOVCO’s PMO.

Table 6-10 The usage of KM processes in GOVCO (developed for this research)


monitoring Closing




In addition, knowledge transferring is the second most frequent-mentioned KM process. This

means that there are quite numbers of practices to assist with transferring project knowledge. As

it was observed in the GOVCO’s PMO, training is an important activity for PMO as well as

email communication to share the knowledge. In addition, there are some practices such as

lunch forums and mentoring programs to facilitate the transferring project knowledge either in

public or person. On the other hand, knowledge creation, with only fourteen percent of total KM

practices, does not appear significantly supported by current practices.

According to the research framework, only knowledge capturing practices should be

employed at the closing phase. This assumption has been confirmed, as 19 out of 20 practices at

closing phase are used to capture project knowledge, mostly for project review and lessons

learned. As Figure 6-7 depicts, more than ninety-five percent of quotes have been mentioned to

emphasis the utilisation of knowledge capturing activities at closing phase, which is consistent

with research framework. In addition, from participants’ point-of-view, the knowledge

capturing process is supported by numbers of practices during the project lifecycle, however,

the current knowledge capturing practices are yet to be developed, as numbers of issues related

to knowledge capturing have been recognised earlier. This means that despite the existence of a

number of practices to capture project knowledge, respondents believe that not only current

processes need to be improved, such as lessons learned, but also there is a significant need to


develop new practices, such as knowledge filtering, to improving the capturing process. [“…

There is obvious need to filter current information…”, quoted by In.Gd.4. ]

Figure 6-7 KM processes at project lifecycle: GOVCO (developed for this research)

According to the research findings, the second most frequently mentioned KM process is the

knowledge transferring, as illustrated at Table 6-10. The study findings show that the majority

of knowledge transferring practices are used at initiation, execution and planning phases, while

there is only one practice, conducting workshops at the end of project, which is utilised at

closing phase. According to the research framework this practice is used at both knowledge

capturing and knowledge transferring points. Since a closing phase is about to terminate all

project activities, it could be assumed that these kinds of workshop are mostly conducted for

capturing purposes rather than transferring. Therefore, there some practices in place to facilitate

knowledge transferring at three phases of projects, however, the existing process needs to be

improved, from a respondent point-of-view, as a number of issues have been mentioned in this

regard. For instance, the following is one of the comments about knowledge transferring in

GOVCO’s PMO

“…knowledge transferring doesn’t always happen at lunch forum, and if it does

people are sometimes more interested in the lunch and their conversation about the

weekend than what’s actually being talked about…”, quoted by In.Gd.3

Knowledge creation is the third most frequently mentioned KM process in the research

findings in which it is supported by numbers of practices at three phases, except closing.

Respondents believe that most knowledge creation activities are conducted at initiation,

execution, and planning phase, respectively. However, it was found that knowledge creation is

not the main priority for the PMO. In other words, fourteen percent of coded comments indicate

that project knowledge creation is not as important as capturing and transferring in GOVCO.

Two reasons could be mentioned to justify this finding: 1) GOVCO’s PMO aims to be the

centre of excellence, which means that PMO does not involve in project execution and

Initiation Planning Execution &Monitoring

Closing

7 6 5

0

23

15

30

19

15

6

10

1 1 0 1 0

Creation Capturing Transferring ResuingReusing


implementation, and 2) at the second level of maturity the major focus has been on developing

processes for facilitating project knowledge capturing and transferring rather than creation and

reusing. Consistently, according to the research framework, knowledge capturing and

transferring are not only the main priority for the lower level of maturity, but also knowledge

creation and reusing are dependent on the efficiency of knowledge capturing and transferring. In

addition, as will be discussed in a later section, respondents consistently ranked the importance

of KM processes, in which knowledge capturing and transferring are chosen as the first priority,

in comparison to knowledge creation and knowledge reusing.

In summary, it could be inferred that the majority of KM processes are supported through

their associated practices during a project lifecycle, however, only knowledge capturing is

managed at the closing phase. Recalling the maturity level of PMO, the existing practices are

not only faced with numbers of challenges, but also there are some requirements yet to be

addressed through developing new practices. In this section, four KM processes have been

discussed in general. In the next sections, each knowledge process will be individually

discussed to answer the second research question (RQ2. How do KM practices contribute to

improve maturity level of the PMO?).

Knowledge Capturing in GOVCO’s Project Management Office 6.5.2.1

According to the current literature, and also the research framework, knowledge capturing is

the only KM process that should be employed from beginning to end of the project lifecycle

(Owen and Burstein 2005). As discussed earlier, the research findings have confirmed the

above-mentioned assumption through examining interview data as well as survey-questionnaire.

In addition, as it was mentioned earlier, knowledge capturing is the most frequently mentioned

KM process, with more than sixty percent of the associated comments. As depicted at Table 6-

11, three columns have been presented to illustrate the knowledge capturing at the GOVCO’s

PMO, in which the first table shows KM categories based on the research framework, the

second column represents the customised practices or systems to support the main categories,

and the third one displays the associated frequency of the KM categories.

The further analysis revealed that more than half of the comments have emphasised

utilisation of a support document management system (DMS) in the PMO. This means that

respondents believe that there are numbers of forms and templates, as well as a document

management system, to support some practices such as project report, meeting minutes, and

lessons learned. In addition, during the document analysis and direct observation stages, more

than sixty forms and templates that are used during the project life cycle were recognised. These

findings indicate that the current DMS in GOVCO’s PMO addresses many the required project

management practices, such as meeting minutes and project reports, as shown in Table 6-11.


The second most frequently mentioned practice for capturing knowledge in GOVCO, is

formal and informal events. The research findings confirm that formal and informal events are

supported through numbers of ways, such as meetings, lunch forums and workshops. According

to the research framework, practices such as forums and workshops could be used for both

knowledge capturing and knowledge transferring purposes. In addition, GOVCO’s employees

believe that during these events not only they could get, formally or informally, some answers

to their questions, but also they help them to transfer some of their knowledge to their

colleagues and project team members, which normally doesn’t happen in other environments.

Table 6-11 Knowledge capturing’s practices: GOVCO (developed for this research)

Knowledge Capturing categories Associated Practices in GOVCO Frequency

Data base • Yellow page • Team contact list • Survey monkey

6


• Technical design • Request for information • Project Reports • Project Proposal • Project Management templates • Project Debriefing • Project Briefing • Post project review • Meeting minutes • Lessons learned

66

Expert locator • Through email and PMO guidance 4 File Management System (FMS) • Windows base system 1

Formal or Informal events • Regular meeting • Lunch forums • Workshops

28

Frequently Ask Questions (FAQ) • None 0

Intranet • A customised web-based intranet 8 Knowledge detection tools • None 0 Knowledge inquiry system • None 0

Knowledge repositories • None 0

Management Information System (MIS) • PM Mate • A-Connect • SAP

20

The Management Information System (MIS) is the third frequently mentioned practice

which contributes to capture project knowledge in GOVCO. During the course of data

collection three applications were recognised which are utilised to support knowledge capturing:

PMMate, A connect and SAP. These applications and their purposes of usage have been

discussed earlier, based on direct observation and document analysis. From interviewees’

points-of-view these tools are useful to assist them with capturing knowledge, however, the

integration among the current systems and other applications are yet to be addressed in the

GOVCO. This finding indicates that the existence of a reliable MIS is necessary for capturing


project knowledge, therefore the PMO is responsible for developing such a system to support

KM.

A customised intranet, numbers of data bases, expert locator, and an internal file

management system are the other KM practices in the GOVCO’s PMO for facilitating project

knowledge capturing. According to GOVCO’s respondents, the current file management system

has been useful for them to locate required knowledge, which is stored internally; however, this

system should be updated since it is not web-based, so it is not capable of searching or filtering

information. In addition, the current database such as yellow page and contact list have been set

up, separately, therefore integrating these systems is another necessary step for PMO, especially

to obtain the next level of maturity. On the other hand, some of the proposed knowledge

capturing practices in the framework, such as knowledge detection tools and knowledge inquiry

system, have not been recognised in GOVCO’s PMO. Since the maturity level of PMO is still at

low levels, it is reasonable to explore some undeveloped KM practices. Having said that, these

practices should be considered when PMO’s managers decide to improve the maturity level of

PMO.

Figure 6-8 Knowledge Capturing in project lifecycle: GOVCO (developed for this research)

From a project lifecycle point-of-view, as depicted at Figure 6-8, more than twenty five

percent of knowledge capturing activities incur in the execution and monitoring phase, twenty

percent at initiation, sixteen percent at closing, and twelve percent at the planning phase. As it

can be found in Figure 6-8, the combination of utilisation of KM practices varies at each phase.

In the Planning phase most of the KM practices are used, while only three practices are

employed at execution phase. Also, DMS are the most utilised KM practice in four project

phases. This could be an indication for PMO at the same level to improve their DMS to support

knowledge capturing speciality at Execution and Closing phases.

02468

101214161820

Management InformationSystem(MIS)Knowledge repositories



Intranet




Expert locator

Document Management System(DMS)


In conclusion, knowledge capturing is recognised as the most frequently mentioned KM

process, with more than 60 percent of the total KM process comments. In addition, the majority

of the proposed knowledge capturing practices, by the research framework, are employed in

GOVCO, but some KM practices such as FAQ are yet to be addressed. According to the

research framework, awareness of knowledge capturing should be raised, at both manager and

employee level, in the second level of maturity (Kerzner 2005). The research findings confirm

this assumption, in which all respondents have mentioned the number of practices to explain

knowledge capturing process in GOVCO.

Knowledge Transferring in GOVCO’s Project Management Office 6.5.2.2

According to the research findings, knowledge transferring is the second most frequently

mentioned KM process, with more than twenty-three percent of the coded data. This means that

about a quarter of coded data for KM processes, support those KM practices which facilitate

transferring project knowledge. In other words during the coding process, interviews were

analysed against research framework and if there was a comment that was related to associated

KM practices, then it was coded accordingly (Lindner and Wald 2011). Then through using

query and classification functions, the model was built up to explain the knowledge transferring

process and its associated practices.

Table 6-12 Knowledge Transferring categories and pratices: GOVCO (developed for this research)

KM transferring categories Associated System and Practices

at GOVCO’s PMO Frequency

Communication channels • Chat rooms • Email • Phone

26

Database • Contact list 2 Discussion forums • None 5

Electronic bulletin board • Project bulletin and reports 2

Formal and informal events • Seminar and workshops • Face to face conversation 29

Intranet • Customised web-based network 3 Knowledge directories • None 0

Knowledge list • None 0

Training& mentoring • Induction • Mentoring 15



The most frequently mentioned practice for transferring project knowledge is “formal and

informal events”, as shown at Figure 6-9 and Table 6-12. According to the research framework,

this practice and its underpinnings, i.e. seminar and workshops, could be used for both

knowledge capturing and knowledge transferring. As discussed earlier, “formal and informal

events” was ranked as the second most frequently mentioned practice for capturing knowledge,

while knowledge transferring is the most important practice from a participant’s point-of-view.


This means that participants believe that workshops and seminar as well as face to face

conversation are used in GOVCO to facilitate the knowledge transferring process. In addition,

discussion forums are other practices which could be considered in this category.

The second most frequently mentioned practice for transferring is the existing

“communication channels”. In fact, GOVCO’s employees believe that email is a very useful

tool for knowledge transferring and the PMO is proactive in sending emails as reminders or

sharing knowledge, as following the comments explain:

“…PMO is sending out alerts is very helpful just to keep to know who needs to be

signing of and everything before you’re going out to tender or going to engage

anyone…”, quoted by In.Gd.4

“… PMO sends that out regular email as to some of the things that we’ve mentioned.

So it is about capturing and transferring that knowledge that way…”, quoted by In.Gd.1

Another KM practice which is part of a communication channel is phone conversations. In

addition, the PMO has a comprehensive contact list for all experts and it facilitates internal and

external phone discussion, which could be considered as another informal event as well.

Training and mentoring are the third most frequent observation for knowledge

transferring, however, the PMO manager and GOVCO senior manager believe that it is the most

important activity that PMO conducts for the purpose of transferring knowledge, as In.Gd.1

describes “…training is definitely something that PMO does… So we coordinate training. Now

what we do is we ask the PMs what sort of training they need and what areas. So we get a fairly

basic course , and then we start to then focus on that training…” and, also In.Gd.2 believes

“…Well we’ve got a structured training program and it’s basically…we’ve just done an

induction manual when people first come into the organisation and these are things you need to

know…”. The training courses are conducted mostly through providing project management as

well as associated technical courses for GOVCO’s employees. Most of the trainings are

managed in the classroom but for remote areas, some video tapes or CDs are provided and sent.

In addition, the mentoring programs have been initiated recently but most of them are managed

informally. However, this needs to be improved, as there are some issues in this regard, “…I

think they’re trying to look at mentoring; the hard thing is we have relatively small teams so I

know when I started they talked about having like a mentor for me but then because lots of work

came in they kind of just dumped the work on you…”, quoted by In.Gd.4.

Moreover, there are some other tools such as internet, DBs and electronic bulletins, which

facilitate the sharing and transferring of project knowledge. But these practices have not been

well developed, as numbers of challenges were discussed earlier in this regard. For instance,

participants believe that the current intranet is not only searchable, but also the access to

required information is not user friendly. Also, the current DBs are not properly integrated to


SAP and internet, which needs to be improved. On the other hand, three important KM practices

for knowledge transfer, i.e. knowledge directory, knowledge list, and teleconference meeting,

are yet to be addressed in GOVCO. Since the maturity level of PMO is two, so it is plausible to

see that some of the advanced KM practices have not been developed yet.

From a project lifecycle perspective, as could be seen in Figure 6-9, the majority of

knowledge transferring activities are managed at initiation, execution, and planning phases,

while at closing phase there are limited practices to support knowledge transferring. According

to the research framework, knowledge capturing should be the only KM process to be employed

at closing phase, therefore this finding is consistent with the research framework and the

proposed assumption. In addition, respondents believe that the majority of knowledge

transferring activities incur at the initiation, and execution and monitoring phases through

“formal and informal events’ as well as training and mentoring programs. This finding is also in

line with PM standards as well as the research framework, as it is assumed that most of training

and events should be managed at execution phase. (Project Management Institute 2013). These

findings indicate the importance of knowledge transferring at initiation and execution phase,

where projects are defined and then executed.

Figure 6-9 Knowledge Transferring practices in GOVCO (developed for this research)

In summary, knowledge transferring is the second most frequent KM process from

participants’ points-of-view. According to the research framework, the above mentioned

findings confirm the research assumptions. From respondents’ perspectives, “formal and

informal events” is the most important practice for transferring project knowledge and,

respectively, communication and training practices are the second and third most important KM

practices. However, there are numbers of practices that are yet to be developed in GOVCO’s

PMO for improving the quality of knowledge transferring, such as knowledge list and

0

2

4

6

8

10

12

14

16

18

Initiation Planning Execution&Monitoring

Closing


Database

Discussion forums



Intranet


Knowledge list

Training& mentoring


Yellow page


knowledge directories. These practices could be addressed by GOVCO’s PMO in order to

achieve the next level of maturity.

Knowledge Creation in GOVCO’s Project Management Office 6.5.2.3

The third most frequently mentioned KM process in GOVCO is knowledge creation,

however, it has been mentioned only 32 times out of more than two hundred and fifty associated

quotes. According to the research framework, there are numbers of practices that could facilitate

knowledge creation process in projects, as shown in Table 6-13. This table shows knowledge

creation practices and their frequencies. It could be inferred that knowledge creation is not used

as frequent as the two previously discussed knowledge processes in GOVCO’s PMO. In other

words, respondents believe that only a small number of practices are in place in GOVCO to

contribute to creating knowledge during the project lifecycle.

Table 6-13 Knowledge creation’s categories in GOVCO (developed for this research)

KM creation categories Associated System/Practices in GOVCO Frequency

Best Practice Cases • None 1

Community of practices • None 9 Data mining • None 0

Decision support system (DSS) • None 0

Deductive & Inductive thinking • Brainstorming 1

Documentation search • None 0

Experience Report • None 3

Expert systems (ES) • Expert Interview • Expert judgment

0

Informal and formal Event • Formal face to face meeting • Workshops & seminar

7


Research services • Experimentation • Simulation • Use of Metaphors

0

As depicted in Table 6-13, the first and second most frequent KM practices for knowledge

creation are “community of practice”, and informal and formal event” in which respondents

believe that there are some tools to facilitate managing a community of practice and formal and

informal events for knowledge creation purposes, as explained in the following comments:

“…People are gathering together to solve a problem. To do the same practice for instance

you know let’s say the IT guys gathering together to create a new, some sort of you know

feature for the software that would be a community of practice…”, quoted by In.Gd.5.

“…We’ve got a section here called professional services portfolio so on our client projects

we need an architect, an engineer and those sorts of people but normally it’s just been allocated

someone in house…”, quoted by In.Gd.3.


Further investigation revealed that despite the existence of some tools to support community

of practice, the respondents believe that PMO needs to be improved in this regards, as In.Gd.2

comments:

“…We don’t have a community of practice as a formal community of practice but

within each work group I actually run sort of like a mini group session…”.

“…We also facilitate our interaction as an organisation with other parts of Public

Works in a community of practice…”.

According to KM theories, “formal and informal event” is a practice to support both

socialisation and externalisation processes for creating knowledge (Julian 2008; Nonaka and

Takeuchi 1995; Srikantaiah, et al. 2010). In other words, participating in seminars, workshops

and discussion forums is useful to create knowledge during the project lifecycle. The research

findings revealed that the current practices should be improved to enhance the utilisation of

formal and informal events in GOVCO, as In.Gd.3 comments:

“… Possibly for risk there would be a workshop but that’s only on the bigger scale

projects. The smaller projects wouldn’t have a workshop… it would be one of those

meetings in the initiation stage…”

Another KM practice to facilitate knowledge creation is “knowledge broker”. According to

the current literature PMO, itself, is considered as a knowledge broker in which it has the

responsibility to facilitate communication among employees for knowledge creation purposes

(Barclay and Osei-Bryson 2010). This means that PMO has a critical responsibility for

facilitating project knowledge management in organisations. The research findings revealed that

the importance of PMO as a knowledge broker is yet to be realised in GOVCO, as participants

have only mentioned the knowledge broker four times, out of more than 30 times. In other

words, from respondents’ points-of-view there some practices in place to support PMO as the

knowledge broker, however, those practices are not significant enough to emphasise the

importance of PMO for managing project knowledge, as In.Gd.3 comments: “…And then

contact us for more information or yes I am the one in a hundred that’s going to have this

problem. Show me someone show me another form or show me someone to talk to or introduce

me to this person in those sorts of less common examples. But I still think we miss stuff because

of that technology barrier…”.

The research findings explored that the other KM practices for supporting knowledge

creation, such as expert system, Research services, and data mining, are yet to be developed in

GOVCO, as little evidence was recognised to facilitate the mentioned practices. This is another

indication for GOVCO’s PMO to improve the quality of project knowledge creation.


From a project lifecycle perspective, GOVCO’s respondents have mentioned that knowledge

creation practices are employed, to some extent, at three project phases: Initiation; planning; and

execution, while there is limited evidence to support knowledge creation at the closing phase.

This finding again confirms one of the research framework premises, which assumes that only

knowledge capturing should be managed at a closing phase. Also, it revealed that in GOVCO’s

PMO, the majority of knowledge creation activities are managed at Planning, then the execution

phase, which is in line with the PM standards, as they advise to create knowledge during

planning and execution phases (Project Management Institute 2013; Reich and Wee 2006). This

might be good guidance for PMOs with the same maturity level to help focus on improving

their knowledge creation practices at planning and execution phases, as there is no need to

create knowledge at closing phase.

Figure 6-10 Knowledge Creation in GOVCO (developed for this research)

In summary, knowledge creation is the third most frequent KM process in the GOVCO’s

PMO. As discussed earlier, GOVCO’s PMO has been designed to be the centre of excellence.

This means that it is not involved in the project and therefore, knowledge creation could not be

the first priority. As discussed earlier, in this case, knowledge capturing and transferring are the

first and second most frequently mentioned KM process, while knowledge creation is the third.

This means that GOVCO’s participants believe that majority of the current KM practices

support knowledge capturing and transferring. According to the research framework, the quality

of knowledge creation is dependent on knowledge capturing and transferring processes (Owen

and Burstein 2005; Owen, et al. 2004). This means that, in order to develop productive

knowledge creation practices, the existence of practical processes for supporting knowledge

capturing and transferring is mandatory. Therefore, a PMO with low level of maturity should

focus on developing, capturing and transferring processes first, and then it may initiate the

0

1

2

3

4

5


Closing

Best Practice Cases


Data mining

Decision support system (DSS)

Deductive & Inductive thinking

Documentation search

Experience Report

Expert systems (ES)


Knowledge Broker

Research services


development of knowledge creation practices. Consistently, the research findings confirm the

research framework and its associated premises in this regards.

Knowledge Reusing in GOVCO’s Project Management Office 6.5.2.4

The last process of KM is knowledge reusing which has been mentioned only 6 times during

the data collection course. This means that participants do not believe that current tools and

systems significantly contribute to reusing of project knowledge. As shown in Table 6-14, only

DBs, DMS and the intranet are relatively facilitated knowledge reusing processes, however,

they are yet to be developed from the respondents’ perspective.

Table 6-14 Knowledge Reusing in GOVCO (developed for this research)

KM reusing categories Associated Practices Frequency

Data base • Internal DB 2 Data mining • None 0

Document Management System • After action review • Post project reports 2

Electronic notice board • None 0 Expert systems • None 0

Formal or informal meetings • None 0 Intranet • The existing intranet 1

Knowledge detection tools • None 0 Knowledge map • None 0 Lessons learnt • Some internal process 1 Yellow page • None 0

According to the research findings, the majority of respondents are aware of the usefulness

of having KM practices to support knowledge reusing, but they believe that knowledge reusing

practices have not been appropriately addressed in GOVCO, as some comments confirm this

statement:

“…We’ve got so much information that we’re actually developing that people are now

starting to struggle with knowing exactly what they do at what point…”, quoted by In.Gd.2.

“…if there was a way of accessing information about a similar project for a similar budget

and similar contract type I would have gone and had a look at it to try and find out some

information about you know what they recommend you do. But I didn’t really get any specific

documentation from anyone…”, quoted by In.Gd.4


Figure 6-11 Knowledge reusing in GOVCO (developed for this research)

Similarly, from a project lifecycle point-of-view, the collected data shown confirms the

status of knowledge reusing in GOVCO, as can be found in Figure 6-11, where they revealed

that the current practices for supporting knowledge reusing are not significant and they need to

be appropriately developed. Having said that, these limited practices are used at initiation,

planning, and execution phase, while there is no practice for reusing knowledge at closing

phase. Similar to previous KM processes, this finding confirms the research framework’s

assumption, in which it is assumed that only knowledge capturing should be conducted at

closing phase.

In summary, knowledge reusing is the least frequently mentioned KM process in

GOVCO’s PMO. In other words, reusing the previous projects’ knowledge has not been

appropriately facilitated, because of the lack of KM practices. According to Love, et al. (2003)

“rework” is one of the significant challenges for projects in Australian companies, costing more

than fifty percent of overrun costs. Therefore, PMOs should significantly contribute to

developing KM practices to improve the knowledge reusing process. According to the research

framework, a reliable knowledge capturing and transferring system is required to develop an

efficient knowledge reusing process. This means that the research findings are in line with the

research framework in this regard. It could be inferred that, at the low level of maturity, the

main focus should be on improving the knowledge capturing and transferring then knowledge

creation, and reusing.

Summary 6.5.2.5


employed in the PMOs?) and its sub-questions were answered in this section. In order to answer

the third sub-question (RQ 1.3 What kinds of KM practices are utilised in each maturity level of

0

1


Closing

Data base

Data mining

Document ManagementSystemElectronic notice board

Expert systems


Intranet


Knowledge map

Lesson learnt


PMO?), it was realised that more than sixty percent of comments support knowledge capturing,

while about twenty-three percent of them discuss knowledge transferring. In addition,

knowledge creation and reusing, together, are supported by only less than fifteen percent of the

collected data. Therefore, it could be concluded that knowledge capturing and transferring

practices are the most utilised KM practices, in comparison to knowledge reusing and creation.

According to the research framework, only knowledge capturing should be employed at

closing phase. This assumption was examined through using some techniques and eventually, it

was revealed that the collected data supports this research assumption. In addition, the research

data explored that the majority of KM activities are undertaken at Execution and monitoring

phases which is in line with PM literature, since PMBOK explicitly addresses numbers of PM

processes to support KM at planning and execution phase (Project Management Institute 2013).

According to the study findings, the following propositions could be made to address the

KM at the second level of maturity: 1) Knowledge capturing and transferring are the most

important processes to be improved at the second level of maturity, which means that the PMO

should firstly focus on improving the current practices for capturing knowledge, and then

transferring, 2) Knowledge creation has the third priority at the PMO with a second level of

maturity, however, the existence of some practices to support the basics is necessary, 3)

Knowledge reusing is the least important KM process at this level, and it is dependent on

capturing and transferring. This means the quality improvement of knowledge capturing and

transferring directly impacts on quality of the knowledge reusing process.

The importance of knowledge management processes in GOVCO 6.5.3

In order to answer the second research question (RQ2-How do KM practices contribute to

improve maturity level of the PMO) a survey–questionnaire was distributed among participants,

and seven of them were returned. In this survey, GOVCO’s participants were asked to rank the

importance of four KM processes: Creation; Capturing; Transferring and Reusing at project

life cycle, i.e. Initiation; Planning; Execution & monitoring; and Closing. After collecting the

respondents’ answers, MS Excel was used to analyse the collected data. As discussed earlier,

the AHP technique is a suitable and accurate method for ranking the priority of competing


to rank KM processes in GOVCO’s PMO.

The research findings revealed that, at the initiation phase, knowledge capturing and then

transferring, were ranked as the most important KM processes, while knowledge creation and

reusing got the third and fourth rank, as depicted at Figure 6-12. According to PMBOK (2013)

two major PM processes: developing project charter; and identifying stakeholders, should be

conducted at the initiation phase. In fact, both the recommended PM processes contribute to

capturing the required knowledge about project stakeholders as well as project boundaries


(Project Management Institute 2013; Reich and Wee 2006). Also, it is important to run

workshops and seminars to transfer the existing knowledge in order to provide accurate

information for the next phase. In addition, the created knowledge should be captured, since it is

a fundamental prerequisite for the next phases, especially planning.

As PMBOK (2012) advises, information about similar projects contributes to better

provision of project charter, scope statement, and planning materials. This means that

knowledge reusing is an important KM process at the initiation and planning phases. However,

GOVCO’s respondents ranked knowledge reusing as the least important process in both

questionnaires, and in the collected data from interviews. This means that research findings are

not in line with the current literature in this regard. In order to analyse this inconsistency, both

PMBOK and the maturity level of GOVCO’s PMO have been considered. In fact, it was found

that PMBOK has an assumption in which it assumes that all PM practices should be conducted

simultaneously, so the capability of the project environment has not been taken into account. In

addition, PMO maturity models have been proposed to develop the mentioned capability and

through implementing PM practices in gradual steps at various levels (Project Management

Institute, 2008b). This means that PM practices should be developed based on priorities as well

as organisational readiness. In other words, at the low levels of maturity, the basic PM practices

should be developed for preparing PMO to manage advanced practices in higher maturity levels

(Kerzner, 2005).

0

1

2

3

4

Initiation Phase

Capturing Creating Transferring Reusing

0

1

2

3

4

Planning Phase


Figure 6-12 Importance of KM process in project lifecycle: GOVCO (developed for this study)

The research findings revealed that, from a KM perspective, knowledge capturing and

creation have higher priorities for GOVCO’s PMO at this level of maturity, therefore

knowledge reusing has been not ranked as an important process at this stage. According to

PMBOK, at the planning phase, knowledge capturing and creation are the most important KM

processes (Reich and Wee 2006). In a consistent manner, GOVCO’s respondents have ranked

knowledge capturing and creation as the first and second most important KM process at

planning phase. This means that these two processes are at this phase, since all project plans are

created and need to be captured accordingly. In addition, knowledge transferring has been

placed as the second most important KM practice, similar to creation. This level of importance

logically makes sense because the created knowledge need to be captured and also transferred

appropriately. In other words, if the created knowledge at planning phase is not captured or

transferred, then the project success rate is significantly reduced (Reich and Wee 2006).

On the other hand, knowledge reusing was asserted as the least important KM process at the

planning phase. As discussed earlier, using knowledge of previous projects has a significant

impact on creating and developing project plans (Project Management Institute 2013), however,

knowledge reusing has been ranked as important as other KM processes. Similar to previous

discussion about the initiation phase, it could be justified that the level of maturity is an

important factor for prioritising the importance of KM processes. This means that at this level of

maturity, participants believe that knowledge reusing is not their first priority, as they are

dealing with numbers of challenges in regards to transferring and capturing project knowledge.

According to PM methodologies and the research framework, all of the KM processes

should be employed at the execution and monitoring phase (Owen and Burstein 2005; Owen,

et al. 2004; Reich and Wee 2006). According to research findings, the maturity level of the

PMO is an important factor to determine what sort of KM processes should be employed. In the

GOVCO’s PMO, respondents have indicated that capturing and transferring are the most

important KM processes, while they believe that knowledge creation and reusing are in their

0

1

2

3

4

Execution and Monitoring Phase 0

1

2

3

4

Closing Phase


next level of priority. According to PM standards, knowledge capturing and transferring should

be selected as the first priority (Project Management Institute 2013; Reich and Wee 2006), so

the research findings are in line with the research framework as well as the current literature.

In order to analyse the importance of knowledge creation over knowledge reusing at

execution phase, other collected data were considered, specifically interviews. As discussed

earlier, GOVCO’s PMO has been designed to be a centre of excellence, which means that it

does not involve itself at project implementation as a resource. In other words, it just facilitates

execution through some forms and they have minimum information about created knowledge in

the execution phase, as one of the respondents explains, “…So in that stage you’re kind of

leaving the consultants to their own devices a little bit because they’re the experts in their field

but then making sure that they’re all on the same path…”, quoted by In.Gd.4. Therefore, it

could be inferred that participants have ranked knowledge creation at the third priority as they

believe that they have less involvement during the execution phase.

The research framework assumes that knowledge capturing should be the only KM process

to be employed at the closing phase. This assumption was examined in the previous section,

and it was confirmed through interview data analysis. As shown in Figure 6-12, knowledge

capturing was ranked as the most important KM process at closing phase, by GOVCO’s

respondents. This means that the research findings from both interview and the survey-

questionnaire confirm the importance of the knowledge capturing process for closing phase.

This could be a useful indication for PMOs in order to focus on managing project knowledge at

closing phase in order to improve their systems to facilitate this KM process.

Figure 6-13 The general ranking of KM processes in GOVCO (developed for this research)

In the next step of analysis, the importance of KM processes in project lifecycle has been

conducted to explore the general rank of KM processes, regardless of project phases. To do so,

the AHP method was employed through assigning appropriate weight to each project phase.

This weighted model enables the researcher to analyse the overall rank of the KM process

regardless of various phases (Lindner and Wald 2011). The research findings explored the

following ranking of KM processes: 1) Capturing, 2) Transferring, 3) Creation, and 4) Reusing,

0

1

2

3

4



as depicted at Figure 6-13. According to the research findings, GOVCO’s respondents believe

that knowledge capturing and transferring are the most important KM processes, while

knowledge creation and reusing are not as important as the other two processes.

In the previous section, interviews have been analysed to investigate the management of

project knowledge in the GOVCOs’ PMO. As discussed, knowledge capturing was revealed as

the most frequently mentioned KM process among other KM processes. In fact, more than sixty

percent of the coded comments have discussed the current KM practices from a knowledge

capturing perceptive. In addition, knowledge transferring was found as the second most

frequently mentioned KM process with more twenty three percent of the collected data. Also,

knowledge creation and reusing were placed as third and fourth most frequently mentioned KM

process in GOVCO’s PMO. As can be seen in Figure 6-13, the outcomes from the survey are

confirmed by the research findings in the interviews. This consistency of the research findings

significantly improves the quality of collected data, and contributes to develop reliable

propositions for this study.

Furthermore, GOVCO’s PMO has developed more than sixty forms and templates to

facilitate the PM. This finding emphasises the importance of knowledge capturing during the

project lifecycle. In addition, the collected data from direct observation and interview analysis

revealed the importance of knowledge transferring, facilitated through numbers of practices

such as workshops, seminars, and discussion forums. However, during the direct observation

some evidence was found for supporting knowledge creation and reusing. These findings, are

also are consistent with the mentioned research findings in regards to the importance of

knowledge capturing and transferring over knowledge creation and reusing.

In summary, the research findings from the survey-questionnaire, interview analysis,

document analysis and direct observation, have consistently revealed that knowledge capturing

and transferring are the most important KM processes in the GOVCO’s PMO, while knowledge

creation and reusing are not as important as the other two KM processes. Therefore, it could be

concluded that current KM practices mainly support knowledge management processes in the

following order: Capturing, Transferring, Creating, and Reusing. In addition, it could be

inferred that, at the second level of maturity, the PMO should focus on developing KM practices

to support knowledge capturing and transferring processes as their first priority. In other words,

if a PMO aims to improve the level of maturity, it should firstly provide a reliable KM system

for supporting KM capturing and transferring, and then it could focus on knowledge creation

and reusing practices. At this section, the first sub-question of the second research (RQ2-How

do KM practices contribute to improve maturity level of the PMO) has been answered. The next

section aims to discuss the remaining part of the second question.



In the previous sections the first question, and initial part of the second research question

have been discussed. At first, the existing challenges of project KM in GOVCO have been

explored at the early sections of this chapter, then the importance of the four KM processes have

been analysed through using both interview, and questionnaire methods. As discussed, the

research outcomes from both mentioned methods are consistent, which contributes to the quality

of research findings (Yin 2009). In this section, each KM process will be discussed to

investigate its relation with both the recognised KM challenges, and its associated sub-

processes.

Knowledge capturing’s sub processes and practices in GOVCO 6.6.1

According to the research framework, knowledge capturing has been classified into four sub-

processes: Identification, Storing, Classification, and Selection, as shown at Table 6-15 (Lytras

and Pouloudi 2003; Nissen, et al. 2000). As discussed earlier, four KM challenges have been

recognised in GOVCO’s PMO: 1) Lack of integration among current processes and systems, 2)

Issue of locating and accessing right information and/or right expert, 3) Lack of KM practices

and KM processes during project life cycle, and 4) Issue of appropriate access to the existing

systems. The collected data was entered into Nvivo as well as the research framework, and then

numbers of Nvivo’s functions, such as queries and relationship, were employed to analyse the

relation between challenges and knowledge capturing sub-processes.

According to the research findings “knowledge storing and classification” are the most

frequent knowledge capturing sub-processes, while knowledge identification and selection are

yet to be addressed in GOVCO’s PMO. In addition, the developed queries in the Nvivo have

revealed that most of the recognised challenges are knowledge identification and selection, as

illustrated in Table 6-15. For instance, “issue of locating right information or person” has

occurred because of lack of some KM practices such as “expert locater” and ‘knowledge

detection tools”, and similarly, “issue of appropriate access to the existing systems” is related to

lack of practices such as data base and FAQ. In addition, the majority of the associated

practices to support knowledge storing and classification have been addressed, to some extent,

as shown in Table 6-15. On the other hand, according to the research findings, most of the KM

practices to support knowledge identification and selection are yet to be addressed in GOVCO.

In a consistent manner, it was revealed that most of the recognised challenges are related to

knowledge identification and selection. This means that the development of some missing KM

practices such as expert locator, FAQ, and knowledge detection tools, will contribute to address

the recognised KM challenges in GOVCO’s PMO.

Table 6-15 Knowledge capturing sub-processes in GOVCO (developed for this research)


K. Capturing Sub

Processes


Associated Challenges Comments



event

• Knowledge detection tools • Knowledge repositories 2, 3, and 4

A few practices in place, however, it

is yet to be developed

Knowledge Storing


event

• Document Management System (DMS) 1


process


• DMS • Frequently ask

questions (FAQ) • Intranet


system (MIS) 4

After knowledge storing this one has

numbers of practices

Knowledge Selection


• Data base • Frequently ask questions

(FAQ) 2 and 4

A few practices in place, however, it

is yet to be developed

The research findings confirm that three KM practices to support knowledge storing, have

been addressed in GOVCO’s PMO, and participants have mentioned this KM sub process as the

most frequent knowledge capturing sub-process. This mean that knowledge storing is supported

through existing KM practices. However, the integration of current KM practices especially for

knowledge storing, is yet to be addressed in the GOVCO’s PMO.

The research analysis revealed that knowledge classification is the second most frequent

mentioned KM sub-process in GOVCO’s PMO. According to the collected data, four out of five

KM practices have been addressed in this case study, i.e. DMS, File management systems, MIS

and Intranet. This means that the majority of the recommended KM to support knowledge

classification has been developed in GOVCO, except for frequently asked questions (FAQ). In

addition, the current knowledge classification practices face one of the recognised KM

challenges, i.e. issue of appropriate access to the existing systems. In other words, GOVCO’s

PMO should develop the access to the current system, to both address the mentioned challenge,

and improve the knowledge classification.

In summary, in GOVCO’s PMO, knowledge capturing is supported by numbers of sub-

processes and their associated practices, as shown in Table 6-15. The research findings revealed

that more than sixty percent of the coded comments support the knowledge capturing process in

this case study. On the other hand, knowledge capturing is faced with numbers of issues and

challenges. According to the research framework, knowledge capturing consists of four sub-

processes: Identification, Storing, Classification, and Selection. The data analysis explored that

knowledge classification and storing have been addressed in GOVCO, while knowledge

identification and selection are yet to be addressed. This means that the development of

knowledge identification and selection contributes to address some of the recognised current

KM challenges in GOVCO.


Knowledge transferring’s sub processes and practices in GOVCO 6.6.2

As discussed earlier, knowledge transferring is the second most frequently mentioned as well

as an important KM process in the GOVCO’s PMO. According to the research framework,

knowledge transferring comprises two sub processes: knowledge distribution & forwarding; and

sharing, as depicted in Table 6-16 (Nissen, et al. 2000). The research framework assumes that

technologies and systems play an important role in supporting knowledge distribution and

forwarding processes, while organisational employees have a significant impact on sharing

knowledge (Alavi and Leidner 2001; Landaeta 2008; Wiewiora, et al. 2009a). As it can be

found in Table 6-16, there are numbers of practices for each sub-process by which knowledge

transfer is supported. For instance email, chat, and phone are examples of distributing

knowledge practices, while training, seminar, and mentoring are employed to share project

knowledge.

Table 6-16 Knowledge transferring sub processes in GOVCO (developed for this research)

K. Transferring Sub Processes




forwarding



• Knowledge list



1,2, and 3

Some of the practices needs to be improved such as yellow pages,

intranet, and knowledge list

Knowledge Sharing

• Discussion forums

• Formal and informal events

• Mentoring • Training 2

Majority of practices have been developed

and are being conducted

As discussed earlier, the research findings explored that formal and informal events are the

most frequently mentioned practices for facilitating knowledge transferring, and respectively

communication channel and training are the second and third most frequent KM practices for

knowledge transferring. This means that, from GOVCO’s employees’ perspective, knowledge

sharing is stronger than knowledge forwarding. In other words, human factors play a better role

in transferring project knowledge, in comparison to technology and systems. Therefore,

GOVCO’s PMO should develop an appropriate system in order to improve the quality of

knowledge distribution and forwarding, and ultimately knowledge transferring.

On the other hand, according to the research findings, there are three KM practices:

knowledge list; knowledge directories; and video and tele conference, which are yet to be

addressed in GOVCO’s PMO. As could be inferred, these three KM practices are part of

knowledge distribution and forwarding sub-process, as depicted at Table 6-16. In other words,

GOVCO’s PMO could develop knowledge transferring through addressing the mentioned

practices. In addition, further analysis revealed that the unaddressed KM practices have created

some challenges such as the issue of finding the right person or information. As shown in Table

6-16, the relations between KM challenges and knowledge transferring sub-processes have been


illustrated. These findings accurately address the required actions to tackle the current KM

challenges in the GOVCO’s PMO.

All-in-all, knowledge transferring in GOVCO’s PMO is the second most frequent KM

process and it is supported through two KM sub-processes: knowledge distribution &

forwarding; and sharing. According to the research findings, current KM practices mainly

support knowledge sharing, while knowledge distribution needs to be appropriately improved

through developing some practices, such as knowledge lists and knowledge directories. In

addition, GOVCO needs to develop numbers of systems and technology to address some of the

existing concerns, such as locating the right person. In other words, knowledge transferring, as

the second most important KM process in GOVCO, should be improved by addressing the

mentioned challenges and KM practices.

Knowledge creation’s sub processes and practices in GOVCO 6.6.3

As discussed earlier, “Knowledge Creation” is the third most important KM process in

GOVCO’s PMO. According to Nonaka and Takeuchi (1995) knowledge is created through four

processes: Socialisation, Externalisation; Combination; and Internalisation, (SECI), which are

depicted in Figure 6-14. The SECI model was adopted in the research framework by which

knowledge creation has been classified to four KM sub-processes and their associated KM

practices, as presented in Table 6-17. The research findings revealed that there are limited

practices to support knowledge creation at GOVCO’s PMO, in which only 14 percent of the

coded comments have mentioned this KM process.

According to the research framework, Socialisation is the process of creating tacit

knowledge through various types of communications (Nonaka and Teece 2001) in which it is

facilitated through some practices such as formal and informal events, and community of

practice, as shown in Table 6-17. Hoegl and Schulze (2005) discuss that informal events are the

best practices for supporting socialisation by which tacit knowledge is discussed and sometimes

transferred among individuals. The research findings revealed that both community of practices

and formal and informal events are the most frequent KM practices to support knowledge

creation through socialisation. In other words, GOVCO’s PMO facilitates the majority of

socialisation KM practices.

Table 6-17 Knowledge creation sub procesess in GOVCO (developed for this research)

K. Creation Sub Processes

Practices for Knowledge Creation Comments


• Workshops & seminar • Community of practices

This is the most satisfactory practices among other

creation practices

Externalisation

• Workshops & seminar • Deductive & Inductive thinking


Except workshop, other practices are yet to be

addressed


Combination

• Community of practices (COP) • Best Practice Cases (BPC)


Except COP and PBC, other practices are yet to be

addressed


• Experimentation All practices are yet to be addressed

Externalisation is the process which aims to transform tacit to explicit knowledge (Nonaka

and Teece 2001). According to the research framework, there are numbers of practices that

could be used to support externalisation, which are illustrated in Table 6-17. The research

findings show that only a few of them are facilitated, to some extent, such as workshops,

seminars and a limited practice of deductive and inductive thinking. In other words, the majority

of KM practices to manage externalisation are yet to be addressed in GOVCO’s PMO. This

means that transformation of tacit knowledge to explicit knowledge is a considerable challenge

in the GOVCO in which employees keep significant amounts of tacit knowledge with them.

These findings indicate that if the PMO aims to get to the next level of maturity through

improving its KM system, externalisation is an important process to prevent knowledge

leakiness in the projects.

The processes of transforming the explicit knowledge to more complicated explicit

knowledge is called combination (Nonaka and Teece 2001), and it is facilitated by numbers of

practices, as shown at Table 6-17. According to the research framework, the process of

combination is supported when there is a system in place for developing current manuals,

instructions, procedures, methodologies and as such (Alavi and Leidner 1999; Nonaka 1994).

This development happens through adding the individual input to current documents. The

research findings show that some KM practices are in place to support the combination process,

such as community of practices, best practices, and knowledge broker. However, other practices

such as documentation search and data mining are yet to be addressed. In addition, despite the

existence of some practices to facilitate combination, they need to be developed to satisfy

knowledge creation process. In other words, the combination process does not significantly

contribute to knowledge creation in GOVCO’s PMO.

According to Nonaka (1994) Internalisation is the process of knowledge creation by which

new tacit knowledge is created through existing explicit knowledge. There are numbers of

practices such as research services, simulation, and experimentation to facilitate knowledge

creation through internalisation, as depicted in Table 6-17. During both the direct observation

process, and also interview, analysis of the limited KM practices recognised support for the

internalisation process. This means that internalisation is the only sub-process in GOVCO’s

PMO in which limited evidence was found to be supported. As discussed earlier, GOVCO’s

PMO has been designed to be a centre of excellence, therefore the quality of project activities is

the most important responsibility for PMO (Walker and Christenson 2005). This means that


knowledge creation is not included in the first priority of GOVCO’s PMO. Consequently, some

practices, such as research services and simulation, might be addressed in higher level of

maturity.


Tacit Knowledge

From

Socialisation (has been addressed in

GOVCO)

Externalisation (yet to be properly addressed)

Explicit Knowledge

Internalisation (yet to be properly

addressed)

Combination (yet to be properly addressed)

Figure 6-14 The SECI model in GOVCO’s PMO (Nonaka and Teece 2001)

In summary, knowledge creation is the third most important KM process in GOVCO.

According to the research findings, only one-out-of four knowledge creation sub-processes

(SECI) has been addressed, i.e. Socialisation. This means that current KM practices need to be

improved to address three sub-processes: Combination, Externalisation, and Internalisation.

According to Nonaka (2001), the SECI model follows a spiral method in which all four sub-

processes should be interconnected, as illustrated at Figure 6-14. This means that the process of

knowledge creation is fully supported when all four sub-processes are being appropriately

utilised. As depicted in Figure 6-14, three-out-of-four knowledge creation wings, Combination,

Externalisation, and Internalisation, are yet to be addressed in GOVCO’s PMO. In other words,

the SECI model does not completely work in the GOVCO’s PMO and it needs to be

significantly improved through addressing numbers of mentioned KM practices.

Knowledge reusing’s sub processes and practices in GOVCO 6.6.4

As discussed earlier, knowledge reusing is the least important KM process in GOVCO, in

which less than two percent of the coded comments support this KM process. According to the

research framework, knowledge reusing comprises three sub-processes, Adapting, Applying,

and Integrating, as depicted in Table 6-18 (Lytras and Pouloudi 2003; Nissen, et al. 2000). In

addition, in the research framework, knowledge reusing has strong correlation with knowledge

capturing and transferring (Owen and Burstein 2005). According to the research findings,

GOVCO’s participants believe that the current practices are not strong enough to support

knowledge reusing. This means that the three mentioned sub-processes of knowledge reusing

should be appropriately developed through addressing associated KM practices.

Table 6-18 Knowledge reusing sub-processes in GOVCO (developed for this research)



Knowledge Adapting

• Electronic notice board • Documents management system (DMS) • Intranet • Data base

• Yellow page • Knowledge detection tools • Formal or informal events

Majority of the mentioned KM

practices are yet to be addressed for knowledge

reusing



purposes


In summary, knowledge reusing GOVCO has been ranked as the lowest KM process in

terms of its importance. Also, there are limited KM practices in place to facilitate any of the

three mentioned sub-processes in the PMO. According to the research framework, knowledge

reusing is improved through developing knowledge capturing and transferring. This means that

GOVCO’s PMO should address the recognised issues of knowledge capturing and transferring,

as their first priority, which ultimately contributes to improving knowledge reusing.

CONCLUSION 6.7

In this chapter it has been planned to answer the first and second research questions (RQ1.

How are KM practices and processes employed in the PMOs, and RQ2. How do KM practices

contribute to improve maturity level of the PMO), and their associated sub-questions (what are

the current challenges of the PMO from a KM perspective, What types of knowledge are

required at each of following project phases, What kinds of KM practices are utilised in each

maturity level of PMO, What is the importance of knowledge processes at each phase of project,

How PMO should contribute for managing the project Knowledge). In the previous chapter,

these questions have been extensively answered to achieve the research objectives. The same

process has been followed in GOVCO, and ultimately the research questions have been

answered. In this section, a summary of the research findings has been discussed as follows.

The research findings revealed that GOVCO is faced with the four following challenges

from a KM perceptive: Lack of integration among current processes and systems, issue of

locating and accessing right information and/or right expert, Lack of KM practices and KM

processes during project life cycle, Issue of appropriate access to the existing systems. This

means that the main focus of PMO should be on addressing these issues and underpinning them.

According to the research findings, the following ranking represents the importance of the

required types of knowledge, from participants’ points-of-view: 1) Project Management

Knowledge, 2) Knowledge about Procedures, 3) Knowledge about Clients, 4) Technical

Knowledge, 5) Knowledge of who knows what, 6) Costing Knowledge, 7) Legal and statutory

Knowledge, and 8) Knowledge about suppliers. This could be a significant indication for

GOVCO, or PMOs with similar maturity level, to prioritise the importance of their required

knowledge.

Furthermore, both interviews and survey-questionnaire outcomes, consistently, have

determined the following order to present the importance of KM processes: 1) Knowledge

Capturing 2) Knowledge Transferring 3) Knowledge Creation, and 4) Knowledge Reusing.


These findings explain that knowledge capturing and transferring are the most important KM

practices, while creation and reusing are not as important as the other two. In addition, in similar

previous case study outcomes, informal and formal event is the most utilised KM practice.

As discussed in the last section, i.e. 6.6, KM challenges and KM processes have been

discussed alongside KM sub processes. The findings at that section shall contribute to prioritise

the development of KM processes, sub-processes and practices. In other words, it addresses

appropriate KM practices and processes with regards to their associated challenges and issues.

This will assist PMOs to improve the quality of project knowledge management, and

consequently the maturity level of the PMO.

In the end, the following have been summarised in GOVCO’s PMO, with second level of

maturity:

• KM awareness have been raised at both senior management and employee levels,

• The main focus should be on the development of knowledge capturing through

addressing the recognised challenges,

• Knowledge transferring is the second priority, which needs to be addressed by

providing adequate practices,

• Knowledge creation has the third level importance in which basic KM practices should

be put in place,

• Since the PMO at this level has one or more PM standards, it is recommended to

integrate both PM and KM practice to prepare for the next level of maturity,

• PMO should provide proper practices to assist project team members with assessing the

three most important types of knowledge:

o Knowledge of project management through providing PM methodology,

o Knowledge about clients through developing proper KM practices, and

o Knowledge of who knows what through addressing appropriate KM practices

Chapter 7 | Case Study Analysis: MINCO 171

Chapter 7

CASE STUDY ANALYSIS: MINCO

INTRODUCTION 7.1

In the previous chapter, the second case study, i.e. GOVCO, was investigated through

following both research framework (Chapter 3) and methodology (Chapter 4). In this chapter,

similar procedures will be followed to investigate a third case study, i.e. MINCO, from a KM

point of view. To do so, MINCO’s PMO will be explored through discussing the two first

research questions (RQ1. How are KM practices and processes employed in the PMOs, and

RQ2. How do KM practices contribute to improve the maturity level of the PMO?). First, the

organisation’s background will be explained, followed by data collection procedures. Second,

the PMO’s maturity level will be discussed alongside the current PM systems. Third, the data

analysis will be undertaken to discuss the current status of MINCO’s PMO from a KM

perspective. Finally, concluding remarks and the research findings will be presented

accordingly.

MINCO’S BACKGROUND 7.2

The third case is a leading global resource company which produces major commodities,

including coal, iron ore, silver and uranium. The corporate strategy is based on owning and

operating assets diversified by commodity, geography and market. As shown in Figure 7-1, this

case comprises the numbers of divisions to manage various assets. For this study, the coal

mining asset met the research criteria (explained in Chapter 4) and it was selected as the third

case study, so it will be called MINCO herein after.

Figure 7-1 Snapshot of MINCO’s structure ((extracted from MINCO’s organisational chart)

MINCO, with more than 15 000 employees, is responsible and accountable to produce,

operate and market coal, locally and internationally. To do so, MINCO undertakes a plethora of

projects and programs to both sustain the current production and operation, and develop new

coal mines as well as markets. In order to manage organisational projects, a department was

GLobal Enterprise

Other Asset Presidents Mining Asset President (MINCO)

Project Group Department

172 Chapter 7 | Case Study Analysis: MINCO

developed about five years ago which is called “Project group”, as depicted at Figure 7-1. This

department plays a key role in undertaking, supporting, and overseeing MINCO’s projects. The

functionality of the MINCO’s Project group department is similar to a classic PMO, therefore it

will be called PMO in this report.

Projects are an important part of MINCO’s daily activities for not only maintaining the

current operations in different coal mines, but also exploring new coal resources for future

purposes. In fact, more than fifty percent of MINCO’s operations deal with various types of

projects to achieve the organisation’s mission, i.e. to be the best coal mining company in the

world. MINCO undertakes various types of projects from construction, building and road, to

drilling and explorations. A well-established PM system is required to centrally facilitate and

support all organisational projects, for delivering quality outcomes. MINCO’s PMO is the major

body to develop the mentioned system in order to manage, oversee, and control MINCO’s

projects from initiation to closing phase. In other words, PMO is responsible to assist projects

and project managers (PMs) by providing appropriate processes, procedures, systems, and

advice in order to improve the quality of project management, and ultimately project success.

The role of MINCO’s PMO is to provide appropriate direction to PMs, and to contribute to

projects by offering technical advice during project implementation; ultimately PMs are

responsible for project success or failure. In other words, PMO has been designed to be a strong

arm for PMs in order to facilitate management of the project from initial to close out phases. In

addition, PMO offers numbers of services such as training, consultancy, controlling, auditing,

risk management, and other administration services to PMs to ensure that they have adequate

resources to manage their projects.

This chapter aims to investigate current PM activities in MINCO’s PMO to discuss how

project knowledge is managed. Similar to previous chapters, the research framework and

methodology have been employed to identify the processes and outcomes of this investigation.

To do so, firstly the research protocol and data collection methods have been used to gather the

required information. In the next section, the data collection processes were discussed

accordingly.


Similar to other cases, the research methodology and the case study protocol were followed

to gather quality information from MINCO, getting assistance from a liaison person. In order to

conduct the data collection methods, a schedule was prepared to organise the required activities,

as shown in Table 7-1 and Table 7-2. In total, six interviews were conducted with MINCO’s

senior manager, PMO knowledge manager, a program manager, two project managers, and a

project planner. Approximately, each interview took about 75 minutes in which was included

the undertaking a questionnaire survey and interview questions. In some cases, interviews were


conducted two times as the researcher needed more clarification. For confidentiality purposes,

interviewees’ names were replaced by a selected code as can be seen in the following Table.

Table 7-1 Interviewees’ list and schedule in MINCO (developed for this research)

Interviewee Position Location 1st interview 2nd interview

In.Mc.1 MINCO senior Manager 19/07/2013 (face to face)


In.Mc.2 knowledge manager 19/07/2013 (face to face)


In.Mc.3 PMO Planner 23/07/2013 (Face to face)


In.Mc.4 Program Manager 23/07/2013 (face to face)


In.Mc.5 Project Manager 25/07/2013 (face to face)


In.Mc.6 Project Manager 25/07/2013 (face to face)


The data collection activities, specifically interviews, were undertaken in MINCO’s office in

Brisbane, from mid-July 2013 to late August 2013. All interviews were electronically recorded

and more than 110 pages of the transcribed interviews were provided to be used in Nvivo. Also,

four days were spent to directly observe the current PM activities in MINCO. In addition, it

took three days to investigate the utilised software and systems in the MINCO’s PMO, as

depicted in Table 7-2. The document analysis stage was conducted for more than 4 months in

conjunction with data analysis.

Table 7-2 The Data collection methods (developed for this research)


Interviews and Questionnaires MINCO office Researcher

Mentioned in Table 7-1

Documents Review MINCO office and QUT

Researcher and MINCO’s liaison person

10/07/2013 till 31/11/2013

Direct Observation MINCO office Researcher and MINCO’s liaison person

16/08/2013 to 19/08/2013

After the data collection stage, the data analysis stage was conducted through: 1) assessing

the maturity level of project management by using collected data from questionnaires, 2)

interviews were conducted, transcribed and then coded in Nvivo, and 3) the second

questionnaire was analysed accordingly. In the next section, data analysis will be discussed to

gain insightful information about the selected case study.

DATA ANALYSIS 7.4

This section has been provided to present the data analysis activities and outcomes. The

research methodology and framework were employed to manage the data analysis process.

According to the research methodology, the maturity level of MINCO’s PMO should be

assessed, in the first stage of analysis. In the next step, MINCO’s PMO challenges were


discussed from a KM point-of-view, followed by analysing the required types of knowledge

during the project lifecycle. At the end, the importance of four KM processes: Creation,

Capturing, Transferring, and Reusing were analysed, and then examined against the explored

KM challenges to discuss the relation between KM process and KM issues in the MINCO’s

PMO. In fact, the first and second research questions (RQ1- How are KM practices and processes

employed in the PMOs, RQ2) How do KM practices contribute to improve maturity level of the

PMO) will be answered at the end of the analysis section.

MINCO’s PMO maturity level 7.4.1

The similar process for the other two cases was followed, in this case to determine the

PMO’s maturity level from a KM perspective, as discussed in section 5.5.1. From project

knowledge perspectives, the average maturity level is 3.18 out of 5, which technically means

that the PMO has the third level of maturity, as depicted in Table 7-3 and Figure 7-2. The data

analysis shows that project risk, communication and cost management have been ranked as the

top three PM knowledge areas, while project procurement, quality and time management are not

as strong as the other six knowledge areas. This means respondents believe that current PM

practices need to be improved to strengthen project time, cost and procurements management.

Table 7-3 PMO’ ML from PM knowledge perspective (developed for this research)

PMBOK’s Knowledge area Maturity level (ML) Average ML

Project Scope management 3.00

3.18

Project Cost management 3.21

Project Time management 3.00

Human Resource management 3.07

Project Quality Management 2.93 Project Risk management 4.21

Project Communication management 3.29

Project Procurement management 2.79

Project Integration management 3.14

In addition, during the document analysis stage, numbers of practices have been recognised

which are designed to support risk and communication. This is consistent with the mentioned

findings, as it was found that, from participants’ points-of-view, project, project risk and

communication are appropriately addressed in MINCO. Also, during direct observation, a

robust Risk and Safety system was recognised which all employees are obliged to follow

accordingly. These outcomes indicate that MINCO’s PMO should be classified as a PMO with

third level of maturity, from PMBOK’s knowledge perspective (Desouza 2006; Kerzner 2005;

Project Management Institute 2008b).


Figure 7-2 ML of MINCO’s PMO’s from knowledge areas perceptive (developed for this study)

From a project lifecycle point-of-view, the maturity level of MINCO’s PMO was determined

as 3.02 out of five, as shown in Table 7-4. This means that PMO’s maturity level has obtained

the third level out of five possible levels of maturity (Kerzner 2005; Kerzner 2013). As shown

in Table 7-4, the planning and execution phase has gained a better maturity level, in comparison

to initiation and closing phases. This means that from participants’ points-of-view the current

PM practices to facilitate planning and execution phases are stronger than closing and initiation

practices. In order to obtain more information in this regard, further investigation were

conducted by looking at interviews and direct observation data. Interestingly, it was realised that

MINCO’s employees believe that inadequate information is obtained at initiation phase, so they

expect to be actively involved at this phase, as In.Mc.3 comments:”…the knowledge transfer

form initiation is not enough to get accurate information….”.

Table 7-4 MINCO’s PMO ML from project lifecycle perspective (developed for this research) Project Phases Maturity level(ML) Average ML

Initiation 2.07

3.02 Planning 3.93


Furthermore, analysis of data indicates that, in general, participants believe MINCO’s PMO

supports projects in a satisfactory manner; they illustrate followings perceptions:

“…it’s again I’d probably say [level] four, again it’s fairly well developed and they’ve

got the frameworks there…”, quoted by In.Mc.4.

“…PMO should be going on without basing on people but we are really based on

people skills still. So let’s say 4 because there is more to go…”

“…I’d probably put it at mid-range, I still think there’s a lot to learn and a lot to

go…”

3.00 3.21

3.00

3.07

2.93

4.21

3.29

2.79

3.14

Project Scope

Project Cost

Project Time

HRmanagement


ProjectCommunicatio

n

ProjectProcurement

ProjectIntegration

ML OL


Figure 7-3 MINCO’s Maturity level from project lifecycle perceptive (developed for this research)

The maturity level of MINCO’s PMO has been graphically presented from both knowledge

and project lifecycle perspectives, in which both indicate the third level of maturity, as shown at

Figure 7-2 and Figure 7-3. This means that MINCO’s PMO has significant numbers of PM

practices to facilitate project management (Kerzner 2005; Kerzner 2013). In a consistent

manner, during interview data analysis, participants responded that MINCO’s PMO is mature

enough to contribute to project success. In addition, during direct observation, numbers of

systems and procedures were recognised that are appropriately used in project lifecycle. An

internal assessment, which has been done by the PMO, shows the maturity of 3.5 out of five,

which is in line with the research findings.

The third level of maturity for MINCO’s PMO means that there are adequate tools and

systems in place to support MINCO’s projects (Kerzner 2005). According to the research

framework, a third maturity level is called “Singular methodology” (Kerzner 2013). This means

that there is a developed- comprehensive PM methodology in place for project management

(Kerzner 2013). In other words, at the third level of maturity it is assumed that PMO has

developed a PM standard to address both basic, and some of the advanced PM practices. In fact,

in a PMO with third level of maturity : 1) all utilised PM practices have been integrated at one

PM standard, 2) all various PM methodologies have been combined in one organisational-wide

PM methodology, and 3) Project team members actively adhere to the developed PM standard

(Kerzner 2005). In general, PMO with third level of maturity should have following

characteristics (Kerzner 2005; Kerzner 2013):

• Organisation has totally committed to the concept of project management,

• The current project management processes and procedures have been integrated into a

single methodology with demonstrated successful execution,

• There is corporate-wide culture that supports informal project management and

multiple-boss reporting, and

2.07

3.93

3.29

2.79

Initiation

Planning

Execution&monitori

Closing

ML OL


• PMO has developed a sense of shared responsibility and accountability for the

principles of project management.

Since previous findings indicate that MINCO’s PMO has the third level of maturity,

therefore, these characteristics should be consistent with the current status of PM in MINCO. In

order to investigate the consistency between the research findings and framework, the collected

data from interviews and documents were analysed to examine data against the above

mentioned characteristics.

In the first step, the MINCO’s PM methodology was analysed against the research

framework. As discussed, in a PMO with the third maturity level, one singular PM standard

should be utilised across the organisations. The direct observation and document analysis

confirms the existence of a comprehensive PM standard in MINCO. This PM framework has

been accepted as the main methodology to be followed during project life cycle and it is

strongly supported by MINCO’s senior managers. This PM framework will be discussed further

in section 7.4.1.1.

Furthermore, appropriate training, workshop and an induction program are provided for new

employees or junior staff to make them familiar with the current culture and develop their

knowledge of project management. In addition, there are numbers of practices and processes, in

line with PM standards, to improve the project success rate through improving their knowledge.

For instance there is a practice which is called “safety share”, by which at every weekly meeting

all participants should discuss a risk that they have faced, and then discuss about both an

appropriate mitigation method and a lesson learned. This means that the current culture of

project management contributes to quality of project outcomes but it does not mean that it is

perfect.

From the participants’ points-of-view the current project management framework is robust

enough to assist project managers (PMs) in conducting their assigned activities. In addition, all

respondents mentioned that they are quite familiar with the existing PM standard and they have

been trained appropriately. Also, the research findings revealed the majority of PMs are familiar

with the current PM standards such as PMBOK and PRINCE2 which made them to criticise the

current PM methodology. This means that in the current culture of PM there is a dynamic

approach to improve the quality of project management environment (Project Management

Institute 2013). Moreover, it was found that there is a good understanding of matrix

organisations in MINCO, in which one employee could have more than one boss (Project

Management Institute 2013). This means that the multiple-boss reporting, as another

characteristic of third level of maturity, has been identified in MINCO’s PMO.

http://www.my-project-management-expert.com/principles-of-project-management.html


As Table 7-5 depicts, two main criteria of PMO with third level of maturity, i.e. PM

methodology and culture, have been selected to present some of participants’ comments in this

regard.

In order to examine other criteria of PMO with third level of maturity, such as a sense of

sharing the responsibility and accountability, direct observation data was analysed

accordingly. According to the current MINCO’s employee assessment procedure, one of the

criteria to assess human resource performance is the employee’s contribution to his/her fellow

team members. This criterion has developed a culture by which responsibility of team members

is not limited to their formal job, but it is linked to project success. Therefore, team members

have a sense of shared responsibility and accountability, as required for the third level of

maturity.

Table 7-5 Participants’ quotes in regards to MINCO’s PMO matuirty (developed for this research) Subject Associated participants’ comments

PM Methodology

In.Mc.2: “…Our project managers are all trained on the PM courses…so that’s yeah your PMBOK…”

In.Mc.3: “…Well I mean [MINCO] has got their project development manual that basically sets out how you manage your project. So that’s the framework for it…”

In.Mc.1: “…there is a defined delivery project management framework that’s defined to manage all project ….”, “…what I mean is like it’s been defined, it’s got the PMBOK elements in it.

The PMBOK elements underpin the project management framework…”

Culture of Project

Management

In.Mc.2: “…let’s say we have a building that has a non-compliant fire system in it because it’s been expanded a lot. So we have to put in, we have to expand the fire system in the project, in

the site. So that becomes a risk reduction project…” In.Mc.4: “…So we go and visit the project every month and check its progress, check its

deliverable quality, are they completing their registers, are they executing the plan? Are they executing the contract...”

In.Mc.5: “…So we rely quite heavily on our tool kit for that. So we have a, there’s something that one of our principals in the assurance team…”, “…Well the PMO provides all the resources so we’ve got…so when you go from selection to definition it’s…so identification and selection

is run by the development group within the projects so they do all the studies…”

In summary, the collected data from different sources are consistent in terms of maturity

levels of MINCO’s PMO (Kerzner 2013; Project Management Institute 2013). This means that

triangulation of various data sources contributes to the quality of research findings (Yin 2009).

In other words, the maturity level of MINCO’s PMO was assessed through not only survey-

questionnaire, but also, analysing the collected data, and both consistently provide similar

outcomes. During the process of document analysis, a PM framework was recognised in

MINCO. In the next section, this framework has been analysed in order to shed more light on

the current PM methodology in MINCO.

Project management methodology in MINCO 7.4.1.1

According to the research findings, MINCO’s PM standard has been developed through

mainly employing PMBOK, and comprises four phases: 1) Identification, 2) Selection &

Definition, 3) Execution, and 4) Operation, as shown in Figure 7-4. Each phase has numbers of

processes and procedures to facilitate the associated activities, as depicted in Figure 7-5.


In the Identification phase, high level activities and feasibility studies should be undertaken

to prepare accurate information. In addition, the project opportunity and its alignment with

organisational objectives should be defined at this phase. Also, it should be justified as to how

this opportunity will benefit whole organisation. This is similar to definition of “business case”

in the PMBOK (Project Management Institute 2013). In fact, significant knowledge is created in

this phase through applying the recommended processes and practices in order to provide

reliable input for the next phase.

Figure 7-4 MINCO's project life cycle (adopted from MINCO’s PM framework)

If the green light is given by MINCO’s senior managers then the next phase, i.e. Selection

and definition phase, is conducted to define and provide project scope, schedule, budget and

deliverables, as shown at Figure 7-4. In fact, this phase is similar to the planning phase in the

PMBOK (Project Management Institute, 2012). As presented at Figure 7-5, in order to manage

the selection phase, there are numbers of processes and procedures in place such as stakeholder

management plan, risk management plan. According to the MINCO’s PM standard at the end of

this phase, the provided plans should be integrated in one plan, which is called a project

management plan.


Figure 7-5 Selection &definition phase (adopted from MINCO’s PM framework)

In the Execution phase, the project management plans should be followed to ultimately

deliver project predefined outcomes and deliverables. According to MINCO’s PM standard,

numbers of activities such as monitoring and control, risk management, change management,

and quality control should be managed during the execution phase. Also, numbers of documents

such as project progress and costing report should be provided for associated stakeholders. This

phase finishes when the project deliverables have been submitted and accepted, so project

stakeholders are satisfied to proceed to the closing phase.

After delivering project outcomes, the Operation phase is commenced to integrate those

outcomes in MINCO’s business. In this phase, there is an assumption in which all undertaken

projects in MINCO should add some value to current business performance. In other words,

MINCO does not aim to undertake any client projects. In this phase, project close out

documents should be provided, as well as manuals and lessons learned. Also, training plan,

operational support documents, and post project review should be managed at this phase. These

processes have been clearly defined in the PM standard and their associated applications were

advised accordingly, which make it user friendly.

In summary, the current PM framework has been developed in the last 10 years, and now

participants believe that it is mature enough to be followed by project managers. In addition, it

is supported by numbers of processes, procedures and systems such as risk management tools, a

close out process and Primavera. These processes and tools are reasonably integrated to

contribute to the project success. On the other hand this PM standard is widely accepted among

MINCO’s employees and there is strong support from senior managers to push everybody to

follow this comprehensive PM standard. This framework has significantly contributed to

support the culture of PM in MINCO. According to the current literature, PM systems and tools


are important factors to facilitate PM alongside the PM methodology. In the next section, the

current PM systems and applications will be discussed to gain insights in this regard.

Project management systems and tools in MINCO 7.4.1.2

The performance of the project management environment is dependent on the current

systems, tools and processes (Project Management Institute 2013). According to the collected

data from interviews, document analysis, and direct observation, MINCO has developed

numbers of tools as systems to assist project stakeholders with managing their activities. For

instance, more than ninety processes and procedures, have been recognised in MINCO, such

as risk management, safety management, quality management and stakeholder management. In

addition, there are some tools in place such as Primavera, MS project, and other similar

applications, in order to facilitate PM in MINCO.

The research findings revealed that there numbers of systems and tools in MINCO to

facilitate project management, as shown in Table 7-6. In fact, MINCO has a collaborated

information technology system, by which the current applications can be accessed through one

gate around the globe. This means that MINCO’s employees could have access to their required

applications through an assigned laptop, regardless of their location. The MINCO’s applications

have been designed for various purposes, therefore, only those applications that are directly

utilised by PMO were discussed in this report. In total, five applications have been recognised,

which are used to manage projects in MINCO: SAP; Primavera; Intranet; Hummingbird; and;

Galileo.

Table 7-6 The current systems and tools in MINCO’s PMO (developed for this research)


SAP To integrate cost and procurement across the MINCO

Primavera To plan and control all projects in one system

Intranet To provide access to different applications used by employees across the globe

Hummingbird To capture and transfer project information

Galileo To save project information from past and have a database of projects history

SAP is a total system in MINCO which is used for cost and procurement purposes. In other

words, project data such as cost, invoices, claims, and contracts are saved and populated in SAP

software. SAP is an organisation-wide solution to capture and somehow transfer the project

knowledge, however, there are some issues with SAP from a PM point-of-view, which are yet

to be addressed. In fact, SAP is not an appropriate software for managing projects and it needs

to be integrated with other software to directly contribute to project success (Crawford 2012).


This gap was found by MINCO’s experts, so the PMO offers some other software, such as

Primavera and Ms Project, in conjunction with SAP for PM purposes.

Primavera is one of the popular PM softwares which is widely used by enterprises to

manage organisational projects (Tang, et al. 2010). This software contributes to project time,

cost and scope management, so the other PM knowledge area such as risk and quality

management cannot be directly managed by Primavera (Tang, et al. 2010). MINCO’s PMO

employs this software to plan and control the existing projects and also to provide appropriate

project progress reports. The central database of Primavera significantly contributes to access

the required information in order to both assess project progress and audit the project

deliverables.

A well-established Intranet is another organisational-wide application, which gives

employees appropriate access to their appointed software. Also, an intranet assists project

stakeholders with accessing different forms, procedures and manuals, such as leave request

form, and project report procedure. During the direct observation, it was revealed that the

current intranet is, also, used as the main gateway to update project databases. In addition,

access to organisational mailbox and appointed folders for each group or division has been

facilitated through the intranet. In fact, the current intranet is a well-structured system by which

the required accesses to various types of applications and databases are authenticated based on

the employees’ role and responsibilities. For instance, access to current PM systems such as

Galileo and Hummingbird, are also managed through the current intranet.

MINCO’s employees are advised to upload all their work related files, presentations, reports,

and manuals into Hummingbird. In other words, all of an organisation’s documents should be

saved and recorded in this database. This means that Hummingbird is one of the major

applications for knowledge capturing and transferring in MINCO. Hummingbird is accepted

among employees and they try to use this application as the main project knowledge repository,

as one interviewee comments:”…within [MINCO] the key knowledge management source or

data base for managing knowledge is Hummingbird…”, quoted by In.Mc.2. The further

investigation revealed that MINCO’s employees are frequently using this software due to its

availability across MINCO.

Galileo is another system in MINCO to record the project information. This system is

utilised to gather project history from the initiation, when an idea is developed, to the end, when

the project is finished. Clearly, Galileo is a system to capture project information for

transferring and reusing purposes. Participants believe that this system has a significant

influence on their works since it is helpful when they need to find information about similar

projects for developing a new idea. Following are the respondents’ comments about Galileo:


“…So a project idea is entered into our reporting system Galileo from where it’s been

adopted and built upon…”, quoted by In.Mc.4

“…No Galileo is to capture all the project in the Galileo it’s sort of a report that you can

run monthly, daily and see which projects have how much actual detail what is the forecast

putting in place…”, quoted by In.Mc.3

In summary, the research findings revealed that current systems have significant

contributions to managing projects in MINCO. For instance SAP is used for project costing and

invoicing purposes and Intranet provides required access to various organisational resources. In

addition, Primavera is used for collaborating project activities and undertaking project control,

and Galileo facilitates the access of project information and also previous project experiences.

However, there are some issues that are yet to be addressed if MINCO’s senior manager aims to

improve the quality of their PM services. For instance, integration between SAP and PM

application needs to be addressed in order to improve collaboration among the current systems.

Having said that, this research aims to focus on the PMO from a KM point-of-view, therefore,

in this section the major issues of MINCO’s PMO from a KM perspective will be discussed

accordingly.

Knowledge Management challenges in MINCO 7.4.1.3

The interview data was used as the main source to recognise issues of MINCO’s PMO from

a KM perspective. In addition, the research framework was followed in which interviews’

transcriptions were uploaded to the Nvivo, as data analysis software. Then the process of

coding, both open coding and axial coding, was managed, as it has been advised by similar

qualitative research (Charmaz 2014; Corbin and Strauss 2008; Wiewiora, et al. 2010). In the

first stage of the open coding process, more than 64 nodes were developed in Nvivo. These

codes or comments have directly or indirectly mentioned the current challenges from a KM

point-of-view. Following are some of the examples of the coded comments:

“…Ideally it shouldn’t be like that but we need some knowledge in that part because

those people are gone and before they …nobody has thought to put some lessons learned

or something like that into place…”, quoted by In.Mc.2.

“…So getting that knowledge passed over from one study manager to the next one is

very difficult unless people actually file it in the correct locations…”, quoted by In.Mc.4.

“…A lot of this information is locked away and people keep it on their hard drives or

they don’t keep them in shared folders and so you can’t access it…” quoted by In.Mc.1.

The similar process of previous cases, was followed to determine the current challenges of

MINCO from a KM point-of-view and eventually the following categories of KM issues have

been developed:


1) Inadequate practices to support knowledge transferring process

2) Issues with current systems to fully support knowledge capturing process

3) Unsatisfactory practices to appropriately support knowledge reusing process, and

4) Lack of training for current systems and applications

Table 7-7 is an example to present how participants’ quotes were related to open codes, and

also, how axial codes were developed accordingly.


Table 7-7 Example of Axial and Open coding in MINCO’s PMO (developed for this study)


Inadequate practices to support knowledge transferring process

Challenges of transferring knowledge form project stakeholder

“…Ideally it shouldn’t be like that but we need some knowledge in that part because those people are gone and before they …nobody has thought to put some lessons learned or something like that into place…”, quoted by In.Mc.2. “…So getting that knowledge passed over from one study manager to the next one is very difficult unless people

actually file it in the correct locations…”, quoted by In.Mc.4. “…A lot of this information is locked away and people keep it on their hard drives or they don’t keep them in shared

folders and so you can’t access it…” quoted by In.Mc.1. Better communication…earlier communication with the project manager and supervisor who are going to do the job,

quoted by In.Mc.3.

Issues of transferring knowledge from study managers at planning phase

Lack of transparency of the exciting information

Lack of practices to facilitate stakeholder communications

Issues with current systems to fully support

knowledge capturing process

Issues of capturing of lesson leaned “…And I guess one of the things that we’re looking at is hopefully there’s a risk management process might start capturing that so we can whilst we’re not involved we can access those lessons learned without imposing upon the

project progress…”, quoted by In.Mc.1 . “…That’s the problem in our process it’s not easy to find old projects and go in and create those documents…”, quoted

by In.Mc.3. “…I’m talking more about the capture and the storage, there’s a, it’s a broken step between capture and storage… So the

storage mechanisms or the story, there is no clear framework for rules on storage…”, quoted by In.Mc.2. “…Had the potential though to cost money, quite a lot of money because we didn’t investigate the risk controls

better…” , quoted by In.Mc.5.

Challenges of findings old process and information

Issues of storing knowledge

Issues of capturing risk management information

Unsatisfactory practices to appropriately support

knowledge reusing process, and

Lack of engagement of project manager at initiation stage

“…My personal opinion is your execution project managers and construction supervisors should be engaged earlier in the process…”, In.Mc.1.

“…And as far as reusing knowledge goes I mean it seems to me that it only really gets reused when you’ve got the same people there that actually created it in the first place…”, quoted by In.Mc.3.

“… Selection phase is about exploring options and alternatives and then coming up with the most preferred alternative. So that might be preferred based on previous projects…” , quoted by In.Mc.2

Issues of knowledge reusing is worse than other KM process

Lack of exploring options and choosing the preferred alternative

Lack of training for current systems and

applications

Training for current systems is not satisfactory “…I mean when I first started I got they say here you are, this is hummingbird this is (?) off you go. So the training side

is probably not there…”, quoted by In.Mc.5. “…So for example the manager, the business owner for this project changed three times in planning, we had three

different managers…”, quoted by In.Mc.3 “…They’ve got the documentation that says this is how you do things. The problem comes with people’s discipline in

actually following…”, quoted by In.Mc.2

Induction does not cover all applications

Lack of appropriate course for at the job trainings

Chapter 7 Case Study Analysis: MINCO 187

Figure 7-6 The current KM challenges in MINCO’s PMO (developed for this study)

In order to analyse the above mentioned challenges, the developed codes were employed,

alongside the research framework. In addition, the frequency of codes and comments was used

as the main criteria for this part of the investigation. As depicted in Figure 7-6, more than 49

percent of coded data has indicated the issue of knowledge transferring. This means that

participants believe that the current KM practices do not appropriately support the processes of

knowledge transferring during the project lifecycle. Further analysis revealed that the majority

of the recognised knowledge transferring issues occurs at Planning and Execution phase. For

instance, participants complained about poor knowledge transferring from the initiation phase,

as they believe that inadequate information is given to commence a planning phase.

“…So getting that knowledge passed over from one study manager to the next one is very

difficult unless people actually file it in the correct locations…”, quoted by In.Mc.5

In addition, respondents have mentioned some issues related to knowledge transferring in the

execution phase, such as lack of transparency and appropriate communication practices. This

means that the issue of knowledge transferring not only is the main concern for MINCO’s

employees, but also it is a significant challenge for the existing project, as could be inferred

from the following comments:

“…I’m not included in initiation phase. However, the knowledge transfer form initiation

is not enough for us to get accurate information form stakeholders…”, quoted by In.Mc.2

“…Lack of communication between different people who are doing the definition,

execution and studies…”, quoted by In.Mc.3

“…Stakeholders were changing all the time and one of the things that could have been

done better was stakeholder knowledge transfer…”, quoted by In.Mc.1

49%

32%

22%

7%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Unsatisfactory practices to appropriately support Knowledge reusing process

Lack of trainings for current systems and applications

Issues with current systems to fully support knowledge capturing process

Inadequate practices to support knowledge transferring process


“… Transparency, better transparency, A lot of this information is locked away and

people keep it on their hard drives or they don’t keep them in shared folders and so you

can’t access it…”, quoted by In.Mc.5

The second most significant challenge is the current issues with existing systems for

capturing project knowledge. As can be found in Figure 7-6, more than 32 percent of the

recognised issues are associated with capturing knowledge. In order to pin down this issue,

further analysis was conducted, and eventually three sub-issues were recognised: knowledge

storage, lessons learnt and insufficient practices, especially in the closing phase. This means that

respondents believe the current practices can be improved to enhance the quality of knowledge

capturing at closing phase. Following are some of the concerns in this regard:

“…So we lose this big opportunity of gathering information progressively through a

project so we got involved up the front, we get involved sort of in the planning and at the

end. But that assumes the people at the end are actually providing us with knowledge that

will happen in the execution phase and that doesn’t tend to happen very well. So it’s that

capturing of the lessons learnt progressively that we miss it…”, quoted by In.Mc.1.

“…In the execution phase. And I guess one of the things that we’re looking at is

hopefully there’s a risk management process might start capturing that so we can whilst

we’re not involved we can access those lessons learned without imposing upon the project

progress. And that’s the hard part…”, quoted by In.Mc.2.

“…So the storage mechanisms or the story, there is no clear framework for rules on

storage…”, quoted by In.Mc.3.

According to the research framework, capturing project knowledge should be the most

important KM process at closing phase (Owen and Burstein 2005). On the other hand, the direct

observation revealed that despite the existence of some tools such as Hummingbird and Galileo,

these systems are yet to be integrated to appropriately address knowledge capturing and

transferring during the project lifecycle. In other words, integration among the current systems

is an issue which needs to be addressed by PMO.

Lack of training for current systems has been recognised as the third most frequent

challenge, with more than 22 percent of the obtained data. According to the research

framework, training has been classified as one of the practices for supporting knowledge

transferring. In other words, this issue is associated with issues of knowledge transferring but

because of its frequency, it has been classified as a main issue. According to the research

findings through collected data from direct observation and document analysis, numbers of

training courses are managed for MINCO’s employees. In addition, there is a comprehensive,

three day induction program in order to make new staff familiar with current systems and tools.


Also, there is budget for training for each employee by which he/she could be nominated for

various types of required training classes.

On the other hand, as discussed earlier, there are numbers of applications and tools in

MINCO, which should be employed during the project lifecycle. The main concern is the

appropriate usage of the right application for associated purposes. Participants believe that on

some occasions they are not quite sure which system should be utilised, due to lack of training.

For instance, both Galileo and Hummingbird should be used for capturing project knowledge,

but there is limited guidance to address how and when these systems should be employed. This

means that lack of training courses to assist employees with suitable usage of the current

applications is a significant challenge, and some of quotes address this issue:

“…They’ve never actually been showed it, which may well be it. I mean when I first

started I got they say here you are, this is hummingbird…off you go. So the training side is

probably not there…”, quoted by In.Mc.4.

“…they’ve got the documentation that says this is how you do things. The problem comes

with people’s discipline in actually following…”, quoted by In.Mc.5

“…Well there’s obviously a gap because the framework is there for how you do it. It’s

just that people don’t, a lot of people don’t bother…”, quoted by In.Mc.2

The fourth most frequently mentioned challenge is the associated concerns about knowledge

reusing with more than 7 percent, as shown at Figure 7-6. According to the research

framework, knowledge reusing should be the last concern, as it is strongly dependent on other

knowledge processes, specially transferring and capturing. As discussed earlier, the initial

findings indicate that there are numbers of KM processes in place to support knowledge

capturing and transferring, such as data bases, procedures, and other applications, therefore

there are some bases for knowledge reusing. In other words, only in this case participants

directly have mentioned a number of concerns about lack of practices to facilitate knowledge

reusing, as could be seen one of the comments as following: “…I was saying it gets worse and

worse as you go through. And as far as reusing knowledge goes I mean it seems to me that it

only really gets reused when you’ve got the same people there that actually created it in the first

place…”, quoted by In.Mc.3.

This means that MINCO’s employees are aware of the importance of knowledge reusing, as

they expect to see some KM practices in place to facilitate this KM process. In order to shed

more light on this issue, the coded comments were analysed, and eventually three main sub-

issues were recognised in regards to knowledge reusing. First, the created knowledge at

initiation [identification] phase is not used because of lack of communication between study

group and project managers. Second, the nature of MINCO’s projects are similar, so

experienced PMs should transfer their knowledge for future usage purposes, but there are few


practices in place to support this process. And third, the current systems and their different

usages make some unambiguity for MINCO’s employees to capture and reuse previous

knowledge.

In summary, four challenges have been recognised in MINCO’s PMO from a KM point-of-

view. According to the research findings, issues of knowledge transferring is the most frequent

challenge from respondents’ point-of-view, and knowledge capturing is faced with a number of

issues, as the second most frequent challenges. Also, lack of training and KM practices to

support knowledge reusing have been recognised as third and fourth frequent-mentioned KM

challenges in MINCO. In this section, the initial part of the first research question (RQ1- How

are KM practices and processes employed in the PMOs?) has been addressed. In order to

answer the parts, the importance of the required knowledge types will be discussed in the next

section.

Types of required knowledge at project life cycle in MINCO 7.4.1.4

According to the research framework, there are eight types of knowledge at the project

environment: Project Management Knowledge; Knowledge about Procedures; Technical

Knowledge; Knowledge about Clients; Costing Knowledge; Legal and statutory Knowledge;

Knowledge about suppliers; and Knowledge of who knows what. In this step, the importance of

each type of knowledge will be discussed accordingly. To do so, survey forms were distributed

among the eleven participants and, eventually, eight completed forms were returned (about 72

% response rate). In the survey, respondents were asked to rank the above mentioned types of

knowledge from 1, the least, to 8, the most important knowledge during four phases of the

project life cycle. After collecting and organising data, similar to the previous case study, an

Analytical Hierarchy Process (AHP) was employed to analyse survey responses. Eventually, the

importance of eight types of project knowledge in MINCO’s PMO has been ranked in the

project lifecycle, as shown at Figure 7-7.

According to MINCO’s respondents at the Initiation phase, following are the three most

important types of knowledge: 8) project management knowledge, 7) technical knowledge, and

6) knowledge of who knows what. This is in line with current PM practices, as PMBOK (2012)

advises to have adequate knowledge of PM and technical knowledge at initiation phase. In

addition, respondents mentioned that finding the right person who has knowledge about similar

projects is important at this phase. As discussed earlier, one of the KM challenges in MINCO is

lack of practice for knowledge reusing. According to the research framework “knowledge of

who know what” contributes to reusing the existing knowledge. Therefore, this is one of the

reasons why participants have mentioned this type of knowledge as an one. On the other hand,

participants ranked the subsequent knowledge types as the less important ones: 3) knowledge

about procedures, 2) Legal knowledge, and 1) knowledge about supplier. This ranking is again


is not contradictory with the research framework since there is no indication of having these

types at initiation phase, in the current KM standards.

Figure 7-7 Types of required knowledge at MINCO’s PMO (developed for this research)

At the planning phase the knowledge of PM still keeps its spot as the most important one,

but “knowledge about procedure” and “knowledge about clients” were chosen as second and

third most important knowledge. According to PM standards, “PM knowledge” and “knowledge

about procedures” are vital at the planning phase by which project plans are developed (Bentley

2009; Kerzner 2013; Project Management Institute 2013). In addition, knowledge about clients

is an important entity, since clients’ expectations play an important role for planning project

deliverables. On the one hand, respondents believe that knowledge costing is not as important as

technical knowledge and knowledge about who knows what. The first impression was that this

finding is not consistent with PM standards, however, more investigation revealed that since the

budget and cost of project is decided at higher levels of MINCO, then participants have less

concerns about it. In addition, choosing “knowledge about supplier” and “legal knowledge’ as

the least important types of knowledge is not against the PM standard, as they should be mostly

considered at execution phase (Project Management Institute 2013).

8

3

7

4 5

2 1

6

Initiation 8 7

4

6

3

2

1

5

Planning

8

4

7

1

5

3

7

2

Execution 8

7

3

6

4

2

1

5

Closing


At execution phase, the importance of “PM knowledge” has still been emphasised by

participants, while knowledge about procedure loses its spot to technical knowledge. In

addition, as was predicted earlier, knowledge about supplier was ranked as the second most

important knowledge at the execution phase. All three mentioned types of knowledge are

advised to be appropriately provided at the execution phase by the current PM standards, as they

are very important to implement the project plans (Project Management Institute 2013).

According to PMBOK (2013), after commencing the execution phase, clients have less

influence in the project. Consistently, participants have ranked “knowledge about client” as the

least important knowledge type at this stage.

According to PM standards, the closing phase is about to formally finish the project through

verifying the project deliverables and terminating the contract (Project Management Institute

2013). Therefore, knowledge of PM is mandatory to professionally follow the closing steps,

and, also, it is very important to have a good knowledge of organisational procedures to

formally finish the projects in accordance with organisational policies. As shown in Figure 7-7,

in a consistent manner both mentioned knowledge types have places as the most important types

of knowledge in the closing phase. Interestingly, “knowledge about client” has jumped from the

least important knowledge at execution, to the third most important knowledge at closing phase.

According to PM practices, one of the most important activities in the closing phase is to sign

off all deliverables and get the clients’ satisfaction, therefore it is very important to have a good

knowledge of clients and their expectations at this phase. In addition, technical knowledge and

legal knowledge have been placed as the least important types of knowledge, which is in line

with the purposes of the closing phase.

Table 7-8 Types of required knowledge in MINCO (developed for this research


Individual Rank Total weighted Rank

Initiation Planning Execution Closing Rank Percentage

Project Management Knowledge 8 8 8 8 8 19.5% Technical Knowledge 7 4 7 2 7 13.1%

Costing Knowledge 5 3 5 4 6 12.9%

Knowledge about Procedures 3 7 4 7 5 12.8%


Knowledge about Clients 4 6 1 6 3 12.2%

Legal and statutory Knowledge 2 2 3 3 2 8.5%

Knowledge about suppliers 1 1 7 1 1 8.4%

In the next stage of investigation, overall ranks of eight types of knowledge have been

analysed, regardless of project lifecycle phases. Similarly, AHP analysis was conducted by

giving the appropriate weight to each type of knowledge. Also, some other statistical

techniques, such as “mode”, were considered in the case of similar weight for some of the


entities. The main aim of this process was to generally recognise the importance of each

knowledge type. The outcomes of this analysis have been illustrated in Table 7-8.

According to research findings, “project management knowledge”, “technical knowledge”,

and “costing knowledge” are the most important types of required knowledge during the project

lifecycle, while ”knowledge about suppliers”, “legal and statutory knowledge”, and “knowledge

about client” are not as important as the other types of knowledge. These findings are not

inconsistent with PM standards as they generally recommend project managers to follow the

current PM practices in order to provide technical and costing knowledge (Kerzner 2013). One

of the explored inconsistencies between the research findings and the PM standard is the rank of

“knowledge about clients” in this analysis. In other words, the current PM standards emphasise

the importance of recognising clients’ expectation, but from MINCO’s participants’ point-of-

view, this knowledge type is not as important as others. As discussed earlier, MINCO mainly

undertakes internal projects, therefore MINCO does not deal in general with the client.

In summary, the importance of knowledge types in MINCO’s PMO could be ordered as

following: 1) Project Management Knowledge, 2) Technical Knowledge, 3) Costing

Knowledge, 4) Knowledge about Procedures, 5) Knowledge of who knows what, 6) Knowledge

about Clients, 7) Legal and Statutory Knowledge, and 8) Knowledge about suppliers. These

findings are consistent with the research framework and the PM standards. In this section, the

second part of the first research question has been discussed. The next section aims to

completely answer the first research question as well as the second research question (RQ2-

How do KM practices contribute to improve maturity level of the PMO?), through discussing

four knowledge management processes and their subsequent KM practices.

Knowledge management processes and practices in MINCO 7.4.2

As discussed in previous chapters, four KM processes were adopted, in which each process

has numbers of KM practices. Also, it was assumed that all four KM processes are employed

throughout the project lifecycle (PLC) except closing phase, as depicted in Table 7-9. This

means that all KM processes should be utilised during PLC, however, knowledge capturing is

the only KM process which should be used at closing phase. This assumption will be examined

during the case study analysis.



& monitoring

Closing

Knowledge Creation √ √ √

Knowledge Capturing √ √ √ √ Knowledge Transferring √ √ √

Knowledge Reuse √ √ √


In this section the second research question (RQ2- How do KM practices contribute to

improve maturity levels of the PMO?) and its two sub-questions will be discussed. To do so the

followings steps have be managed: 1) investigating the utilisation of KM practices and KM

processes at four phases of PLC, 2) examining the above-mentioned assumption about KM


of project lifecycle. To do so, the research framework and research methodology were followed

thoroughly, as explained in Chapter 5, Section 5.5.2. After following all required processes, the

obtained information was entered into Nvivo and eventually similar categories have been

developed, as depicted in Figure 5-9.

Similar to the previous case studies, frequency was used as the main criteria to explore the

current status of knowledge management in MINCO. During the process of coding interviews,

more than two hundred and fifty-four (254) comments and quotes, which have been directly


After analysing MINCO’S employees’ comments, it was revealed that more thirty five percent

of KM practices are employed at execution and monitoring phase, while only less than fourteen

percent of KM practices are utilised at initiation phase, as depicted in Table 7-10. This is an

indication of the importance of KM practices at the execution phase. In addition, the closing and

planning phases are the next important phases from a KM point-of-view. These findings are not

contrary to both current PM and KM literature as the majority of project activities are being

done at execution and planning phases (Project Management Institute 2013). Also during the

project closing phase, numbers of KM practices should be managed to prevent any knowledge

lost or leakiness (Owen and Burstein 2005).

Table 7-10 The usage of KM processes in MINCO (developed for this research)


monitoring Closing




From a KM process perspective, it was found that more sixty percent of current practices are

utilised for knowledge capturing, while only about three percent are employed for facilitating

project knowledge reusing. In addition, knowledge creation with about 26 percent and

knowledge transferring with about nine percent, are the second and third most utilised KM

practices in MINCO’s PMO. This means that the majority of the current KM practices have

been developed to support KM capturing and creation, while transferring and reusing are yet to

be developed. As discussed earlier, from a respondent’s point-of-view, knowledge transferring

and reusing are the most challenging KM processes in MINCO’s PMO (see section 7.4.1.3).


This is consistent with the new findings as it was realised that knowledge transferring and

reusing should be appropriately addressed. In other words, both findings not only are in line but

also they indicate the importance of developing of reliable KM practices to support transferring

and reusing knowledge.

From respondents’ points-of-view, knowledge creation is the second most utilised KM

process with more 26 precent of the analysed data, as shown in Table 7-10. As discussed earlier,

MINCO operates projects to develop its business capabilities and competitive advantage. Also,

the majority of projects in MINCO are managed for exploring and discovering new coal mines.

This entails creating significant knowledge during a project’s life cycle, which needs to be

managed appropriately. MINCO’s senior managers have realised the importance of facilitating

and capturing the created knowledge, therefore, this process is supported through numbers of

practices which will be discussed in detail.

According to the research framework, only knowledge capturing practices should be

employed at the closing phase. This assumption has not been completely confirmed in MINCO,

as it was revealed that numbers of transferring practices are employed at the closing phase, as

shown Figure 7-8. This means that this assumption is faced with some challenges; the research

findings explored that there are a number of KM practices in place to support project knowledge

transferring at closing phase. For instance, respondents believe that at the end of each project,

when it is ready to be signed off, a workshop is held to discuss a project from initiation to

closing, in which participants are being asked to have some input, so this contributes to both

knowledge transferring, and also capturing lessons learned. As one of the project managers

explains: “…Well that’s a function of the PMO. They used to do lessons learned or lessons

learnt workshops after every project…”, quoted by In.Mc.5

Figure 7-8 KM processes at project lifecycle in MINCO (developed for this research)

Investigating theKM at project

stages


Closing

40

10

18 12

0

97

13

23 29

32

13

2 3 7

3 5

0 2 2 0

Creation Capturing Transferring ResuingReusing


The most frequently mentioned KM process in MINCO is the knowledge capturing

process, as shown at Figure 7-8. This means respondents believe that the majority of the current

KM practices facilitate the process of knowledge capturing. As could be found in Figure 7-8,

during all phases of project lifecycle, knowledge capturing is the most frequent mentioned by

participants, which indicates the use of numbers of KM practices that support knowledge

capturing. In order to get better understanding of this KM process, it will be discussed in the

next section.

In summary, MINCO’s PMO has a reliable system to support KM activities. Knowledge

capturing and creation are the most developed KM processes, while knowledge transferring and

reusing are yet to be developed. According to the research framework, knowledge capturing is

an important process by which other KM processes are facilitated. In other words, a strong and

robust knowledge capturing system is an essential part of a KM system, which supports

knowledge transferring, creation and reusing. Therefore, it could be inferred that MINCO’s

PMO has an appropriate knowledge capturing system in place in order to develop other KM

processes, especially knowledge reusing and transferring. In addition, the research framework

assumes that only knowledge capturing should be managed at the closing phase, however, in

this case it was revealed that numbers of knowledge transferring practices are used at closing

phase. In this section, four KM processes have been discussed in general. In the next sections

each knowledge process will be individually discussed to answer the second research question

(RQ2. How do KM practices contribute to improve maturity level of the PMO?).

Knowledge Capturing in MINCO’s Project Management Office 7.4.2.1

According to the research framework, knowledge capturing should be employed during all

the phases of project life cycle, from beginning to the end of project lifecycle (Owen and

Burstein 2005). The previous findings have indicated that knowledge capturing not only is the

most frequent–mentioned KM process, but also it consists of a number of KM practices to

support the process of project KM, as depicted in Table 7-11. This table comprises three

columns in which the first table shows KM categories based on the research framework, the

second column represents the customised practices or systems to support the main categories,

and the third column displays the associated frequency to the KM categories.

The research findings revealed that document management system (DMS) is the most

frequent practice among other knowledge capturing, and it comprises a number of sub-

practices and applications, as shown in Table 7-11. This is a strong indication of the importance

of a document management system in MINCO’s PMO, by which project staff are advised to

follow the existing DMS for capturing project knowledge. There are numbers of documents in

various formats, forms and templates, such as project reports, meeting minutes, technical

designs, post project review and lessons learned. During the direct observation and document


analysis stages, more than eighty documents and forms were found through which knowledge of

projects could be captured in various formats. In fact, the research outcomes explored that

knowledge capturing is significantly facilitated through the existing DMS in MINCO’s PMO.

The second and fourth most frequently mentioned practices in MINCO’s PMO are

database (DB) and management information system (MIS), as depicted in Table 7-11 and

Figure 7-9. According to Eriksson (2013), an advance form of data base is MIS, in which data

could be analysed and interpreted. This capacity has been developed in MINCO, in which the

current data bases are used to make business analysis and decision making. In other words, data

bases and MIS in MINCO’s PMO are employed for both knowledge capturing and knowledge

creation, which is the advance form of data and information management (Eriksson 2013).

There are couple of DBs in MINCO, such as Gbiz for coal exploration purposes, Galileo for

project repositories, and Hummingbird to capture project knowledge. According to the research

findings, the collaboration of current DBs and MISs is the next step to be addressed by

MINCO’s PMO.

Table 7-11 Knowledge capturing categories and practices: MINCO (developed for this research)

Knowledge Capturing categories Associated Practices at MINCO Frequency

Data base

• Galileo • Gbiz • Hummingbird • Lesson learnt database

20


• Technical design • stakeholder mgmt. plan • Scope mgmt. plan • Risk assessment form • Project Reports • Project close out report • preliminary budget and schedule • Post project review • Opportunity statement for initiation • Meeting minutes • Lessons learned • End of the months report • close out report

85

Expert locator • Active directory 2 File Management System (FMS) • Windows base system 2

Formal or Informal events • E. room • Regular meeting • Workshops

16

Frequently Ask Questions (FAQ) • None 0 Intranet • A customised web-based intranet 3

Knowledge detection tools • None 0 Knowledge inquiry system • None 0

Knowledge repositories • Galileo 1

Management Information System (MIS)

• SAP • Gbiz • Galileo

15


The third most frequent-mentioned knowledge capturing process in MINCO’s PMO is

formal and informal events. This KM practice is supported through numbers of methods such as

meetings, e-rooms and workshops. According to the research framework, KM practices such as

forums and workshops could be used for both knowledge capturing and knowledge transferring

purposes. MINCO’s respondents believe that during these events not only they could get,

formally or informally, some answers to their questions, but also these events help them to

transfer some of their knowledge to other colleagues and project team members. As one of the

respondents comments: “…So we would have, oh not weekly it would be nearly daily catch ups

between the planner, project manager, myself cost controller and the supervisor when he was

free to discuss aspects of the project…”, quoted by In.Mc.4

Figure 7-9 Knowledge Capturing in MINCO’s PMO (developed for this research)

A customised intranet, expert locator, and an internal file management system and

knowledge repository are the other KM practices in the MINCO’s PMO for facilitating the

capture of project knowledge. As discussed earlier, MINCO has a robust server-client system by

which each client connects to MINCO’s server farms and gets access to the appointed

applications, so the file management system is another useful environment by which the

required knowledge is captured or stored. In addition, some of the current DBs such as yellow

page and contact list have been developed in separate environments. This is another indication

of the importance of integrating the current documents. On the other hand, some of the proposed

knowledge capturing practices in the framework, such as frequently asked question (FAQ),

knowledge detection tools (KDT) and knowledge inquiry (KI) system have not been recognised

in MINCO. This means that developing these practices could be the next step of the PMO for

improving the current KM system.

0

5

10

15

20

Management Information System(MIS)




Intranet




Expert locator

E-rooms


Data base


In summary, knowledge capturing is the most frequently mentioned KM process with more

than 62% of the associated comments in MINCO’s PMO. As discussed, document management

system, data bases, management information systems and formal and informal event are the

most frequently mentioned KM practices to support knowledge capturing, while some other

practices, such as intranet and expert locators are yet to be developed. In addition, three KM

practices, FAQ, KDT, and KI, have to be explored in MINCO. This means that MINCO’s PMO

has not completely addressed all the proposed KM practices. In other words, MINCO’s PMO

not only should address the mentioned KM practices, but also it should integrate the current

systems and applications, in order to improve the quality of project management. According to

the research framework, this will contribute to both the quality of project knowledge

management and also, improving the maturity level of MINCO’s PMO.

Knowledge Creation in MINCO’s Project Management Office 7.4.2.2

The second most frequently mentioned KM process in MINCO is knowledge creation,

with more than sixty times frequency out of more than two hundred and fifty. This means

MINCO’s respondents believe that there are a number of reliable practices to assist them with

creating knowledge during a project life cycle. According to the research framework,

knowledge creation could be facilitated through a number of practices, as shown in Table 7-12.

The frequency number of each associated KM practice has been pointed out in the following

table which is based on the research findings. From a respondent’s perspective, community of

practices and the existing research services are the most usable practices to create knowledge

in projects. On the other hand, they believe that some practices such as data mining and expert

systems are yet to be developed in MINCO’s PMO.

Table 7-12 Knowledge creation categories and pratices: MINCO (developed for this research)

KM creation categories Associated practices Frequency

Best Practice Cases • None 1

Community of practices • None 24 Data mining • None 0

Decision support system (DSS) • None 0

Deductive & Inductive thinking • Brainstorming 4

Documentation search • None 1

Experience Report • None 0

Expert systems (ES) • Expert Interview • Expert judgment

0

Informal and formal Event • Formal face to face meeting • Workshops & seminar

11


Research services

• Simulation • Use of Metaphors • Market research • Data analysis

13


As discussed, the community of practice is the most frequently mentioned practice to

support knowledge creation. According to the research framework, a community of practice is a

group of experts with different specialities, which gather together to discuss a subject(s) from

various points-of-view (Bell 2010). The research findings revealed that this practice is common

in MINCO and there are a number of procedures to support a community of practice. For

instance, when an issue or unresolved subject occurs, then a project manager invites different

experts from various divisions to discuss it, whether via phone or face-to-face meeting. In fact,

internal processes in MINOC strongly support the facilitation of this KM practice. Following

are some of participants’ comments in this regard:

“…the opportunity statement was based on the knowledge of processing engineers,

chemists, coal experts …”, “…We took we got all of the experts together in at the mine site

for about four to six hours we sat down and we went through an opportunity framing

workshop if you like…”, quoted by Im.Mc.2.

“…So you’ve got the two different mindsets are starting to meet and fill in the blanks on

the project…”, quoted by In.Mc.4.

“…So you get the right people around you that know the stuff that you don’t know and

then you go down that track. Workshops, it doesn’t even have to be a formal thing…”,

quoted by In.Mc.5.

Figure 7-10 Knowledge Creation in MINCO (developed for this research)

From respondents’ points-of-view, research services are reasonably facilitated in the

MINCO’s PMO, as it has been ranked as the second most frequently mentioned practice for

knowledge creation. There are a number of research services such as market research,

simulation and data analysis in place, by which project team members are enabled to create

knowledge for both making proper decisions and adding more value on project deliverables. For

instance, market research is conducted when an opportunity is recognised, so its potential

0

1

2

3

4

5

6

7

8

9

10

11

12

Initiation Planning Execution& Monitoring Closing

Best Practice Cases


Data mining




Experience Report

Expert systems (ES)


Knowledge Broker

Research services


profitability is investigated, as In.Mc.2 explains: “…So at initiation phase there was a lot of

research market research and specialist coal producer research that showed this new

technology …will greatly improve coal product…”. According to the research findings research

service is managed during the planning and initiation phase, as shown at Figure 7-10.

The third most frequent KM practice for knowledge creation is “informal and formal

event”. MINCO’s respondents believe that the PMO contribute to manage various types of

formal and informal events. According to KM theories, “formal and informal events” is a

practice to support both socialisation and externalisation process for creating knowledge

(Nonaka and Takeuchi 1995). In other words, participating in seminars and workshops are

useful to create knowledge during the project lifecycle. These kinds of workshops are conducted

at various stages of projects for different purposes. For instance, project managers run a

workshop at the planning phase to discuss the project risk management with team members

and/or external advisors, as In.Mc.4 explains: “…So the initial documents that were provided

were the justification for the idea, the safety stats to help support the idea and a highlight of the

risks of not following through on this project…”. The research outcomes revealed that formal

and informal events are also employed to manage some other KM practices such as a

community of practice and brainstorming.

According to research findings, “knowledge broker” is another KM practice, which is used

to facilitate knowledge creation in MINCO’s PMO. According to Barclay and Osei-Bryson

(2010), the PMO is considered as a knowledge broker in which it has the responsibility to

facilitate communication among employees for knowledge creation purposes. From

respondents’ points-of-view, the PMO contributes to being a knowledge broker as it supports

KM through numbers of practices, such as transferring knowledge from external consultants,

and making reliable communications among different divisions of MINCO in order to capture

the required knowledge for projects. Following is the comment of PMO’s knowledge manager

in this regard: “…I believe for delivering projects and it’s what their expectations are that

you’ll go through and you know making sure that you engage the right people”. This means the

senior managers of MINCO’s PMO have realised that important role pf PMO as the project

knowledge broker.

The other KM practices for supporting knowledge creation such as expert system, decision

support systems, and data mining are yet to be developed, as little evidence was observed in this

regard. This means that despite the existence of numbers of reliable KM practices to support the

process of knowledge creation, however, there are numbers of KM practices yet to be addressed

in the MINCO’s PMO, which could be improved in order for achieving the next level of

maturity.


From a project lifecycle perspective, knowledge creation is conducted at initiation, planning

and execution phases, while there is no sign of creating knowledge at closing phase, as shown at

Figure 7-10. This finding again confirms one of the research framework premises, which

assumes that only knowledge capturing should be managed at closing phase. Also it revealed

that in MINCO’s PMO, knowledge is created during the three other phases, however, numbers

of improvements are yet to be done to improve the maturity level of PMO. This might be a good

guidance for PMOs with the same maturity level to focus on improving their knowledge

creation practices at planning and initiation phases, as there is no need to create knowledge at

closing phase.

In summary, knowledge creation is the second most frequent KM process in the

MINCO’s PMO. There are some reliable practices for knowledge creation such as research

services, community of practices, and formal and informal event by which MINCO’s employees

could create knowledge during initiation, planning and execution phases. However, some useful

KM practices, such as data mining and decision support systems need to be addressed in

MINCO’s PMO. In other words, the PMO should consider improving its level of maturity

through both developing the existing KM practices, and also establishing new KM practices.

This means that for the next level of maturity, MINCO’s PMO should develop its capability not

only from the PM point-of-view, but also through improving the current status of project

knowledge management. According to the research framework, developing KM practices in the

PMO contributes to improve the quality of project management, and maturity level of PMO.

Knowledge Transferring in MINCO’s Project Management Office 7.4.2.3

Knowledge transferring is the third most frequently mentioned KM process, with less

than 9 percent of total comments for KM practices, as shown in Table 7-10. This means

respondents believe that knowledge transferring is supported not as well as knowledge creation

and capturing. In other words, the current KM practices need to be improved to support

knowledge transferring process in MINCO. This is consistent with previous findings as it was

discovered that the majority of current challenges are related to knowledge transferring (see

section 7.4.1.3). As shown in Table 7-13, more than forty percent of the knowledge transferring

practices have not been recognised in MINCO’s PMO.

Table 7-13 Knowledge transferring pratices in MINCO (developed for this research)

KM transferring categories Associated System/Practices in MINCO Frequency

Communication channels • Chat rooms • Email 11

Database • Wikis 2 Discussion forums • None 2

Electronic bulletin board • Project bulletin and reports 0 Formal and informal events • Seminar and workshops 16

Intranet • None 1


Knowledge directories • None 0 Knowledge list • None 0

Training& mentoring • Induction • Mentoring 19



According to the research findings, Training and Mentoring are the most frequent KM

practices in MINCO, as depicted in Table 7-13. The research findings recognised numbers of

training courses, such as induction and SAP training in MINCO for facilitating the usage of

some of the current systems. However, participants believe the offered training courses do not

cover their current needs. As discussed in section 7.4.1.3, lack of training was found as one of

the current challenges in MINCO as respondents have numbers of concerns in this regards. This

means that MINCO’s PMO should improve their training services to both enhance the project

KM and also achieve the next level of maturity. Following are some of evidence in this regard.

“…So beforehand you have to operate that… train and put the training package in so everyone

can use. Not only training those people but also put the training package in as well…”, In.Mc.3.

“…And that’s from all stages of projects down to the point where site engineering take over. So

we have a learning tool …”, quoted by In.Mc.4

The research findings revealed that “formal and informal events” are the second most

frequent practice for transferring project knowledge. This means that some practices such as

informal conversation and workshops contribute to transfer knowledge from the owner to other

project team members, as In.Mc.4 explains: “…we had with the contractors involved, me

getting them into the office to sit down and discuss it with them. I found that a face-to-face

discussion achieved more…”. According to the research framework, this practice could be used

for knowledge capturing and creation as well, but the tone of interviewees’ explanation have

guided this researcher to put it in the right KM process. Discussion forums, workshops and

seminars as well as face-to-face conversation are employed to facilitate formal and informal

events, however, respondents have mentioned some issues in this regard. For instance,

participants believe that the current instructions for discussion forums and workshops are not as

productive as they had expected.

The third most frequently quoted practices for knowledge transferring are

“communication channels”. According to the research framework, communication channels

such as phone and chat room could be useful during the project life cycle. MINCO has a strong

phone system by which conference calls among project stakeholders is easy to manage. Also,

email is widely used among project staff and is one of the main communication practices. In

addition, during the direct observation stage, it was explored than both email and phone are used

productively among MINCO’s employees. In fact, the current email has provided a reliable


system for project team members in MINCO to make the required communications alongside

MINCO’s PMO offices. In addition, MINCO’s respondents have mentioned there are some

tools to support using databases and the intranet for knowledge reusing purposes. As can be

found in Table 7-13, the frequency of these practices is not significant, which means that they

are not significantly able to contribute to the process of project knowledge transferring, from

participants’ points-of-view. According to the research framework, both DBS and Intranet are

useful tools for knowledge management purposes, especially for transferring project knowledge

(Ajmal, et al. 2010; Julian 2008). This means that MINCO’s PMO should consider the

development of these two practices, as they significantly contribute to knowledge management.

Figure 7-11 Knowledge transferring in MINCO (developed for this research)

From a project lifecycle perspective, most of the knowledge transferring activities happen at

closing, execution, and planning phases, while only a little evidence was found to support

knowledge transferring at initiation, at shown at Figure 7-11. In fact, this is one of the existing

challenges in MINCO, in which respondents believe that the created knowledge as an initiation

phase is not appropriately transferred to the next phases, as the following comment explains:

“…so getting that knowledge passed over from one study manager to the next one is very

difficult unless people actually file it in the correct locations…”, quoted by In.Mc.5. This means

that knowledge transferring faces some issues in MINCO, especially in the initiation phase. This

is consistent with previous research findings, as it was revealed that knowledge transferring is a

significant challenge in MINCO.

In summary, knowledge transferring is the third most frequent KM process from a

participant point-of-view. According to the research findings, “training and monitoring”,

“formal and informal events”, and “communication channels” are the most frequent KM

practices to support knowledge transferring. As discussed earlier, knowledge transferring is one

of MINCO’s major challenges, which needs to be appropriately addressed. According to the

0

1

2

3

4

5

6

7

8

9

10


Closing


Database

Discussion forums



Intranet


Knowledge list

Training& mentoring

Video and Tele Conferencemeeting


research findings, knowledge transferring is employed in all four project phases as well as

closing phase, as depicted at Figure 7-11. This is not consistent with the adopted assumption in

the research framework. This means that from MINCO’s participants’ perspective, there are

some practices in place to support knowledge transferring at closing phase, such as workshops

and mentoring to prevent any knowledge leakiness or stickiness. This is a significant finding in

this case study and will be discussed further in the next chapter.

Knowledge Reusing in MINCO’s Project Management Office 7.4.2.4

The least frequent KM process in MINCO is knowledge reusing, with less than four

percent of total coded comments. This means MINCO’s participants believe that there are

limited numbers of KM practices in place to facilitate project knowledge reusing. As shown in

Table 7-14, the usage of the only four KM practices: databases; lessons learnt ( part of DMS);

expert system; and formal and informal events are fairly mentioned participates, while limited

evidence was found to support the employment of other 7 KM practices in MINCO. In other

words, knowledge reusing needs to be improved comprehensively, from the participant point-

of-view. Also, it was previously explored that MINCO’s employees have mentioned knowledge

reusing as one of the significant challenges in MINCO. Therefore, this is an obvious indication

for MINCO’s PMO to improve the current activities of knowledge reusing.

Table 7-14 Knowledge Resing practices in MINCO (developed for this research)

KM reusing categories Associated Practices Frequency

Data base • DB 7 Data mining • None 0

Document Management System • Mentioned in lesson learnt 0 Electronic notice board • None 0

Expert systems • None 2 Formal or informal meetings • None 1

Intranet • None 0 Knowledge detection tools • None 0

Knowledge map • None 0 Lesson learnt • None 4 Yellow page • None 0

According to the research finding, the importance of knowledge reusing has been realised by

both senior managers and project staffs in MINCO. In other words, the role of knowledge

reusing to reduce project costs, and risk in order to improve project quality has been emphasised

by participants, as the following have been mentioned by interviewees:

“…there any kind of process within the PMO which tells you okay for reusing

knowledge go to this…”, quoted by In.Mc.4.


“…experience like all the documents but it’s not like a web base that you can go and

filter for those similar projects. But they are starting to make it like that. Not mature

enough yet…”, quoted by In.Mc.3

As Figure 7-12 depicts, the majority of the current knowledge indicated that reusing

activities are managed at initiation, and planning, while there was limited evidence of applying

knowledge reusing practices at the closing phase. This is consistent with the research

framework as it is assumed that knowledge reusing should be employed at all three project

phases, except closing phase (Owen & Burstein, 2005). This also consistent with the current PM

practices as they advise managing activities such as signing off project contracts and handing

over project deliverables at closing phase (Project Management Institute, 2012).

Figure 7-12 Knowledge reusing at project lifecycle: MINCO (developed for this research)

In summary, knowledge reusing is the least frequently mentioned KM process in

MINCO’s PMO. According to research findings, only four out of eleven KM practices have

been mentioned by MINCO’s employees. This means they believe that the current KM practices

do not significantly support the knowledge reusing process. According to Love, et al. (2003)

“rework” is one of the significant challenges for projects in Australian companies in which

“reworks” cost up to fifty percent of overrun costs. According to the research framework,

employing knowledge reusing practices significantly reduces rework. This indicates the

importance of knowledge reusing for increasing the project success rate. As discussed earlier,

knowledge reusing is considered as one of the major MINCO challenges. This means that

MINCO’s PMOs should focus on developing KM practices to improve the knowledge reusing

process, in order to achieve the level of maturity.

Summary 7.4.2.5


employed in the PMOs?) and its sub-questions have been answered in this section. According to

0

1

2

3


Closing

Data base

Data mining



Expert systems


Intranet


Knowledge map

Lesson learnt

Yellow page


research findings, the recognised challenges in MINCO are mainly related to knowledge

transferring and reusing. In order to answer the third sub-question (RQ 1.3 What kinds of KM

practices are utilised in each maturity level of PMO?), all four KM processes were analysed,

and, eventually, it was realised that knowledge capturing and creation are the most frequently

used KM processes in which more than sixty-two percent of comments support knowledge

capturing. In addition, knowledge transferring and reusing, together, are supported by only less

than thirteen percent of the collected data.

According to the research framework, only knowledge capturing should be employed at

closing phase. The research findings revealed that there are a number of knowledge transferring

practices in place, which are used at closing phase. This means that the mentioned assumption

has not been confirmed in MINCO as respondents believe they employ knowledge transferring

and capturing at closing phase. In addition, research data revealed that the majority of KM

activities are undertaken at Execution and monitoring phases, which is in line with PM

literature, since PMBOK explicitly addresses numbers of PM processes to support KM at the

planning and execution phase (Project Management Institute 2013).

According to the above mentioned findings, the following propositions could be proposed to

address the KM at the second level of maturity: 1) Knowledge capturing and creation are the

most important processes to be improved at third level of maturity, which means that PMO

should firstly focus on improving current practices for capturing knowledge and then creation,

2) Knowledge reusing is the least important KM process at this level, and it is dependable on

capturing and transferring. So it is recommended to focus on this knowledge process at the next

levels of maturity.

The importance of knowledge management processes in MINCO 7.4.3

This section aims to answer the second research question (RQ2-How do KM practices

contribute to improve maturity level of the PMO) and its sub-questions. Similar to previous case

studies, the survey–questionnaire was used at the main source of data in order to determine the

importance of four KM processes; Creation; Capturing; Transferring and Reusing at project

life cycle, i.e. Initiation; Planning; Execution and Monitoring; and Closing. As discussed

earlier, AHP technique is a suitable and accurate method for ranking the priority of competing


to rank KM processes in MINCO’s PMO.

According to the data analysis, knowledge reusing and creation were placed as first and

second important KM processes at the initiation phase, while knowledge capturing and

transferring have got the third and fourth rank, as depicted at Figure 7-13. This shows the

importance of knowledge reusing and creation at this phase, from a respondent point-of-view.

The direct observation revealed that in the initiation phase, the main focus in MINCO is to


investigate the project idea and analyse the different options. In other words, research data

indicates that knowledge is significantly created at this phase. In addition, due to the similarity

of projects in MINCO, project managers are strongly advised to use the knowledge of previous

projects as well as lessons learnt. This means that participants believe that it is important to have

appropriate KM practices for reusing knowledge at the initiation phase. This is consistent with

the current PM practices as they recommend to use previous projects’ knowledge in the

beginning of a project definition (Project Management Institute 2013). According to PMBOK

(2013), information about similar projects could contribute to better provision of project charter,

scope statement, and planning materials. In addition, PMBOK assumes that knowledge is

significantly created during initiation and planning phases, while during the execution and

closing phase, knowledge capturing has become more important (Reich and Wee 2006).

Figure 7-13 The importance of KM processes in MINCO (developed for this research)

In a consistent manner, knowledge creation is ranked as the second and first important KM

process during the initiation and planning phase, while it is the lowest one at closing phase.

This means that participants confirm the above mentioned theory and emphasised the crucial

role of knowledge creation at the planning and initiation phase. Having said that, the main aim

of the planning phase is to develop the required detail plans to achieve project objectives

(Project Management Institute 2013). In fact, planning consists of creating plans, technical

designs, budget analysis and other related knowledge to make sure that all activities have been

defined and appropriately planned for the execution phase (Project Management Institute 2013;

0

1

2

3

4

Initiation Phase

Capturing CreatingTransferring Reusing

0

1

2

3

4

Planning Phase

0

1

2

3

4

Execution and Monitoring Phase

0

1

2

3

4

Closing Phase


Reich and Wee 2006). This finding is another confirmation of the importance of knowledge

creation at the planning and initiation phase.

Moreover, at planning phase, knowledge transferring is ranked as the least important KM

process. This finding is not inconsistent with the research framework, as the project is still at the

initial steps of creating knowledge. In other words, knowledge could be transferred when the

created knowledge is captured and ready to be used by others. Therefore, participants

consistently have put the knowledge transferring in the fourth spot as they believe that the other

KM processes are more useful at the planning phase. This means that knowledge transferring

should get a better ranking spot at execution and closing phase. This assumption is confirmed as

it was realised that knowledge transferring has become the second most important KM process

at both closing and execution phase, as depicted in Figure 7-13.

At the execution phase, knowledge capturing and transferring were ranked as the first and

second most important KM processes, as shown at Figure 7-13. On the other hand, knowledge

creation and reusing have got the third and fourth positions. According to the PMBOK (2013),

at the execution phase the majority of activities should be undertaken through following the

provided plans, so project activities should be reported and measured regularly. This means that

knowledge capturing is the most important activity from KM point of view. Also, employees

should be trained, mentored or taught in order to undertake their assigned job. The research

findings are consistent with the current literature as MINCO’s respondents have ranked the

importance of KM processes. This means that MINCO’s employees believe that in the

execution phase, most of the KM activities should be focused on knowledge capturing and

transferring, while knowledge reusing is the least important process in this phase. In addition,

respondents believe that knowledge creation is more important than knowledge reusing at

execution phase. According to the findings from document analysis during the execution phase,

a number of PM activities are employed in MINCO, such as change management, and risk

management processes.

Figure 7-14 The general ranking of KM processes: MINCO (developed for this research)

As discussed earlier, the research framework assumes that knowledge capturing should be

the only KM process to be employed at closing phase (Owen and Burstein 2005). This means

0

1

2

3

4



that at closing phase, knowledge capturing should be the most important KM process. As shown

in Figure 7-13, MINCO’s employees consistently have ranked knowledge capturing as the most

important KM process at the closing phase. In addition, they have ranked knowledge

transferring as the second most important KM process. As discussed earlier, some evidence was

found that MINCO’s PMO advises knowledge transferring practices at the closing phase. This

finding is in line with previous findings as participants believe that some KM practices should

be employed at the closing phase to transfer knowledge to other MINCO employees.

After discussing the KM processes at each project phase, the next level of analysis was

conducted to investigate the rank of KM processes in the project lifecycle regardless of

individual phases. Similar to other cases, the same processes of employing the AHP technique

has been managed, and eventually the following rank of KM processes has been determined: 1)

knowledge capturing, 2) knowledge creation, 3) knowledge transferring, and 4) knowledge

reusing. According to the research findings, MINCO’s employees believe that knowledge

capturing and creation are the most important KM processes, while knowledge transferring and

reusing are not as important as the other two processes, as depicted at Figure 7-14.

In the previous section, i.e. section 7.4.2, KM processes and their usage have been analysed

to answer the first research question. The research findings revealed the following ranking of

KM processes, from data frequency point of view: 1) knowledge capturing, 2) knowledge

creation, 3) knowledge transferring and 4) knowledge reusing. As can be inferred from both KM

rankings, they are following the same order in which knowledge capturing and creation are the

most important KM processes in MINCO’s PMO, while knowledge transferring and reusing

have been ranked at third and fourth of the KM processes. This means that consistent outcomes

have been obtained from different data collection methods, which contributes to the quality of

the data collection methods as well as research outcomes.

In summary, findings from the survey, interview analysis, documents analysis, and direct

observation all emphasised that knowledge capturing and creation are the most important KM

processes in MINCO’s PMO, while knowledge transferring and reusing have not been

recognised to be as important as the other two KM processes. Therefore, it could be concluded

that at the third level of maturity the current KM practices should support KM in the following

order: Capturing, Creating, Transferring, and Reusing. In addition in could be concluded that,

at the third level of maturity, since PMOs have developed basic practices for supporting

knowledge capturing and creation, then the focus should be on improving knowledge

transferring and reusing through developing appropriate KM practices such as knowledge

detection tools, knowledge map, and electronic notice board. This not only will improve the

quality of KM process in the PMO but also it contributes to achieve better maturity levels.



In the previous sections of this case study, the two first research questions, i.e. how are KM

practices and processes employed in the PMOs, and how do KM practices contribute to improve

maturity level of the PMO, have been answered. In addition, during the data analysis stage, both

the importance of KM processes and the existence of challenges have been discussed in

MINCO’s PMO. In this section, each KM process will be discussed to investigate its

relationship with both KM associated sub-processes. and the following KM challenges: 1)

Inadequate practices to support knowledge transferring process, 2) Issues with current systems

to fully support knowledge capturing process, 3) Unsatisfactory practices to appropriately

support knowledge reusing process, and 4) Lack of training for current systems and

applications.

Knowledge transferring’s sub-processes and practices in MINCO 7.5.1

As discussed earlier, both knowledge transferring and reusing have been ranked as the third

and fourth most important KM process, among four KM processes. In addition, it was

recognised that the majority of the current KM practices in MINCO support knowledge

capturing and creation, while there are few KM practices to facilitate knowledge reusing and

transferring. Also it was revealed that MINCO’s respondents believe that majority of KM issues

are related to knowledge transferring and reusing, as discussed in section 7.4.1.3.

All these findings consistently confirm that knowledge transferring is one of the challenges

in MINCO’s PMO. In other words, knowledge transferring has been faced with numbers of

challenges in MINCO’s PMO, specifically challenges number one and four. According the

research findings, issues such as transparency and lack of access to the current knowledge are

some of the KM challenges in MINCO, as In.Mc.3 explains “…We need better transparency at

execution. A lot of this information is locked away and people keep it on their hard drives or

they don’t keep them in shared folders so you can’t access…”. In order to analyse the issue of

knowledge transferring in MINCO, the research framework was employed accordingly.

Table 7-15 Knowledge transferring sub processes in MINCO (developed for this research) K. Transferring Sub Processes




forwarding



• Knowledge list



1 and 4

Except communication channels such as email

and, other practices should be developed

Knowledge Sharing

• Discussion forums

• Formal and informal events

• Mentoring • Training 4

Training and formal and informal events are

mostly used


According to the research framework, knowledge transferring consists of two-sub processes:

distribution & forwarding; and sharing knowledge, as shown in Table 7-15 (Lytras and

Pouloudi 2003; Nissen, et al. 2000). The communication channels (such as email, chat), and

intranet are an example of “knowledge distribution”, and, training, discussion forums, and

mentoring are instances of “knowledge sharing”. As a matter of fact, for distribution process

technologies are more influential, while for knowledge sharing procedures and people play an

influential role (Hurt and Thomas 2009; Nonaka and Takeuchi 2011; Wiewiora, et al. 2010). In

Table 7-15 both sub-processes and their associated practices have been illustrated clearly.

According to the research findings formal and informal events as well as training and

mentoring are the most frequently mentioned practices for facilitating knowledge sharing, while

only communication channels have been recognised to support knowledge distribution and

forwarding. This means that MINCO’s PMO has developed some practices for sharing

processes, but, there are some gaps in place to support knowledge transferring from a

technological point of view. In other words, MINCO should develop some practices such as

project bulletin or yellow page to improve the knowledge transferring, and consequently to

address some of the current challenges, such as lack of transparency.

Further analysis revealed that knowledge distribution faces two challenges (1 and 4), while

knowledge sharing encounters the fourth challenge, i.e. lack of training for current systems and

applications. This is consistent with the previous findings as it was discussed that the current

knowledge transferring mostly facilitates knowledge sharing, so knowledge sharing should face

less of an issue, in comparison to knowledge distribution. This means that MINCO’s PMO

should develop the missed KM practices, such as knowledge list and yellow pages, in order to

address the current challenges, and ultimately improve the quality of project knowledge

management.

Knowledge reusing’s sub processes and practices in MINCO 7.5.2

The research findings explored that knowledge reusing is the second KM process, in terms of

KM challenges. In other words, after knowledge transferring, the majority of the recognised

KM challenges are related to knowledge reusing. On the other hand, knowledge reusing has

been ranked as the first and second most important KM process in initiation and planning

phases, as depicted at Figure 7-13. This means that participants have picked up the importance

of knowledge reusing for project planning and initiation purposes, and consistently they believe

that knowledge reusing faces some challenges, specifically at the two mentioned phases.

Table 7-16 Knowledge reusing sub-processes in MINCO (developed for this research)




Knowledge Adapting




Majority of the mentioned KM

practices are yet to be addressed for knowledge

reusing purposes Knowledge Applying • Expert systems • DMS


In order to drill down these issues, the next level of analysis has been managed to investigate

knowledge reusing practices against the recognised challenges. According to the research

framework, knowledge reusing has strong collaboration with knowledge capturing and

transferring. In other words, knowledge reusing is the process in which captured and/or

transferred knowledge is utilised for future or similar projects (Tan, et al. 2007). According to

the research framework, knowledge reusing comprises three sub-processes: adapting, applying,

and integrating, as shown in Table 7-16.

According to the research findings, knowledge reusing is the least frequently mentioned KM

process in MINCO, with less than four percent of the total coded comments. This means

MINCO’s employees believe that there are few practices to support knowledge reusing. For

instance some applications such as Galileo for project history, and some experienced reports,

are used for knowledge reusing purposes, however, they are not enough to significantly support

knowledge reusing in MINCO’s PMO. The research analysis confirms that knowledge adapting

and applying are somehow employed at MINCO, however, knowledge integration is a

significant issue from a knowledge reusing point-of-view. This means that both knowledge

integration practices, i.e. data mining and knowledge map, are yet to be addressed in MINCO’s

PMO. In fact, MINCO’s PMO should focus on improving the recognised KM challenges to

improve the quality of project KM and, ultimately to achieve the better maturity level.

On the other hand, according the research framework, reusing project knowledge is

dependent on a reliable capturing and transferring system. This means that knowledge reusing

could not be improved without the existence of a robust KM system, especially transferring and

capturing. In other words, MINCO’s PMO should focus on addressing the existing challenges of

knowledge transferring and capturing. This is also is consistent with the research framework, as

it is advised to focus on improving knowledge transferring and capturing, prior to knowledge

reusing.

Knowledge capturing’s sub processes and practices in MINCO 7.5.3

As discussed, knowledge capturing is the most important KM process in MINCO, from

participants’ points-of-view. On the other hand, the research analysis revealed that after

knowledge transferring and reusing, knowledge capturing is the third frequently mentioned KM

process, in term of the recognised KM challenges in MINCO. In other words, participants


believe that knowledge capturing faces issues such as access to the required knowledge.

According to the research framework where knowledge capturing has been classified into four

sub-processes: Identification, Storing, Classification, and Selection, as shown in Table 7-17

(Lytras and Pouloudi 2003; Nissen, et al. 2000).

The research outcomes indicate that document management system (DMS), Database (DB),

formal and informal events, and management information system (MIS) are the most frequent

practices among other KM practices for knowledge capturing. This means that knowledge

storing is the most frequent mentioned KM sub-process in MINCO. In other words, participants

believe that the majority of the current KM practices have been developed to improve

knowledge capturing through storing sub-process. After knowledge storing, knowledge

classification is the second most frequent knowledge sub-process in MINCO. According to the

research findings, MINCO has strong systems and tools to store and classify the project

knowledge. In other words, the majority of the current KM practices facilitate the knowledge

storing and coalification part of knowledge capturing.

On the other hand, there is little evidence to appropriately support knowledge identification

and selection. This means that MINCO’s PMO is yet to improve the mentioned two sub

processes of knowledge capturing. For instance, limited practices were recognised to address the

KIS and FAQ, which both facilitate knowledge selection. In addition, knowledge detection tools

and expert locater are other KM practices which are yet to be addressed in MINCO’s PMO.

However, some practices for knowledge identification have been recognised in MINCO, such as

formal and informal interview and knowledge repositories, but they need to be improved to

appropriately address the knowledge capturing process.

Table 7-17 Knowledge capturing sub-processes in MINCO (developed for this research)

K. Capturing Sub Processes

Practices for Knowledge Capturing Comments


• Expert locator • Formal and

informal event

• Knowledge detection tools

• Knowledge repositories

This is the second most frequent mentioned sub

process

Knowledge Storing

• Data base • Formal and

informal event



process



• Frequently ask questions

• File management system

• Management information system(MIS)

• Intranet

This is the most frequent mentioned KM

sub process.

Knowledge Selection


• Data base • Frequently asked

questions (FAQ)

The current status is not satisfactory as is yet to be addressed


Knowledge creation’s sub processes and practices in MINCO 7.5.4

The research findings have recognised “Knowledge Creation” is the second most frequently

mentioned KM process in MINCO’s PMO. According to Nonaka and Takeuchi (1995)

knowledge is created through four sub-processes (SECI) : Socialisation, Externalisation;

Combination; and Internalisation. The SECI model was adopted in the research framework as

the main sub-processes of knowledge creation, as shown in Table 7-18.

According to the research findings, a community of practice is the most frequent of the KM

practices, and respectively research services and formal and informal events are the second and

the third KM practices for supporting the process of project knowledge creation in MINCO, as

depicted in Table 7 12. Similarly, the research analysis recognised the utilisation of other

practices, such as knowledge broker, deductive and inductive thinking, best practices and

documentation searching in MINCO’s PMO, by which knowledge creation is facilitated.

According to the research framework Socialisation is the process of creating tacit knowledge

through various types of communications (Nonaka and Teece 2001) in which it is facilitated

through some practices such as formal and informal events, and community of practice, as

shown in Table 7-18. Hoegl and Schulze (2005) explain that formal and informal events are

good tools for supporting Socialisation through which tacit knowledge is discussed and

sometimes transferred among individuals. The research findings revealed that all three KM

practices for Socialisation have been recognised in MINCO. This means MINCO’s employees

believe that “formal and informal events”, community of practices”, and workshops and

seminars are conducted during the project lifecycle. In other words, the knowledge creation

process is significantly supported through the Socialisation sub-process.

Table 7-18 Knowledge creation sub procesess in MINCO (developed for this research) K. Creation


Knowledge Creation Comments

Socialisation

• Formal and informal event


• Community of practices

Most of them have been put in place and utilised

Externalisation


• Deductive & Inductive thinking

• Experts system • Experience Report • Community of

practices

Most of them have been put in place and utilised but some of them such as expert system should be

improved

Combination

• Community of practices (COP)

• Best Practice Cases (BPC)

• Knowledge Broker • Data mining • Documentation

search

Except the community of practices, other are yet

to be addressed


• Experimentation This is the second most facilitated KM practices

Externalisation is the process to transform tacit to explicit knowledge (Nonaka and Teece

2001). According to the research framework there are a number of practices that could be used

to support externalisation, as depicted in Table 7-18. The research findings showed that some of


the mentioned practices, such as community of practice, are significantly addressed in MINCO,

while there are number of KM practices, such as expert system and deductive and inductive

thinking, that are yet to be developed in MINCO. This means that transformation of tacit

knowledge to explicit knowledge is yet to be improved in MINCO’s PMO. In other words,

MINCO’s PMO should develop the externalisation process in order to achieve the next level of

maturity. In fact, externalisation is an important process to prevent knowledge leakiness in the

projects (Nonaka and Teece 2001).

Nonaka and Teece (2001) define the combination as the process of transforming explicit

knowledge to more complicated explicit knowledge. According to the research framework, the

process of combination is satisfied when there is a system in place for developing current

manuals, instructions, procedures, methodologies and as such (Alavi and Leidner 2001; Nonaka

and Teece 2001). According to the research findings, the combination process has been fairly

developed in MINCO as some of its associated KM processes, such as data mining and

documentation search, are yet to be developed in MINCO. This means that MINCO’s PMO

should focus on addressing the recognised gap in order to improve the quality of the KM.

According to Nonaka (1994) Internalisation is the process of knowledge creation by which

a new tacit knowledge is developed through using existing explicit knowledge. As can found in

Table 7-18, there are a number of practices such as research services, simulation, and

experimentation to facilitate knowledge creation through internalisation. The research findings

revealed that internalisation is the second most utilised KM process to support the knowledge

creation process. In other words, a number of practices such as simulation, alternative analysis

and market research are managed, especially at initiation and planning phases, in order to create

accurate knowledge for decision making purposes. This means that internalisation significantly

contributes to the process of knowledge creation developed in MINCO.


Tacit Knowledge

From

Socialisation (has been addressed in

MINCO)

Externalisation (is yet to be developed in

MINCO)

Explicit Knowledge

Internalisation (has been addressed in

MINCO)

Combination (is yet to be addressed in

MINCO)

Figure 7-15 The SECI in MINCO’s PMO (Nonaka and Teece 2001)

In a nutshell, knowledge creation has been significantly addressed in MINCO, but, there are

some issues that are yet to be addressed accordingly. According to Nonaka (2001) the SECI

model follows a spiral method in which all four sub-processes should be interconnected, as

illustrated in Figure 7-15. According to the research findings both Socialisation and

Internalisation have been appropriately addressed in MINCO so they significantly contribute to

the process of knowledge creation, while Externalisation and Combination are yet to be


developed in MINCO’s PMO. This means that MINCO’s PMO should address the missing KM

practices in order to improve the quality of KM, and consequently the level of PMO maturity.

CONCLUSION 7.6

This chapter aims to answer the first and second research questions (RQ1. How are KM

practices and processes employed in the PMOs, and RQ2. How do KM practices contribute to

improve maturity level of the PMO), and their associated sub-questions (what are the current

challenges of the PMO from KM perspective, What types of knowledge are required at each of

following project phases, What kinds of KM practices are utilised in each maturity level of

PMO, What is the importance of knowledge processes at each phase of project, How PMO

should contribute for managing the project knowledge). As it was explored, the selected case

study, MINCO, is an international mining company, which developed a PMO with the third

level of maturity. In order to answer the research questions in this case, the research framework

(Chapter 3) has been employed through following the research methodology (Chapter 4). In the

section, a summary of the research findings has been succinctly presented.

The research findings revealed that the following are the main challenges of MINCO from a

KM perspective: Inadequate practices to support knowledge transferring process, Issues with

current systems to fully support knowledge capturing process, unsatisfactory practices to

appropriately support knowledge reusing process, and Lack of training for current systems and

applications. These findings are useful indications for MINCO in order to improve the quality of

the project KM and, consequently to enter the next maturity level of PMO.

The research findings revealed the following order, from participants’ points-of-view, for the

required types of knowledge: 1) Project Management Knowledge, 2) Technical Knowledge, 3)

Costing Knowledge, 4) Knowledge about Procedures, 5) Knowledge of who knows what, 6)

Knowledge about Clients, 7) Legal and statutory Knowledge, and 8) Knowledge about

suppliers. This is a clear indication for MINCO, or PMOs with similar maturity levels, to

prioritise the importance of their required knowledge.

Furthermore, the importance of KM processes has been discussed through analysing both

interviews and survey, and consistently both revealed the following order: 1) Knowledge

Capturing 2) Knowledge Creation 3) Knowledge Transferring, and 4) Knowledge Reusing. This

means that knowledge capturing and creation are the most important KM practices, while

transferring and reusing are not as important as the other two. In addition, informal and formal

events are the most utilised KM practices that contribute to all four KM processes. These are

valuable findings for the PMO to improve this practice, as it plays a significant role for project



In the last section, i.e. 7.5, the relationship between KM challenges and KM processes, has

been investigated. It was found that knowledge reusing and transferring are the most

challenging KM processes. These findings shall contribute to prioritise the development of KM

processes, sub-processes and practices. In other words, the research findings address appropriate

KM practices and processes with regards to their associated challenges and issues. These

findings also address appropriate practices to improve the quality of project knowledge

management, and consequently the maturity level of PMO.

In the end, the following have been summarised in MINCO’s PMO, with a third level of

maturity:

• At the third level of maturity the project KM is supported by senior managers and there

are significant numbers of KM practices in place to facilitate the project KM,

• There is a unit in the PMO to address and develop the project KM,

• Knowledge capturing and creation are the most important KM processes and the

majority of current PM practices support them,

• At the third level of maturity, there is a comprehensive PM methodology in place, so it

is recommended to improve the current PM standards through integrating with KM

practices.

220 Chapter 8 | DISCUSSION and RESULT

Chapter 8

DISCUSSION and RESULT

INTRODUCTION 8.1

In the previous chapters, three cases were individually discussed to investigate from a KM

point-of-view. The research framework was employed to outline KM practices for each

organisation. The main objective of the analysis in the last three chapters was to get insightful

information about each case as a standalone entity, in order to use the collected data for

conducting the cross-case analysis phase. In the previous chapters, the process of “within-case

analysis” was managed to answer the first two research questions, while in this chapter the

process “cross-case analysis” will be conducted to compare the collected data from each in

order to answer the third research question, as shown in Table 8-1.

Table 8-1 The research questions (developed for this study)

1. To what extent are KM processes and practices employed in the PMOs? 1.1. What are the current challenges of the PMO from KM perspective?



2. How do KM practices contribute to maturity level of the PMO? 2.1. What is the importance of knowledge processes at each phase of project? 2.2. How PMO can contribute for managing the project Knowledge?

3. How can knowledge be integrated in the PM maturity model? 3.3. How is knowledge created, captured, transferred and reused in PMOs?

3.4. How can KM practices be employed in each maturity level of PMO?

In this chapter, first the analytical procedures will be discussed followed by an overview of

the three cases. Second, the research questions will be answered through comparing the

collected data from each case. Third, the framework will be scrutinised through discussing the

theoretical assumptions and the collected data from cross case analysis. Finally, the research

findings will be summarised accordingly.

THE ANALYSIS PROCEDURE 8.2

The aim of cross case analysis is to look for differences and similarities of various cases in

order to explain the reasons behind them (Yin 2009). According to the current literature, the

pattern matching technique is a useful and efficient way to undertake cross case analysis

(Creswell 2009; Eisenhardt and Graebner 2007; Yin 2009). Also, Grounded theory is reliable

Chapter 8 | DISCUSSION and RESULT 221

method to make plausible conclusions based on findings of pattern matching and other cross-

case analytical techniques (Corbin and Strauss 2008).

A range of Nvivo techniques such as matrix queries, relationship nodes, figures, and

diagrams have been employed to follow both pattern matching and Grounded theory techniques

to explain the phenomena. This means that the research framework that has been employed for

this investigation by the research findings has been compared to the research framework for

following pattern matching processes. In the case of inconsistency of the collected data, the

Grounded theory has been used to make a plausible explanation for the recognised phenomena.

These investigations and activities have been managed to explore the role of knowledge

management at various maturity levels of the PMO in order to make a number of plausible

propositions. The proposed theories will be discussed in the next section in order to compare

research findings with the current literature.

AN OVERVIEW OF CASE STUDIES 8.3

As stated in Chapter 4, the following criteria were employed to select suitable cases for this

research : 1) the organisation should have an office, centre or unit for managing their projects

which could be called a PMO, or similar name, 2) The organisation should have a project

management methodology in place for managing projects, which could be very abstract or

comprehensive, 3) The PMO maturity model for improving the quality of PMO functionality

should be adopted or followed, (If there is none, assessment will be implemented), and 4) PM

unit or office is supported by top managers. As discussed, the three following cases were

selected and investigated in the last three chapters:

• SCIENCO is a research organisation which has a PMO with first level of maturity,

• GOVCO is a governmental organisation which has a PMO with second level of

maturity, and

• MINCO is a mining company which has a PMO with third level of maturity.

As depicted in Table 8-2 and Table 8-3, three cases have been compared through considering

the following criteria: 1) Nature of business, 2) Types of organisational chart, 3) Interviewees

and their position, 4) Functionality of their PMO, 5) PMO’s maturity level, 6) their current PM

systems, 7) their PM methodology, and 8) their challenges from a KM point of view. Both

tables present a snapshot of three cases to understand their general characteristics from a project

management point-of-view. As discussed earlier, the selected cases have various natures of

business which contribute to provide unbiased information for this research (Creswell 2009;

Gray 2009; Yin 2009).

The research findings revealed that each of the three cases have their own characteristics

from both KM and PM perspectives, by which they manage their project knowledge. For


instance in SCIENCO, knowledge management is part of their activities as it is a research

organisation, however, some of the KM practices for managing project knowledge, especially

for reusing and transferring, are yet to be developed. On the other hand in GOVCO, awareness

of project knowledge management has been raised among project managers and senior staffs in

which they are developing useful systems to improve the quality of project through managing

the project knowledge. In addition, in the MINCO project, knowledge management is in the

priority in which there is an assigned employee in the PMO, i.e. project knowledge manager, to

develop and maintain the current systems for improving quality of project knowledge

management. These details will be discussed further in the next sections.

ORGANISATIONAL STRUCTURE 8.4

According to the research findings, each of the three case studies has adopted a matrix

organisation structure by which project staff could be managed by both project manager and

their functional manager (Project Management Institute 2013). In the weak matrix structure, the

functional manager’s authorities overrule the project manager, which means that the project

could be impacted by functional managers. The collected data from SCIENCO revealed that

the current structure is similar to a weak matrix, as functional managers have more power. This

means that the project could face challenges from a resource management point of view as the

project manager or coordinator has inadequate authority (Project Management Institute 2013).

The GOVCO has a balanced matrix structure in which responsibilities of resources are

equally shared between project manager and functional manager (Project Management Institute

2013). The research findings confirm this assumption in which some projects, functional

managers are assigned as project managers, as they get appropriate PM trainings. In addition, a

developed roles and responsibility document has defined the role of resources during project life

cycle. This means that in the GOVCO, with second level of maturity and a balanced matrix

structure, the issue of resource management among functional managers and project managers

has been addressed.

In a strong matrix structure, the project manager has adequate authorities for assigning

project staff in different projects, which means that one of the functional manager’s

responsibilities is to provide resources for project managers (Project Management Institute

2013). According to the research findings in MINCO, project managers have access to their

required resources as there are numbers of functions to assist them with preparing project

resources. This means that in MINCO with a third level of maturity and strong matrix structure,

the project resource management has appropriately been addressed in which few issues have

been recognised in this regard. In addition, the position of project knowledge manager has been

found in the MINCO PMO structure.


According to the PMBOK (2013) there is a relationship between project management

authority and type of organisational chart, in which the stronger the matrix structure, the more

the project manager’s authority. The research findings revealed in the weak matrix structure, i.e.

SCIENCO with the first level of maturity, the authority of project managers was low, while in a

strong level of maturity, i.e. MINCO with third level of maturity, project managers have

adequate power to control the project resources. This means that in PMOs with a better maturity

level it should be expected there are fewer challenges from a resource assignment point of view.

These outcomes have led researchers to develop another research proposition as following:

There is correlation between project management maturity level, project managers’ authorities

as well as organisational types, as shown at Figure 8-1.

Figure 8-1 PMO level of maturity and project managers authorities (developed for this research)

Level of maturity • From first to fifth level of matuirty

Organisational chart

• Weak Matrix • Balance Matirx • Strong Matrix

project manager's Authrity

• Weak • Balance • Strong


Table 8-2 A snapshot of three case studies (developed for this research)

Case study SCIENCO GOVCO MINCO

Nature of business Research Organisation State-Government Organisation Resource and Mining Enterprise

Type of organisational

chart Weak matrix Balance matrix Strong matrix

Numbers of Interviewees and

their position

Seven interviewees included one senior

manager, one program manager, two project

managers, one project staff, PMO staff, and

PMO coordinator

Seven interviewees included one senior manager,

one program manager, two project managers, one

project staff, PMO coordinator, and PMO manager

Six interviewees included one senior manager, one

program manager, two project managers, one project

planner, and PMO knowledge manager

Functionality of PMO

PMO has been developed in the last two years

to support organisational projects. PMO unit is

under the middle management level, with an

appointed PMO coordinator. PMO is

responsible to develop PM practices, however,

it has less authority to direct organisational

projects as well as project resources assignment

PMO has been established 4-5 years ago to be a

work as the centre of excellence PMO to provide

adequate services to projects to increase the quality

of project management. This means that PMO does

not directly manage projects. This PMO has a

manager who reports directly to senior manager. As

a centre of excellence, PMO controls quality of PM

as well.

PMO was established more six years ago and it has

been developed since then. The current PMO works

under senior managers and CEO of company with

numbers of staffs and managers. Also there is a KM

manager in place to oversee project knowledge

management. PMO has numbers of authorities on

behalf of company’s CEO and it could intervene to

change direction of project

Current systems that contribute to

project management

• SAP • Enterprise Opportunity Pipeline • Wiki • Off System Tools • Common Costing Framework

• SAP, • PMMate • Intranet • Risk Management system • AConnect • PM software such as MS project

• SAP • Hummingbird • Galileo • Intranet • Global Network • PM software such as MS project and

Primavera


Table 8-3 A snapshot of three case stuides (continued )

Case study SCIENCO GOVCO MINCO

Level of PMO maturity and its characteristics

SCIENCO’s PMO maturity level is one which means:

• Benefits of project management yet to be

recognised, • No unique PM framework in place, • lack of PM tools and techniques, • Lip Services to project managers so they

have to manage project with different methods,

• PMs’ self-interest comes before organisational best Interest, and

• lack of investment for PM trainings

GOVCO’s PMO maturity level is two which means:

• Benefit of PM has been recognised by senior managers,

• There are some common processes for supporting PM,

• There are some PM guidelines in place, but a unique PM standard are yet to be developed,

• Importance of project cost, scope and quality have been recognised , and

• Training for project management has become an important need.

MINCO’s PMO maturity level is three which means :

• There is a unique - integrated PM methodology in place to demonstrate successful execution,

• Organisation has totally committed to the concept of project management,

• There is a corporate-wide culture to support informal project management and multiple-boss reporting,

• There is a developed sense of shared responsibility and accountability for the principles of project management

Current PM methodology

There is no unique PM methodology so

project managers are free to choose their own

method as they are not obligated to any

methods

There is a customised PM methodology in place but

it is not comprehensive enough to be forced ,

however, the process of developing unique

methodology is being managed

There is a unique and comprehensive PM

methodology which has been developed by PMO and

it should be followed during the management of all

organisational projects and PMO is responsible to

oversee all processes.

Challenges of PMO from KM methodology

1) Difficulties of searching and detecting required knowledge


3) Lack of KM practices and processes during project life cycle

4) Lack of appropriate systems to support project KM


1) Lack of integration among current processes and systems


3) Lack of KM practices KM processes during project life cycle


1) Inadequate practices to support knowledge transferring process

2) Issues with current systems to fully support knowledge capturing process

3) Unsatisfactory practices to appropriately support knowledge reusing process, and

4) Lack of training for current systems and applications




PROJECT MANAGEMENT MATURITY LEVEL IN THREE CASE STUDIES 8.5

As depicted in Table 8-2, numbers of interviewees have been mentioned; for both SCIENCO

and GOVCO, 7 interviews were conducted, while six interviews were managed for MINCO.

The main criteria to finish conducting interviews was reaching “the redundancy of information”,

when the researcher was realising that the same information was being provided, then the

interview process was terminated. For both SCIENCO and GOVCO redundancy was observed

after 7 interviews, while in MINCO after 6 interviews the researcher realised that no new

information was added. This means that when interviewees started to repeat the similar

explanations, researcher preferred to stop interviews to prevent any redundancy issues in data

collection.

From the PMO maturity and functionality points of view, all three cases have different

characteristics. As shown at Figure 8-2, from a project lifecycle point-of-view, in general

MINCO has the most mature PMO, while SCIENCO’s PMO has the lowest maturity level. This

means that PM practices in SCIENCO have not been appropriately developed to support project

lifecycle, in comparison to MINCO and GOVCO. In addition, MINCO’s PMO has the best

maturity level, from project lifecycle point-of-view, among all three cases, which indicates that

the current PM processes in MINCO significantly impact on quality of projects.

Figure 8-2 Maturity of PMOs from project lifecycle perspective (developed for this study)

From a project knowledge area perspective, the research findings revealed similar outcomes

in which the maturity of MINCO is the best among all three cases, while SCIENCO has the

lowest maturity level. According to PMI (2008b), nine areas of project knowledge should be

assessed to examine the level of maturity in the PMO. The research findings indicated that the

0.64 2.14

1.71

1.21

2.50

2.79

2.00

2.29

2.07

3.93

3.29

2.79 0.0

1.0

2.0

3.0

4.0

5.0Initiation

Planning

Execution andmonitoring

Closing

SCIENCO GOVCO MINCO


current PM practices in MINCO have been appropriately developed, in comparison to

SCIENCO and GOVCO. In other words, the existing PM practices in MINCO support all nine

knowledge areas, as shown in Figure 8-3. For instance, risk management is the most developed

PM practice in MINCO, while the current PM practices for procurement management are not as

developed as other knowledge areas. In addition, as it could be seen in Table 8-2, MINCO’s

PMO has developed a comprehensive project management methodology, while GOVCO is still

in the stage of uniting the existing PM methodologies, and SCIENCO’s PMO faces significant

challenges in this regard.

Figure 8-3 Maturity of PMOs from knowledge area perspective (developed for this research)

In general, the PMO maturity level in three cases indicates their status of project

management development. The research findings confirmed that from both the project lifecycle

and knowledge area, MINCO has the higher maturity level, i.e. three, GOVCO’s PMO has the

second level of maturity and SCIENCO has the lowest maturity level, i.e. one. According to the

current PM maturity models the higher level of maturity is a significant indication of the

advanced PM practices by which projects are supported through robust and reliable systems

(Kerzner 2005; Project Management Institute 2008b). In other words, MINCO’s projects

receive better support in comparison to GOVCO and SCIENCO’s projects. However, it should

be examined whether the PMO maturity level impacts on project knowledge management or

not. This means that if the research findings endorse the relation between PMO level of

maturity and project KM, then it could be claimed as one of the significant contributions of this

research. This hypothesis will be examined at the end of this chapter.

0.6 2.6

1.6

1.4

0.9

2.4

1.0

1.5

1.3

1.9 2.6

2.1

1.9

2.8

2.8

2.0

2.3

2.4

3.0 3.2

3.0

3.1

2.9

4.2

3.3

2.8

3.1

0.0

1.0

2.0

3.0

4.0

5.0Project Scope

Project Cost

Project Time

HRmanagement


ProjectCommunicatio

n

ProjectProcurement

ProjectIntegration

SCIENCO GOVCO MINCO


KNOWLEDGE MANAGEMENT PRACTICES IN VARIOUS LEVELS OF PMO 8.6

The first research question (RQ 1.How are KM practices and processes employed in the

PMOs) comprises three sub questions as followings: 1) what are the current challenges of the PMO

from a KM perspective, 2) what types of knowledge are required at each of following project phases, and

3) what kinds of KM practices are utilised in each maturity level of PMO). In this section each

question will be answered through integrating and analysing findings from the previous

chapters. At the end of this section the first question will be answered, as well as the first

research objective.

The Challenges of PMO from knowledge management perspective 8.6.1

As discussed in the previous chapters, numbers of challenges were recognised in all cases

from a KM point-of-view, which should be addressed by PMOs. As depicted in Table 8-3, in

total, the 10 following KM challenges have been developed through analysing more than one

hundred and sixty comments by using open and axial code technique: 1) Lack of appropriate

systems to support project KM, 2) Difficulties of searching and detecting required knowledge,

3) Issue of appropriate access to the existing systems, 4) Issue of locating and accessing right

information and/or right expert, 5) Lack of KM practices and processes during project life cycle,

6) Lack of integration among current processes and systems, 7) Issues with current systems to

fully support knowledge capturing process, 8) Inadequate practices to support knowledge

transferring process, 9) Unsatisfactory practices to appropriately support the knowledge reusing

process, and 10) Lack of training for current systems and applications.

1) Lack of appropriate systems to support projectKM

2) Difficulties of searching and detecting requiredknowledge

3) Issue of appropriate access to the existingsystems

4) Issue of locating and accessing right informationand/or right expert

5) Lack of KM practices and processes duringproject life cycle

6) Lack of integration among current processes andsystems

7) Issues with current systems to fully supportknowledge capturing process

8) Inadequate practices to support knowledgetransferring process

9) Unsatisfactory practices to appropriatelysupport knowledge reusing process

10) Lack of trainings for current systems andapplications


Figure 8-4 Challenges of KM at different maturity levels (developed for this study)

In the next step, these challenges were examined in the Nvivo through employing queries

and relation functions. At this phase of analysis, some other factors such as level of maturity

and the current systems and procedures were taken into consideration, by which numbers of

valuable outcomes have been obtained, as shown at Figure 8-4. According to the research

findings, some of the current challenges are common among these cases which confirm the

same issues from a KM point-of-view, for instance, the issue of locating the right information

and lack of KM practices. In addition, some of the KM challenges in the PMO with a low level

of maturity have been addressed in the next or upper level of maturity. For instance, in

SCIENCO’s PMO with the first level of maturity the first two challenges (Lack of appropriate

systems to support project KM; and Difficulties of searching and detecting required knowledge)

were recognised, while these issues have been addressed in both GOVCO and MINCO. In a

similar manner, while both SCIENCO and GOVCO face issues number 3, 4, 5 ( Issue of

appropriate access to the existing systems; Issue of locating and accessing right information

and/or right expert; and Lack of KM practices and KM processes during project life cycle),

these challenges have been resolved in MINCO.

Furthermore, the research analysis revealed that both SCIENCO and GOVCO have faced

three common challenges, while SCIENCO and MINCO do not share any common challenge.

This means that the current practices in MINCO’s PMO have contributed to address those

issues that SCIENCO has still been challenged with, and similarly, the existing practices in

GOVCO have addressed the first and second challenges of SCIENCO. In addition, challenges 7

to 10 have been explored neither in SCIENCO nor in GOVCO, but they are main issues of

MINCO at a third level of maturity. This means that MINCO has gone to the level of maturity

in which it deals with new types of issues that are not the main concerns of other two cases.

In the next level of analysis, the types of challenges have been considered to shed more light

on the existing KM challenges in various levels of maturity. The first four mentioned challenges

are mostly associated with the current systems and procedure. This means that SCIENCO and

GOVCO, with low levels of maturity, are dealing with issues such as applications, tools, and

access to the current systems, while MINCO, with a higher maturity level, have addressed these

kinds of issues and currently it faces other types of challenges such as the collaboration of the

current systems and database. In addition, both SCIENCO and GOVCO’s employees have

generally mentioned their concerns about lack of practice for all KM process (challenges

number 4 and 5), while in MINCO, knowledge transferring and reusing have been especially

mentioned as their current issues. This is another finding to claim that PMOs with a higher level

of maturity deal with various types of KM challenges.


The required types of knowledge in Project Management Offices 8.6.2

According to the research framework, eight types of project knowledge are important during

the project lifecycle: project management knowledge, knowledge about procedures, technical

knowledge, knowledge about clients, costing knowledge, legal and statutory knowledge,

knowledge about suppliers, and knowledge of who knows what. In the previous chapters, it was

discovered that the importance of each type of knowledge varies from one phase to another

phase. In this chapter, the general ranking of knowledge types will be discussed to analyse the

similarities and differences of required knowledge types at various levels of maturity.

Figure 8-5 Importance of knowledge types in various maturity level (developed for this research)

As can be seen in Figure 8-5, project management knowledge is the most important type of

knowledge at MINCO and GOVCO, while is the third one in SCIENCO. With regards to the

maturity level of the three cases, SCIENCO has the lowest and MINCO has the highest.

According to the research framework, at the lowest level of PMO maturity, the importance of

project management knowledge has been raised and there is no PM methodology in place, while

in the next level of maturity a PM framework should be in place to address the knowledge of

project management. This means that in SCIENCO’s PMO the importance of PM knowledge

has not been appropriately realised due to its level of maturity, while knowledge of project

management is the most important type of knowledge in both MINCO and GOVCO, as they

have a PM method in place. This could be an indication of increasing the importance of project

management knowledge at a higher level of maturity. In addition, one of the PMO’s

responsibilities is to oversee the employment of PM methodology in the organisational project

SCIENCO (ML=1)GOVCO (ML=2)MINCO (ML=3)0

2468

ProjectManageme

ntKnowledge

Knowledgeabout

Procedures

TechnicalKnowledge

KnowledgeaboutClients

CostingKnowledge

Legal andstatutory

Knowledge

Knowledgeabout

suppliers

Knowledgeof who

knows what

SCIENCO (ML=1) 6 3 3 8 5 3 4 7

GOVCO (ML=2) 8 7 5 6 3 2 1 5

MINCO (ML=3) 8 5 7 3 6 2 1 4


to control how PM knowledge is applied in various projects, which increases the importance of

PM knowledge.

Knowledge about procedures is the next type of knowledge which could be used with

project knowledge management. As depicted at Figure 8-5, this type of knowledge is the second

most important one in GOVCO, while it is the fourth in MINCO and sixth in SCIENCO.

According to Kerzner (2009) the second level of maturity is called “common process”, in which

the PMO focuses on providing practical processes and procedures to improve the quality of

project management. The direct observation findings revealed that there are more than sixty

processes in the GOVCO which justifies the importance of the type of knowledge in this case.

In other words, the importance of procedure knowledge in the second level of maturity is

consistent with both the research framework and the current literature. However, in SCIENCO,

procedures are not important as the PMO has just been established and it has not gone to the

next level to raise the importance of knowledge about procedures. In addition, since MINCO

has passed the second level of maturity, knowledge about procedures is not as important as it

was before.

Technical knowledge is the second most important type of knowledge in MINCO, while it is

fourth in GOVCO and sixth in SCIENCO. The ranking of technical knowledge is somehow

similar in MINCO and GOVCO, but in SCIENCO, participants believe that this type of

knowledge is not as vital as other knowledge types such as costing or PM knowledge. This

means that SCIENCO’s employees have fewer concerns about technical knowledge as they

believe that it exists in the organisation. In other words, SCIENCO is a research organisation

with numbers of scientists and researchers which they could trust with their own technical

knowledge. Therefore, they prefer that the PMO assist them with provision of other types of

knowledge, as they have fewer challenges with technical knowledge.

Knowledge about client is the most important type of knowledge in SCIENCO, and the third

one in GOVCO, while it has been ranked as the sixth most important knowledge type in

MINCO. According to the PMBOK (2013) knowledge about client is the crucial element to

increase the rate of project success. This assumption has been confirmed in both SCIENCO and

GOVCO, but in MINCO, participants believe that there are other priorities ahead of knowledge

about client. In order to shed more light on this issue, types of PMO were considered, and it was

revealed that both SIENCO and GOVCO have numbers of clients from outside of organisations,

while the majority of MINCO’s projects are undertaken to improve and maintain organisational

business. In other words, external clients do not play a crucial role in MINCO’s projects, while

in GOVCO and SCIENCO, clients are the main resource of organisational income.

Costing knowledge is the third and fourth important type of knowledge in MINCO and

SCIENCO, while it is the sixth in GOVCO. This is the first time that both MINCO and


SCIENCO have similar rankings of knowledge type in which both emphasise the importance of

costing knowledge in their projects, while GOVCO’s respondents do not have the same

thoughts. To analyse this difference, the types of PMOs have been taken into consideration in

which both SCIENCO and MINCO have a PMO which intervene in the projects, while

GOVCO’s PMO is the centre of excellence so it is not responsible for project implementation.

This means that in GOVCO, the PMO is not responsible during project implementation so cost

of project is not as important as other types of knowledge, while in MINCO and SCIENCO both

have many concerns about costs of project, as project managers are responsible for project

failure or success. In other words, types of PMO could impact on the ranking of project

knowledge types, as the research findings revealed.

Both legal knowledge and knowledge about suppliers have been similarly ranked as the

lowest important types of knowledge in all three cases. This means that participants in the

selected cases have consistent thoughts in ranking these two types of knowledge. In other

words, they believe that the provision of other types of knowledge is more important for them at

this stage. In addition, it could be inferred that in the higher level of maturity, i.e. four and five,

the PMO could focus on facilitating the access of legal knowledge as well as knowledge about

suppliers, as other types of knowledge have been addressed appropriately.

Knowledge about who knows what is the second most important type of knowledge in

SCIENCO, while it is fifth in MINCO and equal to fourth in GOVCO. This means that for

SCIENCO’s employees it is a crucial issue to find the right person with right information. As

discussed in the previous section, “Issue of locating and accessing right information and/or right

expert” is one of the challenges that SCIENCO and GOVOC are faced with. This is consistent

with their ranking of knowledge types as they believe that finding the right person is a

significant challenge, so the PMO should assist them with accessing “knowledge of who knows

what”. This means that SCIENCO’s PMO could address one of the recognised challenges

through facilitating the access to “knowledge of who knows what”. In addition, direct

observation revealed that both MINCO and GOVCO have addressed this issue through

providing a reliable system and procedures.

In summary, it could be concluded there are two important factors which significantly

impact on importance of knowledge types: 1) level of PMO maturity and the existing systems,

and 2) types of PMO, whether it is a centre of excellence or practical. This means that a higher

level of maturity is an indication of the current system efficiencies by which some of knowledge

types have been appropriately addressed. In addition, type of PMO is another influential factor

for ranking required knowledge type. For instance in the centre of excellence, the PMO does not

intervene in projects and it is not responsible for project success and failure, while the practical

PMO is the opposite. Therefore, some types of knowledge are very important in PMOs, such as


costing knowledge, while it is not important in the centre of excellence. This means that above

mentioned factor should be considered for ranking the importance of types of knowledge.

KM PROCESSES AND KM PRACTICES AT VARIOUS LEVELS OF MATURITY 8.7

This section aims to answer one of the sub-questions of the first research question, i.e. what

kinds of KM practices are utilized in each maturity level of PMO, through analysing and

comparing the research findings from the previous chapters. To do so, each KM process has

been considered alongside its KM practices, and then they have been investigated through

employing the research framework. In addition, Nvivo and MS Excel were used as the main

tools for this part of analysis. This analysis consists of discussing four KM processes in separate

categories to get insightful information about KM practices in various levels of maturity.

Figure 8-6 Numbers of the coded comments for KM processes (developed for this study)

In a nutshell, as shown in Figure 8-6, from a knowledge capturing perspective MINCO and

GOVCO have the highest number of codes, while SCIENCO has the lowest one. On the other

hand, the number of MINCO and SCIENCO’s KM practices for supporting knowledge creation

is more than GOVCO. In addition, the data analysis shows that GOVCO has the most comments

for knowledge transferring while SCIENCO has the lowest. Also, knowledge reusing has the

best situation in MINCO among other two cases. In general, MINCO has the highest number of

KM practices for supporting the KM process, while SCIENCO has the lowest. In other words,

the research findings revealed the PMO with higher maturity has better KM practices in place,

in comparison to the PMO with lower maturity level. This could be a significant finding for this

research which will be examined later. In the next sections each KM process will be discussed,

accordingly.

Knowledge Capturing 8.7.1

According to the research framework, knowledge capturing is facilitated through employing

numbers of KM practices, as depicted in Figure 8-7. As discussed in the previous chapters,

KnowledgeCapturing

KnowledgeCreation

KnowledgeTransferring

KnowledgeReusing

SCIENCO (ML=1) 75 56 39 6

GOVCO (ML=2) 132 31 83 6

MINCO (ML=3) 129 60 51 14

0

20

40

60

80

100

120

140


these practices were examined in each case individually. In this section each KM practice will

be discussed to explore the process of project knowledge creation in various levels of maturity.

The research analysis revealed that DMS in the most frequently mentioned KM practices for

facilitating knowledge capturing. Document management system (DMS) is a set of forms,

software and procedures to record and track organisational documents (Spalek 2012). It is a

recommended practice to capture project knowledge by which project information could be kept

appropriately (Project Management Institute 2013). The comparison among cases explored that

all participants believe that this practice is the most utilised KM practice for knowledge

capturing, as depicted in Figure 8-7. This means that all cases have realised the importance of

DMS for knowledge capturing, but they are in different situations in this regard. In MINCO’s

PMO, there is a robust and reliable DMS, which is supported through a number of software and

processes, while in SCIENCO it is yet to be improved, as the majority of the current DMS has

not been electronically facilitated.

Figure 8-7 Knowledge capturing in various levels of maturity (developed for this study)

Formal and informal events, such as meetings and any kinds of gathering, are the second

most frequently mentioned KM practice among other KM practices. According to the research

framework, these practices could be used for all KM processes and they are practical events to

support “communication and networking” (Julian 2008; Nissen, et al. 2000). In other words,

formal and informal events are one of the most influential practices for managing project

knowledge. The research analysis revealed that all three cases have realised the importance of

formal and informal events for project KM, however, the usage varies from one case to another.

For instance, in SCIENCO, formal and informal events are mostly employed for knowledge

creation, while in GOVCO and MINCO they are used for knowledge transferring and capturing

0

10

20

30

40

50

60

70

80

Data base


Expert locator

File Management System (FMS)



Intranet




Management Information System (MIS)


purposes. In other words, a PMO with higher maturity level has various usages of formal and

informal events, as they are facilitating project communications through formal and informal

networking.

The third frequently mentioned KM practice for knowledge capturing is both MISs and DBs.

Management information system (MIS) is the advanced level of database (DB) by which

decision making is facilitated (Koskinen 2010). This means that the DB includes raw

information, while the MIS comprises the processed information to be used for decision

making. The research findings revealed that numbers of DBs in SCIENCO are more than in

MINCO and GOVCO. On the other hand, both MINCO and GOVCO have developed numbers

of MISs in place, while SCIENCO is yet to develop appropriate MIS to manage project

knowledge. This confirms that the maturity of a PMO has significant impact on addressing

MISs through developing the existing DBs. In other words, a PMO with higher level of maturity

should have robust MISs for knowledge capturing process, while a PMO with a lower maturity

level should focus on improving MISs through developing the current DBs.

Intranet is the fourth most frequently mentioned KM practice in this study, which is used by

all three cases; however, its frequency is not as strong as the previously discussed practices. An

intranet is an internal web-based network to share information within an organisation (Aubry, et

al. 2010). According to the research framework, the intranet could be utilised for all KM

process except knowledge creation. The research findings revealed that this practice is used by

all three cases for various purposes, specifically knowledge capturing and transferring.

However, SCIENCO’s intranet is not as robust as the other two cases. In addition, MINCO has

developed a reliable intranet which could be accessed from all around the globe. In other words,

PMOs with better maturity levels have developed a more useable intranet to facilitate project


Some of the proposed KM practices such as expert locater have not been recognised in

PMOs with a lower maturity level. As discussed earlier, “finding the right person or

information” was recognised as a challenge in SCIENCO and GOVCO, while it has been

addressed in MINCO. Expert locator is a practice to resolve the mentioned issue in which it was

addressed in MINCO, which is yet to be addressed in SCIENCO. This shows the consistency

between the current challenges and PM practices. On the other hand, there are three practices

which have not been recognised in any case: knowledge detection tools; knowledge inquiry

system; and frequently asked question (FAQ). This finding indicates that the missing KM

practices will be addressed in the next levels of maturity. In other words, KM practices should

be developed based on maturity of the PMO and the readiness of the organisations.

In conclusion, DMS, formal and informal events, DBs, and MISs are the most frequently

mentioned KM practices for facilitating knowledge capturing, which are employed in all three


cases. According to the research findings, some KM practices either have not been recognised,

such as the expert locator, or are yet to be developed, such as the intranet, in SCIENCO with

first level of maturity. In addition, there are three practices that have not been addressed in any

of the cases. This means that maturity level of a PMO has a significant relationship with

utilising KM practices, in which the higher the level of maturity the stronger and reliable are

the KM practices.

Knowledge creation 8.7.2

The research framework advises eleven practices to support knowledge creation, as shown in

Figure 8-8. Knowledge creation has received the highest data frequency in SCIENCO, while it

is lowest in the GOVCO, as depicted in Figure 8-6. This is consistent with the nature of

SCIENCO’s business as a research organisation which manages projects to create knowledge.

On the other hand, GOVCO’s PMO, as the centre of excellence, does not interfere in projects

which means that it has less contribution for creating knowledge in projects. In other words,

SCIENCO and MINCO’s PMO significantly contributes to knowledge creation, while

GOVCO’s PMO is a centre of excellence so knowledge creation is not the first priority.

According to the research findings, formal and informal events are the most frequently

mentioned practices for knowledge creation in all three cases. According to Nonaka (2001) this

practice is used for knowledge creation through socialisation in which the owner of knowledge

communicates with others to create or transfer his/her knowledge. Formal and informal events

are the most frequently mentioned KM practices for knowledge creation in SCIENCO in which

participants believe that knowledge is mostly created through their social gathering or friendly

events. During direct observation, it was explored that SCIENCO’s PMO does not have a

significant role to facilitate these kinds of events, while in GOVCO and MINCO, the PMO

contributes to manage social events through facilitating forums or social gatherings. This means

that PMOs with higher maturity have realised the importance of formal and informal events to

manage project knowledge, which is consistent with the research framework.


Figure 8-8 Knowledge creation at various levels of maturity (developed for this study)

The community of practices is the second most frequently mentioned KM practice for

facilitating knowledge creation. Community of practice is a group of experts with various

specialties which gather together to form a team for different purposes (Yazici 2009).

According to the research outcomes, community of practice is the most frequent-mentioned KM

practice for knowledge capturing in MINCO and GOVCO, while it is the fifth one in

SCIENCO. This means that community of practice has not been appropriately developed in

SCIENCO, with a lower maturity level. As discussed earlier, expert locator is a challenge for

SCIENCO, therefore it could be an issue to find the right experts in order to manage the

community of practices for knowledge creation purposes. This means that a community of

practices should be improved at the lower levels of maturity, while it is considered as an

important practice for knowledge creation at higher maturity levels.

The research findings revealed that research service and deductive and inductive thinking are

the fourth and fifth most frequently mentioned KM practices in total, however, both are yet to

be developed in GOVCO. In others words, little evidence was found to support these two

practices in GOVCO. As discussed, GOVCO’s PMO has been deigned to operate as the centre

of excellence, which means that it doesn’t involve project implementation. This means that

GOVCO’s PMO does not significantly contribute to knowledge creation at execution phase,

while both MINCO and SCIENCO’s PMOs, as practical PMOs, are involved in all project

phases, so they contribute to the knowledge creation process. In other words, in practical PMOs,

knowledge creation is facilitated through a number of practices such as community of practice

and research services. For instance, research services play a crucial role at the initiation phase in

MINCO by which the project feasibility study is managed to decide whether the project is

viable or not. Also, deductive and inductive thinking methods, such as brain storming and think-

tank, are managed to discuss project risk management in order to create the knowledge of risk

05

10

15

20

25

30

Best Practice Cases


Data mining




Experience Report

Expert systems (ES)


Knowledge Broker

Research services


treatment plans. So, it could be concluded that a PMO with higher level of maturity should

facilitate both mentioned practices to contribute to the knowledge creation process.

According to Barclay and Osei-Bryson (2010), the PMO is a knowledge broker which could

facilitate creation of knowledge through facilitating the communication among knowledge

owners. The research findings explored that both MINCO and GOVCO’s PMOs have realised

their role as a knowledge broker in organisational projects, however, this is yet to be addressed

in SCIENCO’s PMO. In other words, a PMO with higher level of maturity has found their role

as an agent through which knowledge could be communicated among different groups of

project stockholders, while this role is yet to be realised.

There are a number of KM practices such as data mining and decision support systems

(DSS) that are yet to be addressed in the current case studies. In other words, little evidence was

found to support the mentioned practices in the selected cases. According to the current

literature, data mining and DSS are the advanced level of MIS and DBs which takes time for an

organisation to transform the current MIS to DSS (Koskinen 2010). This means that these

practices could be developed in the next level of maturity, as the current level is not capable

enough for such a development.

In summary, informal and formal events and community of practice are the most frequent-

mentioned KM practices in the selected cases for the purpose of knowledge creation. The

research findings revealed that type of PMO is an influential factor for facilitating knowledge

creation in which if a PMO is a centre of excellence, then it could not interfere in a project, and

consequently it will have less influence on facilitating the knowledge creation process. In

addition, the PMO maturity level impacts on selecting the type of KM practices in which the

higher the level of PMO, the more advanced the KM practices.

Knowledge Transferring 8.7.3

According to the research framework, eleven KM practices are employed to transfer project

knowledge, as depicted at Figure 8-9. The research findings explored that knowledge

transferring has obtained the highest data frequency in GOVCO, while it is lowest in

SCIENCO, as shown in Figure 8-6. In other words, despite the fact that GOVCO has the second

level of maturity, it has better knowledge transferring in comparison to MINCO and SCIENCO.

As discussed earlier, GOVOC’s PMO has the lowest rank in knowledge creation because of the

nature of PMO as the centre of excellence. So this means that GOVCO’s PMO has focused on

developing knowledge capturing and transferring, since it does not interfere in organisational

projects. It could be included that if the PMO has been designed to be a centre of excellence,

then the main focus of PMO should be on facilitating knowledge capturing and transferring

processes, at low or medium level of maturity.


Figure 8-9 Knowledge transferring at various levels of maturity (developed for this study)

The research outcome revealed that formal and informal events are the most frequently

mentioned KM practices to support knowledge transferring, in three cases. The research data

analysis explored that GOVCO’s PMO has the strongest system to support these kinds of events

through managing some methods such as lunch forums, while both MINCO and SCIENCO are

yet to be developed from this point-of-view. In other words, GOVCO’s PMO, as a centre of

excellence, has focused on developing more practices for knowledge transferring at this level of

maturity. This means that knowledge transferring is considered as the second most important

KM process in GOVCO, after knowledge capturing, while it is the third most important KM

process in both MINCO and SCIENCO.

As shown in Figure 8-9, communication channels are the second most frequently mentioned

KM practices to facilitate knowledge transferring in all three cases. Similar to formal and

informal event, GOVCO has the highest frequency to support communication channels. This

means that numbers of tools such as email, video conference and phone are mainly used at these

organisations for knowledge transferring purposes. In addition, participants in MINCO and

GOVCO believe that there are numbers of communication channels in place to facilitate

knowledge transferring, while in SCIENCO, communication channels are not as developed as

the other two cases. It could be concluded that communication channels should be gradually

improved, as one of basic and fundamental tools for knowledge transferring, from lower to

higher levels of maturity.

Training and mentoring are the third most frequent mentioned KM practices for knowledge

transferring. The research findings revealed that the importance of training for transferring

project knowledge that has been realised by all cases, depends on their maturity level. For

instance, in MINCO and GOVCO, training and mentoring procedures have been appropriately

0

5

10

15

20

25

30


Database

Discussion forums



Intranet


Knowledge list

Training& mentoring


Yellow page


developed, while in SCIENCO this KM practice is yet to be appropriately developed. Direct

observation that explored training and mentoring in MINCO is supported through some tools

such as induction and mentoring programs, while in SCIENCO participants believe the current

training system does not meet their expectation. In addition, training is still a challenge for all

cases, specifically MINCO (see section 8.6.1). In other words, training and mentoring still need

to be developed in higher levels of maturity, i.e. fourth and fifth.

As Figure 8-9 represents, data bases and intranet are the fourth most frequently mentioned

practices to facilitate knowledge transferring. As discussed earlier, according to the research

framework, DBs and intranet could be used for supporting both knowledge capturing and

transferring. The research findings revealed that MINCO and GOVCO have developed their

DBs, while in SCIENCO’s PMO the current DBs are yet to be appropriately developed.

According to the study, outcomes from the current DBs in all cases have not been appropriately

utilised for knowledge transferring purposes, as all cases are still faced with the issue of system

integration. In other words, all three cases have different situations in this regard in which

MINCO’s DBs are fairly stronger than other cases but they have not been collaborated with

current systems, while GOVCO and SCIENCO both are in the stage of developing the current

DBs to satisfy business requirements.

According to the research findings, the other KM practices for knowledge transferring have

not been either developed or addressed in the selected cases. For instance, little evidence was

found to support knowledge list, yellow page, and knowledge directories which means these two

practices should be addressed in the next level of maturity. In addition, little evidence was

recognised to support discussion forums and video conference meeting which means they

should be developed to satisfy current expectations. This is another reason to advise that KM

practices should be developed with regards to PMO’s capability, and consequently PMO

maturity level.

In summary, formal and informal, training and mentoring, and communication channels are

the most frequently mentioned practices to facilitate the knowledge transferring processes. As

discussed earlier, formal and informal events could facilitate all KM processes, so it should be

one of the most important priorities for PMOs to improve the quality of project knowledge

management. The research findings confirmed all cases have realised the importance of formal

and informal events; also this is consistent with the findings of similar research in SCIENCO by

Wiewiora, et al. (2010). Training and mentoring are other KM practices which are used by all

three cases, however, they are yet to be developed in all cases, specifically in SCIENCO. In

general, six out of eleven practices for knowledge transferring are yet to be developed or

addressed in the selected cases. This means that knowledge transferring need to be improved in

the next level of maturity.


Knowledge Reusing 8.7.4

According to the research framework a number of practices could be used to manage the

project knowledge reusing process, as depicted at Figure 8-10. As can be found in Figure 8-10,

knowledge reusing has some common practices with other KM processes such as capturing and

creation. For instance, data mining could be used to support knowledge creation and reusing,

which means that knowledge reusing has relationships with other KM processes. According to

Owen, et al. (2004), knowledge reusing is dependent on knowledge transferring and capturing,

so this assumption has been adopted in the research framework. According to the research

findings, knowledge reusing has the minimum data frequency among other KM processes. As

Figure 8-10 depicts, a small number of knowledge reusing practices have been recognised in the

selected cases. Having said that, their frequency indicates that they are yet to be developed

accordingly. This is consistent with other research findings as it was revealed that knowledge

reusing has been mentioned as the main issue in three cases, especially in the MINCO

(section 8.6.1).

According to the research framework, a robust knowledge reusing process requires a reliable

knowledge transferring and capturing system. The research findings have explored that all

selected cases have been in the processes of developing other KM processes, therefore it could

be expected that knowledge reusing should be their next priority. Specifically in the MINCO’s

PMO it was realised that participants have directly mentioned their issues with knowledge

reusing as they believe that other KM processes have been appropriately developed.

Figure 8-10 Knowledge reusing at various levels of maturity (developed for this study)

In summary, knowledge reusing is the least frequently mentioned KM practices which is yet

to be developed in all three cases. In fact, some evidence was recognised in the selected cases

0

1

2

3

4

5

6

7

Data base

Data mining



Expert systems


Intranet


Knowledge map

Lesson learnt

Yellow page


for the purpose of supporting knowledge reusing, however, respondents believe that knowledge

reusing is not appropriately supported through current KM practices. According to the research

framework, knowledge capturing and transferring provide the required basics to facilitate

knowledge reusing process. This means that PMOs should focus on developing other KM

processes such as knowledge creation and knowledge capturing before initiating the knowledge

reusing process. Consequently, development of knowledge reusing should be considered at

fourth or higher maturity level.

PMO’S CONTRIBUTIONS TO KNOWLEDGE MANAGEMENT 8.8

In the last section the first research questions have been discussed. In this section the second

research question will be answered through discussing the importance of KM processes and

addressing the appropriate KM practices for three maturity levels. Similar to previous sections,

Nvivo and Ms Excel were used as the analysis tools alongside Grounded theory.

The importance of KM processes in various levels of PMO 8.8.1

The first part of the second research question aims to rank the importance of KM processes.

In the first level of analysis the rank of KM processes was managed, regardless of the various

project phases. According to the research findings knowledge capturing has been ranked as the

most important KM process in all three cases, while knowledge reusing has received the lowest

ranking order, as depicted in Figure 8-11. As discussed in the previous section, knowledge

capturing is the most frequently mentioned KM process and on the contrary knowledge reusing

is the least frequently mentioned process in all three cases. These two findings show similar

outcomes in three selected cases in which the ranking of KM processes are consistent with

research outcomes in terms of data frequency.

In addition, knowledge creation is the second most important KM process in SCIENCO and

MINCO, but it is the third important process in GOVCO. In a similar manner, knowledge

transferring is the third important process in SCIENCO and MINCO, while it is the second in

GOVCO. The research findings revealed similar ranking in both SCIENCO and MINCO; on the

contrary, ranking of knowledge creation and transferring in GOVCO is different from the two

other cases. In other words, the importance of knowledge creation and knowledge transferring

in SCIENCO and MINCO is similar, while they have different rankings in GOVCO, as shown

in Figure 8-11.


Figure 8-11 Importance of KM processes in project lifecycle: All cases (developed for this study)

As discussed, GOVCO’s PMO is a centre of excellence so it is not practically involved in

project execution phase, while the PMO is involved at the execution phase in both projects in

SCIENCO and MINCO. Therefore, according to the findings, knowledge creation is the second

most important KM process in practical PMOs, while knowledge transferring is considered as

the second most important KM process when the PMO operates as a centre of excellence. In

other words, in the centre of excellence, importance of knowledge capturing and reusing

remains the same, i.e. first and forth, while knowledge transferring and creation are the second

and third most important KM process.

In a consistent manner these findings are similar to the previous findings in terms of data

frequency. As discussed earlier, knowledge creation and transferring are the second and third

most frequently mentioned KM processes in SCIENCO and MINCO, while they are the

opposite in GOVCO. In other words, knowledge transferring has been ranked as the second

most frequently mentioned KM process in GOVCO, which is similar to its ranking from a

knowledge importance point-of-view. Therefore, the research findings revealed similar ranking

from both a data frequency point of view, and the importance of KM perspective.

As discussed in section 8.6.1, the types of PMO challenges vary from one case to another.

For instance in SCIENCO knowledge capturing is a major concern, while MINCO’s

participants have mentioned their issues with knowledge reusing and transferring. This means

that maturity of PMO has correlation with the recognised issues. In other words, a PMO with

higher maturity level has addressed some of the concerns which still exist in a PMO with lower

maturity level. This is consistent with the research framework, as it advises to improve the

quality of KM in a gradual and steady manner. Therefore, the mentioned ranking of the KM

process should be employed through considering both the PMO maturity level and type of KM

challenges.

Capturing

CreatingTransferringReusing

01234

SCIENCO(ML=1) GOVCO

(ML=2) MINCO(ML=3)

SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Capturing 4 4 4

Creating 3 2 3

Transferring 2 3 2

Reusing 1 1 1

Project Lifecycle


For instance, in SCIENCO’s PMO, with first level of maturity, knowledge capturing was

ranked as the most important and frequently mentioned KM process (see section 8.7.1

and 8.8.1). In addition, SCIENCO faces significant issues in regards to the current systems for

capturing project knowledge (see section 8.6.1). According to the research framework,

knowledge capturing should be developed in the first level of maturity. This means that

SCIENCO’s PMO should focus on improving the knowledge capturing practices as the first

priority, as knowledge capturing is in the first priority and the current challenges are mostly

related to lack of KM practices in this regard.

On the other hand, in MINCO’s PMO, with the third level of maturity, knowledge

transferring and reusing were ranked as the third and fourth most important and frequently

mentioned KM processes. The research findings revealed that MINCO faces some significant

issues for reusing and managing project knowledge (see section 8.6.1). This means that in

MINCO there is a reliable system in place to facilitate knowledge capturing and creation,

however, knowledge reusing and transferring should be addressed. According to the research

framework, all KM processes should be developed in the third and fourth level of maturity.

Therefore, MINCO’s PMO should focus on improving knowledge transferring and reusing

practices, in order to increase the level of maturity.

How PMO can contribute for managing the project knowledge 8.8.2

In this section the second research question will be completely answered through discussing

the PMO’s contributions to manage project knowledge. To do so, four KM processes and their

sub-processes will be investigated to explore project KM in various level of maturity. Data

frequency will be used as the main analysis input through using Nvivo and Ms Excel in order to

compare project KM in the three selected cases.

According to the research framework, knowledge capturing comprises four KM sub-

processes, as shown in Table 8-4. As discussed earlier, knowledge capturing is the most

frequent and important KM process in all three cases. In addition, it was explored that

knowledge capturing still faces some issues in the mentioned cases (see section 8.6.1). So on

one hand knowledge capturing is the most developed KM process, and on the other hand it

needs to be improved from some other aspects. In order to explore the priority for development

of knowledge capturing, the sub-processes of knowledge capturing were considered, as depicted

in Table 8-4. As it can be found from the following table, data frequency and maturity level are

consistent and the PMO with higher maturity level has better data frequency to support KM

practices.

Table 8-4 Knowledge capturing's sub-processes in various PMOs (developed for this study)

Sub-process Associated Practices SCIENCO (ML=1)

GOVCO (ML=2)

MINCO (ML=3)




event

• Knowledge detection tools

• Knowledge repositories

16 32 19

Knowledge Storing


event


56 100 118



• Frequently ask questions

• Intranet

• File management system

• Management information system(MIS)

49 95 105

Knowledge Selection


• Data base

• Frequently ask questions (FAQ) 18 6 17

The data frequency analysis revealed that both knowledge storing and knowledge

classification have been relatively developed in the three selected case studies, while knowledge

selection and identification are yet to be improved, as shown in Table 8-4 and Figure 8-12. This

means than more than 80% of the current KM practices facilitate knowledge storing and

classification. In other words, the majority of the PMOs’ activities have been focused on

addressing knowledge storing and classification. Therefore, it is plausible to face some

challenges in regards to the other two sub-processes, i.e. knowledge selection and identification.

For instance, participants have mentioned their concerns about finding the right expert, in both

SCIENCO and GOVOC. This is a strong indication for the PMOs in order to focus on

addressing the undeveloped KM processes, identification and selection, in order to address the

current issues from a KM point-of-view.

In addition, data analysis revealed that knowledge storing has higher frequency in the three

cases, in comparison to knowledge classification. This means participants believe that

knowledge storing practices, such as DBS and MISs, are important as they are employed to

support other KM capturing practices such as Internet and FAQ. Similarly, the research analysis

revealed that knowledge identification has the higher frequency in comparison to knowledge

selection. So, it could be concluded that development of knowledge identification should be

prioritised before developing the knowledge selection.


Figure 8-12 Knowledge caprtuing's sub-processes (developed for this study)

According to the research findings it could be recommended that in order to develop

knowledge capturing in a PMO with first level of maturity, the development of knowledge

storing should be the first priority. At the same time, basic practices shall be addressed to

improve the knowledge classification process. In the second level of maturity, both knowledge

classification and storing should be constantly improved, but the development of knowledge

identification should be the first priority. At the same time, some basic practices to address the

knowledge selection should be considered. In the third level of maturity, knowledge

classification, storing and identification should be continuously improved, however, knowledge

selection should be significantly developed to address all four sub-processes of knowledge

capturing. These recommendations have been graphically represented in the following figure

and they will be used as the research propositions to develop KM processes in the PMOs.


Knowledge Storing

Knowledge ClassificationKnowledge Selection

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

SCIENCO(ML=1) GOVCO

(ML=2) MINCO(ML=3)

SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Knowledge Identification 11.51% 13.7% 7.3%

Knowledge Storing 40.29% 42.9% 45.6%

Knowledge Classification 35.25% 40.8% 40.5%

Knowledge Selection 12.95% 2.6% 6.6%


Figure 8-13 K. capturing’s sub processes in various level of maturity (developed for this study)


As discussed, knowledge creation is the second most important KM process in SCIENCO

and MINCO, but is the third in the GOVCO. According to the research framework, knowledge

creation has four sub-processes, as depicted in Table 8-5. These processes were investigated in

the selected cases and it was found that Socialisation and Externalisation are the most

frequently mentioned processes; in contrary the data frequency for Combination and

Internalisation is not as strong as for the other two processes. This means that from participants’

points-of-view the current KM practices mostly support Socialisation and Externalisation, while

Combination and Internalisation are yet to be developed.

Table 8-5 Knowledge creation’s sub-processes in various PMOs (developed for this study)


GOVCO (ML=2)

MINCO (ML=3)



• Community of practices

32 16 32

Externalisation

• Workshops & seminar • Deductive & Inductive

thinking

• Experts system • Experience Report • Community of

practices 21 13 28

Combination

• Community of practices (COP)

• Best Practice Cases (BPC)

• Knowledge Broker • Data mining • Documentation

search

5 14 32

Internalisation • Research services • Simulation • Experimentation 12 0 13

On the other hand, it was revealed that there are numbers of issues in regards to knowledge

creation in all cases, especially in MINCO and SCIENCO. For instance, SCIENCO’s

participants believe that PMO does not strongly contribute to project management and it needs

to be developed in this regard. In addition, some practices such as Expert systems and Data

mining have not been recognised in the selected cases. This means that knowledge creation

needs to be improved in project environments through addressing appropriate practices. To do

so, knowledge creation’s sub-processes have been analysed to propose suitable KM practices

for each level of maturity.

According to the research framework, knowledge Socialisation is the most frequently

mentioned practice to facilitate knowledge creation, as shown in Table 8-5 and Figure 8-14. The

data analysis indicated that some practices such as formal and informal events, and community

of practice have been developed in the three cases, but knowledge creation through seminars

and workshops needs to be improved in SCIENCO. Therefore, SCIENCO should focus on

addressing the mentioned practices for the next level of maturity. So it could be proposed that in

order to facilitate knowledge creation in PMO at the first level of maturity, Socialisation should

be the first priority. In addition, formal and informal events and community of practices shall be


addressed in the first level of maturity, while seminars and workshops should be developed in

the second level of maturity.

Figure 8-14 Knowledge creation's sub-processes in three case studies( developed for this study)

The research findings revealed that Externalisation is the second most frequently mentioned

practice to support knowledge creation in the three cases, as presented in Table 8-5 and

Figure 8-14. Further analysis explored that “community of practice” and “deductive and

inductive thinking” have been relatively developed in the selected cases, while seminars and

workshops need to be improved in SCIENCO, with first level of maturity. In addition, both

expert system and experience report have not been recognised in the PMOs. This means

participants believe that the mentioned practices have not been addressed in the selected case

studies, so they could be addressed in the next levels of maturity. So it could be proposed that

Externalisation should be developed from the first level of maturity in which “community of

practice” and “deductive and inductive thinking” should be addressed at this level. In a

consistent manner, “workshops and seminars” should be addressed at the second level of

maturity, and then Expert systems and experienced report should be initiated at third and/or

fourth level of maturity, as depicted at Figure 8-15.

According to the research findings Combination is the third most frequently mentioned sub-

process to support knowledge creation in the selected cases in which SCIENCO has the lowest

and MINCO has the highest frequency in this regard, as shown in Table 8-5 and Figure 8-14.

Further investigation explored that only community of practice has been recognised in all three

cases. In addition, knowledge broker, another KM practice, was observed in MINCO and

GOVCO. Also, little evidence was found to support “documentation search” in MINCO,

Socialisation

Externalisation

Combination

Internalisation

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

SCIENCO(ML=1) GOVCO

(ML=2) MINCO (ML=3)

SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Socialisation 45.71% 37.2% 30.5%

Externalisation 30.00% 30.2% 26.7%

Combination 7.14% 32.6% 30.5%

Internalisation 17.14% 0.0% 12.4%


however, the other two KM practices, i.e. data mining and best practices, have not been

recognised during the data collection stage. This means that they should be addressed in the

third or fourth level of maturity. Therefore, it could be proposed that in the first level of

maturity community of practices should be developed to address the Combination, and then

PMO should operate as knowledge broker in the second level of maturity. In the third level of

maturity, a documentation search should be developed, alongside the best practices. In the

fourth level of maturity data mining should be addressed to complete the Combination process,

as shown at Figure 8-15.

The research findings revealed that Internalisation has the lowest frequency among all

knowledge creation sub-processes, in which only some evidence was found to support this

process in MINCO and SCIENCO. In addition, the number of recognised practices for

supporting Initialisation in MINCO is slightly more than SCIENCO, despite the fact that

SCIENCO is a research organisation. In other words, SCIENCO has developed a number of

research practices in place as a research company, regardless of its level of maturity. According

to current literature, basic PM practices should be developed in the first level of maturity

(Kerzner 2009; Kerzner 2013). This means that in SCIENCO, as a PMO with first level of

maturity, it was expected to explore a few practices to support KM, specifically the knowledge

creation process. However, the nature of SCIENCO’s business contributes to improve the KM

in the PMO. On the other hand, GOVCO’s PMO is a centre of excellence where knowledge

creation was ranked as the third most important KM process. In other words, it is plausible to

find some evidences for supporting internalisation process in GOVCO.

Therefore it could be proposed that Internalisation should be the lowest priority for

developing knowledge creation in the PMO. Since limited evidence was found in GOVCO, it

could be advised to initiate the process of internalisation from the second maturity level through

developing simulation practices. Then, using metaphors and experimentation should be

developed in the third level of maturity. In the fourth level of maturity all related research

activities should be developed to address the process of Internalisation, as presented at

Figure 8-15.


Figure 8-15 K. creation’s sub processes in various levels of maturity (developed for this study)


Knowledge transferring is the third most frequently mentioned KM process in MINCO and

SCIENCO, while it is the second in GOVCO, as shown in Table 8-6. As discussed, this

difference is because of the type of GOVCO’s PMO as a centre of excellence. According to the

research framework, knowledge transferring comprises two sub processes: knowledge

distributing and forwarding, and knowledge sharing. As it can be found in Table 8-1 and

Figure 8-16, the frequency of knowledge sharing is more than knowledge distribution not only

in each case individually, but also from a frequency aggregation point-of-view. This means that

from participants’ points-of-view the current KM practices mostly support the knowledge

sharing process, while knowledge distribution is yet to be developed in the three cases.

Table 8-6 Knowledge transferring’s sub-processes in various PMOs (developed for this study)


GOVCO (ML=2)

MINCO (ML=3)

Knowledge Distribution

and forwarding



• Knowledge list



18 34 14

Knowledge Sharing

• Discussion forums • Formal &informal

events

• Mentoring • Training 19 49 37

According to the research findings formal and informal event is the most frequently

mentioned practice to support knowledge sharing, and ultimately knowledge transferring.

Communication channels, such as email and phone, and training & mentoring are the second

and third most frequently mentioned practices in the selected case studies. The research findings

explored that the majority of the current practices have focused on addressing the mentioned

KM practices, while the other practices either have not been addressed or are yet be developed

appropriately. For instance, some evidence supports the usage of Intranet or data bases to

facilitate the process of project knowledge transferring, while little evidence was found to

facilitate a knowledge list or knowledge directories. This means that the current systems in

PMOs need to be significantly developed to address knowledge transferring in project

environments.

As mentioned, it was revealed that knowledge sharing is the most frequently mentioned KM

practice to facilitate knowledge sharing. According to the research framework knowledge

sharing comprises three practices, as shown in Table 8-6. The research findings explored that

formal and informal events, and training and mentoring have been addressed in the three

mentioned cases, but discussion forums are yet to be addressed in the SCIENCO. This means

that SCIENCO with a lower level of maturity has not developed this practice. Therefore it could

be proposed that in the first level of maturity both formal and informal events, and training and

mentoring should be developed. In a consistent manner, the discussion forums should be


developed in the second and third level of maturity in order to fulfil the knowledge sharing

practices, as depicted at Figure 8-17. All three practices should be improved in a higher level of

maturity.

Figure 8-16 Knowledge transferring's sub-processes case studies (developed for this study)

According to the research findings, knowledge distribution is the second most frequently

mentioned KM process to support knowledge transferring. As depicted in Table 8-6, there are

seven practices in the research framework to facilitate knowledge distribution. The research

findings explored that communication channels have the most data frequency among others

which has been addressed in three selected cases. This means that communication channels are

the basic practices for knowledge distribution in any PMOs, regardless of level of maturity.

Intranet and Data bases are the second and third frequently mentioned practices which have

been recognised in the three cases, but direct observation has revealed that MINCO and

GOVCO have developed better facilities in this regard. This means that the database and

intranet play stronger roles for knowledge transferring, in a PMO with higher maturity levels.

The research findings explored some evidence to support practices such as video conference and

yellow page in GOVCO and MINCO, however, they are yet to be developed to satisfy

participants’ expectations. In addition, little evidence was found to support practices such as

knowledge repository and knowledge list, which could be addressed in a higher maturity level.

Therefore, it could be proposed that communication channels and some basic features of DBS

should be addressed in the first level of maturity. In the second level of maturity, intranet and

video conference should be developed. In a consistent manner, yellow page and electronic

bulletin should be developed in the third level of maturity. Eventfully, a knowledge list and

directories should be developed in the fourth level of maturity to apply all knowledge related

practices, as shown in Figure 8-17.

Knowledge Distribution and forwarding

Knowledge sharing0.00%10.00%20.00%30.00%40.00%50.00%60.00%70.00%80.00%

SCIENCO(ML=1) GOVCO

(ML=2) MINCO(ML=3)

SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Knowledge Distribution and

forwarding 48.65% 41.0% 27.5%

Knowledge sharing 51.35% 59.0% 72.5%


Figure 8-17 K. transferring’s sub-processes in various levels of maturity (developed for this study)

Chapter 8 DISCUSSION and RESULT 255

According to the research findings knowledge reusing has the lowest frequency among all

four KM processes. According to the research framework, knowledge reusing has three sub-

processes, as depicted in Table 8-7. The research analysis showed that knowledge reusing has

not been appropriately developed in the selected case studies, specifically in SCIENCO and

GOVCO. In other words, the current KM practices need to be improved to address the processes

of knowledge reusing in project environments. According to the research outcomes a majority

of associated practices to support knowledge reusing have not been observed in SCIENCO and

GOVCO, however, MINCO’s PMO has developed some practices to facilitate the mentioned

KM process, as depicted in Table 8-7 and Figure 8-18.

Table 8-7 Knowledge reusing’s sub-processes in various PMOs (developed for this study)


GOVCO (ML=2)

MINCO (ML=3)

Knowledge Adapting

• Electronic notice board • Documents

management system (DMS)

• Formal or informal events

• Data base • Yellow page • Knowledge

detection tools • Intranet

5 5 12

Knowledge Applying • Expert systems

• DMS 1 1 2

Knowledge Integrating • Knowledge map • Data mining 0 0 0

The research findings revealed that knowledge adapting has the highest data frequency

among knowledge reusing sub-processes, as shown in Table 8-7. According to the research

framework there are seven practices to facilitate knowledge reusing, in which some are used for

knowledge capturing and transferring as well. The way of applying these common practices,

determines whether they are utilised for knowledge reusing or/and capturing. For instance,

databases (DBs) could be used for knowledge capturing and reusing, however, some

preparations are required to develop DBs for knowledge reusing purposes (Newell, et al. 2006).

The research findings revealed that current DBs are often used to support knowledge reusing

processes, despite the fact that DBs are the most frequent practices to address knowledge

reusing in the selected cases. In a similar manner, a document management system (DMS) is

used to support knowledge capturing and reusing. As discussed earlier, this practice has been

appropriately developed for knowledge capturing purposes, however, limited evidence supports

the utilisation of DMS for reusing project knowledge. This means that the common systems

should be developed in a way that they could support knowledge reusing. The collected data

from case studies revealed that DBs are often used in the three cases, especially in MINCO. In

addition, intranet, formal and informal events, and DMS are fairly utilised by MINCO and

GOVCO, but limited evidence was found to support them in SCIENCO for knowledge reusing.

Also, the electronic notice board is only used by MINCO, while the other cases have not


improved this practice for knowledge reusing purposes. The usage of other KM practices, for

supporting knowledge adapting, have not been observed during the course of data collection and

analysis. So it could be inferred that they should be addressed in the next level of maturity.

Therefore, it could be proposed that in the first level of maturity DBs should be developed to

address knowledge adapting, then to achieve the second level of maturity, DMS and intranet

should be addressed as presented in Figure 8-19. Electronic Notice board and yellow pages

should be developed in the third level of maturity, and eventually knowledge detection tools

should be addressed in the fourth level of maturity, in order to fulfil the process of knowledge

adapting. In the fifth level continuous improvement should be conducted to enhance the quality

of knowledge reusing.

Figure 8-18 Knowledge reusing’s sub-processes in three case studies (developed for this study)

According to the research findings, both knowledge applying and integrating are yet be

developed in the three cases, specifically SCIENCO and GOVCO, as shown in Table 8-7. This

means that there is limited evidence to address appropriate practices at each level of maturity.

Since the proposed practices for knowledge applying and integrating are mostly in common

with other KM processes, therefore the following could be proposed to address these two KM

sub-processes, as shown at Figure 8-19. Knowledge applying and integrating shall be developed

from the second level of maturity in which DMS should be addressed. In the third level of

maturity Expert system and data mining should be developed, and then a knowledge map should

be developed in the fourth level of maturity. Continuous improvement should be conducted in

the fifth level of maturity to enhance the quality of project knowledge reusing, and ultimately the

project KM.

Knowledge Adapting

Knowledge ApplyingKnowledge Integrating

0.00%20.00%40.00%60.00%80.00%

100.00%

SCIENCO(ML=1) GOVCO

(ML=2) MINCO(ML=3)

SCIENCO (ML=1) GOVCO (ML=2) MINCO (ML=3)Knowledge Adapting 83.33% 83.3% 85.7%

Knowledge Applying 16.67% 16.7% 14.3%

Knowledge Integrating 0.00% 0.0% 0.0%


Figure 8-19 K. reusing’s sub processes in various level of maturity (developed for this study)


In summary, the second research question, i.e. how do KM practices contribute to improve

maturity level of the PMO, has been discussed through analysing various KM practices in the

three levels of PMO maturity. In the last section, KM processes, their sub-processes, and

also associated KM practices were considered to investigate how they are utilised in various

levels of maturity. Based on the research findings, numbers of propositions have been

developed to address each KM process and sub-process in different maturity levels. These

propositions are part of this research’s contribution, by which a road map has been proposed

to develop KM processes in three levels of PMO maturity. In the next section, these findings

will be employed to answer the third research question in order to propose the

comprehensive framework to address KM processes in five levels of PMO maturity.

MODEL DEVELOPMENT 8.9

In this section, the final research framework will be developed through integrating the

research findings in the nominated case studies and the preliminary research framework.

Five maturity levels of PMO have been utilised to address appropriate KM processes and

practices. The research findings were used to develop the first three levels and for levels four

and five, numbers of suggestions and recommendations have been proposed. This part

answers the third research question and fulfils the research objectives.

Integration of KM practices at various level of maturity 8.9.1

The third research question (RQ.3 how can knowledge be integrated in the PM maturity

model?) comprises two research questions: how is knowledge created, captured, transferred

and Reused at PMO maturity levels; how should KM practices be employed in the each

maturity level of PMO. These questions will be discussed through integrating all the research

findings as well as the developed propositions. In addition, the developed research

framework (Chapter 3) will be considered and then refined, based on the research findings.

At the end of this section, numbers of propositions will be presented to address the project

knowledge management in various levels of maturity.

Knowledge management in the first level of maturity 8.9.1.1

According to the conceptual research framework (Chapter 3), in the first level of

maturity, the following criteria should be observed from a KM point of view: 1) PMO and

project team members are not appropriately aware of the importance of project knowledge

management, 2) There is little or no intention to formally manage project knowledge, 3)

There no specific KM technology or infrastructure in place, and 4) There is no formal

process to manage project knowledge. The research findings revealed that some of the

mentioned criteria do not conform to the current situation in SCIENCO’s PMO. For instance,

there are some formal processes in place to manage project knowledge. In addition, some


infrastructure and technologies, such as the SAP and Intranet, were observed in SCIENCO’s

PMO.

On the other hand, SCIENCO is a research organisation, so it is plausible to find some

KM practices in place, despite its PMO having the first level of maturity. This means that the

above mentioned criteria should be slightly refined to satisfy the current situation of

SCIENCO’s PMO. Therefore, the following could be proposed as the main criteria of PMO

with first level of maturity:

• The importance of project knowledge management has not been significantly

realised by PMO and senior managers,

• There are limited KM technology and infrastructure to support project KM, and

• There are limited formal processes to manage project knowledge.

As discussed in Chapter 3, the research framework assumes that in the first level of

maturity there are some practices in place to support knowledge capturing and creation. The

research findings revealed that not only knowledge capturing and creation are the first and

second most frequently mentioned KM processes, but also they were ranked as the first and

second most important KM processes in SCIENCO. This means that the research findings

and the research framework are consistent in this regard. In addition, numbers of practices

were found in SCIENCO, which are used for knowledge transferring. Also, a few practices

were observed in SCIENCO which in some ways support knowledge reusing. This means

that both knowledge transferring and reusing could be initiated in the first level of maturity.

In addition, KM sub-processes have been discussed in the previous section, i.e. 8.8.2.

Therefore, the following recommendations have been developed to refine the conceptual

research framework through reflecting the research findings, in order to address the KM

process in the first level of maturity.

• Knowledge capturing is the most important KM process, so it should be

supported through developing basic practices to address subsequent sub-

processes: knowledge storing and classification,

• Knowledge creation is the second most important KM process, so it should be

supported through developing basic practices to facilitate the following sub-

processes: socialisation, externalisation and combination.

• Knowledge transferring is the third most important KM process, so it should be

facilitated through developing basic practices to support the following sub-

processes: knowledge sharing and knowledge distribution, and


• Knowledge reusing is the least important KM process, so it could be addressed

through develop basic practices to address the following sub-process: knowledge

adapting.

The mentioned propositions have been graphically represented in Figure 8-20. As can

found in this figure, four KM processes have been addressed, with their sub-processes. The

stronger colour represents the importance of the process.

Figure 8-20 KM sub processes in the first level of maturity (developed for this study)

According to the research framework, the KM development plan should be prepared in

the first level of maturity. The research findings revealed that this plan has been considered

in the PMO development plan, however, it needs to be refined with regards to the research

findings.

In summary, no inconsistency was explored between the conceptual framework (Chapter

3) and the research findings in the PMO with first level of maturity (Chapter 5), i.e.

SCIENCO. However, some refinements have been proposed to develop the preliminary

conceptual framework, which was discussed earlier. In other words, the theoretical research

framework was examined in the selected cases, and then refined based on the research

findings in SCIENCO. Therefore, the revised framework shall be a practical guideline to

address the KM in the first level of maturity.


Knowledge management in the second level of maturity 8.9.1.2

According to the preliminary research framework (Chapter 3), following criteria should

be explored in the second level of maturity: 1) senior managers have realised the importance

of project KM, however, 2) There is no person or unit responsible for project KM in PMO,

3) The concept of KM has been understood by PMs and project team members, 4)

Knowledge capturing and creation are being managed through developing appropriate

systems, 5) There are some practices in place to support knowledge transferring and reusing.

These criteria were examined in GOVCO with the second level of maturity and two

inconsistencies were found during the course of data analysis. First, it was revealed that

knowledge capturing and transferring are the first and second most important KM processes.

Second, knowledge creation has not been appropriately developed in GOVCO, as the

research framework assumes. This means that GOVCO’s main priority has been on

development of knowledge capturing and transferring. On the other hand, it was revealed

that GOVCO’s PMO is a centre of excellence which means that it is not involved in project

implementation, therefore the PMO does not significantly contribute to knowledge creation.

In other words, GOVCO’s PMO focuses on addressing knowledge capturing and transferring

in the first place, then supporting knowledge creation. Apart from the mentioned

inconsistencies, the other mentioned criteria have been confirmed by the collected data from

GOVCO. In order to reflect on the research findings, the following have been proposed to

refine the preliminary research framework, in order to address the KM criteria in the second

level of maturity:

1) The importance of project KM has been realised and supported by senior managers,

2) The concept of KM has been understood by PMs and project team members,

3) Knowledge capturing is the most important KM process and knowledge transferring

and creation, should get the same priority,

4) There is no person or unit responsible for project KM in PMO, and

5) There are limited practices in place to support knowledge reusing.

According to the preliminary research framework, all KM processes should be employed

to some extent, in the second level of maturity. This assumption was confirmed as numbers

of practices were found in GOVCO by which knowledge capturing, creation and transferring

are facilitated, however, limited practices are in place to support knowledge reusing. It was

assumed that knowledge reusing has a few practices to be supported and this assumption was

confirmed through the collected data from GOVCO. As discussed, the major inconsistency

between the research findings and the preliminary research framework is the importance of

knowledge transferring over knowledge creation which was justified earlier. Therefore, the


following suggestions could be proposed to address project knowledge management in the

second level of maturity:

• Knowledge capturing is the most important KM process, so it shall be improved

through

o Developing basic practices to address subsequent sub-processes:

knowledge identification and selection,

o Developing advanced practices to improve knowledge storing and

classification,

• Knowledge creation is the second most important KM process, so it shall be

supported through

o Developing basic practices to facilitate the internalisation sub-process

o Developing advance practices to improve socialisation, externalisation

and combination.

• Knowledge transferring is the second most important KM process, so it shall be

facilitated through improving appropriate practices to support knowledge

sharing and knowledge distribution,

• Knowledge reusing is the least important KM process, so it shall be developed

through

o Addressing basic practices to facilitate knowledge applying,

o Developing appropriate practices to improve knowledge adapting.

The mentioned propositions have been graphically represented in Figure 8-21. As can be

found in this figure, four KM processes have been addressed with their sub-processes. The



Figure 8-21 KM sub processes in the second level of maturity (developed for this study)

In summary, there is no significant inconsistency between the research findings in the

PMO with a second level of maturity, i.e. GOVCO, and the research framework. However,

some refinements have been proposed to develop the preliminary research framework, which

was discussed earlier. In fact, the theoretical research framework was examined in the

selected case study, and then it was revised based on the research findings in GOVCO. The

revised framework shall be a useful method to address the KM in the second level of

maturity.

Knowledge management in the third level of maturity 8.9.1.3

According to the preliminary research framework (Chapter 3), in a PMO with the third

level of maturity, the following criteria should be observed from a KM point of view: 1)

PMO and top managers are aware of their role in encouraging project KM, 2) There is a unit

or person to take the responsibility and accountability of KM in the PMO, 3) KM is

systematically supported through appropriate systems and established standards, 4) There are

some incentives in place to encourage project team members to follow KM procedures, 5)

there are training courses to instruct KM in the PMO, and 6) Some of the developed KM

practices have been integrated at enterprise-level.

The mentioned criteria were examined in MINCO, as the case study with third level of

maturity. The research findings revealed that there is no significant inconsistency between

the preliminary research framework and the collected data from MINCO, however, some of

the criteria have been not completely observed in MINCO. For instance, there is a person


who is in charge of project knowledge management unit in MINCO’s PMO, but he is the

only person who teaches KM to the others. In other words, there is no specific course or

manual to formally instruct project knowledge management in MINCO. In addition, there

are numbers of KM systems, which are yet to be collaborated at the organisational level.

These findings explored that some of assumed criteria are yet to be completely addressed in

MINCO’s PMO. On the other hand, MINCO’s PMO has recently achieved the third level of

maturity so it takes time to fulfil all the mentioned criteria. However, the proposed criteria

have been refined as follows, to both conform to the MINCO’s PMO, and also satisfy the

research framework:

1) Senior executives, and PMO managers are aware of encouraging project knowledge

management,

2) There is a unit and/or person to take the KM responsibility in PMO,

3) Project KM is systematically supported through appropriate systems and procedures,

4) There are some incentives in place to encourage project stakeholders for following

KM procedures,

5) There is a plan to integrate the developed KM practices at the enterprise-level.

This advice should be used by PMOs with same maturity level in order to develop and/or

access the current level or maturity.

From a KM process point of view, the collected data from MINCO data has been

examined against the research framework. According to the research findings, KM processes

have the following order in terms of their importance: capturing, creation, transferring, and

reusing. This investigation revealed that, except for knowledge reusing, the collected data for

the other three KM processes are in line with the research framework. In other words,

knowledge capturing, creation and transferring are consistent with the proposed

functionalities in the preliminary research framework, while knowledge reusing’s data

showed some inconsistency in this regard. In fact, the research framework assumes that

knowledge reusing should be appropriately addressed in the third level of maturity, but the

collected information explored that knowledge reusing is yet to be developed in MINCO’s

PMO. As discussed, MINCO’s PMO is at the beginning of its journey at the third level of

maturity, so this gap might be addressed in the end of its journey to achieve the fourth level

of maturity. Having said that, the proposed assumptions for knowledge reusing have not

been confirmed in MINCO’s PMO. Therefore, some of the preliminary assumptions have

been revised to suit the collected data, as followings:

• Knowledge capturing is the most important KM process, so it should be improved

through developing advanced practices to improve knowledge storing,

classification, identification, and selection.


• Knowledge creation is the second most important km process, so it should be

supported through developing advance practices to improve socialisation,

externalisation, combination, and internalisation

• Knowledge transferring is the third most important KM process, so it should be

facilitated through improving appropriate practices to support knowledge

sharing and knowledge distribution,

• Knowledge reusing is the least important KM process, so it should be developed

through

o Developing appropriate practices to improve knowledge adapting and

applying,

o Addressing basic practices to facilitate knowledge integrating.

The mentioned propositions have been graphically represented in Figure 8-22. As it can

be found in this figure, four KM processes have been addressed with their sub processes. The


In summary, the research findings, in the PMO with third level of maturity, have not

shown any significant inconsistency against the preliminary research framework. However,

some refinements have been made to develop the research framework, which was discussed

earlier. In fact, the theoretical research framework was examined in MINCO, and then it has

been revised based on the research findings. The revised framework presents a practical

method to address the KM in the third level of maturity.


Figure 8-22 KM sub processes in the third level of maturity (developed for this study)

Knowledge management in the fourth and fifth level of maturity 8.9.1.4

According to the research framework in the fourth level of maturity, the following

should be observed from a KM point of view: 1) The role of project KM to improve

organisational competitive advantages has been realised by senior managers, 2) PMO, KM

practices and processes have been integrated with organisational KM activities, 3) Advance

trainings and workshops are being conducted to improve project KM, 4) Measuring the KM

utilisation on project productivity is being conducted, 5) Everybody is responsible for

managing project knowledge, 6 ) Numbers of quantitative index, critical success factors

(CSF), and metrics have been developed to measure the effectiveness of KM processes. As

discussed, only three cases were examined in this study, from level one to three, so the

mentioned criteria have not been examined in this study. However, these criteria could be

used by PMOs with fourth level of maturity as they have been developed based on the

current literature, but it is advised to be examined as a subject for future research.

From a KM process point-of-view, it is assumed that all KM processes should be

appropriately utilised in the fourth level of maturity. This means that at this level four KM

processes have been developed to be used by project stakeholders. As discussed in the

previous section, knowledge reusing was the only KM process that has not developed in the

third level of maturity. In other words, the research findings revealed that the development of

knowledge reusing has been initiated in the second level of maturity, while in the framework

it is assumed that knowledge reusing should be established from the first level of maturity.

Because of the recognised inconsistency between theory and practice, the framework has

been revised to satisfy the research findings. The same approach has been managed to

address knowledge reusing in the fourth level of maturity. In other words, the last sub-

process of knowledge reusing should be completely developed in the fourth level of

maturity, while it was assumed in that it should have been conducted in the previous

maturity level. Therefore, this is only change in the research framework to address

knowledge reusing in the fourth level of maturity, based on the research findings. This

means that the following should be followed to develop KM processes in the fourth level of

maturity, as shown at Figure 8-23:

• Knowledge capturing should be improved through developing complementary

KM practices,

• Knowledge creation should be supported through developing advance KM

practices,

• Knowledge transferring should be facilitated through improving advanced KM

practices,


• Knowledge reusing is the only KM process which has not been completely

addressed, so it should be developed through

o Developing complementary practices to improve knowledge adapting

and applying,

o Addressing advance practices to support knowledge integrating.

According to the research framework in the fifth level of maturity the following should

be observed from a KM point-of-view: 1) The culture of sharing and knowledge transferring

has been institutionalised, 2) Both organisation and PMO utilise an integrated KM system, 4)

An audit unit has be developed to measure project KM, 5) Project KM is integrated into

organisation and it is continually improved, 6) KM procedures are integrated in the PM

methodology as well as organisational process-assets, and 7) Project KM and competitive

advantages have been collaborated to support organisational strategies. Similar to the fourth

level of maturity, these criteria have not been examined in this study, however, they have

been proposed based on the current literature of PM and KM. In addition, examining the

proposed criteria for the fourth and fifth level of maturity could be a potential subject for

future research.

From KM process perspectives, the conceptual research framework assumes that all KM

processes have been appropriately developed and customised in the fifth level of maturity. In

addition, the research framework advises to assess and continuously improve the developed

KM processes through managing research and development activities. This means that the

current KM practices should be enhanced based on researching the existing gaps to address

them appropriately. Figure 8-23 depicts the proposed activities to improve the KM in the

fifth level of maturity.


Figure 8-23 KM processes in the fourth and fifith level of maturity (developed for this study)

In summary, this section discussed the third and last research question. The research

findings have been used to address project knowledge management in the first three maturity

levels. The preliminary research framework has been refined based on the research findings

in the selected case studies. For the fourth and fifth level of maturity, the research framework

has not been significantly revised, as there was no data with which to do so. Therefore, this

could be a potential subject of the future research.

CONCLUSION 8.10

In this chapter, three cases and their results were analysed against both each other and the

conceptual research framework, to answer all three research questions. The first and second

research questions have been answered through conducting cross case analysis, while the

third question was answered via comparing the conceptual framework and the research

findings. Both within-case and cross-case data analyses have been conducted by using

numbers of techniques such as grounded theory and pattern matching. Grounded theory was

utilised to develop evolving phenomena through coding the data and analysing the data

behaviour. Other techniques were also conducted to explore other aspects such as similarities

and differences.


Figure 8-24 Summary of the research findings (developed for this study)

This process contributed to uncovering numbers of patterns and behaviours in the

collected data to answer the research questions. Also it assisted with developing numbers of

suggestions and propositions to address the KM practices in the PM maturity models. As can

be seen in Figure 8-24, management of the project knowledge in the PMO was recognised as

the research gap (known-unknown). The collected data from three cases with three various

maturity levels were analysed by using Grounded theory and other analytical methods.

Numbers of unrevealed project knowledge management subjects have been explored during

the course of data analysis and they became “known” during this process, as shown in

Figure 8-24. However, numbers of questions were recognised during the data analysis which

could be answered through conducting another research study in the future.


Figure 8-25 KM challenges in PMOs (developed for this research)

In addition, the following propositions have been developed during the data analysis

stage:

• There is a significant relation between the level of PMO maturity and the utilised

KM practices,

• The importance of KM processes could be ranked as follows: Capturing,

Creation, Transferring and Reusing,

• The challenges of KM are different in various levels of maturity as depicted in

Figure 2-1, and Figure 8-25; also, the types of required knowledge have a

significant impact on the level of PMO maturity.

• Issues of both integration between knowledge management systems and

processes, and advanced challenges of knowledge reusing and transferring, could

be observed in the fourth level of maturity, and

• Collaboration of organisational knowledge management practices with PMO’s

knowledge management systems could be observed as the main challenge in the

fifth level of maturity.

In summary, this chapter has provided practical implications to address appropriate KM

practice in various levels of maturity. The developed framework in the previous section shall

be used by various types of organisation, specifically in PMOs with a one to three level of


maturity. The proposed suggestions and propositions have been developed based on the

collected data and data analysis techniques. The obtained KM challenges should be

considered by all types of PMOs in order to be prepared for the next level of maturity. Also,

the types of required knowledge are good indications for PMOs to provide knowledge, based

on their importance. In the next chapter, the research conclusion will be presented to discuss

the highlights of the research findings, the developed propositions, research limitations, and

future research.

Chapter 9 | Conclusions 273

Chapter 9

CONCLUSIONS

OVERVIEW 9.1

Organisations manage projects to achieve diverse objectives such as technological

enhancement, customer satisfaction, service improvement, and organisational development.

Project Management (PM) is the combination of skills, knowledge, tools and techniques to

fulfil project objectives, and project management methodologies recommend appropriate

practices to manage projects. A Project Management Office (PMO) centrally manages and/or

controls organisational projects, and also institutionalises project management practices

within organisations. Due to the complexity of project management practices, Project

Management Maturity Models (PMMM) have been developed to address the development of

PMOs. In other words, PM maturity models contribute to improve the quality of PMO

services, and ultimately enhance the project success rate.

The management of project knowledge is another critical factor to improve the project

success rate, and contributes to the quality of project outcomes. According to the findings of

this research, the current PM maturity models have not appropriately addressed the

management of project knowledge in various levels of maturity. In fact, the existing PM

maturity models are yet to be developed from knowledge management perspectives.

Following a succinct introduction to outline the research structure in Chapter one, a

comprehensive literature review was undertaken in Chapter two, to investigate the current

debates in both project management and knowledge management fields. In Chapter three, the

conceptual framework, as a preliminary research framework, was developed through

identifying factors that potentially influence project knowledge management in PMOs. In

this framework, four knowledge management processes were adopted, i.e. Capturing;

Creation; Transferring; and Reusing, to address knowledge management in five levels of

maturity. To investigate the conceptual framework, a case study method was selected as the

research methodology alongside Grounded theory as the main analysis technique, which was

presented in Chapter four.

Three large organisations with diverse sectors were chosen for investigation. The within-

case analysis was conducted for each case, i.e. SCIENCO; GOVCO; and MINCO, in

conformance with the research methodology. The research findings were analysed and

presented in chapters five, six and seven. In Chapter five, SCIENCO’s PMO, with the first

274 Chapter 9 | Conclusions

maturity level, was discussed to explore the utilisation of knowledge management processes

and practices. Both research methodology and the conceptual framework were used to reveal

the management of project knowledge in SCIENCO. Similar processes were conducted to

investigate GOVCO and MINCO, and the outcomes of both investigations were presented in

chapters six and seven.

In Chapter eight, the cross case analysis was conducted to compare the research findings

from the selected case studies, and also overall discussions of the research findings were

presented accordingly. According to the research findings, in Chapter eight, MINCO with a

third level of maturity has more developed knowledge management practices in comparison

to GOVCO and SCIENCO. In a similar manner, the research findings revealed that GOVCO

with a second level of maturity has developed more knowledge management practices in

place, in comparison to SCIENCO, with the first maturity level. This means that there is a

relationship between project knowledge management, and the maturity level of the project

management office. At the end of this chapter, a number of suggestions and propositions

were discussed to address appropriate KM practices and processes in various levels of

maturity.

This chapter aims to succinctly summarise the research findings to address the research

questions. Also, it presents the research contributions and significance of this research,

followed by acknowledging the research limitations. At the end, a number of directions and

subjects have been proposed for future studies.

KNOWLEDGE MANAGEMENT CHALLENGES IN THE PMO 9.2

This research aimed to explore the management of project knowledge in the project

management office. To do so, numbers of questions and sub-questions were developed, as

discussed in section 2.5.4. The current challenges of PMOs, from a KM point of view, were

the first subject to be investigated. As presented in section 8.6.1, the following KM

challenges were explored in the selected case studies: 1) lack of appropriate systems to

support project knowledge management, 2) difficulties of searching and detecting required

knowledge (recognised in SCIENCO only), 3) issue of appropriate access to the existing

systems, 4) issue of locating and accessing right information and/or right expert, 5) lack of

knowledge management practices and processes during project life cycle (were revealed

only in SCIENCO and GOVCO), 6) lack of integration among current processes and

systems (explored in GOVCO only), 7) issues with current systems to fully support

knowledge capturing process, 8) inadequate practices to support knowledge transferring

process, 9) unsatisfactory practices to appropriately support the knowledge reusing process,

and 10) lack of training for current systems and applications (explored in MINCO only).


According to the research findings, in the lower levels of maturity (first and second

levels), the majority of knowledge management challenges are related to the current systems

and their access, while in higher levels of maturity the integration of current systems

becomes more challenging. In addition, in higher levels of maturity, knowledge transferring

and reusing are more challenging in comparison to knowledge capturing and creation. As

can be found in Figure 8-25, there is relationship between the level of maturity and type of

KM challenges in PMOs.

Practical Implications

It is suggested that a PMO with low levels of maturity (one and two) shall focus on

developing the required systems and applications, and also provide appropriate access to

project stakeholders. In addition, knowledge capturing and creation issues should be resolved

at lower levels of maturity. This means that in the third or higher level of maturity, issues

such as access to systems, or lack of required systems should be addressed. In the third and

fourth levels of maturity, the main focus should be on both integrating the current systems,

and developing appropriate knowledge management practices to address the existing issues

related to knowledge transferring and reusing. In other words, in the fourth level of maturity,

the PMO should not be faced with major challenges from knowledge management process

perspectives. In the fifth level of maturity, PMO should focus on addressing issues of

integrating and collaborating knowledge management with the organisational knowledge

management system.

THE REQUIRED TYPES OF KNOWLEDGE IN VARIOUS LEVELS OF MATURITY 9.3

According to the research findings, “project management knowledge”, “knowledge about

clients”, and “knowledge of who knows what” are the most important types of knowledge,

while “knowledge about supplier” and “legal knowledge” are ranked as the least important

types of knowledge. This research revealed that the importance of required knowledge is

changed when the maturity level of the PMO improves, since the PMO develops new

knowledge management practices in a higher level of maturity to address the recognised

needs. In addition, this study explored that the type of PMO and its level of maturity are two

important factors to determine the type of required knowledge, as discussed in section 8.6.2.

This means that in a practical PMO, such as SCIENCO, some types of knowledge (such as

costing knowledge) are important pieces of information, while in a centre of excellence

PMO, such as in GOVCO, costing knowledge is not as important as other types of

knowledge, as the PMO is not involved in project execution. In addition, in a PMO with a

low level of maturity, such as SCIENCO, providing some types of knowledge such as

“knowledge of who knows what” was ranked as the second most important type of required

knowledge, contrary to a PMO with a higher level of maturity, i.e. MINCO, where provision


of “knowledge of who know what” is not as important as in SCIENCO as it has been

addressed through numbers of practices.

Practical implications

A PMO with low levels of maturity shall focus on developing a comprehensive project

management methodology to address two types of knowledge: “project management

knowledge’ and “knowledge about procedures”. Also, according to the findings of this study

it is advised to develop appropriate practices to address “knowledge about who know what”,

and “knowledge about clients”. In the PMO with a higher maturity level the main focus shall

be on developing practical exercises to address “costing knowledge” as well as “technical

knowledge”, since they significantly impact on the quality of a project outcome. After

addressing the provision of the mentioned types of knowledge, the PMO shall focus on

facilitating the other types of knowledge such as legal knowledge and knowledge about

suppliers.

UTILISATION OF KNOWLEDGE MANAGEMENT PRACTICES IN PMO 9.4

Similar to the previous section, types of PMO and level of maturity are important factors

to determine the required knowledge management practices in a PMO. As discussed in

section 8.7, this research revealed that in a normal PMO (practical PMO), the majority of

KM practices should support knowledge capturing and creation, while in a centre of

excellence most of the KM practices should facilitate knowledge capturing and transferring.

In addition, numbers of KM practices in a PMO with low level of maturity, i.e. SCIENCO,

are less in a PMO with higher level of maturity, i.e. GOVCO and MINCO. This means that a

PMO with a higher maturity level has more knowledge management practices in place in

comparison to a low maturity level PMO. For instance, “expert locator” has not been

developed in SCIENCO, while it is used in GOVCO and MINCO. In a similar manner,

“expert system” has not been addressed in SCIENCO and GOVCO, but it is utilised in

MINCO. From a knowledge management process point-of-view, knowledge reusing is yet to

be addressed in SCIENCO and GOVCO, while MINCO has addressed some practices to

facilitate knowledge reusing. This means that in a PMO with low maturity levels (one and

two) knowledge capturing, creation and transferring, in order, have been addressed and

knowledge reusing has not be appropriately considered. Meanwhile, in a PMO with a higher

level of maturity, the mentioned three KM processes have been developed, hence knowledge

reusing gains more attention.


In a PMO with a first level of maturity, the development of appropriate practices to

address knowledge capturing and transferring shall be the first priority. In the second level of


maturity, it is recommended to improve the current practices, and develop new practices to

facilitate knowledge transferring. In the third level of maturity, addressing knowledge

reusing shall be the first priority alongside the improvement of other knowledge

management processes. In the fourth and fifth level of maturity, the PMO shall focus on

continually enhancing the four knowledge management processes through developing

advance knowledge management practices.

THE IMPORTANCE OF KNOWLEDGE MANAGEMENT PROCESSES IN PMO 9.5

As discussed in section 8.8.1, this research explored the notion that knowledge capturing

is the most important knowledge management process, while knowledge reusing is the least

important one. In addition, knowledge creation is the second most important knowledge

management process in SCIENCO and MINCO, which are both practical PMOs, but it is the

third important knowledge management process in GOVCO. In other words, in the centre of

excellence’s PMO, knowledge transferring is the second most important knowledge

management process, after knowledge capturing. This is another indication to determine the

type of PMO, as it impacts on knowledge management activities. In general, the following

order can be proposed to address the importance of the knowledge process: 1) Capturing, 2)

Creation, 3) Transferring, and 4) Reusing.


According to the research findings, PMOs shall focus on developing practices to address

KM processes in the following order: capturing, creation, transferring, and reusing. It is

advised to focus on developing capturing and creation practices, in a PMO with a first level

of maturity. In a similar manner, knowledge transferring and reusing shall be developed in

higher maturity levels. This is consistent with the research findings and implications in the

previous section.

PMO’S CONTRIBUTIONS TO KNOWLEDGE MANAGEMENT 9.6

As discussed in section 8.8, four knowledge management processes, their sub-processes

and associated practices were considered to address the development of knowledge

management in three levels of maturity. In addition, multiple propositions were developed

based on the research findings to address project knowledge management in the fourth and

fifth levels of maturity. This study explored that knowledge management processes should

be developed and improved based on three factors: Level of maturity, the importance of

knowledge management process (discussed section 8.8.1), and importance of the associated

sub-processes as well as practices (discussed in section 8.8.2). The PMO’s contributions to

develop knowledge management, in three levels of maturity, have been graphically depicted


in Figure 8-13 to Figure 8-19. In addition, Figure 8-23 has been provided to propose the

contributions of a PMO in levels four and five.


In the first level of maturity, knowledge capturing is the most important knowledge

management process, so in order to develop knowledge capturing, firstly knowledge storing

and classification should be established as the most important knowledge capturing sub-

processes. In other words, to develop knowledge capturing in the first maturity level, the

main focus should be on addressing knowledge storing and classification through

establishing associated knowledge management practices, such as document management

systems and databases. For the second maturity level, the other sub- processes, i.e.

knowledge selection and identification, should be developed through using some practices

such as expert locator and file management systems, as shown at Figure 8-13.

Similar process could be followed to develop other knowledge management processes, as

addressed in section 8.8.

KNOWLEDGE MANAGEMENT PROCESSES IN FIVE MATURITY LEVELS 9.7

This research revealed that the following factors should be considered in developing the

knowledge management in a PMO: level of maturity, type of PMO, the current knowledge

management issues and challenge, types of required knowledge, and the importance of

knowledge management processes. The maturity level of a PMO addresses the PMO’s

readiness and the types of issues that a PMO generally is faced with, as discussed in

sections 8.6.1. In addition, the types of required knowledge are addressed in regards to the

maturity level of a PMO, as presented in sections 8.6.2 and 9.3. The importance of

knowledge management processes addresses their priority to be developed in various level of

maturity, as discussed in sections 8.8.1, 8.8.2, and 9.6. Finally, the integration of all factors

addresses the development of knowledge management processes in the project management

office, as discussed in section 8.9.1. In addition, the integration of knowledge management

processes in five levels of maturity has been graphically addressed in the following figures:

Figure 8-20 to Figure 8-23. These figures address knowledge management processes in three

levels based on the research findings, and propose appropriate steps for improving the

quality of PM in the fourth and fifth levels of maturity.


The PMO in various levels of maturity, specifically the first three levels, shall develop its

knowledge management systems through the following steps: 1) recognising the current

challenges, and comparing them to the research findings in section 8.6.1, and 2) providing

the required types of knowledge, discussed in section 8.6.2, with regards to the level of


maturity, and 8.8, and 8.9.1. These steps shall improve the maturity of a PMO from a

knowledge management perspective.

RESEARCH CONTRIBUTIONS 9.8

General Contributions 9.8.1

This study aimed to make two following contributions: developing and applying a

framework to address KM practices at the current PMMM and PMO; and proposing new

criteria to assess the maturity of the PMO from a KM point-of-view. To achieve the

mentioned contributions, a conceptual framework was developed after a comprehensive

literature review. This was the first attempt to propose a framework for theoretically

addressing knowledge management processes and practices in five maturity levels of the

project management office, as presented in Table 3-11. In addition, for the first time in the

current literature, four KM processes and their associated KM practices have been discussed

in the proposed framework.

The conceptual framework was examined in three PMOs with various levels of maturity.

The empirical findings not only were consistent with the developed framework, but also they

contributed to reveal the following aspects of project knowledge management in PMO: the

importance of KM processes in various levels of maturity; the KM challenges of PMO in

various maturity levels; importance of the required knowledge in PMO. These findings were

utilised to refine the conceptual framework and reveal some of the unknown subjects in

PMOs from a knowledge management point-of-view, as shown in Figure 8-24. In addition,

numbers of suggestions and propositions have been developed to address knowledge

management in various maturity levels of the PMO, as discussed in section 8.9.

The researcher strongly believes the study outcomes significantly impacts on delivering

successful project through addressing practical advices on project KM. The recommended

KM practices address four KM processes, i.e. Creation; Capturing; Transferring; Reusing,

to bridge the recognised gap in the PMO. This research also has significantly contributed to

the existing discussions of the transformation of Tacit knowledge to Explicit knowledge in

the Project-Based Organisations. In addition, this is the first attempt to investigate PMO

maturity models from KM point of view, in order to address a road map for improving KM

capability in PMOs.

The developed framework is recommended to be employed by all types of PMOs

because: 1) it has a robust and reliable theoretical background, 2) it was examined in

different types of PMOs, 3) it was investigated in various types of organisations, and 4) it

has been refined based on the research findings in three organisations. To the best of this

researcher’s knowledge, this is the first attempt to address knowledge management processes

in the five maturity levels of project management office.


In addition, there are numbers of KM processes, sub-processes and practices in the

developed research framework. The utilisation of each practice and process is addressed in

various levels of maturity, as discussed in section 8.9 and shown in Table 3-11. The maturity

of PMO from a KM perspective shall be assessed through examining the addressed KM

practices in each level of maturity. This means that in a specific level of maturity, if the

proposed practices are not in place, they will need to be addressed to achieve the next level

of maturity. In other words, utilisation of the proposed framework shall be a strong

indication to address the maturity of PMO from a knowledge management point-of-view.

Theoretical Contributions 9.8.2

To the best of this researcher’s knowledge this is the first attempt to address knowledge

management processes and practices in various maturity levels of the Project Management

Office. The integration of knowledge management practices in the PM Maturity model is the

significant contribution of this research. Also, this study has developed a theoretical

framework to assess and address the maturity of project management environments,

specifically the PMO, from a knowledge management perspective. In addition, eight types of

project knowledge for the first time have been proposed and integrated in the proposed

framework. Finally, this research has provided a new direction for future studies to

investigate Project Management Office from a knowledge management point of view.

RESEARCH LIMITATIONS 9.9

The studies of knowledge management in project-based organisations have been recently

considered as an important subject, so there are still many aspects yet to be addressed in this

regard. This means that current literature is yet to be developed to address issues of project

knowledge management. In fact, the absence of adequate studies that discuss project

knowledge management was one limitation for this study. In other words, the proposed

theoretical framework would have been more comprehensive if the existing literature had

richer discussions from the associated field.

The selection of appropriate case studies was another limitation of this study. There are

five levels of maturity in the research framework, so it was initially planned to investigate

five organisations with various levels of maturity in order to examine the proposed

framework. After developing the preliminary research framework, it was realised that

finding case studies with high PM maturity is difficult, as PMO is relatively new for

industries, especially in Australia. In fact, the lack of information and evidence to undertake

this study in fourth and fifth levels of maturity forced this researcher to confine the scope of

study. Therefore, three organisations were finalised for this study to explore the utilisation of

knowledge management practices in the first three levels of maturity. However, this


researcher aims to investigate the developed framework in higher maturity levels in the

future.

The proposed research framework has been not been examined in fourth and fifth

maturity levels. This is another limitation of this study, as the research findings do not

discuss the PMO maturity level in the mentioned levels. In other words, the proposed

framework is yet to be examined in the highest maturity levels. This could be a subject for

another research project which will be discussed in the next section.

FUTURE RESEARCH 9.10

Several directions could be proposed from the emergent findings during the research the

data collection and analysis stage.

The research framework was examined in three large organisations from diverse sectors

and various levels of maturity. This research framework could be extended to numbers of

complementary studies. First, the framework could be examined in numbers of organisations

with similar maturity levels. For instance, PMOs with the second level of maturity could be

investigated through use of the developed framework. Second, the framework could be

examined through choosing PMOs in similar industries, such as research or mining. Third,

the combination of first and second levels could be managed as another direction for the

future study. This would significantly contribute to improving the proposed case study, by

either validating or refining the proposed framework.

Also, the four and fifth levels of maturity in the framework are yet to be examined. In

other words, this research did not cover the investigation of the highest maturity levels, due

to the existing limitations. This could be an interesting subject for another PhD project.

In addition, the outcomes of this study could be examined through appropriate methods in

order to validate the whole research framework. This is one of the directions that this

researcher intends to undertake in his future career.

Also, the proposed knowledge management practices could be examined through

conducting a number of comprehensive surveys. For instance, the proposed types of

knowledge and also the recognised KM challenges of PMO could be tested in various levels

of maturity.

In addition, integrating the research framework with the organisational KM systems could

be another research subject, by which project KM could be collaborated into an

organisation’s KM systems. In fact, this research project is another subject that this

researcher is interested in implementing in the near future.

This original research investigated Knowledge Management and PMO maturity levels in

one of the current major PM methodologies, i.e. PMBOK, developing deeper understanding,


and contributing new knowledge, and hence forms a strong foundation for future studies.

Future research may explore the study of Knowledge Management in other project

management methodologies and extend knowledge of these areas of concern in project

management.

Bibliography 283

284 Bibliography

BIBLIOGRAPHY

Aita, V. A., and H. McIlvain, 1999, An Armchair Adventure in Case Study Research. Doing qualitative research 2:256-268.

Ajmal, M., P. Helo, and T. Kekäle, 2010, Critical Factors for Knowledge Management in Project Business. Journal of Knowledge Management 14(1):156-168.

Ajmal, M., and K. U. Koskinen, 2008, Knowledge Transfer in Project-Based Organizations: An Organizational Culture Perspective. Project Management Journal 39(1):7-15.

Alavi, M., and D. E. Leidner, 1999, Knowledge Management Systems: Issues, Challenges, and Benefits. Commun. AIS 1(2es):1.

Alavi, M., and D. E. Leidner, 2001, Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly 25(1):107-136.

Anand, G., P. Ward, and M. Tatikonda, 2010, Role of Explicit and Tacit Knowledge in Six Sigma Projects: An Empirical Examination of Differential Project Success. Journal of Operations Management 28(4):303-315.

Anbari, F. T., 2005, Innovation, Project Management, and Six Sigma Method. Current topics in Management 10:101–116.

Andersen, B., B. Henriksen, and W. Aarseth, 2007, Benchmarking of Project Management Office Establishment: Extracting Best Practices. Journal of Management in Engineering 23:97.

Andersen, E., and S. A. Jessen, 2003, Project Maturity in Organisations. International Journal of Project Management 21(6):457-461.

Arora, P., D. Owens, and D. Khazanchi, 2010, A Pattern-Based Tool for Knowledge Management in Virtual Projects The IUP Journal of Knowledge Management VIII(3):60-80.

Artto, K., I. Kulvik, J. Poskela, and V. Turkulainen, 2011, The Integrative Role of the Project Management Office in the Front End of Innovation. International Journal of Project Management 29(4):408-421.

Aubry, M., B. Hobbs, and D. Thuillier, 2007, A New Framework for Understanding Organisational Project Management through the Pmo. International Journal of Project Management 25(4):328-336.

Aubry, M., B. Hobbs, and D. Thuillier, 2008, Organisational Project Management: An Historical Approach to the Study of Pmos. International Journal of Project Management 26(1):38-43.

Aubry, M., R. Müller, and J. Glückler, 2013, Governance and Communities of Pmos. Project Management Journal 44(1):108-108.

Bibliography 285

Aubry, M., M. Richer, M. Lavoie-Tremblay, and G. Cyr, 2011, Pluralism in Pmo Performance: The Case of a Pmo Dedicated to a Major Organizational Transformation. Project Management Journal 42(6):60-77.

Aubry, Mon., R. Müller, B. Hobbs, and T. Blomquist, 2010, Project Management Offices in Transition. International Journal of Project Management 28(8):766-778.

Bakker, R., B. Cambré, L. Korlaar, and J. Raab, 2011, Managing the Project Learning Paradox: A Set-Theoretic Approach toward Project Knowledge Transfer. International Journal of Project Management 29(5):494-503.

Barclay, C., and K. Osei-Bryson, 2010, An Exploration of Knowledge Management Practices in It Projects: A Case Study Approach. AMCIS 2010 Proceedings:Paper 452.

Bell, S., 2010, Project-Based Learning for the 21st Century: Skills for the Future. The Clearing House 83(2):39-43.

Bentley, C., 2009, Prince2: A Practical Handbook: Butterworth-Heinemann.

Berg, B. L., 2004, Qualitative Research Methods for the Social Sciences. Volume 5: Pearson Boston.

Bredillet, C., 2008, Exploring Research in Project Management: Nine Schools of Project Management Research (Part 4). Project Management Journal 39(1):2-6.

Bresnen, M., L. Edelman, S. Newell, H. Scarbrough, and J. Swan, 2003, Social Practices and the Management of Knowledge in Project Environments. International Journal of Project Management 21(3):157-166.

Brown, A. E. , and P. Duguid, 1998, Organizing Knowledge. California Management Review 40(3):90-111.

Byounggu, C. , and L. Heeseok, 2002, Knowledge Management Strategy and Its Link to Knowledge Creation Process. Expert Systems with Applications 23(3):173-187.

Caniëls, M. CJ., and R. JJM. Bakens, 2012, The Effects of Project Management Information Systems on Decision Making in a Multi Project Environment. International Journal of Project Management 30(2):162-175.

Carrillo, P., 2005, Lessons Learned Practices in the Engineering, Procurement and Construction Sector. Engineering, Construction and Architectural Management 12(3):236-250.

Charmaz, K., 2014, Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. London: Sage Publications.

Christensen, K. S. , and H. K. Bang, 2003, Knowledge Management in a Project-Oriented Organization: Three Perspectives. Journal of Knowledge Management 7(3):116 - 128.

Corbin, J., and A. Strauss, 1990, Grounded Theory Research: Procedures, Canons, and Evaluative Criteria. Qualitative Sociology 13(1):3-21.

Corbin, J., and A. Strauss, 2008, Basics of Qualitative Research : Techniques and Procedures for Developing Grounded Theory Thousand Oaks: SAGE Publications.

Crawford, J., 2002, Project Management Maturity Model: Providing a Proven Path to Project Management Excellence. Volume 4: CRC Press.

Crawford, J. K., 2012, The Strategic Project Office: CRC Press.

286 Bibliography

Crawford, J. K. , 2006, The Project Management Maturity Model. Information Systems Management 23(4):50-58.

Creswell, J. W., 2009, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches Thousand Oaks: Sage Publication.

Dai, C. X. , and W. G. Wells, 2004, An Exploration of Project Management Office Features and Their Relationship to Project Performance. International Journal of Project Management 22(7):523-532.

Damm, D., and M. Schindler, 2002, Security Issues of a Knowledge Medium for Distributed Project Work. International Journal of Project Management 20(1):37-47.

Davenport, TH., 1997, Ten Principles of Knowledge Management and Four Case Studies. Knowledge and Process Management 4(3):187-208.

Davenport, TH., 2013, Process Innovation: Reengineering Work through Information Technology: Harvard Business Press.

Davenport, TH., and L. Prusak, 2000, Working Knowledge: How Organizations Manages What the Know. Boston-USA: Harvard Business School Press.

Davidson, P., and R. Jillian, 2009, Systematising Knowledge Management in Projects. International Journal of Managing Projects in Business 2(4):561 - 576.

Desouza, K. C., 2006, Knowledge Management Maturity Model: Theoretical Development and Preliminary Empirical Testing, University of Illinois at Chicago.

Desouza, K. C., and J. R. Evaristo, 2006, Project Management Offices: A Case of Knowledge-Based Archetypes. International Journal of Information Management 26(5):414-423.

Diakoulakis, I. E. , N. B. Georgopoulos, D. E. Koulouriotis, and D. M. Emiris, 2004, Towards a Holistic Knowledge Management Model. Journal of Knowledge Management 8(1):32-46.

Drucker, F. P. , 1993, Post-Capitalist Society. New York: Harper Paperbacks.

Drucker, P. F., 2013, Managing in a Time of Great Change: Harvard Business Press.

Ein-Dor, P., 2008, Taxonomies of Knowledge. In Knowledge Management: Concepts, Methodologies, Tools, and Applications. Pp. 162-170. Hershey, PA: Information Science Reference.

Eisenhardt, K. M., and M. E. Graebner, 2007, Theory Building from Cases: Opportunities and Challenges. Academy of Management Journal 50(1):25-32.

Eriksson, P., 2013, Exploration and Exploitation in Project-Based Organizations: Development and Diffusion of Knowledge at Different Organizational Levels in Construction Companies. International Journal of Project Management 31(3):333-341.

Feng, J. , 2006, A Knowledge Management Maturity Model and Application. Technology Management for the Global Future, 2006. PICMET 2006, 2006. Vol. 3, pp. 1251-1255.

Gajic, D., and R. Riboni, 2010, Effective Knowledge Management Processes and Tools in Project Environments : A Case of Dell Computers Emea, Business Operations Pmo, Faculty of Social Sciences, Umeå School of Business, Umeå University.

Bibliography 287

Gasik, S., 2011, A Model of Project Knowledge Management. Project Management Journal 42(3):22.

Ghodsypour, S., and C. O'brien, 1998, A Decision Support System for Supplier Selection Using an Integrated Analytic Hierarchy Process and Linear Programming. International journal of production economics 56:199-212.

Goffin, K., U. Koners, D. Baxter, and C. Van der Hoven, 2010, Managing Lessons Learned and Tacit Knowledge in New Product Development Research-Technology Management 53(4):39-51.

Grant, K. P. , and J. S. Pennypacker, 2006, Project Management Maturity: An Assessment of Project Management Capabilities among and between Selected Industries. Engineering Management, IEEE Transactions on 53(1):59-68.

Gray, D., 2009, Doing Research in the Real World. London: Sage Publications.

Guba, E. G. , and Y. S. Lincoln, 1994, Competing Paradigms in Qualitative Research. Handbook of qualitative research 2:105-117.

Guide, P., 2004, A Guide to the Project Management Body of Knowledge. Estados Unidos: PMI.

Hoegl, M., and A. Schulze, 2005, How to Support Knowledge Creation in New Product Development:: An Investigation of Knowledge Management Methods. European Management Journal 23(3):263-273.

Hsieh, P. J. , B. Lin, and C. Lin, 2009, The Construction and Application of Knowledge Navigator Model (Knm™): An Evaluation of Knowledge Management Maturity. Expert Systems with Applications 36(2, Part 2):4087-4100.

Hurt, M., and J. Thomas, 2009, Building Value through Sustainable Project Management Offices. Project Management Journal 40(1):55-72.

Jugdev, K., and J. Thomas, 2002, Project Management Maturity Models: The Silver Bullets of Competitive Advantage: Project Management Institute.

Julian, J., 2008, How Project Management Office Leaders Facilitate Cross‐Project Learning and Continuous Improvement. Project Management Journal 39(3):43-58.

Kamara, J.M. , C.J. Anumba, P. M. Carrillo, and N. Bouchlaghem, 2003, Conceptual Framework for Live Capture and Reuse of Project Knowledge. CIB REPORT 284:178.

Kankanhalli, A., and L. G. Pee, 2009, A Model of Organisational Knowledge Management Maturity Based on People, Process, and Technology. Journal of Information & Knowledge Management 08(02):79-99.

Kasten, J., 2010, Knowledge Organization and the Project Management Process. Convergence of Project Management and Knowledge Management:174.

Kasvi, J. J. J., M. Vartiainen, and M. Hailikari, 2003, Managing Knowledge and Knowledge Competences in Projects and Project Organisations. International Journal of Project Management 21(8):571-582.

Kerzner, H., 2005, Using the Project Management Maturity Model Hobokon- New Jersey: John Wiley& Sons

Kerzner, H., 2009, Project Management , as System Approach to Planning, Scheduling and Controling. New Jersey: John Wiley & Sons.

288 Bibliography

Kerzner, H., 2013, Project Management , as System Approach to Planning, Scheduling and Controling. New Jersey: John Wiley & Sons.

Kidwell, J. J., K. Vander Linde, and S. L. Johnson, 2000, Applying Corporate Knowledge Management Practices in Higher Education. Educause Quarterly 23(4):28-33.

Kitzinger, J., 1995, Introducing Focus Groups. BMJ: British Medical Journal 311(7000):299-302.

Kloppenborg, T., 2014, Contemporary Project Management: Cengage Learning.

Knight, T., and T. Howes, 2003, Knowledge Management: A Blueprint for Delivery: A Programme for Mobilizing Knowledge and Building the Learning Organization. Burlington -MA: Butterworth-Heinemann.

Koskinen, K., 2010, Recursive View of the Project-Based Companies' Knowledge Production. Journal of Knowledge Management 14(2):258-268.

Koskinen, K. U., 2000, Tacit Knowledge as a Promoter of Project Success. European Journal of Purchasing & Supply Management 6(1):41-47.

Koskinen, K. U., and P. Pihlanto, 2008, Knowledge Management in Project-Based Companies Hampshire, UK: Palgrave Macmillan.

Koskinen, K. U., P. Pihlanto, and H. Vanharanta, 2003, Tacit Knowledge Acquisition and Sharing in a Project Work Context. International Journal of Project Management 21(4):281-290.

Kotnour, T., 2011, An Emerging Theory of Enterprise Transformations. Journal of Enterprise Transformation 1(1):48-70.

Kotnour, T. , 2000, Organizational Learning Practices in the Project Management Environment. International Journal of Quality & Reliability Management 17( 4/5):393 - 406.

Kulpa, M. K., and K. A. Johnson, 2008, Interpreting the Cmmi: A Process Improvement Approach: Auerbach Pub.

Landaeta, R. E., 2008, Evaluating Benefits and Challenges of Knowledge Transfer across Projects. ENGINEERING MANAGEMENT JOURNAL-ROLLA- 20(1):29.

Larmer, J., and J. Mergendoller, 2010, Seven Essentials for Project-Based Learning. Educational leadership 68(1):34-37.

Leedy, P. D., and J. E. Ormrod, 2001, Practical Research: Planning and Design New Jersey: Merrill Prentice Hall.

Leidner, D., M. Alavi, and T. Kayworth, 2008, The Role of Culture in Knowledge Management: A Case Study of Two Global Firms. Global information systems: The implications of culture for IS management:265-289.

Leseure, M. J., and N. J. Brookes, 2003, It-Based Project Knowledge Management. IT-based management: challenges and solutions:90.

Liang, C., A. Wiewiora, G. G. Gable, and B. Trigunarsyah, 2009, Project Team’s Internal and External Social Networks and Their Influence on Project Performance. 10th European Conference on Knowledge Management, Università Degli Studi Di Padova,Vicenza., 2009.

Bibliography 289

Liebowitz, J., and I. Megbolugbe, 2003, A Set of Frameworks to Aid the Project Manager in Conceptualizing and Implementing Knowledge Management Initiatives. International Journal of Project Management 21(3):189-198.

Lindner, F., and A. Wald, 2011, Success Factors of Knowledge Management in Temporary Organizations. International Journal of Project Management 29(7):877-888.

Liu, L., and P. Yetton, 2007, The Contingent Effects on Project Performance of Conducting Project Reviews and Deploying Project Management Offices. Engineering Management, IEEE Transactions on 54(4):789-799.

Love, P. E. D., P. S. Fong, and Z. Irani, 2005, Management of Knowledge in Project Environments: Butterworth-Heinemann.

Love, P. E. D., Z. Irani, and D. J. Edwards, 2003, Learning to Reduce Rework in Projects: Analysis of Firm's Organisational Learning and Quality Practices. Project Management Journal 34(3).

Lytras, M. D., and A. Pouloudi, 2003, Project Management as a Knowledge Management Primer: The Learning Infrastructure in Knowledge-Intensive Organizations: Projects as Knowledge Transformations and Beyond. Learning Organization 10(4):237 - 250.

Lytras, M. D., A. Pouloudi, and A. Poulymenakou, 2002, Knowledge Management Convergence - Expanding Learning Frontiers. Journal of Knowledge Management 6(1):.40 - 51.

Morales-Arroyo, MA., Y. K. Chang, and G. De las Nievas Sánchez-Guerro, 2010, The Use of Km Tools and Techniques to Reduce Coordination Problems in Project Management. Convergence of Project Management and Knowledge Management:57.

Müller, R., J. Glückler, and M. Aubry, 2013, A Relational Typology of Project Management Offices. Project Management Journal 44(1):59-76.

Newell, S., M. Bresnen, L. Edelman, H. Scarbrough, and J. Swan, 2006, Sharing Knowledge across Projects: Limits to Ict-Led Project Review Practices. Management Learning 37(2):167.

Newman B D, and Conrad K W, 2000, A Framework for Characterizing Knowledge Management Methods, Practices, and Technologies, 2000, pp. 1-16. Citeseer.

Nissen, M., M. Kamel, and K. Sengupta, 2000, Integrated Analysis and Design of Knowledge Systems and Processes. Inf. Resour. Manage. J. 13(1):24-42.

Nonaka, I., 1994, A Dynamic Theory of Organizational Knowledge Creation. Organization Science 5(1):14-37.

Nonaka, I., and H. Takeuchi, 1995, The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York Oxford University Press, USA.

Nonaka, I., and J. D. Teece, 2001, Managing Industrial Knowledge: Creation, Transfer and Utilization. London SAGE Publication

Nonaka, IK., and H. Takeuchi, 2011, The Wise Leader. Harvard Business Review 89(5):58-67.

Office of Government Commerce, 2005, Managing Successful Projects with Prince2. London TSO.

290 Bibliography

Owen, J., and F. Burstein, 2005, Where Knowledge Management Resides within Project Management. Case Studies in Knowledge Management:138-153.

Owen, J., F. Burstein, and Steven. Mitchell, 2004, Knowledge Reuse and Transfer in a Project Management Environment.

Owen, J., and H. Linger, 2011, Knowledge-Based Practices for Managing the Outsourced Project. Scandinavian Journal of Information Systems 23(2):4.

Peltola, S., M. Tihinen, and P. Parviainen, 2002, What Are the Knowledge Needs During the Project Lifecycle in an Expert Organisation? Product Focused Software Process Improvement:423-435.

Pemsel, S., and A. Wiewiora, 2013, Project Management Office a Knowledge Broker in Project-Based Organisations. International Journal of Project Management 31(1):31-42.

Pemsel, So., and Ra. Müller, 2012, The Governance of Knowledge in Project-Based Organizations. International Journal of Project Management 30(8):865-876.

Polanyi, M., 1983, The Tacit Dimention. Gloucester, Massachusett: Peter Smith.

Polyaninova, T., 2010, Suitable Knowledge Management in Project Environment.

Porter, M. E., 1985, Competitive Advantage: Creating and Sustaining Superior Performance. New York: Free Press.

PRINCE2 Foundation, 2008, Portfolio, Program and Project Office Norwich: TSO.

Project Management Institute, 2008a, A Guide to the Project Management Body of Knowledge : Pmbok Guide. Newtown Square, PA, USA: Project Management Institute

Project Management Institute, 2008b, Organizational Project Managment Maturity Model. Pennsylvania: Project Management Institute.

Project Management Institute, 2013, A Guide to the Project Management Body of Knowledge : Pmbok Guide. Newtown Square, PA, USA: Project Management Institute

Raymond, C., I. Fazey, M. Reed, L. Stringer, G. Robinson, and A. Evely, 2010, Integrating Local and Scientific Knowledge for Environmental Management. Journal of Environmental Management 91(8):1766-1777.

Reich, B., and S. Y. Wee, 2006, Searching for Knowledge in the Pmbok Guide. Project Management Journal 37(2):11-26.

Ribeiro, F. L., and V. L. T. Ferreira, 2010, Using Knowledge to Improve Preparation of Construction Projects. Business Process Management Journal 16(3):361 - 376.

Rose, Kenneth H., 2013, Governance and Communities of Pmos. Project Management Journal 44(1):108-108.

Santosus, M., 2003, Office Discipline: Why You Need a Project Management Office. CIO Magazine, July 1.

Schacht, S., and A. Mädche, 2013, How to Prevent Reinventing the Wheel?–Design Principles for Project Knowledge Management Systems. In Design Science at the Intersection of Physical and Virtual Design. Pp. 1-17: Springer.

Scherkenbach, W. W., 1986, The Deming Route to Quality and Productivity: Road Maps and Roadblocks: George Washington Univ Dept of.

Bibliography 291

Senaratne, S. , and M. G. Sexton, 2009, Role of Knowledge in Managing Construction Project Change. Engineering, Construction and Architectural Management 16(2):186-200.

Singh, R., M. Keil, and V. Kasi, 2009, Identifying and Overcoming the Challenges of Implementing a Project Management Office. European journal of information systems 18(5):409-427.

Söderlund, J., 2010, Knowledge Entrainment and Project Management: The Case of Large-Scale Transformation Projects. International Journal of Project Management 28(2):130-141.

Spalek, S., 2012, The Role of Project Management Office in the Multi–Project Environment. International Journal of Management and Enterprise Development 12(2):172-188.

Srikantaiah, T., M. E. D. Koenig, and S. Al-Hawamdeh, 2010, Convergence of Project Management and Knowledge Management: Scarecrow Press.

Stam, A., and A. Silva, 1997, Stochastic Judgments in the Ahp: The Measurement of Rank Reversal Probabilities. Decision Sciences 28(3):655-688.

Stretton, A., 1994, A Short History of Project Management: Part Two: The 1970s. Aust Project Manager 14(2):48.

Tan, H. C., P. M. Carrillo, Ch. J. Anumba, Bouchlaghem. N., J. M. Kamara, and C. E. Udeaja, 2007, Development of a Methodology for Live Capture and Reuse of Project Knowledge in Construction. Journal of management in engineering 23(1):18-26.

Tang, A., P. Avgeriou, A. Jansen, R. Capilla, and M. Ali Babar, 2010, A Comparative Study of Architecture Knowledge Management Tools. Journal of Systems and Software 83(3):352-370.

Teerajetgul, W. , and C. Chareonngam, 2008, Tacit Knowledge Utilization in Thai Construction Projects. Journal of Knowledge Management 12(1):164 - 174.

The Standish Group, 1995, The Chaos Report.

The Standish Group, 2003, The Chaos Report.

von Krogh, G., I. Nonaka, and L. Rechsteiner, 2012, Leadership in Organizational Knowledge Creation: A Review and Framework. Journal of Management Studies 49(1):240-277.

Walker, D. H. T., and D. Christenson, 2005, Knowledge Wisdom and Networks: A Project Management Centre of Excellence Example. Learning Organization 12(3):275 - 291.

Ward, John, and Elizabeth M Daniel, 2013, The Role of Project Management Offices (Pmos) in Is Project Success and Management Satisfaction. Journal of Enterprise Information Management 26(3):316-336.

Whittaker, B., 1999, What Went Wrong? Unsuccessful Information Technology Projects. Information Management & Computer Security 7(1):23-30.

Wideman, R. M., 2002, Comparing Prince2® with Pmbok®. http://www. pmforum. org/library/papers/Prince2vsGuide3easrd1. htm. Acessado em 1(04):2004.

http://www/

292 Bibliography

Wiewiora, A., C. Liang, and B. Trigunarsyah, 2010, Inter- and Intra- Project Knowledge Transfer : Analysis of Knowledge Transfer Techniques. In PMI Research and Education Conference. Gaylord National Hotel & Convention Center, Washington DC.

Wiewiora, A., B. Trigunarsyah, G. D. Murphy, and C. Liang, 2009a, Barriers to Effective Knowledge Transfer in Project-Based Organisations. International Conference on Global Innovation in Construction Proceedings, Holywell Park, Loughborough University, 2009a.

Wiewiora, A., B. Trigunarsyah, G. D. Murphy, G. G. Gable, and C. Liang, 2009b, The Impact of Unique Characteristics of Projects and Project-Based Organisations on Knowledge Transfer, 2009b.

Wiig, K. M., 1997a, Knowledge Management: An Introduction and Perspective. Journal of Knowledge Management 1(1):6 - 14.

Wiig, K. M., 1997b, Knowledge Management: Where Did It Come from and Where Will It Go? Expert Systems with Applications 13(1):1-14.

Yazici, H., 2009, The Role of Project Management Maturity and Organizational Culture in Perceived Performance. Project Management Journal 40(3):14-33.

Yin, R. K., 2003, Case Study Research: Design and Methods. Thousand Oaks: Sage.

Yin, R. K., 2009, Case Study Research: Design and Methods: Sage Publications, Inc.

Yuan, M., and J. Yang, 2009, A Knowledge Management Framework to Promote Infrastructure Project Sustainability, 2009. Vol. 29, pp. 31st.

Bibliography 293

294 Appendices

APPENDICES

Appendix A - The Case Study Protocol

Background A.

Project Management Office (PMO) is a new approach to improve the quality of managing

projects. Knowledge Management (KM) is recognised as a crucial factor for delivering

successful projects. Contemporary organisations are strongly recommended to develop their

project activities through utilising PMO maturity models. The existing PMO Maturity

Models (PMMM) are process – based, which advise appropriate project management process

for each level of maturity.

Despite the importance of KM in a project, however, KM practices have not been

considered in the mentioned models. In other words, PMMM have not been addressed as to

how knowledge should be managed for each level of maturity.

In order to achieve research objectives the following research questions have been

proposed:

1. To what extent are KM processes and practices employed in the PMOs?

2. How do KM practices contribute to improve the maturity level of the PMO?

3. How can knowledge be integrated in the PM maturity model?

The Case study method has been chosen to cover the above-mentioned gap through

investigating the role of knowledge in different PMOs. The main criteria to select

appropriate cases are those organisations that:

I. Have an office, centre or unit for managing their projects; II. Utilise project management methodologies for managing projects, PMBOK or

PRINCE2; III. Use a methodology to develop their project management centre/unit; and IV. Show strong support of top managers for developing this centre/unit.

This protocol aims to explain key concepts, design of case study, data collection methods,

procedures and appropriate instruments for conducting case studies.

Key Concepts B.

The following specific terms will be regularly used during this research:

• PM is defined as the application of knowledge, skills, tools, and techniques to

Appendices 295

meet project objectives (Project Management Institute 2008a). • PMO, PM Unit/Centre is an organisational unit for developing PM

methodologies and practices through following proper PMMM (Project Management Institute 2008a).

• PMMM is a process-based model to establish and develop PM office or unit in five levels.

• KM is defined as a systemic and organisationally specified process for capturing, creating, organising, transferring, utilising and maintaining both tacit and explicit knowledge of project team members

• Explicit Knowledge is articulated knowledge that exists in current documents while

• Tacit Knowledge is embedded in individuals’ minds and it’s difficult to be transferred or documented.

• KM Practices are best practices or processes for Capturing; Creating; Organising; Transferring/Sharing; Utilising; and Maintaining that have been utilised and/or planned to be employed for managing knowledge within a project environment.

Case study design C.

In order to collect accurate as well as adequate information, multiple cases will be chosen

instead of one case. The ideal number of cases is 5 or 6 , however, we have planned to

undertake this research with at least 3 case studies. The units of analysis are PMOs, PM

centres or units within organisations. Also, holistic approach will be conducted instead of

embedded one.

For achieving quality outcomes, both data and methodological triangulations will be

managed. For methodological triangulation interview, observation, documents analysis

and questionnaire have been chosen while for data triangulation, multiple sources of data

such as organisational information and documents, current processes and procedure and

individuals’ thoughts or beliefs will be investigated.

Case study procedures D.

Followings steps will be preceded during case study implementation:

1. Getting formal agreement from organisational authorities; 2. Obtaining QUT’s Ethic Clearance; 3. Asking organisation to appoint liaison for communications during case study; 4. Assessing and determining the maturity of the PMO, if it is required ; 5. Conducting the in-depth interviews; 6. Undertaking focus interviews; questionnaires; document analysis and

observations; 7. Managing the obtained data; and 8. Analysing case study outcomes through utilising appropriate analysis methods.

Data collection methods E.

296 Appendices

The following methods will be employed for collecting data:

Interview F.

Two type of interviews will be undertaken: In-depth interview; and Focused interview:

For the in-depth one, numbers of questions, will be asked (please see attachment).

Afterward, the focused interview will be managed based upon findings of in-depth

interviews. Both conversational and two-way communications will be managed for all

interviews. This method will be undertaken through following steps:

1. Introducing researcher; the study and aims of interview ( approx. 2 mins) 2. Explaining concepts and key words: PMO, Maturity models; KM practices (

approx. 3 mins) 3. Requesting interviewee to study ,then sign the confidentiality and ethics form

(approx 5 mins); 4. Getting interviewee’s permission to record the whole interview; 5. Asking proposed research questions (approx. 45 mins); and 6. Terminating the interview and asking his/her contact for further clarification if

required.

Direct Observation G.

This method will be employed alongside the study implementation through observing and

recording what researcher notices during case. Participating in the project meetings, formal

and informal discussions, studying existing KM practices or applications in the PMO and

other type of observations will be part of this technique.

Questionnaire: H.

Alongside the other data collection methods, self-administered type of questionnaire will

be employed to improve the quality of research data. It will be conducted among targeted

respondents: Top managers; Project managers; PMO specialists; PMO staffs and PMO

consultant through utilising appropriate facilities, namely Key Survey software.

Documentations analysis I.

This source of evidence is the only explicit knowledge within project environments.

Researchers might obtain insightful information about targeted cases through investigating

administrative documents, work procedures and processes, instructions, reports and other

similar documents.

Managing obtained data J.

• Developing and maintaining Case study database through utilising NVIVO 7 and MS Excel in order to organise appropriate database for case study findings.

• Providing meeting minute for each interview and meeting, then, sending them to participant(s), and, documenting in word or PDF format.

• Providing A comprehensive list of interviewees

Appendices 297

• Analysing recorded voices then, confidentially, keeping them in appropriate places.

• Keeping organizations’ confidential documents then, returning them after investigations.

Providing comprehensive report for each data inquiry method.

Appendices 298

Appendix B - The research questions and Survey-questionnaire

SECTION A: INTRODUCTION TO THE RESEARCH (2-3 MINS)

1. Introducing myself and the research. 2. Explaining required concepts: Knowledge Management (KM), Project Management

and etc. 3. Ensuring that confidentiality and ethics consent form have been signed. 4. Asking for permission to record the interview. SECTION 1: DEMOGRAPHIC (5 MIN)

5. What is your current position in your organisation? 6. What is your education and background? 7. What is your professional background and how long is your experience in Project

management? SECTION 2: GENERAL INVESTIGATION QUESTIONS

8. Please explain what types of project your organization undertakes ( in terms of Research, Strategic, Client ordered, process improvement and etc)

9. Please elaborate how projects are started and finished at your organization (how they are initiated, planned, executed, monitored and closed)?

10. What are methodologies of PM utilized in your organizations? (PMBOK, PRINCE2, Agile and/or others)

11. Has your organization established/developed PMO or a unit to coordinate organizational projects?

12. How the PMO/PSO contributes for managing projects at your organization? 13. How you could find the required knowledge/information, during the project’s phases

(from Initiation to Closing)? Please elaborate it by providing an example(s). 14. How your PMO/PSO contributes to provide, organize and/or create the required

knowledge/information for projects? If you don’t believe so, please explain your expectations.

15. Do you know what the PMO’s level of maturity is? SECTION 3: INVESTIGATION BASED UPON THE MOST RECENT SUCCESSFUL PROJECT

At Initiation phase

16. What kinds of documents/information were required and how they were provided (practices or Technology)?

17. How did you provide the required resource, especially knowledge resources at this stage?

18. How did your PMO contribute to provide above mentioned resources and information?

19. What should have been done or developed to improve the quality of this phase? At Planning Phase

20. What kinds of documents/information were required and how they were provided

Appendices 299

(practices or Technology)? 21. How did you provide the required resource, especially knowledge resources at this

stage? 22. How did your PMO contribute to provide above mentioned resources and

information? 23. What should have been done or developed to improve the quality of this phase? At Execution Phase



26. How did you manage changes during the execution and how the new knowledge managed?

27. How did your PMO contribute to provide above mentioned resources and information?

28. What should have been done or developed to improve the quality of this phase? At Monitoring and Control Phase



31. How did you manage the corrective actions as well as corrections? 32. How did your PMO contribute to provide above mentioned resources and

information? 33. What should have been done or developed to improve the quality of this phase? At Closing Phase



36. How did you dismiss /terminate the cooperation of team members? 37. How did your PMO contribute to provide above mentioned resources and

information? 38. What should have been done or developed to improve the quality of this phase? 39. Do you believe that your project environment/PMO contributed to create

knowledge?

• If yes, please explain what kinds of processes, practices, technology and/or software were used to create the knowledge. Please provide an example.

• If no, please explain what was missed? And how it could have been done better. 40. Do you believe that knowledge was properly captured for that project?

• If yes, please explain what kinds of processes, practices, technology and/or software were used to capture the knowledge. Please provide an example.

300 Appendices

• If no, please explain what was missed? And how it could have been done better. 41. Do you believe that the project’s knowledge was properly transferred?

• If yes, please explain what kinds of processes, practices, technology and/or software were used to transfer the knowledge. Please provide an example.

• If no, please explain what was missed? And how it could have been done better. 42. Do you believe that there were some facilities to help you for reusing existing

knowledge?

• If yes, please explain what kinds of processes, practices, technology and/or software were used. Please provide an example.

• If no, please explain what was missed? And how it could have been done better. 43. Please recall one of the projects which was less successful or failed, Do you believe

that proper knowledge management would contribute to success of project?

• If yes, please explain what kinds of techniques/technology should have been used.

SECTION 4: RATING THE IMPORTANCE OF PHENOMENA

44. Please rate the importance of following knowledge types at each phase of project (1 is the lowest and 9 is the highest level of importance).

Type of knowledge/ Project Phase Initiation Phase

Planning Phase

Execution Phase

Monitoring phase

Closing phase

Project Management Knowledge Knowledge about Procedures

Technical Knowledge Knowledge about Clients

Costing Knowledge Legal and statutory Knowledge

Knowledge about suppliers Knowledge of who knows what

45. Please fill out the following table in order to describe how the required knowledge is

provided at your project environment.

Type of knowledge/ Provision

Exists in Organization

or PMO

Is accessible through existing

procedures

Should be Captured by staff

Should be Created by

staff

Should be Shared/transferred

by owners

Yes No Yes No Yes No Yes No Yes No Project Management

Knowledge

Knowledge about Procedures

Technical Knowledge Knowledge about Clients

Costing Knowledge Legal and statutory

Knowledge

Knowledge about suppliers

Knowledge of who knows what

Appendices 301

46. Please rate the importance of following Knowledge Management processes at each phase of project (1 is the lowest and 4 is the highest level of importance).

KM Process / Project Phase Initiation Phase

Planning Phase

Execution Phase

Monitoring phase

Closing phase

Capturing Creating

Transferring Reusing

47. From knowledge management Point of view, please rate the importance of following sub-processes. (1 is the lowest and 5 is the highest level of importance at each phase).

Knowledge Capturing sub-process

Level of importance

(1 to 5) knowledge Identification

knowledge Filtering Knowledge Selection Knowledge Storing


Knowledge Transferring sub-process

Level of importance

(1 to 3) Knowledge Distribution

Knowledge Sharing Knowledge forwarding

Knowledge Creating sub-process

Level of importance

(1 to 4) Knowledge formalization Knowledge Codification

Knowledge Representation Knowledge Mapping

Knowledge Reusing sub-process

Level of importance

(1 to 4) Knowledge learning

Knowledge Applying Knowledge Integrating

Knowledge adapting

48. Is there anything that I have missed? 49. Do you mind to be approached for complementary information if required? If yes

please leave your contact detail.

Appendices 302

Appendix C - Ethics Approval

Appendices 303

304 Appendices

Appendix D - Samples of interview transcription in SCIENCO

In.Sc.1 Interview

Demographic A.

Interviewee’s background

Senior Manager

General Investigation B.

Types of project being undertaken

R . So in terms of the sort of project it’s a research and development project but it has a commercial outcome in the sense that it’s being prepared for a, or it was being done directly for a commercial client

Project management methodology

R: in general there’s not a formal methodology that’s been outlined. We’re beginning to develop tools within the organisation that stage a project in various ways. So that you’re required to fill out a range of different forms associated with various stages of the project but not, but there really isn’t a specific methodology no.

PMO’s status

R: There are people who are called project support officers but their role is probably more along the lines of… I wouldn’t say book keeping but it’s effectively keeping track of and giving …reports about hours booked to the job, you know budgets that kind of thing. So there’s, there are people who can help us to get those reports out of the, out of SAP which is the accounting/management software that we use across the organisation. Now we can do that ourselves and typically I’ll do that myself but they will also produce reports for us from time to time so…

How PMO contribute to Project management

R: Well currently and this is something that I think has been missing for a while. There isn’t a kind of easy way of maintaining what we used to call production control back in my previous order which was maintaining control over the various aspects of the system that we’re actually running. Yeah. So for example labor keeping track of labor in a more real time manner. I mean we do, we can batch report things from month to month but it’s still a bit of a clunky process. Better management of things like materials procurement, things like that. There’s probably a bit of a disconnected as well between the dynamics of a research and development organisation and the structure of this program. So this program would, SAP was originally designed in a manufacturing context where you know everything was fairly predictable. You know the system may change but there are fairly basic rules that everything develops by. In a research and development environment typically most of our projects begin with us not knowing the research outcome when we start. So we will make an offer to a client or a customer to

Appendices 305

help solve a problem of theirs using some kind of technology but we will be very clear and upfront that in a research cycle we may find out that some of the methods that would work won’t work or that things are not going to proceed as easily as what we thought. And this happens all the time, it’s very common to say oh well we believed that this particular sensor or this technology would resolve the problem.

How your PMO help to manage project knowledge

R: I suppose in terms of knowledge management there’s umm I mean there’s the research knowledge, the technical knowledge associated with particular problems and outcomes in a project and that’s probably reasonably well managed because of course in the context of the research work we do we have a kind of a split priority. We have the priority to achieve the project outcome but at the same time we also have a research priority to do things like get publications or possibly file the patent for a technology or something like that. So there’s those two outcomes and typically the organisation is quite good about emphasizing the importance of publications and things like that. So the research knowledge is usually better managed from that point of view however, the practical knowledge of the use of the technology or the implementation of the technology in a project, that sometimes varies. There is again the potential for a disconnect there. How will I explain it? Umm….the implementation of a…of a technology or some new research based knowledge in an area in a particular sort of area, a mining area…is often half the battle. Maybe three quarters of the battle because the environment is usually very difficult and sometimes dangerous and therefore given the opportunities to actually implement the technology at the coal face which can be very difficult. So, the process whereby that’s done need to be better captured and better propagated to other people because it seems very often that whenever we come to do a new project we’re starting again from square one to try and do ….relearn the lessons that we’ve already learnt on other projects. So that’s an area of issues.

R: no I think it’s largely the project officer or the project leader’s responsibility to attempt to manage that. Certainly for the practical knowledge of project processes umm unless the project officer or the project leader themselves decided to capture that knowledge in some way or develop some kind of personal system, there’s not really a strong system there to do it. No well certainly not in my experience anyway within the division and the flag ship that I typically work. Also , there is no system strategy or process for managing knowledge, it means that , we are at the beginnings of a…you know they are taking steps in this direction so we probably umm you are probably asking these questions at a time where I think there is a growing awareness of this issue. So some very simple things for example that have been passed on and just not being done that we recommend. Are things like post project reviews, for example, going back and actually performing a formal post project review. There is now umm a form to do that which they’ve developed. However, I think oh well I think that’s been developed for a little while, it isn’t typically enforced. Usually what happens is that there’s a limited time available as there always is and there comes a point where a project is completed and people race off to do the next project. And there’s usually very little option or time for or time made available to actually do a kind of a formal post project review. You get ad hoc ones there’s a….

306 Appendices

Level of PMO Maturity

R: Probably I’d have to say fairly mature. It’s not…..the management system SAP is relatively recently introduced, it’s only been with us for three or four years and it’s been quite a struggle to convert people over to that. And I think the role of the project support officers has generally been just to help people who can’t use the software to get the information out of it. But there certainly is not a, typically it’s not a very proactive role. They will you know send you an email when an invoice is due to be paid on a project for example and you’ll have to explain why it’s not going to happen or why it is happening. However, apart from that there’s not really a structured approach to providing support for the ongoing project management. So typically it’s left up to the individual in charge of the project.

Expectations from PMO

R: So typically the expectation there is that we need to be able to dynamically adjust the parameters of the project outcomes and deliverables in order to cope with the realities that we discover as we do the research process. So this is a difficult concept to put into the context of a very rigid umm kind of a management trading system where you know the expectation as you said, you were going to invoice at this stage of the project on such and such a day. And then you know you need to go through and try to manipulate the system to accept these changes. So it’s a…in one sense it sounds like a trivial thing I suppose. It’s not a you know it’s a matter of managing a piece of software but it’s more the context of the … a fairly rigid structure associated with the expectations about project outcomes compared with the more dynamic reality of what actually happens. And usually what happens is that we, to bridge that gap, we, the project manager has to fill in the detail with a lot of explanation and running back and forth and often times trying to convince the client that look you know if you can see your way clear to allow us to invoice you for this stage, we’re hopeful that we’ll be able to resolve this issue at the next point or something like that.

Investigating the KM at project stages C.

Initiation Phase

What sort of document /knowledge are given

R: Okay well I guess there’s the usual basics for an approach of our sort of, we need to know….the scope of the project. The customer, the key deliverables, the time frames, the budget and during the project initiation stage I guess just to clarify are we talking about when we’re at the project proposal stage or are we at the point where the project has been approved? Would you be, do you mean so for example….

How the information are/were provided

R: Alright well typically the process that happens just to give you the understanding and there might be a little bit of blurring here between the different phases because of this. We will either approach or be approached by potentially somebody in the industry and they have a particular problem in their area. So the mining area. And we would propose a technology solution to them. Now to do that we usually will prepare a short

Appendices 307

document, two or three pages describing the sorts of technologies that we think could be used to do that. So in that document there is already …there is already the beginnings of the thinking about planning but it’s not a formal proposal as yet. If the customer or client is interested then they may ask for a formal proposal at which point we will prepare a more extensive document that will probably include a basic project plan like a Gant chart with some time frames and deliverables and we’ll give them a budget for the project.

How PMO/Current system contributes

R: usually at this stage the proposal is simply logged within our publication system. Our electronic publication system, usually….what we do do is we prepare what’s known as a CCF a common costing framework. It’s an elaborate spread sheet that allows the…allows the budget to be worked out accurately so that you can list the people that you want involved in the project and their pay scales. The amount of time that you believe that you want from each of them, the materials’ budgets and things like that. And then you can go through and determine the sort of project that you’re talking about. So if it’s a new technology and development and collaboration then there’s one kind of pricing structure, if it’s direct consulting work there’s another so there’s a range of them and you’ve got to sort it out through that. That project that system allows us to set a formal budget that’s acceptable within SCIENCO in the first step to approval. And then depending on the size of the project that’s been proposed it will then have to be approved at various levels. So up to I think about sixty thousand dollars I think can be approved at the project manager level or one level up. What we call the stream level. Above that say up to about 250 thousand or something it goes to the next one, there are various levels you know for approvals. So all that process kind of defines the context and the parameters of the project. But then in terms of the knowledge beyond that, so I guess I would call that project initiation and if the client has accepted that, has accepted that process, has accepted that….

Expectations to make it better

R: It’s the notion of the project pipeline which is something they’ve been trying to gradually work on but it’s still I think largely not well understood by most of the project leaders and doesn’t as yet provide an easy one stop shop. But the idea that they’re trying to do which I think is good is that all projects should be registered within a common system and the basic area and domain for that project works across should be easily flagged. So there needs to be you know whether it’s a key word type scenario or something like that so that you can search and filter on a range of, you know across all the projects that have been done in the organisation to find out who is working with say scanning lasers for example. You know if I had a project that’s using a scanning laser system and then find out well who is doing the work with you know profile measurement using that kind of instrument or something like that. However, the system isn’t at that stage yet. The idea is there but that’s the kind of thing that I think would need to happen because all too often we find ourselves looking at or working on things and then finding out you know these guys have done something similar. So usually because of the knowledge that’s around in the general population things don’t go too far before somebody puts their hand up and says oh hold on I do that. and researchers

308 Appendices

and scientists tend to be very who are very protective of their knowledge domain. So because of that people pretty quickly let you know if you might be transgressing into their area. But it would be a lot better obviously if it was a system whereby you didn’t have to stumble upon it through that way. And so ….so at the moment the PMO doesn’t do what I think it needs to do is to provide a system whereby those sort of fundamentals can be flagged and people can identify okay well this is something….and as you say not only to avoid you know issues with people who…. You know from other divisions or outside your own group but even within your own organisation. We have a pretty good feel say the group that I work in my team is about five people or so but I’m in a group of about 25-30 people and we know pretty well what we all can do and people have a pretty good idea of what people have worked on. But it’s still umm there is still a specific need I think to be able to search through a PMO to identify or individuals or identify the particular individuals that have worked with a particular type of technology. And again there’s no formal way to do that. So as a project manager or project leader I might know vaguely that this person over here has experience in writing visualisation software. But it would be a lot easier if I knew that there are three people who have had specific experience with this type of technology and I can discuss with them or with their team leaders to find out about their availability for a project.

Ordering the KM process at PMO

R: Well we umm the creating and capturing is still not happening well enough for us to be able to, I mean it is creative to an extent and it is captured in various forms. Well I suppose if you really want to say you’d probably focus on organising because the umm it is created in various forms. But no doubt the information is out there and it’s captured for various reasons. But umm it’s like they’ve poorly written relational data base where you’re storing the same information in lots of different places and sometimes it’s contradictory when in fact it ought to be stored in a common location and then able to be queried for specific reasons. And that’s what we really would like to have. So yeah organisation is probably key there

Planning Phase


R: Okay the formal requirement internally once we get to the planning phase are not very, there’s essentially once the project has been awarded and commenced so we’re into that phase of planning how it will actually be executed. We do have to provide, the key thing really that’s required for the PMO is the project timeframe. The deliverables but even still, even within that context they are really mostly just interested in the milestones and the invoices associated with them. So we might from a project point of view be saying I need to deliver this technology by the 10th June or something and then the client will be invoiced to that milestone. From RMT side of the things the only thing that the 3 dimensional system requires is milestone on the 10th June, invoice payment of forty thousand dollars or whatever, that’s it. There’s not a great requirement from that point of view to do much more in terms of the project management. Oh except of course they do require the knowledge of how the people’s time will be spent. So labour has to be planned in terms of you know people’s time will

Appendices 309

be allocated, so many hours for that month. So say I have a project with a dozen people working on it, I am required to plan out where their time will be allocated throughout that project. However, typically what happens is the system automatically will just allocate it across the board on average. So if I’ve said that I need a particular person for twenty per cent of his time for the next six months then the system will just boom, boom, boom, boom for the next six months, it will put him in at twenty per cent each month and that will be that. You know I can if I choose to, I can go back and request that, well in fact I believe that I’m only in for eighty per cent for the first month and then only ten per cent for the rest. I can make that kind of request but ….


R: In that context one of the things that has to be reviewed and it’s not probably managed as formally as what it could be, it still needs improvement I think, whenever you are proposing a new project you are potentially developing or discussing or proposing technology solutions. And there is the issue of umm the potential to, that intellectual property is created that SCIENCO needs to manage carefully because that’s our key product if you like is intellectual property associated with the project. And so one of the things that is supposed to happen in the initiation phase is that the project proposal is reviewed by various people within the management chain in order to say are we offering something to the client that we want to protect from an intellectual property point of view? And if so how do we define that? So umm there is a procedure there to do that in a sense that the various levels of management are supposed to review and identify those kinds of areas and it’s up to the project leader to kind of at least give them an idea. But umm again as I say, it’s probably not a good, there’s no good formal mechanism whereby that can happen. So it’s still you know largely based on reading the proposal, having conversations about it and then making a decision. You know which works up to a point but umm in terms of a formal knowledge management system it’s not really there.

How PMO/Current system contributes

R: there’s no formal mechanisms for that at all. In fact that’s probably one of the greatest challenges within the organisation is the fact that there isn’t a straight forward way of even finding out you know is this a domain which somebody else might already be doing something in another division for example in SCIENCO. And as you can imagine a very large organisation spread out across Australia and often it’s only by word of mouth that you might find out oh actually somebody down in Sydney was doing something similar to that you know five years ago or eight years ago or something. But there’s no, the PMO doesn’t provide help in that way. I mean it’s up to again the project leader to search on the intranet and find out if anybody within SCIENCO has … There is a system but there’s no incentive or reason to do that because how will I put it? Well in the end all they ultimately care about is that the books balance at the end. So that as long as the time is covered and you know the invoices are paid on time the system doesn’t really care too much and the project support officers are really only there to ensure that the books balance or that the times add up. So, it’s you know they do want to know about large capital items. So for example if I’m working on a

310 Appendices

project, I had a very large project over in Western Australia a few years ago and there were some very large capital items that had to be purchased. And so I did need to let them know well okay in April we’re going to need to spend thirty thousand dollars on some equipment, boom. And then you know a couple of months later you know a bit more. So that kind of thing they like to know but again it’s the motivation is primarily from the point of view of managing cash flow and budgets. So it’s not, it isn’t really done for the sake of the project it’s done for the sake of the organisation. I: How does the intranet work or you know for instance find for instance so people know? R: Not real good it could be a lot better. It could be a lot better because they are attempting and they are attempting to try to standardise a little bit more the structure of the different groups and things so that you can search for key words about what various people have worked on. But it’s still a long way from being really well developed and there’s still a lot of knowledge which is retained in people’s heads basically. People who have been around for a long time and they know that that fellow down there was working on a project like this ten years ago. So no the PMO doesn’t really capture that knowledge or make it easily available that way.

I : Does your PMO ask any kind of information knowledge at this stage? R: Let me think just to make sure. I would initiate…at first glance I would say no, you just think if there’s any way that it does. Again probably not in a formal way. There is the, during the planning process there is the opportunity for management to identify or to request that we essentially protect certain parts of the intellectual property that we might be creating. And certainly capturing some kind of record of that might be requested but it isn’t a part of the, it’s not really a part of the PMO. It’s not part of what the, a formal part of the process. So once you get to this point it really does become more about the project leader managing that, you know in a more personal way, sort of an ad hoc way. I: What sorts of practice or process or procedure are being undertaken by your PMO? R: Let me think. I’m just thinking of their performance at the project and I …at the planning stage I don’t believe so, no, no. I don’t believe there’s any formal process. the knowledge that is come through at the planning stage is purely the structural knowledge associated with that particular project and its particular financial parameters. It isn’t really associated with the knowledge generated in the project or even the plan of knowledge of umm so typically that kind of thing will be bigger. Will actually be happening on an informal basis, not only by the project leader but also I suppose by graduate staff as they start to develop their plans for what they’re going to do. But it’s not a, it’s not, there’s nothing in the PMO that really captures that I don’t believe.


R: I think probably at the planning stage, because again the planning stage things are still….not aware and it may not be known. But ideally would be the first thing that allows you to begin a register of potential knowledge base. Not knowledge of you

Appendices 311

know new knowledge that’s going to be developed in the project. So for example a system whereby fairly quickly and easily you could say well this project umm is going to be associated with the following work. And just you know and at the planning stage has identified we’re going to be developing you know knowledge associated with this aspect of this industry. Using this technology perhaps umm something that collating or at least classify in broad categories or domains the kinds of areas that we’re going to be working in so that when you go back to it later on you’re able to say well…or when somebody outside the project looks at this information they can say okay looks like you’re going to be working in the areas of X, Y and Z and they can provide some input or help to assist you. Or they can say well that looks very much like a project that we have here that is doing something similar. So you can just kind of classify in broad terms the knowledge that is likely to be generated. That would be sufficient I think at the planning stage. Just to… I: So what about knowledge capturing? R: Well because as I say at the planning stage typically there’s not, the knowledge that’s generated at the planning stage is typically, well in my experience, it’s not very significant. Or it’s not a very complete knowledge. You know ideas are being generated but they’re largely uncertain. Speaking from a research and development point of view if you are working with something that you know all about already you can probably have a very clear idea. But if you’re working with new technologies or technologies that haven’t been applied to that problem it’s likely that umm you won’t have specific knowledge. What you’ll have is hypothesis. So you will hypothesise that I will be working with this sort of equipment, I will be doing something in this area and I think at the planning stage it would be sufficient to be able to categorise the kinds of domains that you’re working in and then as you then move on from the planning stage you can begin to fill those, fill in the details. So you’re basically at least laying the ground work for the kind of knowledge map if you like that’s going to be developed later on. So you …it just gets you out in the big areas but you may not have a really clear idea of what’s going on at that stage. If that makes sense?

Execution Phase


R: Same question and I’m ….I guess I’m trying to think of it in execution context specifically now. Again the PMO is not umm really set up to deliver that kind of information or knowledge in any formal way, at least that I’m familiar with.


R I suppose the process is umm…the processes are there to a certain extent but again they’re largely informal. What will happen or semi-formal I should say. Typically within your group we will organise projects or group meetings where we will review projects and discuss the status of the project during the execution phase. So what that will involve is sometimes everybody in the group but more typically the sort of the leadership team. So the team leaders [?] leaders came in together and discussing what’s going on with their projects and where they’re at. And through that process there will be opportunity for people from outside the project to provide input to the

312 Appendices

project to say look if you’re working on such and such have you considered doing this or that. so from that point of view we’ve developed mechanisms whereby we seek to provide knowledge to the project leader about the situation that they’re in. But it’s not done through a structured project management system. It’s done through a…it’s largely done I would say on the capability side. So it’s done from the group and team structure looking at, oh you’ve got a project working in this area and we have people with capabilities in this area, let’s talk about how those things can work together or let’s get some ideas going about that and what can be done. I: Do you have this kind of meeting for instance for planning or… R: The meetings will be usually fairly regular and they’re not specific to one project. So they will be across…. I suppose from that point of view you could say that those meetings could apply across the various stages of the project because they’re not typically, they’re typically organised as I said on the group level. So if you think of this matrix management model, in a group we have a range of people who are project leaders. Or working on projects. And those projects may be at any of the different phases when it comes time to discuss, in our regular meetings, what’s currently going on, what are people working on? So at any time within the project management cycle I suppose it’s possible that you could be discussing with others this is the situation that I’m working on, these are the sorts of challenges that I’m facing or I think I will face. And then it’s an opportunity to discuss those things and to have other people provide input. So I suppose that’s probably, and I guess I neglected to mention it in those earlier phases because usually the focus in those meetings is on the projects that are currently happening. So it’s on what …so it’s much… So people might say oh I’ve got a project that I’m trying to get up in this area and people might give some advice about that but it’s usually the focus will tend to be on what’s going on now. What are we doing and what can we, you know, how is everything tracking? You know do we need extra resources allocated to this project at the time and certainly from a knowledge management point of view there’s two questions I suppose that come up fairly regularly. One is how can we help you kind of thing, other people thinking about oh you’ve got a problem here could we do that? And the second one is probably what sort of intellectual property is being generated in the project and should we be thinking about publishing or possibly signing a patent or doing something like that. so there’d be an intention to try and capture knowledge to a certain extent through that mechanism. So as I said the organisation is pretty strong on you know the fact that our product if you like is….intellectual product is knowledge. That’s the product that we have. And so capturing that at the various stages whether it’s through publication or through umm patents or similar things or.. you know modifying the commercial terms of a project for example. Or making sure that the commercial terms allow us to have freedom to operate with our technology that we [?]. Those are the kinds of things that often will be discussed.

Ordering the KM process at PMO

R: we’re probably pretty good on the creation and capture side of it because it’s a key part of what we do and …again talking about the matrix model if you like, the capability side, the input side if you like of the matrix…is the domain which we are

Appendices 313

concerned mostly with the creation and capture of knowledge. And that’s because the whole point of that’s the capability development is to say we want to maintain and develop our knowledge base, our capability but the organisation of that knowledge so that it is efficiently applied to the output side if you like. To the present and future projects that’s where I think there’s a bit of a disconnected. Also I’d have to say it’s probably the transferring more than anything. Because the information has this certainly created, certainly captured….it seems quite well organised in the sense of being in its own domain. If the knowledge is well organised, well-structured you could go there but it isn’t being transferred into a kind of a useful format from a project management point of view. Yeah it’s probably still in the organisational side again I think yeah you have to have those basic organisational things done before you can then do that kind of transfer. So I mean every…you know there would be issues on the transfer side as well but that is first things first yeah.


The PMO is primarily focused on budgets and invoices and the formal financial aspects of the project. R: There is definitely I mean that’s yeah I wouldn’t want to minimise it completely. They do do a good job of capturing the I guess the basic stuff, the bare bones of the project what the you know what the project is, how it is structured and what’s going on. So there’s no doubt about that, it does all that kind of thing very well. But the meat of the project and how that is…is…. Everybody is very clear about it and everyone is conscious of it but they’re not really as concerned about how that is made available to existing or new projects. I: so what do you think that would be good to your PMO? R: In terms of knowledge management umm I’m trying to think of the best sort of way that that could happen. I mean I think what needs to happen is that the umm the information that’s been captured already through the structures [?] called e-publish for example where papers and reports of all sorts, internal, external you know publications, papers, everything is logged or is supposed to be logged into this e-publish repository. So we have a very well structured mechanism for capturing that kind of knowledge creation and….there’s no real connection between that and an appropriate management structure. What would be ideal would be, as you say, an effective knowledge management system that allows that kind of information to be umm searched, interrogated, examined, from the point of view of the project so from the point of view of matching a project’s deliverables or outcomes with the capabilities and the knowledge that’s already been generated. At the moment that isn’t typically done.

Monitoring


R: …project progress and a similar kind of dynamic. So in terms of information and knowledge provided for the project the basic framework of the project as we’ve already discussed is provided you know. We are kept informed of is the budget on track you know. We are notified you have a milestone coming up, you need to invoice.

314 Appendices

If you can’t can you explain why? So those basic I suppose you know baseline, bottom line things that are managed but in terms of providing information, knowledge or guidance through that process there’s probably not a lot. It’s not very strong at all and certainly in terms of providing some means of using that information from prior learning from projects it’s probably pretty weak I’d say. Again it’s more the informal knowledge of the project leader who has done projects before and has had experience. So. I mean that is one of the things that they put into the structure in the initiation phase I didn’t mention. But it is you know the project leader is if you like ranged in certain categories in terms of have you done projects in this sort of domain before? Do you have you know how much experience do you have? What’s the biggest project you’ve managed to date? All that kind of thing. So there is a process of trying to establish the credentials if you like of the project leader and that is associated with the project risk. So there is you know there is the notion of the amount of risk being engaged in the project. But that kind of thing is really in the initiation phase. Once the project has begun it’s not formally pursued. I suppose it’s not …it’s not usual to find an enforcement of this kind of thing as well but if I dare say some of these forms and things are available but they’re not being utilised in the sense that from time to time we’ve had you know…the information put across you know all of these things have to be filled out and ready to go for any new project. But they tend to get filed and forgotten so nobody really uses them or looks at them and therefore there’s nobody that’s really asking for a lot of that information during the time. So if a project leader is managing you know two or three different projects and they have their own research work as well it’s typically likely that they’re not going to spend a lot of time filling out forms that just get put into a directory somewhere and forgotten. So that’s just the way of things so….so again it’s a…that’s a part of the process thing. So not a lot this, again it’s the same basic the bare bones information is provided. What type of information generally asked by project managers? During the monitoring phase…well typically I suppose it’s…our expectations are matched to the, what the system currently provides. So most project managers just want to know from the system how much money has been spent. Whose you know whose booking time to my job? You know how much budget I’ve got left and more or less can I have however enough money left to finish the project. So it’s you know the bare bones financial information which is I’m not trying to minimise that. I mean that’s a key aspect to managing a project. But it does ignore the knowledge dimension a lot. You know the…it’s up to the project leader in an internal or an informal way to deal with the question of are there you know are there technical challenges that haven’t been resolved yet that I need to resolve? Or are there issues that I’m going to face in this process that could stop me from completing the project? That’s traditionally left to the project leader to use his experience or his or her experience. How change are managed R: Yeah so well typically so if there’s a change of …for whatever reason….some kind of approach or variation will have to be carried out. So if it’s a change that’s going to impact on the time or the budget then we have to submit a project variation. So at this point there is a, there’s a…the system requires that we develop a… we put together a small mini project plan if you like, again using the (6CF?) form we work out the cost of

Appendices 315

this variation work and how long we think it will take. That has to be submitted internally. And then a legal modification to the contract has to be drawn up. I should say almost all of this is on the assumption that you’re dealing with an external client. If it’s an internal strategic project that will be a very different story but those are much more fluid anyway. So I’m you know again dealing with an external client where there is a contract in place. In that sort of a context the umm the variation has to be submitted, approved by the client and then you can go on. So again it’s really, what they’re mostly concerned about is the time and the dollars. And you can invoice on time or if you can’t then there’s some… I: is here any system for change management? R: Okay again you’re spot on, there isn’t a system or a systematic way of doing that. It is umm typically again I suppose those project meetings might be an opportunity or even informal meetings between project leaders or senior people there’ll be the opportunity for conversations. People will say look you know umm well let’s say you’ve tried one type of sensor for a particular occasion and it hasn’t worked very well. You might start looking around and saying well what might work better in this scenario? But that key bit of information which is this sensor doesn’t work very well in this environment that’s not formally captured which it should be. It should be captured because it’s an important piece of knowledge that we should be building on. It’s informally captured I mean it becomes known, it becomes common knowledge if you like within the group and certainly from a capability point of view again it’s likely that you know there might even be a publication or something that comes out of it. Because you might then implement a different technology that works and it might be something new and therefore you say okay we’re going to publish some results that we’ve got showing what we’re going to achieve. But that isn’t captured by a knowledge management system at all. I: Is your KM satisfactory? R: Well that would be not certainly Expectations to make it better R: okay if you could be….a little more specific in terms of you know you can get some actual hard data usually about performance and things like instruments and stuff like that. It would be very nice if they system was able to identify and categorise the kinds of umm you know first of all the knowledge domains that you’re working in. So it might be, because it might be something about a…something to do with a piece of hardware a technology or an instrument but it might also be something to do with you know a software implementation or learning about you know finding that a particular method of processing breaks down under these circumstances. It would probably be good if they system had some way of capturing internally that kind of thing. Now I see an issue here though with the fact that again amongst research and scientific, people of research/scientific mindset there will be a tendency to kind of protect their knowledge to a certain extent. So sometimes the lessons learned may not be captured or be forthcoming because people were keen to say well oh you’ve got that information to get publication, I don’t want to just put it out into this you know…so there would be a need to reassure people that a knowledge management system is a secure system. That it’s used internally. That kind of thing just off the top of my head thinking about it

316 Appendices

that would be an issue in this kind of environment because people are very happy to view the knowledge generated to get as I said to put it into this knowledge repository to be published. To be publications or to get patents or to do anything. That’s the kind of thing that will reflect well on them, it’s useful from a career development point of view so they’ll do that. But the incentive to put it into a knowledge management system from a project point of view I think it would be, it would be important to make the system you know fairly streamlined so that people could put the information in without having to umm…well without having to sort of rewrite their publications or do you know do things along those lines. But that’s where I can see there could be some issues. You know most people are relatively open about things but I think you do have those people who will be kind of closed about their knowledge. Closing What sort of document /knowledge are given R: one of the key things at a project close out there’s two kinds of knowledge I suppose that need to be captured. There’s the …there’s knowledge related to the project processes itself. And they can be things like well we’ve learnt that this particular client is very slow at paying invoices. And they are very and we need to develop better mechanisms to deal with them or in the future we need to ensure that our contract is tighter with these guys. Because that sort of that kind of knowledge and I mean that’s just an example. How the information are/were provided R: There’s a whole host of project related processes that we might have discovered. There was a problem here or we ended up travelling to site a dozen times. If we planned it better we could have gone three times, you know something like that. Capturing that is the purpose of the post project review and as I said we traditionally although there is a form and structure for doing some kind of post project review, that hasn’t typically been used a lot. In my experience it has been used very little. So the project is done, people will write the final project report and even that they’re usually rushing to get that done for the client while they’re trying to pick up new work or do other things. And you know once that’s done the thing is put to bed. From a system’s point of view the project management system once the last invoice has been paid or it’s been invoiced, it really is, it’s no longer, there’s no longer much interest expressed Ordering Km processes R: From the point of view of the knowledge created in the project, the technical knowledge the research and development knowledge usually the staff involved are usually pretty strong about again capturing that knowledge and you know giving things like publications and whatever. That’s often if you like the reward at the end of a project for the researcher is to say when we did this project, blah, blah, blah yes but I got two publications because I got you know I did this and I did that. And that’s kind of the umm the knowledge use that’s there. So the …it’s pretty strong on capturing the knowledge. And I suppose from an organisation point of view you could say it’s even, the knowledge is in a sense organised in terms of that kind of a thing, in terms of getting you know publications done and it’s put into the knowledge register but umm

Appendices 317

the key area of relating that information to the project management system there’s a big gap there. And once again in terms of what to do about that I’d suggest yeah it probably you know is vital I think to have….some mechanism that relates the domain of operation of a project which might be a particular part of a say mining industry or particular parts, or particular clients or whatever, relates that kind of domain knowledge with the research and development knowledge that’s been produced. So that we’re able to say okay we learnt the following about the use of this type of technology in this domain and in future you know we can say do this and this and this but don’t do that. You know for a … I’m trying to think from a point of view of a future project leader trying to use the information what they would like to know is what worked, what didn’t and what don’t you know. What were still open questions? So that often happens and as I say we do tend to do that with project management. Well not project review meetings because not so much that but these group meetings we will often talk informally about how a project went and during that time again you know the senior leadership might be encouraged to discuss alternative ways of doing things or saying well we could try this and this and this. But it’s not you know it’s not been captured in any way apart from the knowledge is now shared amongst the sort of the senior leadership group. And you know maybe other staff as well but it …although that’s good you know and that does grow the knowledge of the group it’s not a…it’s not been all logged, recorded or organised in any sort of formal way. Expectations to make it better R: Yeah for sure so I think the umm the key thing that a formal system should do, it should be able to easily classify knowledge according to the kind of the capability areas. The sorts of areas in which you know the knowledge is created or the kinds of people that have the capabilities to do it. The domain of operation of the knowledge, so where is it being deployed and the limitations, the known limitations of various technologies or I mean I keep saying technologies because that’s a common one but it could be even processes or approaches to doing things. So you know what may have worked very well in one particular domain may not work very well at all in another and that might just be a process or it could be you know the way that a project has been rolled out or chosen to be rolled out might work very well for one type of but not for another. Kind of like oh as an analogy I suppose if you’re studying for physics or chemistry it works very well to memorise a lot of facts. But if you’re studying for a Maths exam memorising a lot of facts isn’t going to do it. What you have to do is do lots of …solve lots of problems because it’s the process that….so you know depending on the domain the way that you assimilate the knowledge is actually, can be very important as well. And it’s the same thing with projects. I think that sometimes for some projects where you’re dealing with umm particular types of environment it probably you probably are going to have to go through a much more formal trial process where you actually trial different technologies or things in order to see what will work. And then you should capture that information for the future whereas in other areas we may be able to say well no we’ve got a pretty good idea of what’s going to work here or even you know it’s a waste of time to trial something here because we’ve already done it in a similar area. So capturing that kind of knowledge as well, so knowledge of the domain, the sorts of technologies and the process that are working

318 Appendices

in that domain and that environment that’s the kind of thing a system should do. And again you know it’s a challenge because there’s such a thing as domain expertise within a research and development organisation and there’s probably a certain resistance, I know this is something that people struggle with when they develop sort of expert systems, there’s often a resistance to umm on the part of the experts to believe that the system is going to be able to do what they do. So they like to be the person who is approached and can you tell me what, how do you think this would work in this environment? Or something like that. So you know, I think one of the challenges facing the development of a knowledge system is that open sharing of knowledge.

General explanation D.

In terms of the sort of project it’s a research and development project but it has a commercial outcome in the sense that it’s being prepared for a, or it was being done directly for a commercial client. So it’s not a government funded project it’s a direct industry project as we call them. And it’s the genesis of the project is the background of a prior more research oriented project using the laser scanning technology to detect and volumetrically analyse coal in coal wagons and things like that. So in terms of the knowledge coming into the project there was specific knowledge that we had gained and technology that we had developed in the earlier research project but it was how will I best put it? It was a surveying tool almost. So it would acquire data and it would …it would allow statistical analysis of the target you know later on. So post processing. And that allowed us to develop the statistical information. What the new project needed to do was to use that information in real time to provide information to the client about what was going through their plant at any time. So it was an interesting because we had to transfer that knowledge in that sense from I guess very much a research oriented mode to a real time 24/7 type robust software package. In terms of the transfer of the knowledge there was also a secondary challenge. And that was in the first project I was responsible for developing a lot of the software. So although I was the project lead I really did the bulk of the work because it’s a very small research effort in some ways. Not small but it was relatively contained. But in the new project I had software engineers who had to implement the new version. So I had to transfer to them an understanding of how the technology you know worked. So in terms of tools to do that the, there are several things. One, the most basic and fundamental thing I suppose was the actual source code itself that I’d used previously. Sitting down and working with the software engineers to say okay these are the modules that are available within the source code. So that involved providing a design specification based on the source code that was available. In terms of capturing that knowledge and ensuring the software engineer in question, there was one particular engineer who had to do most of the development work, to be sure that that person had that information there was a point that I required a design document back from this person to see that they’d actually understood the processes. And I think maybe there was an opportunity for something to be done a little bit better because the …there are kind of two conceptual levels at which the thing works. There was the bare bones of the software and understanding how to make the thing work and work in real time and

Appendices 319

communicate and all those sorts of software related low level things. But there was the high level conceptual concept of how the detection process worked. And that kind of knowledge you know which is more a theoretical or research oriented type of thing was more difficult to transfer because it had to be re-implemented in a new code base. It really required that this person understood that knowledge very, very well and I think there was a… I know there was a good period of time where there was a struggle to confirm that this person understood and I was under the impression oh yes they understand what’s going on and they’ve understood it. And then it wasn’t until you know several weeks down the track that I realised that some of the fundamental ideas haven’t yet been captured here. So in terms of you know knowledge management I guess I can see there looking back on it, although I wouldn’t have used those terms, I could see that there was an opportunity there for something to be done a bit better in terms of transferring that knowledge and you know capturing what the core ideas were. In terms of tools to do that one of the things I’ve done in other projects before this and I started to do almost you know instinctively and this was to break the thing down into you know structure diagrams. Either flow charts or things like that, but also even kind of pictorial not …I’d shy away from the term you know mind map or anything like that but you know more conceptual diagrams that just sort of allowed the picture to build up in that person’s mind of what it was that I’d been doing. Because ideas you know are intangible and so difficult to manage that process obviously of ensuring that the other person really understands what it is that you’re after and why it matters. So there are certain aspects of the detection system that there were subtleties in the way that it was designed that made a big difference in how well it worked. But if you didn’t understand it you could, you might think it didn’t matter, I’ll do it my way or I’ll do it this way. So umm so that’s one thing. Then there’s the second stage of it as we’ve come to the end of that project. Well the project is still ongoing we’re still working with this client but we’re also now looking to commercialise this product. So we’re now in a position where we’ve developed documentation and put it out to various commercial entities to see if they’re interested in taking the technology on and further developing it and supporting it as a commercial product. That has involved transferring that knowledge and understanding to them. And here I think one of the key methods that we’ve often used here at SCIENCO for capturing that information comes about, and that is that we typically will look to publish. You know scientific publications of our work where it’s appropriate and inevitably in the process of developing a paper, whether it’s a journal paper or a conference paper you have to go through and explain how the thing works and break down those ideas in a much more formal structured manner because you’re producing a document for public consumption. So one of the things that happened was that I presented a paper on this project to a rail engineering conference and using that just slightly modified and a bit more detail, that formed a core technical information that we put out to tender or put out for reviews of commercial parties. So I think and I may have mentioned this last time, but I think that that’s one of the key ways that we capture knowledge and transmit at SCIENCO. Is that we have the project going on here, and there’s almost three lines. There’s the project itself and the client, there’s the kind of the knowledge capturing process of publications and papers and then there’s also this commercialisation line which is best

320 Appendices

to transfer it on. Do you believe that your project environment/PMO contributed to create

knowledge? R : No I’d say the knowledge creation is typically a fairly free process within the organisation in terms of the fact that people can use the tools that they prefer. So some people don’t use (Mal??) for example they’ll do other things. They have their own preferred methods you know people tend to be fairly umm open or free in terms of the tools they use or the processes they go through. Probably because it’s most… I: What sort of practices have you used? R: Yeah these sorts of things. Well we certainly for a lot of the things that we do and I think there’s a slightly different approach at the moment but it’s one, it was a successful large project that I managed about four or five years ago. But brainstorming sessions was one of the things that we did do, we sat down and I had an idea of how I thought something should work. And I took it to the group though and we talked through it and we spent you know several hours in several meetings going through and fleshing out the bones of how the project was going to work and how the different parts of the system would work together. So we definitely did that. In terms of sorry in terms of knowledge creation that’s definitely a tool that does get used. Being in a research organisation there’s also as I said I would say there’s probably just as often or maybe even more often will typically be one researcher who will spend a lot of time developing the concept themselves and fleshing it out and then they will communicate that idea. So there’s a kind of scientific prerogative almost of people from a science background in particular tend to enjoy that process of discovery. And we’re encouraged within the organisation to spend some time you know just working with ideas and thinking of ideas. So there’s a certain amount of time that’s made available. So that’s certainly another tool if you like is that we’re encouraged to have, we’re in a capability development time…and that might be going to a conference and getting some other ideas or doing some training. But it might even just be you know spending a couple of days reading some journal papers and doing some work in an area to try and get some ideas. With the intention that you know there’s a problem here in industry or something that we’re looking to solve and I’ve got an idea, I want to try that out. So we’ll play around and do some things. And maybe one or two people will work together and they’ll do a little trial of something and then produce you know a…what we often will do is what we do is like a demonstrator concept and this is something which for this project as well we did do. We have a weekly group mining technology discussion group we call it. The group gets together it’s only half an hour and somebody will present something on what they’re currently doing. So they’ll and you know the group is about 25 people. Not everybody always shows up, it’s usually an audience of say you know 15 people or so and you’ll present something on what you’re working on. Probably you know no more than half a dozen PowerPoint slides, some ideas and that’s a good process in terms of not only I guess it’s a combination of knowledge generation and knowledge capture and transfer because you’re proposing,

Appendices 321

you’re raising what it is that you’re proposing. During the process of delivering it people talk about it, it spreads the idea to the group…so that everybody gets a…and by the end of it you’ve had to formally connect the dots on your own thinking. Because you’ve transmitted it to others. So that’s a powerful tool within the group that we’ve, our current group leader initiated that a couple of years ago now and I think it’s been quite successful in terms of doing that kind of knowledge transfer. So that might sound a bit unrelated to the project stuff but typically things that you’ve presented are associated with particular projects that people are working on. So it becomes a method whereby it also informs the wider group of what’s going on in a particular project because we might have up to 25 people you might only have 2 or 3 working on a project over here and it’s good for others to get an idea of what’s going on. Yeah well probably there is more of this kind of thing beginning to happen from the point of view of the there’s been more attempts to do things like workshops. Develop people’s abilities to I mean even just to do basic things with project management like using Gant charts and certain things like that. There’s been…so there are, probably in the last couple of years there’s been an attempt to start doing more of this kind of thing. So some of the people who are newer to the organisation have gone on some of these courses and I think the impression I get, the feedback I get is that you know it’s a good start in some areas but umm …. In terms of the knowledge creation I think it’s probably still a ways to go. So we are encouraged to you know do this kind of thing in informal ways as is aid you know within our group structure we are very much encouraged to those sorts of meetings and we have them and you know we do, we will discuss not just the specifics of individual projects but the processes around it at times. So that kind of thing will happen as well. But in terms of umm well let’s see… I: What about the project briefing for instance or best practice, do you have something like that? R: Yeah. Project briefing yes we will have, SCIENCO you know we’ll do some briefing about yeah things like you know giving you know giving overviews of projects doing you know project presentations doing that kind of thing. That happens quite a lot and internally umm in fact this is an area where the strategic projects which by strategic I mean typically internally funded projects that are more focused on developing you know… R: Yeah for or doing things with in terms of more pure research and development which may not be directly funded by, so it’s not solving a particular problem for a customer but it’s a…so that kind of project which is, has a different kind of a structure to it, although usually it’s not as, it’s not tracked in anything like the formal ways of an external project because there’s no, you don’t have the external pressure of invoices and deadlines and milestones and deliverables. One of the things you do usually have is a more formal process of presentation of project briefing. So what are we doing, where are we going, what have we found out, what have we discovered? So that kind of thing does happen in that context. So again I think what we see here and I suppose it’s becoming clearer to me talking about it is that those internal projects tend to be more capability oriented. You know developing, they’re more of an input side almost if you like of growing our capability and that side of things requires (?) and capturing that knowledge and doing things. So there is the requirement to be very clear about what it

322 Appendices

is that you’re doing and part of that briefing will always be well yes there’s some technology here that we might be looking something in terms of a patent. Certainly you know what publications have you done, what publications are you planning to do? So that kind of thing would be relatively strong in that kind of domain. On the sort of outlook side if you like the external side it’s probably less, it’s probably less strong. Because the real, there’s an awareness of it, but the real emphasis tends to be on those more fundamental aspects of a project. The deliverables, milestones, and budget you know. Do you believe that knowledge was properly captured for that project? R: Okay at the risk of sitting on the bench, I would say yes and I think ultimately yes we do capture the knowledge. And we have successfully transferring it onwards and I think probably the umm one of the key processes that actually helped to do that was the process of publication because it forces the researcher to formalise his or her ideas. So in this case things which were in my mind, but maybe not umm maybe not formally enunciated as principles or theories…or concepts….had to be structured in that way in order to demonstrate what I’d done and to talk about it in a formal publication for review. So that’s a key method that was one thing. And even more so then moving from that point to the point of umm then providing that as documentation for a potential commercial partner. Because they really want to know you know there’s one level of scrutiny that comes from someone reviewing a paper but a much greater level of scrutiny in some ways comes from a commercial client or it can come from a commercialise-side where they’ll be saying what am I really getting myself into? Do I want to sink time and effort and potentially money into something, is it going to work? So those steps are very good. The reason why I say yes, so I say yes ultimately, the reasons why I say no or with a process is that internally and in terms of the knowledge transfer internally to other staff, I think there was some deficiencies in the way that that happened. And it occurred to me and maybe it’s only been on reflection afterwards that using that kind of process of formalising the knowledge into a publishable document would have been well served to have had that information available internally earlier so that these people, so that the software engineer I was working with could read through that and get a coherent understanding of the overview of the project. Having said that one of the potential failures of that is very often when we publish we can’t, we don’t reveal the underlying techniques and technologies that we’ve used or even the methods perhaps. Because there might be some commercially confident information or know how that we want to use for other projects. Or potentially information that could be patented so we can’t you know we won’t publish that. in those cases and even you know even when those sort of things don’t apply you never go into the level of detail in a publication that you might need to go into when you transfer the knowledge technically to an associate. I: So my question is that in that specific let’s say section do you have, do you think that your organisation has some sort of things…for instance your intranet or something like that to help you to capture that knowledge? R: Yes. And that’s a good question and a good point and we have used, we do use a confluence website which is a part of the SCIENCO intranet but you can set up specific

Appendices 323

pages or project based pages where you can put information. Typically what happens and this is a valuable enough thing in itself. Typically what gets recorded is the nuts and bolts of the project. So IP addresses, the different machines, pass words, log in details and things like that. And it’s all knowledge and it’s all invaluable stuff that you have to have in order to do the job, and particularly if you’re working on multiple projects and you come back to a project after two or three weeks. You know you think oh now how do I log into that machine? So at a superficial level that kind of knowledge, the working day knowledge is captured. For some projects in the past and I’m thinking about other ones at this time you know we’ve been probably much more exhausted about keeping source code and things like that available through the intranet. We do use SBN which is a sort of a source code repository system. So for all the projects that we do, we do ensure that we keep the code checked in and any changes are updated so that we can always be on the same, we’re always on the same code. So that’s you know source control is important. But I think there’s scope there for better use of that resource in terms of …the core ideas, the core technical ideas of a concept, ensuring that those are transmitted or the information is there for a person to go and find out more and I think that’s probably, I’d see that as the primary challenge of the way that these sorts of things typically work. Is usually one person who’s done the research, the initial research, has that idea in their head and the capacity for that to be transmitted to others, sometimes it can be a tricky process for them to actually really understand what did he actually do to make this work? How did that happen? So ….yeah I …I think one of the things that I did do and very often what will happen is that the research will happen in a stage process. So we might acquire some data and then prior to writing formal source code for our application we would look at, well I know I would use a (???) for example and actually I’d begin to do some scripts and writing some simulations and trials, some algorithms with the data to see what would work. In the process of doing that you usually develop a handful of different scripts and other little routines that you can use to test the data. And you produce a lot of plots and information stuff like that. Just the PMO itself I’d say really it doesn’t really do it at all in terms of the identifying, even re-identifying sort of stage of the knowledge as I said there’s no formal connection between that captured knowledge base that we have and the actual PMO proper. Very much there’s a reliance of getting the right people on the project to start with and then the assumption is that those people have the knowledge and that they will do the right thing Do you believe that the project’s knowledge was properly transferred? R: Yeah sure okay. I would say the primary knowledge transfer formal knowledge transfer system that we use would be things like publications, papers and that sort of thing with the intention to publish those ideas or to put them into a form where they can be captured within the organisation. So there will be, in terms of the things that are here, and I guess that would come down to communities of practice and also looking here, information or knowledge repositories we have an e-publish system an online system where all…and that’s not just scientific publications but project reports, proposals you know even you know within reason even sort of project interim reports or memos, things like that are all captured within the published system now. So that’s

324 Appendices

been oh that’s been 2 or 3 years now that that’s been across the whole organisation and that’s probably raised the level of rigor in terms of knowledge management. Simply because now in order to get something submitted to e-publisher it has to go through a formal review process. So somebody will, you have to nominate people to review it. They will read it, they have to say they understood what you’ve done and then it can be accepted for publication or release. So that umm that process is probably a powerful way of doing that. In terms of the internet and things like that there certainly are as I said project, internal internet facilities or intranet facilities that we’ll use. Not on this project but on another one this other larger project that I was mentioning before we did establish and external or it was a wiki site if you like. Or a confluence site again which is a form of wiki but it was open to the external partners in the project as well so it became a repository for storing information. So on that we all, we were working on a large project with Rio Tinto and they …we opened up this website to their people as well so that we could store information, they could read it, and we could share documentation and discuss ideas. That became a tool for transferring the day to day knowledge of the project as well as the more formal reports and things like that. In terms of the core research knowledge and technical stuff that’s …it’s quite strictly mandated that that kind of stuff stays within the organisation and it’s only via the formal procedures of publication or reports or things like that that we’re meant to be releasing that kind of information. Ultimately that knowledge is the product that we have so we… you know so the …they really…they’ve then as an organisation SCIENCO has become much more aware of that in recent times. So these sorts of procedures have been in place because of that. Also well we did have a group wiki for example a confluence site that we will use and we will put up, the intention is that you put up a little blurb about your project there. So I probably should have mentioned that previously but it’s kind of slipped my mind. Again probably because it’s more of a voluntary than a necessary mentoring, it’s not, a lot of these things probably suffer from the point of view that they’re not mandatory. Or if they’re mandatory they’re mandatory but there’s no penalty if you don’t…,laughter….so umm the difficulty is that people aren’t actually held to that and I guess not from the point of view of being forced to do it but I think people need to be motivated to see the value in it. And I think often times there isn’t sufficient recognition of the value. Except again when it’s a question of transferring knowledge from that more basic research and development work you know the fundamental research, transferring that knowledge into a more formal project domain. People usually are pretty good about doing that like they’ll develop a case for that. They’ll… because again that, at that fundamental research level there’s always the intention of showing you what’s this about? What’s it for? So I the organisation I do think is actually very good, probably in some ways excellent in trying to identify from that fundamental point of view the knowledge that can be taken from a fundamental technology and applied into a domain. The …so like that information flows into the project domain from that area but within the project domain keeping that going as it were you know keeping, feeding that information back as projects have performed and more lessons are learned I think there is a bit of a, that’s where I think the main gap is. Is in you know organising that information in such a way that it continues to allow further

Appendices 325

improvement. So…

Do you believe that there were some facilities to help you for reusing existing knowledge?

R: Okay so certainly for the project I’ve been discussing here yes absolutely. As I said the its genesis was in a previous project which was a research, a more research oriented project I suppose with less of a commercial outcome. It was still working with the external client because we needed someone to work with to get the data but its goal was a much more research oriented goal. So the primary, well I guess the knowledge was transferred in two ways. One that project and its results which were published as results and knowledge that became the motivation for the client to request a further project. So that was used in order to actually generate the following project. But more obviously the technical knowledge that was gained in that project and the algorithms used for the detection and all that kind of thing that was used and transferred to the new project. Now as I say in some ways it was a, there was an element of it being a fairly informal process initially because I was the person who had done the original work and I commenced the process of re-implementing those concepts. However when it came time to transfer that knowledge within the project to other engineers and software engineers that’s where, as I said, the some of the typical approaches that we have used which is to provide resource code, talk through it and let the person start to work on their own version, as I said I think there’s a bit of a deficiency in that method because reading somebody else’s source code doesn’t give you the umm it doesn’t provide an adequate explanation of the ideas. You know the intangible aspect of the research knowledge. And so as I said the process of using a more formal transfer mechanism so that knowledge can be reused properly I think is important. And probably there’s scope for an internal publication if you like which has much more technical detail which could be a summary of the project mechanisms, algorithms and things which could be passed onto the person and allow them to do that. Now in the end I did produce documentation of that sort but it wasn’t produced at the outset as part of the transfer. It came about because of the need to use the knowledge. I sat down and worked together with this person and we gradually developed the information that they needed to do the job. So… I: do you think your existing PSO had a kind of contribution for the knowledge you’re using? R: Yeah I ….probably in that area, I think that’s, that I guess what I’d call the core technical research knowledge it’s probably, there’s a bit of a deficiency in the project support culture or mechanism at the moment. There’s certainly I think as I said, I think there’s an awareness of it that we you know we haven’t done as good a job as we could transferring that kind of knowledge from one project to another. And as I say I think this comes about because we do typically think of the knowledge as being something that we use to generate publications. And as I said I think that’s a very good mechanism but it’s probably the fact that when you produce a publication for external consumption you hold back some of the core knowledge. You don’t want to show everybody in the world exactly how you did it. You want to just tell them we did this and then we got these results. But what you’re holding back is the very knowledge that

326 Appendices

other people within your organisation will need if they’re going to work on that and continue to develop that process, the product. So there needs to be, between the level of the publication and just the raw source code which is difficult to work through if it’s not your own, in between that there needs to be this kind of intermediate level where the ideas are transferred in a more formal manner. And as I said, typically in my experience anyway that has tended to be more informally done. We do produce things like software specifications for example but in my experience you know the very, very formal software specifications that are often produced are such, there’s such an amount of work and effort that goes into them that they’re very well suited to big, big projects. You know where you have maybe at least a dozen programmers or more and several years of time and obviously your first step is to develop the specification so everybody knows what they’re doing. But this particular project I’m talking about had a short time span, really only one or two people working on it and you simply couldn’t afford the investment of time required to produce a really formal, exhaustive specification. You’d spend your whole budget before you even started to do the job. So yeah so I think there’s a deficiency in there in terms of transferring some of those ideas. You know in the end we did manage to do that but I think it was done in a somewhat informal fashion as compared to that. And yeah so it could have been better. Okay. Umm….yeah. Well it’s umm …the I suppose within an organisational sense there is the intention at the level above the project leader, the stream leader level as it’s called and higher again, the intention should be that these umm leaders should be able to identify knowledge outcomes from particular projects and provide that or utilise that, their kind of Meta knowledge if you like of that knowledge they should use that information to assist project leaders in other projects and say well I’m aware that we have had projects in this domain or that domain and you should talk to so and so about that project. But that’s a…so the intention there was in our organisational structure to do that but you can see that even in our (?) views that it’s not a formal linkage. It’s something the leadership structure will do and then the intention is go and find out from this person how that worked or whatever. So there’s no systemic method for doing that. I mean I’m probably, I don’t want to paint it too black because I think that can work quite well and sometimes knowledge, the sorts of knowledge that we deal with can be sufficiently complex that it’s difficult to summarise and that you might need to you know have a direct interview with the expert in this area and find out and ask questions and flesh things out. So I think that’s important. But there’s not a mechanism whereby you can kind of check that you haven’t missed something. And that’s the key thing you could, if something is overlooked well it’s overlooked and nobody will…if somebody forgets to talk to the guy down the hallway who knows about this or that well that’s just too bad. So if it’s remembered then great you know everything will be fine, so that’s probably where it breaks down. I: Right so what, do you think at this stage you have some sort of system for the knowledge management in terms of IT, forms, process, instruction, IT system or so forth? R: Yeah further….so there are some forms that have been developed. So I mentioned the post project review form which the intention, part of the intention of that form is

Appendices 327

to identify aspects of you know knowledge creation from the project and to identify how that can be sort of captured and organised. Well captured anyway I don’t know if it’s been formally organised. So there are forms and I suppose the post project review would be a process but as I say it’s not one that’s actually usually carried out. You know it you know it usually is a look so that’s an issue. In terms of other processes I mean we do have you know umm certainly at the outset of you know the financial year for example, if there are strategic projects being developed there’s certainly an effort made to examine you know the knowledge domain and to try and look at what projects have been done. So there would, in terms of processes I think it’s probably fairly heavily reliant on meetings, reports or workshops from time to time. You know we might have a workshop where we discuss applications of technologies in certain areas. But there’s no sort of online register or system you can go to in order to access that information. It’s umm you know it’s sort of word of mouth type thing yeah.

Please recall one of the projects which was less successful or failed, Do you

believe that proper knowledge management would contribute to success of project?

R: Okay so let me think of a project that would be considered unsuccessful…umm….let me think. Well I guess there are levels and levels. Like in terms of projects that haven't gone on, like they may have achieved some sort of a goal but they haven’t developed into further work. I can think of a couple of projects where they kind of came to a standstill at, you know at the end of their time. And so I guess from that point of view you wouldn’t call them highly successful. So in a particular case that I’m thinking of, we developed a technology system implemented for a particular at a mine site, a particular customer. And in the end it didn’t really go any further than that. They used the system on site but the…but it didn’t…actually would knowledge management or better knowledge management have helped? Well let me think. Yes in some ways yes because umm part of the problem was the use of the system was that would be knowledge management across the entire project chain, was that within the internal structures of the client company the person that they had designated to do the job didn’t have very much authority within the company. So that he was given the task of arranging to work with SCIENCO to develop this technology but he didn’t have the kind of authority to communicate the project as an important aspect of what was going on in the company. So as far as the client was concerned it was a kind of some little project running on the side and the majority of people within the client company probably didn’t really care about it or know much about it. And so there was one failure there immediately of the knowledge management which would be the goals of the system and what it was doing for them were not well communicated to the customer. Or at least they were well communicated to our immediate contact but not well communicated within the wider organisation. That probably came about partly because it was a two-step process. There was an independent consultant who had contacted SCIENCO and said oh well this might have this particular problem. And then he, through him we arranged a contact within the company but the knowledge part if you like went between, went through this sort of two stage process and even then when it got to the company the person that was the recipient of the knowledge

328 Appendices

probably didn’t have the capacity or the authority to really promote the knowledge within the company. So from a knowledge management point of view I’d say yes there was certainly some deficiencies there and from SCIENCO’s point of view it’s probably, this was a few years ago, and we probably wouldn’t work that way now anyway. But from SCIENCO’s point of view it would have been important for us to establish a better formal and direct relationship with the customer so that we had clear lines of authority within the organisation that we would report to. And as it was we didn’t have that and therefore the project was hampered from day one by that kind of thing. Secondly the information that we then produced for the client or that we produced you know specifications and some detailed information about the system, the client didn’t give us any clear concept of how they wanted the knowledge presented. So the fellow who was in charge of the project there you know very informally said oh you know look we just want to know how it works. Just maybe something here and could you give us a bit of a report on what happens. But it was very, very vague and you know we more or less had to go through the process of saying is this what you would like? Do you want this? Do you want that? Now that meant that I wasn’t confident at the end of the project that they really had a clear grasp of what it was that they were using and for that reason I think that you know it was not at all unlikely that they were going to…well I’m not surprised that it didn’t go any further because I think that the fellow who was in charge of that project there, he got moved to another section, somebody else came in to that area and because there was no clear transfer of the knowledge this other person didn’t have any particular interest in the technology. It all kind of just fell in a heap you know. I mean…the project was not financially unsuccessful I mean we….we made you know we made a profit out of it if you like or whatever but it’s not the sort of thing that we want to do. Like we’re not really interested in just doing little engineering projects that go nowhere. We really are interested in sort of you know actual research and development that creates improvements in the mining process so it was, whilst it wasn’t a disaster or anything like that it was a wasted effort I think in some ways because… So you know from that point of view and I think there it was that you know if you want to point to a deficiency in knowledge it was the transfer of understanding of the idea and why it mattered. Which is ironic because in this case it was a case where they, the company had approached the consultant and said that we’ve got this problem. The consultant approached us and said they’ve got a problem can we solve it? But then you know internally they didn’t seem to value the solution or didn’t seem to, you know they just passed it on to this fellow. So even though they were the ones looking for the solution they didn’t really umm you know they didn’t really kind of structure or manage very well the way that they dealt with it. So that’s yeah that’s a good example I suppose. Anything missed R: I’d say just to reiterate that one key area, the nature of the knowledge creation process in a research and development organisation is non-linear. You know it’s a umm you know ideas will come to people, there’ll be…so the process is a little bit mysterious almost how that happens, how that knowledge is being created. And it’s not something that you can pre-plan exactly how that will happen certainly in the

Appendices 329

context of the project work that we do. We often find out a lot the first time we are doing it and by contrast with my previous career which was in more industrial engineering sort of environment where you’ve got a known problem and you knew that you could apply knowledge to that problem and it would solve the problem and that meant you could pretty well guarantee you’re going to need these tools and this amount of time and we will make that work. In contrast to that in this sort of environment the knowledge development process is not always quite so clear. So you can be a knowledge management system for example could inform the project leader about options or possibilities or prior knowledge but there’s probably no way of completely capturing that kind of intangible element of the research. So umm I guess from that point of view I can see how …well it’s just something a knowledge management system would have to be flexible enough to handle. Is that kind of reality. And as I said it’s one where in terms of the project management system in which I wish there was greater flexibility because very often the sorts of projects that we do, even though we specify in the contract or whatever that research is an inherently uncertain process and therefore things may change. Nevertheless we still tend to tie ourselves into the typical contracts that are familiar to other industries. Which typically have very fixed timeframes, budgets, deadlines and milestones and there’s a lot of effort that has to be gone through in order to vary those parameters once the thing is laid down. And so that’s probably a frustration for a project leader well for me it’s personally a frustration as a project leader in a research and development environment that on one hand there’s a recognition of that aspect of research in terms of the organisation but there’s not a recognition in terms of the systems. The systems don’t allow for the flexibility as a… sometimes you just aren’t going to get the answer you want straight away. You might have to do something again several times and that might take longer than what you’d originally planned to do. So how that, how the integration of that kind of knowledge management can happen in that context of you know the project management system, that’s a tricky question. That’s not immediately you know it’s not immediately obvious to me how you could capture all the data and certainly there has to be, the system has to have a certain amount of flexibility built into it to do.