methods to increase itil adoption
TRANSCRIPT
Methods to Increase ITIL Adoption
Nuno Encantado Faria
Thesis to obtain the Master of Science Degree in
Information Systems and Computer Engineering
Supervisors: Prof. Miguel Leitao Bignolas Mira da SilvaProf. Rui Antonio dos Santos Cruz
Examination Committee
Chairperson: Prof. Francisco Joao Duarte Cordeiro Correia dos SantosSupervisor: Prof. Miguel Leitao Bignolas Mira da Silva
Member of the Committee: Prof. Ruben Filipe de Sousa Pereira
October 2018
Acknowledgments
I would like to express all my gratitude to everybody that contributed to make this thesis possible.
To my supervisors, Prof. Miguel Mira da Silva, who with his skill, knowledge and experience accom-
panied and helped me, specially making the bridge with the companies involved in this work; and Prof.
Rui Cruz for all his commitment and pleasure on supporting and advising me. I thank both for all the
knowledge, motivation, critical thinking and advises given to me, which increased my experience and
helped me a lot in this work.
To the teams in both involved companies, for their support, shared experience, dedicated time and
precious data to the demonstration and evaluation of my proposal.
To my friends for all the amazing moments in my life and for their special support and comprehension
in this journey.
And finally, i would like to thank with all my heart to my mother, father, brother and family for all their
sacrifice, love, support and presence in all my life. No words can express all my gratitude to them.
Abstract
Besides the many benefits Information Technology Infrastructure Library (ITIL) can provide to compa-
nies there is still lack of its adoption. The barriers, specially the difficulty on its implementation lead
companies to make mistakes and to abandon it. The appearance of Critical Success Factors (CSFs),
adoption models and road-map to help achieving success in this complicate process is representative
of the increased effort to solve this problem, but at some point, they are still high-level solutions. Using
Design Science Research Methodology (DSRM), two methods that contribute to increase ITIL adoption
through technology and evaluation, focused on people and processes, by improving the effects of two
CSFs are proposed in this thesis. These methods were demonstrated in two companies to assess its
relevance: one from the bank sector (for the first method) and the other from the Information Technol-
ogy (IT) consulting area (for the second method). Using Osterle principles, critical analysis and Moody
and Shanks quality framework, the two methods were validated and evaluated, showing their effective
potential to increase ITIL adoption.
Keywords
Information Technology Infrastructure Library (ITIL), ITIL Implementation, ITIL Adoption, Critical Success
Factor (CSF), Design Science Research Methodology (DSRM).
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Resumo
Apesar dos inumeros benefıcios que o ITIL pode fornecer as empresas, ainda ha falta da sua adocao.
As barreiras, principalmente a dificuldade na sua implementacao, levam a que as empresas cometam
erros, abandonando-a. O aparecimento de CSFs, modelos de adocao e road-map para ajudar a
alcancar o sucesso neste processo complicado e representativo do crescente esforco para resolver
este problema, sendo ainda, em certos aspectos, solucoes de alto-nıvel. Usando DSRM, sao propostos
nesta tese dois metodos que, pela melhoria dos efeitos de dois CSFs, contribuem para aumentar a
adocao do ITIL atraves da tecnologia e avaliacao centradas nas pessoas e processos. Estes metodos
foram demonstrados em duas empresas para avaliar a sua relevancia: uma do sector bancario (para o
primeiro metodo) e a outra da area de consultoria de IT (para o segundo metodo). Usando os princıpios
de Osterle, a analise crıtica e a framework de qualidade de Moody e Shanks, os dois metodos foram
validados e avaliados, mostrando o seu potencial efectivo para aumentar a adocao do ITIL.
Palavras Chave
Information Technology Infrastructure Library (ITIL), Implementacao de ITIL, Adocao de ITIL, Critical
Success Factor (CSF), Design Science Research Methodology (DSRM).
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Contents
1 Introduction 1
1.1 Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Document Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 The Problem 7
3 Theoretical Background 11
3.1 Information Technology Infrastructure Library (ITIL) . . . . . . . . . . . . . . . . . . . . . . 13
3.2 Multiple Criteria Decision Analysis (MCDA) . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.2.1 Outranking Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2.2 Analytical Hierarchy Process (AHP) . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2.3 Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) 15
3.3 Monitoring and Evaluation Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.3.1 Implementation-Focused Monitoring and Evaluation Systems . . . . . . . . . . . . 16
3.3.2 Results-Based Monitoring and Evaluation Systems . . . . . . . . . . . . . . . . . . 16
4 Related Work 17
4.1 Critical Success Factor (CSF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.1.1 Origin and Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.1.2 Relations between CSFs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.2 ITIL Adoption Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.2.1 ITIL Adoption Model with TAM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.2.2 ITIL Adoption Model with UTAUT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
4.3 ITIL Implementation Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
5 Research Proposal 29
5.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.2 ITIL Tool Selection Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.2.1 Identify the Criteria and Define their Performance Levels . . . . . . . . . . . . . . . 32
5.2.2 Weight the Criteria and Evaluate their Performance Levels . . . . . . . . . . . . . . 33
5.2.3 Test the Tools and Analyze their Documentation . . . . . . . . . . . . . . . . . . . 34
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5.2.4 Analyze the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.3 ITIL Processes’ Performance Evaluation Method . . . . . . . . . . . . . . . . . . . . . . . 35
5.3.1 Select the Evaluation Criteria and Metrics . . . . . . . . . . . . . . . . . . . . . . . 35
5.3.2 Define the Analysis Period and its Metrics’ Targets . . . . . . . . . . . . . . . . . . 36
5.3.3 Calculate the Metrics in the Analysis Period . . . . . . . . . . . . . . . . . . . . . . 36
5.3.4 Analyze the Results and Evaluate them According to the Selected Criteria . . . . . 36
5.4 Principles of the Evaluation Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.4.1 Design Science Research Evaluation Framework . . . . . . . . . . . . . . . . . . . 37
5.4.2 Four Principles of Osterle et al. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.4.3 Moody and Shanks Quality Framework . . . . . . . . . . . . . . . . . . . . . . . . 38
6 ITIL Tool Selection Method 39
6.1 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.1.1 Identify the Criteria and Define their Performance Levels . . . . . . . . . . . . . . . 41
6.1.2 Weight the Criteria and Evaluate their Performance Levels . . . . . . . . . . . . . . 41
6.1.3 Test the Tools and Analyze their Documentation . . . . . . . . . . . . . . . . . . . 43
6.1.4 Analyze the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
6.2 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
6.2.1 Design Science Research Evaluation Framework . . . . . . . . . . . . . . . . . . . 45
6.2.2 Four Principles of Osterle et al. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
6.2.3 Moody and Shanks Quality Framework . . . . . . . . . . . . . . . . . . . . . . . . 46
7 ITIL Processes’ Performance Evaluation Method 49
7.1 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
7.1.1 Select the Evaluation Criteria and Metrics . . . . . . . . . . . . . . . . . . . . . . . 51
7.1.2 Define the Analysis Period and its Metrics’ Targets . . . . . . . . . . . . . . . . . . 51
7.1.3 Calculate the Metrics in the Analysis Period . . . . . . . . . . . . . . . . . . . . . . 52
7.1.4 Analyze the Results and Evaluate them According to the Selected Criteria . . . . . 53
7.2 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
7.2.1 Design Science Research Evaluation Framework . . . . . . . . . . . . . . . . . . . 54
7.2.2 Four Principles of Osterle et al. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
7.2.3 Critical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
7.2.4 Moody and Shanks Quality Framework . . . . . . . . . . . . . . . . . . . . . . . . 57
8 Conclusion 59
8.1 Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
8.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
8.3 Main Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
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8.4 Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
8.5 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Bibliography 67
A Criteria Weighting Judgments Matrix 73
B Sensitivity Analysis 75
C Performance Analysis 77
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List of Figures
1.1 Design Science Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
3.1 ITIL v3 core . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.1 Relations between key factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.2 ITIL adoption model using TAM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.3 ITIL adoption model using UTAUT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
4.4 Roadmap for ITIL implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
6.1 MACBETH judgments matrix and numerical scale for criterion “Activities”. . . . . . . . . . 42
6.2 Weighting scale for the criteria for each process or data source presented in Table 6.1. . . 43
6.3 Overall value scores of the alternatives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
6.4 Robustness analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
7.1 Performance analysis support system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
7.2 Distances to the ITIL process’s targets from the demonstration of the method . . . . . . . 55
7.3 Prediction’s precision and process’s statuses deviation from the demonstration of the
method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
8.1 Validation and evaluation profiles of the ITIL tool selection method (blue line) and the ITIL
processes’ performance assessment method (orange dots). . . . . . . . . . . . . . . . . . 64
A.1 Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) judg-
ments matrix for the criteria weighting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
B.1 Complete sensitivity analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
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xii
List of Tables
4.1 CSF in ERP implementations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 Comparison of CSF in ITIL implementations . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.3 Comparison of Pollard and Cater-Steel CSF in ITIL . . . . . . . . . . . . . . . . . . . . . . 20
4.4 Mapping between ITIL CSF and their classes . . . . . . . . . . . . . . . . . . . . . . . . . 22
6.1 Mapping between assessment criteria and process/data sources. . . . . . . . . . . . . . . 42
6.2 Mapping between evaluation criteria and ITIL recommendations for the selected pro-
cesses and data sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
7.1 Mapping between selected metrics and criteria and their implementation. . . . . . . . . . 52
C.1 First subperiod performance’s results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
C.2 Second subperiod performance’s results. . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
C.3 Performances’ comparison between subperiods. . . . . . . . . . . . . . . . . . . . . . . . 78
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xiv
Acronyms
AHP Analytical Hierarchy Process
AT Attitude Towards use
BI Behavioral Intention to use
CSF Critical Success Factor
DACH Deutschland, Austria and Switzerland
DM Decision Maker
DSRM Design Science Research Methodology
ERP Enterprise Resource Planning
IS Information System
IT Information Technology
ITIL Information Technology Infrastructure Library
ITSM Information Technology Service Management
KPI Key Performance Indicator
MACBETH Measuring Attractiveness by a Categorical Based Evaluation Technique
MCDA Multiple Criteria Decision Analysis
OGC Office of Government Commerce
PEU Perceived Ease of Use
PU Perceived Usefulness
TAM Technology Acceptance Model
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U system Use
UK United Kingdom
USA United States of America
UTAUT Unified Theory of Acceptance and Use of Technology
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1Introduction
Contents
1.1 Research Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Document Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1
2
The evolution of technology is leading the world to a “second machine age” [1] where service quality
is becoming more than an option. By investing in strategic quality improvement, companies can better
face disruption, along with economic difficulties and increased demanding costumers.
Information Technology Infrastructure Library (ITIL) has many benefits [2–5] that increase the interest
in many countries [4, 6–11], making it a widely accepted methodology [12]. However, many companies
still make mistakes when trying to implement it [13], due to the great amount of barriers for its adop-
tion [14]. One of the most impactful barriers is the difficulty in its implementation, mostly because ITIL
does not provide advice on how to implement its best practices [15]. Because of that, many compa-
nies abandon their intentions to implement ITIL [9], leading to the research problem: the lack of ITIL
adoption.
To address this problem, two methods focused on two Critical Success Factors (CSFs) for ITIL adop-
tion are proposed, due to the importance of these elements for a successful ITIL implementation, as
evidenced in the literature review (cf. Chapter 4). The objective is to create a mechanism that through
technology and evaluation focused on people and processes contributes to increase ITIL adop-
tion.
The first method focuses on selecting ITIL tools based on Measuring Attractiveness by a Categorical
Based Evaluation Technique (MACBETH), increasing the positive effects of the “ITIL tool selection”
CSF; the second one is a method to evaluate the performance of the selected ITIL processes based
on results-based monitoring and evaluation systems’ building actions that aims to increase the positive
effects of the “monitoring and evaluation of ITIL implementation” CSF.
To demonstrate their use, the two methods were applied in two companies (one for each method).
For the method to select ITIL tools, a company of the bank sector was selected since they had doubts
about the software tool they would use to implement four ITIL processes. The method to evaluate the
performance of ITIL processes was demonstrated in an Information Technology (IT) consulting company
since they wanted to improve the performance of their ITIL processes.
To validate and evaluate the proposal and its results, the four principles of Osterle et al. [16], critical
analysis, and the Moody and Shanks quality framework [17] were used. From that evaluation, it could
be concluded that the methods can contribute to increase ITIL adoption, since they are able to improve
the two CSFs for ITIL adoption that they are focused in.
To communicate the results to proper audiences and obtain scientific appraisal, demonstrations of
the two methods to their practitioners were made, along with the submission and presentation of a
scientific paper in an international conference [18].
3
1.1 Research Methodology
The methodology applied in this research was the Design Science Research Methodology (DSRM).
DSRM incorporates principles, practices and procedures required to carry out design science research,
providing a nominal process model for doing it and a mental model for presenting and evaluating this
kind of research in Information Systems (ISs) [19].
Aiming to create and evaluate IT artifacts such as constructs (vocabulary and symbols), models
(abstractions and representations), methods (algorithms and practices) and instantiations (implemented
and prototype systems) [20], this methodology intends to overcome explanatory research paradigms
such as descriptive and interpretive ones borrowed from social and natural sciences [19].
DSRM is an iterative methodology including the following phases [19]:
• Problem identification and motivation: definition of the specific research problem and justifi-
cation of the value of a solution. Atomizing this problem conceptually should be done in order to
develop an artifact that can effectively provide a solution capturing its complexity. In this research,
the identified problem is the lack of ITIL adoption (Chapter 2).
• Define the objectives for a solution: identification of the objectives of a solution from the problem
definition and knowledge of the state of the problem and possible and feasible solutions. The
objectives can be quantitative or qualitative. For the identified problem, the objective of the solution
is the creation of a mechanism that, through technology and evaluation focused on people and
processes, contributes to increase ITIL adoption (Chapter 5), and the related work shows the most
relevant concepts and models to address this problem (Chapter 4).
• Design and development: determination of the artifact’s desired functionality and its architecture
followed by its construction. A design research artifact can be any designed object with embedded
research contribution. This research’s artifacts are two methods focused on two CSFs (Chapter 5).
• Demonstration: usage of experimentation, simulation, case study, proof or other appropriate
activity to demonstrate the use of the artifact to solve one or more instances of the problem. The
demonstrations of the artifacts were made in two companies: the first one from the bank sector
(Chapter 6) and the second one was an IT consulting company (Chapter 7).
• Evaluation: observation and measurement of the adequacy of the artifact to a solution to the
problem. Requires knowledge of relevant metrics and analysis techniques in order to compare the
results observed from the use of the artifact to the objectives of a solution. The validation and
evaluation of the artifacts were made using the four principles of Osterle et al. [16], critical analysis
and the Moody and Shanks quality framework [17] (Chapter 6 and Chapter 7).
4
• Communication: communication of the problem and its importance, the artifact, its utility and
novelty, the rigor of its design, and its effectiveness to researchers and other relevant audiences.
This step was accomplished with the demonstrations of the two methods to its practitioners and the
submission and presentation of a paper in an international conference (as described in Chapter 8).
With a great focus on organizational context in the solution design, this methodology was the ap-
propriate for this research (see Figure 1.1) since a solution for the identified problem needs to combine
theory with organizational acceptance in order to extend the boundaries of their capabilities [20].
Figure 1.1: Design Science Research Methodology (DSRM).Adapted from [19] to this research work.
1.2 Document Structure
This document is divided in eight different chapters and three appendixes, described as follows:
1. Introduction (Chapter 1) provides the context of the thesis, explains the used research methodol-
ogy and describes the structure of the document.
2. The Problem (Chapter 2) details the motivation and the research problem.
3. Theoretical Background (Chapter 3) explains the theory behind the construction of the artifacts.
4. Related Work (Chapter 4) presents an overview of the literature on the research area, explaining
the most relevant concepts and models to solve the identified problem.
5. Research Proposal (Chapter 5) identifies the objective of the solution, describes the produced
artifacts and explains the principles used in the proposed methodology to evaluate the artifacts.
5
6. ITIL Tool Selection Method (Chapter 6) explains how this artifact was used to prove its capability
to solve one or more instances of the research problem and presents the results of applying the
evaluation methodology to this method.
7. ITIL Processes’ Performance Evaluation Method (Chapter 7) explains how this method was used
to prove its capability to solve one or more instances of the research problem and presents the
results of applying the evaluation methodology to this artifact.
8. Conclusion (Chapter 8) describes how the results were communicated to proper audiences, sum-
marizes the main conclusions, lessons learned, limitations and main contributions of this research,
and presents some proposals for future work.
9. Appendixes present:
A - Criteria Weighting Judgments Matrix
B - Sensitivity Analysis
C - Performance Analysis
6
2The Problem
7
8
This chapter defines the specific research problem and justification of the value of a solution, corre-
sponding to the first step of DSRM: problem identification and motivation.
As technology innovation increases, constraints are removed and new possibilities created, which
affects people’s lives and enterprises [21].
In recent years, technology evolved so much that this new era is now being called “the second
machine age” [1], in comparison to the first one with the rise of Industrial Revolution.
But, besides the positive aspects that this can bring to business, which goes from better forecasts to
quicker ways to modify processes and structures, only a small part of companies have mastery on using
technology to improve their productivity, performance and profit levels [21]. One of the characteristics
identified in these “digital masters” is that they see technologies as tools to transform their processes,
empowering their employees and improving their relations with customers, instead of being just goals or
signals to send to their investors [21].
Service quality is intrinsically related with improving relations with customers by listening to their
needs. Lewis and Booms [22] defined it as a “measure of how well the service level delivered matches
customer expectations” and Cronin and Taylor [23], besides removing expectations from the equation,
considered the customers’ perceptions as a basis to service quality level. Both considered the same
objective for service quality: improve the satisfaction of customers.
In this new era, where even more companies face disruptive technologies that constantly change the
rules of the game along with economic difficulties and increased demanding from customers, method-
ologies that improve service quality in a strategical way become more than just an option.
ITIL is now a widely accepted methodology to improve service quality by increasing its effectiveness
and efficiency. Benefits from its adoption were identified in [2–5] being more than service quality im-
provement and going from reduction in IT downtime to raising of IT staff morale and documented and
consistent IT processes across the organization, which all led to an increased interest on ITIL adop-
tion in many countries as evidenced in studies in China [7], Australia [6, 8, 9], United States of Amer-
ica (USA) [6, 9], Norway [4], United Kingdom (UK) [9, 10], Malaysia [11] and Deutschland, Austria and
Switzerland (DACH) [9].
But, besides the benefits of using ITIL and its wide range increased interest, many organizations are
still far from a full adoption of this methodology or did not have implemented it at all [9].
Shang and Lin [14] identified some barriers to ITIL adoption in their multi-case study:
• Dissatisfied customers due to the gap between the degree of improved service quality and cus-
tomers’ perception;
• Inability to satisfy customers’ specific needs in time;
• Extra costs occurred in education and management;
9
• Time lag between investment in ITIL project and performance outcome;
• Conflicts between urgent needs for quality improvement and cost consideration;
• Difficulties in implementation;
• Employee resistance;
• Lack of integration ability.
Difficulties in implementation is one of the most common and impactful barriers to ITIL adoption,
mostly because ITIL indeed offers a set of best practices but does not provide advice on how to imple-
ment them [15].
This absence of a guide to successful implementation leads many companies on making mistakes
which compromises the entire investment on ITIL with consequent spent of time and money with no
benefits. Some of these mistakes were identified in [13]:
• Lack of management commitment;
• Excess of time spent on complicated process diagrams;
• Not creation of work instructions;
• Not assignment of process owners;
• Too much concentration on performance;
• Exaggerated ambition;
• Failure on momentum maintenance;
• Allowance of departmental demarcation;
• Ignorance of ITIL maintenance importance;
• ITIL implementation based only on book memorization.
This dark side of ITIL can make companies turn off their intentions on its adoption, specially because
it requires a lot of effort and resources which can lead to no benefits.
In a short, the problem is the lack of ITIL adoption.
10
3Theoretical Background
Contents
3.1 Information Technology Infrastructure Library (ITIL) . . . . . . . . . . . . . . . . . . . 13
3.2 Multiple Criteria Decision Analysis (MCDA) . . . . . . . . . . . . . . . . . . . . . . . . 14
3.3 Monitoring and Evaluation Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
11
12
This chapter is divided in three sections: ITIL, Multiple Criteria Decision Analysis (MCDA) and Moni-
toring and Evaluation Systems.
In Section 3.1, the origin of ITIL and how it evolved through time is explained, starting with its defini-
tion and the goal leading to its first version, to then detail the components of its last version (ITIL v3).
Section 3.2 explains some of the most used MCDA methods. Finally, Section 3.3 provides a summary
on the most used types of monitoring and evaluation systems.
3.1 Information Technology Infrastructure Library (ITIL)
ITIL is a set of good practices to be applied on infrastructure, operations and management of IT services,
being now “the most widely accepted approach to Information Technology Service Management (ITSM)
in the world” [12]. In this section the origin and evolution of ITIL is first explained to then detail its last
version (ITIL v3).
Its origin comes from the 80’s, being introduced and distributed by the Office of Government Com-
merce (OGC) in the UK in order to promote efficient and cost-effective IT operations as a consequence
of growing dependence on IT.
The initial version (ITIL v1) consisted on a set of more than 30 volumes covering all the IT Service
Management, leading to its recognition as a reference framework in this area.
In order to make it more accessible and affordable, ITIL v2 was created in 2000 as a consolidation
of the v1 volumes into logical sets divided into two main areas: service delivery (focused on services
needed to adequately support business) and service support (focused on ensuring costumer access to
the appropriate services).
ITIL v3 appeared in 2007 as an extension of v2 and is now the current version with its update from
2011. Contrary to ITIL v2 which was more focused on process, v3 gives more importance to lifecycle with
its holistic perspective on the full service cycle that covers all IT parts of organizations and supporting
components needed to deliver services to the customer.
Five components constitute the core of ITIL v3 as seen in Figure 3.1.
• Service Strategy: provides the view of business and information technology alignment and the
guidance for service management as a strategic asset of the organization. Includes the processes:
Financial Management, Service Portfolio Management, Demand Management [24].
• Service Design: provides guidance for design and development of services and their manage-
ment processes. Includes the processes: Service Level Management, Service Catalogue Manage-
ment, Supplier Management, Availability Management, Capacity Management, IT Service Conti-
nuity, Information Security [25].
13
• Service Transition: provides guidance for the management of complexity related to changes in
services and their management processes executed in Service Operation from the encoding in
Service Design as a consequence of their requirements’ changes in Service Strategy. Includes
the processes: Change Management, Service Asset and Configuration Management, Release
and Deployment Management, Knowledge Management, Transition Management and Support,
Service Validation and Testing, Evaluation [26].
• Service Operation: provides guidance on delivering and supporting services with effectiveness
and efficiency in order to increase value for the customer and the service provider. Includes the
processes: Incident Management, Problem Management, Request Fulfillment, Access Manage-
ment, Event Management [12].
• Continual Service Improvement: provides guidance on ways to increase quality of design, intro-
duction and operation of services and their linkage with Service Strategy, Design and Transition.
Includes the processes: Service Measurement, Service Reporting, Service Improvement [27].
Figure 3.1: ITIL v3 core. Source: [12]
3.2 Multiple Criteria Decision Analysis (MCDA)
MCDA is “a collection of formal approaches which seek to take explicit account of multiple criteria in
helping individuals or groups explore decisions that matter ” [28]. In this section, a summary of some of
the most used MCDA methods is provided.
14
3.2.1 Outranking Methods
For each criterion, partial preference functions are defined, which may correspond to natural attributes
on a cardinal scale, or may be constructed as ordinal scales, not needing to satisfy all the properties
of value functions. Only the ordinal preferential independence is necessary. In this method, if there is
enough evidence to justify that an alternative a is least as good as another alternative b and no strong
argument to the contrary, taking all criteria i into account, we can conclude that a outranks alternative b
if Zi(a) ≥ Zi(b) for all criteria i [28].
A state of indifference is not necessarily implied when this does not occur. When comparing two
alternatives, the result can be one outranking the other (definitive preference), indifference or incompa-
rability [28].
3.2.2 Analytical Hierarchy Process (AHP)
AHP uses additive preference functions to evaluate alternatives. First, a hierarchy of criteria (value
tree) and identification of alternatives is made. Then, assuming ratio scales for all judgments, pairwise
comparison is used to score alternatives on each criterion and weight the criteria. Finally, using weighted
summation of its scores on the different criteria, an overall score for each alternative is obtained, allowing
to compare all the alternatives [28,29].
3.2.3 Measuring Attractiveness by a Categorical Based Evaluation Technique
(MACBETH)
MACBETH is a method for multicriteria value measurement [30, 31]. For each alternative, the Decision
Maker (DM) quantifies its relative attractiveness with the help of semantic judgments about the differ-
ences in attractiveness of several stimuli. Two elements are compared at a time, in an initial, iterative
questioning procedure that requests only a qualitative preference judgment. The consistency of those
answers is then automatically verified by the MACBETH decision support system [32].
By solving a linear programming problem, this system can also generate a numerical scale, repre-
sentative of the DM’s judgments, and weighting scales for all criteria [33–35]. It is then possible to obtain
overall value scores for all the alternatives to make sensitivity and robustness analyses, which allow the
elaboration of an informed recommendation.
3.3 Monitoring and Evaluation Systems
A monitoring and evaluation system provides an organization with information on progress toward
achieving stated targets and goals but also evidence as the basis for any necessary corrections in
15
policies, programs, or projects [36]. This section summarizes two different types of monitoring and
evaluation systems.
3.3.1 Implementation-Focused Monitoring and Evaluation Systems
This is a traditional type of monitoring and evaluation of systems used for projects and designed to
address compliance. It is focused on monitoring and assessing how well the execution of a project,
program or policy is being made [36].
Some of the key features of this type of systems are: systematic reporting on provision of inputs
and production of outputs, provision of information on administrative, implementation and management
issues and data collection on inputs, activities and immediate outputs [36].
3.3.2 Results-Based Monitoring and Evaluation Systems
This is a more recent type of monitoring and evaluation systems which help answering questions like
“what are the goals of the organization?”, “are they being achieved?” and “how can achievement be
proven?”. Its focus goes on providing feedback on the outcomes and goals, comparing how well a
project, program or policy is being implemented against the expected results [36].
Some of the key features of this type of system are: data collection on outputs and how and whether
they contribute toward achievement of outcomes, reporting with more qualitative and quantitative in-
formation on the progress toward outcomes and provision of information on success or failure of the
strategy in achieving desired outcomes [36].
The essential actions to build a system like this are [36]:
• Formulate outcomes and goals;
• Select outcome indicators to monitor;
• Gather baseline information on the current condition;
• Set specific targets to reach and dates for reaching them;
• Analyze and report the results.
16
4Related Work
Contents
4.1 Critical Success Factor (CSF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.2 ITIL Adoption Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
4.3 ITIL Implementation Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
17
18
This chapter covers the first half of the definition of the objectives for a solution step of DSRM, in
which the state of the problem and feasible solutions are presented, to then identify the objective for a
solution (Chapter 5) from the problem definition (Chapter 2). The chapter begins with the presentation
of some of the most relevant work about CSFs of ITIL and how they can contribute to successful ITIL
implementations. An overview of their origin and evolution is first provided to then explain their relations
and classifications. Finally, an analysis over the models and roadmap for ITIL implementation based on
those factors is made.
4.1 Critical Success Factor (CSF)
In this section, the origin and evolution of CSFs is provided with an overview of the most relevant contri-
butions from the definition of CSFs to their classification and relations.
4.1.1 Origin and Classification
The concept of CSF was first proposed by Daniel [37] in 1961 and popularized by Rockart [38], 18 years
later. In his definition “Critical success factor (CSF) is the term for an element that is necessary for an
organization or project to achieve its mission. It is a critical factor or activity required for ensuring the
success of an organization or a company” [37].
Somers and Nelson [39] developed in 2001, a list of CSFs across stages of Enterprise Resource
Planning (ERP). In their study, responses from 86 organizations that completed or were in the pro-
cess of completing ERP implementation were used associated with an extensive review of the literature
on IT implementation, business process reengineering and project implementations and descriptions,
resulting in a list of 22 CSFs ranked by their importance (see Table 4.1).
Table 4.1: CSFs in ERP implementations [39]. Source: [6]
19
Besides the focus on ERP implementation, it seemed “reasonable to expect that some of those
CSFs will also be important in the successful implementation of an enterprise-wide service and process
framework such as ITIL” [6], since “ITSM involves organization-wide IS planning” [6] and consequently,
some ERP.
Studies about CSFs in ITIL implementations were made by Hochstein et al. [40] in their study of
six large German organizations and by Tan et al. [41] in a study of an Australian large public-sector
organization. Table 4.2 shows the comparison of those results as in [6].
Table 4.2: Comparison of CSFs in ITIL implementations [40,41]. Source: [6]
Lately, in 2009, Pollard and Cater-Steel [6] studied the implementation of ITSM using ITIL v2 frame-
work in four companies: two located in USA and two in Australia. By analyzing CSFs presented in
Tables 4.1 and 4.2, they compared them with those attributed to the four successful ITIL implementa-
tions studied. Some CSFs were confirmed, and new ones were identified. Table 4.3 shows the results
of this study compared with those of Somers and Nelson [39], Hochstein et al. [40] and Tan et al. [41].
Table 4.3: Comparison of Pollard and Cater-Steel CSFs in ITIL [6] with previous ones [39–41]. Source: [6]
20
Pollard and Cater-Steel [6] concluded that the three new CSFs identified “align well with the core ITIL
philosophy: the need to extend IT thinking beyond the technology to include people and process” [6]
as well as “emphasize the broad reach of ITSM beyond the concerns of IT infrastructure to viewing
IT as a service organization that supports end-to-end business operations” [6]. The new “customer-
focused metrics” CSF evidences that, by giving importance to the rising change from technology-focus
to costumer-focus metrics.
The first steps on creating classes of CSFs for ITIL appeared in 2011 with a study on adoption of
this framework in order to create a model that could help understand it [42]. Through qualitative meta-
Synthesis, seven key factors were identified based on ITIL CSFs, being them:
• Top management support;
• Communication and cooperation;
• Training and competence of involved stakeholder in ITIL project;
• Change management and organizational culture;
• Project management and governance;
• ITIL process implementation and applied technology;
• Monitoring and evaluation.
Later on, in 2013, Ahmad et al. [15] used those seven factors as classes for ITIL CSFs identified in a
extensive literature review. 18 CSFs were identified and mapped into seven classes (see Table 4.4).
4.1.2 Relations between CSFs
In 2002, one year after Somers and Nelson [39] developed a list of CSFs for ERP, Akkermans and van
Helden [43] studied the relations between those CSFs, proposing that they would not act isolated. Using
an ERP implementation in the aviation industry, they not only validated the importance of those factors
on explaining initial failure and eventual success of the implementation, but also found that those CSFs
appeared highly correlated, with changes in one influencing others.
With the evolution of CSFs’ research in ITIL implementations, Pollard and Cater-Steel [6] identified
relations between CSFs for ITIL, evidencing dependencies among them which affected their efficiency
and effectiveness. ITIL-friendly culture was seen as a crucial first-step in any ITIL implementation in
order to increase its possible success, as well as a careful software selection needed process addressing
in order to best succeed, otherwise the effects could be negative for the implementation.
The relations between CSFs were studied in more detail by Mehravani et al. [42] in their examination
of CSFs and their effect on ITIL adoption. The result was a model that illustrates not only the key factors
21
Table 4.4: Mapping between ITIL CSFs and their classes [15]. Adapted from [15].
identified from the CSFs, which were the basis for the creation of classes, but also the relations between
those key factors (see Figure 4.1).
In this model, top management support is the most important key factor since it impacts directly
change management and organizational culture, communication and cooperation, project management
and governance, and monitoring and evaluation, and indirectly ITIL process implementation and tech-
nology. This makes top management support the root of every ITIL adoption, which when increased
gives a boost to most of other factors, but when decreased will affect them negatively.
As a second line, directly influenced by top management support, there are communication and co-
operation, project management and governance, monitoring and evaluation, and change management
and organizational culture. Some relations between them are identified: change management and or-
ganizational culture is not influenced by any other factor of the second line, but it is by training and
competence of stakeholder which is a less important first line key factor than top management support,
with the same happening with communication and cooperation; project management and governance
is directly influenced by communication and cooperation and has a direct impact on monitoring and
evaluation which does not affect any factor.
Finally on the third line there is only ITIL process implementation and technology which does not
influence any other factor and is directly affected by project management and governance.
Based on this model, Ahmad et al. [15] created a similar one for their classes of CSFs with only one
change: they considered that training and competence of stakeholder is part of change management
22
Figure 4.1: Relations between key factors. Adapted from ITIL adoption model using TAM [42].
and organizational culture and consequently influenced by them. This way, training and competence
of stakeholder would be a third line factor directly affected by change management and organizational
culture but maintaining its direct impact on another second line factor: communication and cooperation.
The position of training and competence of stakeholder in the relational model is still somehow con-
troversial since both interpretations are valid: training indeed affects the way organizations understand
ITIL and consequently their culture, but the way training is applied is part of the change management
process. A two-way influence relation would be an hypothesis to consider.
4.2 ITIL Adoption Models
Besides being a less explored field in ITIL research, two adoption models appear as main references
based on technology adoption models in order to explain the effect of ITIL CSFs on behavioral intention
to use this framework which is crucial to actually put people using it, since most CSFs relate to user
acceptance instead of just application selection. This section explains and discusses those models.
4.2.1 ITIL Adoption Model with TAM
Mehravani, Sarvenaz in [42], the proposed ITIL adoption model combines CSFs with the well known
TAM in order to represent their influence as external variables on its components, and consequently on
ITIL adoption.
TAM is the most widely applied technology adoption model [15] proposed by Davis [44] and Davis et
al. [45] to address the reasons for rejection or acceptance of information technology and its consequent
23
use. It is an adaptation of the Theory of Reasoned Action from Fishbein and Ajzen [46] to explain and
predict the behaviors of people in a specific situation [47].
In TAM, the effect of external variables is traced trough beliefs which affect attitudes, intention to
use and consequently, the actual system use. Its original version was composed by five components:
Perceived Usefulness (PU), Perceived Ease of Use (PEU), Attitude Towards use (AT), Behavioral Inten-
tion to use (BI) and actual system Use (U).
In this proposed ITIL adoption model, only PU, PEU, AT and BI are present, being PU, PEU and AT
the only ones linked to ITIL CSFs (see Figure 4.2).
Figure 4.2: ITIL adoption model using TAM. Source: [42]
Top management support is the most important CSF since affects all others directly or indirectly and
all the components of TAM. PEU is directly affected by training and competence of stakeholders, change
management and organizational culture and process implementation and technology, and PU is directly
impacted by communication and cooperation, project management and governance and also change
management and organizational culture.
Contrary to the first TAM version where only PU and PEU are affected by external variables, this
model shows that monitoring and evaluation can directly influence the AT since the simple fact that
people know their feedback will be used to review the implementation performance will make them feel
more obliged to support and cooperate.
The model gives a first approach to the relations between CSFs and adoption factors in a simple
way. Still, some problems may arise since its simplicity comes from explaining those relations in a very
high level which is a known critic on TAM and practical validation is still needed, since this model has
lack of it.
24
4.2.2 ITIL Adoption Model with UTAUT
Ahmad, Norita in [15], the proposed ITIL adoption model uses another acceptance model: Unified
Theory of Acceptance and Use of Technology (UTAUT).
UTAUT is a technology adoption model proposed by Venkatesh et al. [48] as a result of reviewing and
synthesizing eight models explaining information systems usage behavior, including TAM, and presents
a unified view of user acceptance composed by four key constructs:
• Performance expectancy: “The degree to which an individual believes that the new system is
helping him/her in performing the tasks in an easy and efficient way.” [48].
• Effort expectancy: “The degree to which an individual believes the new system is easy to use.” [48].
• Social influence: “The degree to which an individual perceives that important others believe he
or she should use the new system.” [48].
• Facilitating conditions: “The degree to which an individual believes that an organizational and
technical infrastructure exists to support the use of the system.” [48].
The first three directly determine the behavioral intention which indirectly influences the use behavior,
and the fourth only has impact on use behavior. Gender, age, experience, and voluntariness of use
moderate the effect of the four key constructs on intention and use behavior. As a consequence of
linking the ITIL CSFs to UTAUT, the following model was proposed (see Figure 4.3).
Again, top management support, due to its influence on all the CSFs, is considered the most impor-
tant one, having impact on all the key UTAUT components. Monitoring and evaluation is the only CSF
to have direct impact on BI for the same reason it had on AT in TAM. Technology applied, for instance,
has increased importance not only as improving the PEU (effort expectancy) but also as a facilitating
condition that can make the difference on using the framework.
The model gives a more detailed view on the effects of CSFs on ITIL adoption, but some problems
may arise from applying UTAUT which uses many variables to predict intentions and behaviors making
it way more complex than TAM. Adding to that, the model doesn’t consider impact of CSFs on inherent
characteristics of the user, like experience (training should be considered as affecting it) and still needs
more practical appliance validation, specially on successful ITIL implementations.
4.3 ITIL Implementation Roadmap
Using the findings of applying the proposed ITIL adoption model based on UTAUT [15] to a failed ITIL
implementation, Ahmad et al. [15] created a roadmap for future ITIL implementations (see Figure 4.4).
25
Figure 4.3: ITIL adoption model using UTAUT. Source: [15]
This roadmap uses lessons from failure to provide a step-by-step guide to success, with the following
steps:
1. Management and employee commitment: by providing necessary resources, giving importance
to the project and noticing employees, management commitment and support help them getting
committed to the success of the initiative.
2. Consultant selection: it is important to select a consulting company that has the expertise nec-
essary for a smooth ITIL implementation. Ideally should be some with ITIL Service Management
Certification.
3. Process identification and selection: organization and consulting company should identify and
select the main processes to adhere to ITIL standards, understanding the business, the roles and
the culture of the organization in order to prepare a smooth change.
4. Understand the current processes, functions and roles: it is important to understand the exis-
tent resistance in the organization and define and document well the processes to implement and
the roles and responsibilities of every person involved in the ITIL initiative.
5. Identifying and understanding the key customers: it is crucial to know the customers that the
organization is investing on, since they can give valuable information in order to understand if the
project is a good investment and drive it to success.
26
Figure 4.4: Roadmap for ITIL implementation. Source: [15]
6. Construct a project plan: adoption of a project management methodology and development of
an implementation plan (includes communications, training and awareness and a metric program
to map improvements) that clarifies the present situation of the organization and creates a vision
for the future.
7. Redesign processes to adhere to ITIL standards: in order to integrate ITIL best practices, pro-
cesses need to be re-engineered. Since ITIL processes have internal dependencies it is important
to understand and follow process governance best practices to ensure that implemented ITIL pro-
cesses will contribute to IT organization’s goals and better use the assigned resources.
8. ITIL tool selection: in order to avoid mistakes and implement ITIL processes in a smoother way,
a proper tool should be selected from the proper vendor.
9. Transition plan and designing training: enough time should be given to carefully consider the
training requirements and goals as well as design the transition plan and training activities.
10. Training the employees: proper training should be provided to employees using a common lan-
guage and understanding of best practices to insure that policy adherence, roles, and responsibil-
ities are understood and procedures are followed.
11. Implementation of ITIL process and technology: consists on the actual ITIL implementation
27
that varies based on scale, required customization and degree of complexity.
12. Evaluation and improvement: this final step includes analysis of the management of the project
and identification of lessons learned, considering any additional benefits and unexpected prob-
lems. In order to do that, the new processes should be roll out with detailed monitoring for ob-
servation and continuous improvement. Progress measurement must be also done, using defined
improvement criteria before and after the implementation.
Besides being a roadmap to success, this guide mixes the roles of the organization and the external
help and it is created based on what should not be done without a practical appliance in an ITIL imple-
mentation in order to actually make it succeed, which is its weakest point. Another problem is that, in
some steps, it does not provide methods to execute them, like when selecting a tool, it does not suggest
any criteria to be applied. Still, this guide provides valuable information from lessons taken from a real
world implementation.
28
5Research Proposal
Contents
5.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
5.2 ITIL Tool Selection Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.3 ITIL Processes’ Performance Evaluation Method . . . . . . . . . . . . . . . . . . . . . 35
5.4 Principles of the Evaluation Methodology . . . . . . . . . . . . . . . . . . . . . . . . . 36
29
30
This chapter is divided in four sections. Section 5.1 covers the second half of the definition of
the objectives for a solution step of DSRM and introduces the third phase of DSRM, in which the
artifacts’ desired functionality is presented. From the problem identified in Chapter 2 and the state
of the problem and feasible solutions presented in Chapter 4, the objective for a solution is inferred.
Section 5.2 to Section 5.3 correspond to the third phase of DSRM, in which the artifacts’ desired
functionality is presented in detail, which aim to achieve the identified objective to solve the problem
stated in Chapter 2. Section 5.4 explains the principles used in the proposed methodology to evaluate
the artifacts.
5.1 Objective
The problem, as stated in Chapter 2 is the lack of ITIL adoption, which results from the many barriers
and mistakes on ITIL implementation.
The objective of this proposal is to present a mechanism that through technology and evaluation
focused on people and processes contributes to increase ITIL adoption.
In order to fulfill the objective mentioned before, two methods are proposed to increase ITIL adoption
focused on two CSFs:
1. Tool selection: proper tool selection helps users see the system as not hard to use [15].
2. Monitoring and evaluation of ITIL implementation: the aim is to determine the relevance and
fulfillment of objectives, efficiency and effectiveness by assessing the strengths and weaknesses
of an ongoing or completed project, program or policy [49].
The choice of these factors comes not only from their importance but mostly from the knowledge that
most of ITIL CSFs are totally dependent on the organizational side (ex. top management support) being
very difficult to be controlled by external entities that support the organization on ITIL implementation.
For that reason, the choice is to the factors that can be controlled externally (but always looking to the
organization’s context) and that are focused on technology and evaluation. Processes and people are
also taken into account but as agents to these CSFs. This is why process priority and people’s feedback
are considered when choosing a tool and creating an ITIL processes’ performance evaluation system.
Since CSFs do not act isolated, the two selected ones are affected by others difficult to control, which
makes it important to take some assumptions in this proposal:
• Top management supports the ITIL initiative;
• IT staff is up to be part of a changing environment and has the inherent ability to adapt to change;
• Organization has the capability of communication and cooperation between departments;
31
• Change management, project management and governance consider external advices for ITIL
initiative;
• Good quality staff is allocated for ITIL;
• Organization knows their processes and customers;
• Processes to implement are previously selected;
• Training is properly provided to the staff.
With those assumptions, the methods correspond to procedures to be incorporated in the implemen-
tation plan to improve both selected CSFs, being a guide for the organizations and for the entities that
help them implement ITIL.
In the following sections, these methods are explained in detail. Section 5.2 details the ITIL tool
selection method based on MACBETH and Section 5.3 explains the method to evaluate the performance
of the selected ITIL processes based on results-based monitoring and evaluation systems’ building
actions.
5.2 ITIL Tool Selection Method
This section is divided in four subsections, corresponding to the sequential process that composes this
method. MACBETH was chosen as the basis technique for this method since only requires qualitative
judgments, instead of quantitative ones to score alternatives and weight criteria, and with the support
of its powerful decision support system M-MACBETH can automatically compute the overall values of
alternatives and make robustness and extensive sensitivity analysis. In the first step, the identification
of the evaluation criteria and definition of performance levels are made (Section 5.2.1). The second
step is the criteria weighting and evaluation of their performance levels on which criteria weights are
assessed and a value function for each criterion is built (Section 5.2.2). The third step corresponds to
the tool testing and document analysis for each criterion (Section 5.2.3). The final step is the analysis
of the results, on which overall value scores are obtained for all alternatives. Sensitivity and robustness
analyses are also performed to help giving a selection recommendation (Section 5.2.4).
5.2.1 Identify the Criteria and Define their Performance Levels
This first step consists on identifying the criteria to evaluate the software tools for ITIL and define the
performance levels. For this proposal a focus on the functionality is proposed to compare tools according
to their core, including processes and people along with technology.
Three groups of criteria are proposed in this method:
32
• Processes: tools are useful to provide help on aligning company’s needs with ITIL’s implementa-
tions as well as a way to perform processes more efficiently, improving results of ITIL implementa-
tion [50]. This way, tool selection must depend on process selection and has to fully focus on tools
that best provide help on executing the selected processes. Three criteria compose this group,
being them: information (data used by processes), activities (tasks that compose the processes)
and measures (quantification of the processes’ performance using metrics and Key Performance
Indicators (KPIs)).
• Exporting Formats: it is important, for each ITIL tool, to consider how data can be extracted from
processes, reports and knowledge base to be used outside. This group is then composed by one
criterion: exporting formats, which is applied to tickets, reports and knowledge base to make an
analysis on the compatible exporting formats for their data.
• Costumers: considering the costumer view over the ITIL tool by emphasizing “the broad reach
of ITSM beyond the concerns of IT infrastructure to viewing IT as a service organization that
supports end-to-end business operations” [6] is also important, following ITIL core philosophy. The
criterion of this group focuses on data available to costumers which come from diverse sources
like knowledge base, processes and their metrics.
Each tool is assessed according to the presence of each criterion as recommended by ITIL best
practices for each selected ITIL process. The levels of performance are then defined considering the
percentage of ITIL recommendations in the tool for the corresponding criterion: level A (>= 75%), level
B (50% - <75%), level C (25% - <50%) and level D (<25%). In any case, a DM can add more relevant
criteria and change the number and range of performance levels to customize this method to more
specific organization’s needs.
This step can also be less human dependent if criteria and performance levels to be applied become
standardized. That way, every company would use the same criteria and number of performance levels,
automating this step.
5.2.2 Weight the Criteria and Evaluate their Performance Levels
In this step, a value function is built for each criterion from the preferences of the DM. For each criterion,
two reference performance levels are defined (“neutral” and “good”). Then, using MACBETH semantic
categories: very weak, weak, moderate, strong, very strong or extreme, the DM judges the differences
in attractiveness between each two levels of performance, choosing one or more of those categories.
Finally, M-MACBETH, the decision support system, uses a linear programming problem to generate a
numerical value scale, representative of the DM’s judgments, which is then analyzed by the DM to make
corrections if necessary. Using the validated value scales, M-MACBETH computes their value functions.
33
Each criterion is also weighted according to ranks attributed by the DM. First, their neutral-good
swings are ranked, then, just like happens with the performance levels, the DM uses the MACBETH
semantic categories to judge the difference in attractiveness between each two neutral-good swings,
which M-MACBETH uses to create a weighting scale for all criteria. In the end, the DM can validate the
proposed weights, adjusting them if necessary.
This is a step that needs a lot of human interaction, turning it both manual and automatic (supported
by a calculating system). Contrary to the first step that can be totally automated using standard criteria
and performance levels, this is a step that translates the company’s preferences, making human interac-
tion a crucial element. By making their judgments, companies specify which criteria and performances
best match their needs according to what was defined in the previous step. Only the generation of
numerical scales for each criterion and the criteria weights are automated.
5.2.3 Test the Tools and Analyze their Documentation
In this third step, tool testing is made for each criterion using free trial versions, which have the purpose of
allowing some tool evaluation before obtaining them. Since these versions can present some limitations
compared to the paid ones, their documentation is also analyzed to obtain additional information. Using
the ITIL recommendation, a mapping between each tool and the ITIL best practices for each criterion is
made, using the percentage scales defined in step 1 for the performance levels.
5.2.4 Analyze the Results
With the performance levels for each criterion attributed to all the alternatives, their conversion into value
scores must be done. In this last step, value functions built in step 2 for each criterion are used for this
purpose. Using weighted summation of its value scores, an overall value score is obtained using the
support system for each alternative, achieving a final ranking of alternatives. Finally, sensitivity and
robustness analyses are made followed by the validation from the DM.
Sensitivity analysis uses criteria weight variations within the limits allowed by the DM’s weighting
judgments to show what changes may be produced in the results by those variations.
The robustness analysis allows detecting the existence of dominance or additive dominance be-
tween alternatives, examining the implication into the global results from variation of all or some of the
parameters of the model.
Dominance of an alternative a over b occurs when a is better than b in at least one criterion and
not worse in any criterion. In M-MACBETH, this case is represented by a red triangle, meaning that the
alternative in row dominates the one in column.
Additive dominance of an alternative a over b occurs when a is always globally more attractive than
34
b using additive aggregation. In M-MACBETH, this case is represented by a green cross, meaning that
the alternative in row additively dominates the one in column.
There are three sub-analyses in the robustness analysis, either using local information (criteria value
scales) or global information (criteria weights), being them:
• Ordinal: using local information, considers the ranking of the options within each criterion. Using
global information, considers the ranking of the criteria “neutral-good” swings.
• MACBETH: considers the judgments in the matrices of judgments for the value scales when using
local information or for the criteria weights when using global information.
• Cardinal: uses the criteria value scales when considering local information or the criteria weighting
scale when considering global information.
With these analyses completed it is then possible to recommend an alternative.
5.3 ITIL Processes’ Performance Evaluation Method
This section details the method to evaluate the performance of the selected ITIL processes. Results-
based monitoring and evaluation systems’ building actions were selected as the basis for this method
since their purpose is to create a system that provides feedback on the outcomes and goals, comparing
how well a project, program or policy is being implemented against the expected results [36]. In the
first step, a selection of the evaluation criteria and their ITIL metrics for the selected processes is made
(Section 5.3.1). The second step is the definition of the analysis period and its metrics’ targets (Sec-
tion 5.3.2). The third step corresponds to the calculation of the metrics’ values in the analysis period
(Section 5.3.3). The final step is the analysis of the results, on which the values for the analysis pe-
riod are compared with their target values and the performance is evaluated according to the evaluation
criteria (Section 5.3.4).
5.3.1 Select the Evaluation Criteria and Metrics
This step is based on the “formulate outcomes and goals” and “select outcome indicators to monitor”
actions to build results-based monitoring and evaluation systems [36]. Therefore, criteria and its metrics
are first chosen to evaluate the performance of the selected ITIL processes. ITIL proposes a set of
metrics for each process according to two criteria: effectiveness and efficiency (the other metrics are
considered as important only for control) with the goal to achieve higher performances [12]. Those met-
rics and evaluation criteria should be used as recommended by ITIL as a basis for evaluation purposes.
Other metrics derived or not from those as well as other criteria can also be added to customize this
35
method. After selecting the evaluation criteria and metrics to use, a mapping between them is made in
order to categorize the metrics for further analysis of the results in step 4.
5.3.2 Define the Analysis Period and its Metrics’ Targets
This step consists on defining the analysis period and specifying its targets. Based on the “gather
baseline information on the current condition” and “set specific targets to reach and dates for reaching
them” actions to build results-based monitoring and evaluation systems [36], targets for each selected
metric are defined based on the current condition of the company and the analysis period, which must
be a relevant one to assess the ITIL processes’ performance. Those targets will then be crucial to step
4, on which the performance will be analyzed and evaluated.
5.3.3 Calculate the Metrics in the Analysis Period
This is an automatic step which consists only on using a support system that periodically calculates
the selected performance metrics during the analysis period. This system must show the updated
values of the metrics, but also give information about how distant are the current metrics’ values to the
defined performance targets for the analysis period. The goal is to provide the company with crucial
performance data during that period so that actions can be taken to achieve the targets, but also be the
basis for step 4.
5.3.4 Analyze the Results and Evaluate them According to the Selected Criteria
The final step is based on the “analyze and report the results” action to build results-based monitoring
and evaluation systems [36]. Consists on analyzing the results of the whole analysis period, on which
the defined targets are used to evaluate the performance by comparing the calculated metrics with their
target values. All the analysis and evaluation is made using the performance criteria (groups of metrics),
giving insides about the strengths and weakness of the ITIL processes’ performance.
5.4 Principles of the Evaluation Methodology
To evaluate each artifact, it is proposed a methodology divided in three steps: the first one corresponds
to the description of the execution conditions of the evaluation, the second step is the validation of the
artifact, and finally, the last step is the evaluation of the artifact’s functionality.
In this section it is provided a brief explanation of the principles used in this methodology, starting
with the Design Science Research Evaluation framework, followed by the four principles of Osterle to
then finalize with the Moody and Shanks quality framework.
36
5.4.1 Design Science Research Evaluation Framework
Evaluation is a crucial step in DSRM because it is what verifies the adequacy of the artifact to a solution
to the problem, comparing its objectives with the results observed. In context of DSRM [20], five design
evaluation methods were defined, being them: observational, analytical, experimental, testing and
descriptive. However, not much more guidance was provided on how to accomplish each of these
evaluation paths.
Taking into account prior research in the area of DSRM evaluation, Pries-Heje et al. [51] proposed a
framework to fill this gap by helping design science researchers build strategies for evaluation, achieving
improved rigor in DSRM.
This framework distinguishes evaluation in three dimensions, each one having two aspects. The first
dimension is the time of the evaluation, which can be done ex ante (the evaluation takes place before
the artifact is developed), or ex post (the evaluation occurs with the artifact already developed). The
second dimension is the form of the evaluation that can be artificial (the evaluation considers a solution
in a non-realistic way), or naturalistic (the evaluation explores the performance of a solution within its
real environment). The third and final dimension distinguishes the artifact between design process
(result of a particular process that can be considered tangible) and design product (set of activities,
tools, methods and practices that can be used to guide the flow of production).
A strategy to evaluate the artifact is also proposed based on three questions:
• When does the evaluation take place?
• How is it evaluated?
• What is actually evaluated?
5.4.2 Four Principles of Osterle et al.
With the objective of providing a contribution to the rigor of research such as criteria for journal and
conference reviewers work, criteria for evaluation of researchers and research organizations and design-
oriented information systems research in the international research community, these principles result
from a memorandum written by 10 authors and supported by 111 full professors to validate artifacts.
These principles are [16]:
• Abstraction: the artifact must be applicable to a class of problems.
• Originality: the artifact must substantially contribute to the advancement of the body of knowl-
edge.
37
• Justification: the artifact must be justified in a comprehensible manner and must allow for its
validation.
• Benefit: the artifact must yield benefit, either immediately or in the future, for the respective stake-
holder groups.
5.4.3 Moody and Shanks Quality Framework
As a result of research on how to evaluate and improve the quality of data models, the Moody and
Shanks quality framework uses the perspective of stakeholders for that purpose and proposes the fol-
lowing quality factors [17]:
• Completeness: refers to the containment of all users and information requirements in the model.
• Integrity: refers to the definition by the model of all applied business rules.
• Flexibility: consists on the ease of applying changes in requirements without changing the model
itself.
• Understandability: is the ease of perceiving the concepts and structures in the model.
• Correctness: refers to whether the model conforms to rules and conventions.
• Simplicity: refers to the containment of the minimum number of entities needed for the model,
turning it easy to follow and apply.
• Integration: refers to the consistency of the model with the rest of the organization.
• Implementability: is the ease to implement the model according to defined constraints.
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6ITIL Tool Selection Method
Contents
6.1 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.2 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
39
40
This chapter is divided in two sections and details the demonstration and evaluation steps of DSRM
for the ITIL tool selection method.
Section 6.1 explains how experimentation, simulation, case study, proof or other appropriate activity
was used to demonstrate the capacity of this artifact to solve one or more instances of the problem,
corresponding to the fourth step of DSRM: demonstration.
Section 6.2 details how the evaluation methodology explained in Chapter 5 was applied to the artifact
and presents its results, corresponding to the fifth step of DSRM: evaluation.
6.1 Demonstration
This section demonstrates the use of the ITIL tool selection method based on MACBETH, corresponding
to the demonstration phase of DSRM for this artifact.
A company from the bank sector that wanted to implement four ITIL processes and had doubts
about the software to use, was selected for this purpose. The four processes that this company wanted
to implement were: incident management, request fulfillment, problem management and change man-
agement.
The DM in the field study here reported was the systems manager of the company. The author of
this dissertation was the decision analyst in this method.
The software solutions assessed were BMC Remedy, ServiceNow, ZenDesk and JIRA SD, which
were selected due to their representativeness in the market as consequence of characteristics like an-
tiquity, usability, popularity and potential of expansion.
The following subsections explain the demonstration for each step of the method.
6.1.1 Identify the Criteria and Define their Performance Levels
In this first step, meetings with the company’s DM were made to validate the criteria and performance
levels to be used in the model. All the proposed criteria and performance levels were validated by the
DM and joint with the four selected ITIL processes or the three data sources on which they would be
applied. The result was a validated mapping between the list of criteria and the selected processes or
data sources (see Table 6.1).
Note that the four proposed and validated performance levels are applied on each criterion.
6.1.2 Weight the Criteria and Evaluate their Performance Levels
In this second step, the M-MACBETH decision support system was used to help the DM define reference
performance levels, weight the criteria and evaluate their performance levels.
41
Table 6.1: Mapping between assessment criteria and process/data sources.
First, the DM was asked to select neutral (neither positive nor negative) and good (significantly attrac-
tive) reference levels. It was defined that all criterion would have the same neutral and good reference
levels, which means that if a level C corresponded to neutral reference level in one criterion, all others
would have level C as the neutral one. For all criteria, the DM chose level A as the good reference and
C as the neutral one.
Then, choosing one or more MACBETH semantic categories, the DM judged the attractiveness
differences between each two performance levels. The DM defined that the judgments would be the
same for all criteria. Figure 6.1 presents the validated DM’s judgments matrix and the numerical scale
computed by the M-MACBETH for the criterion “Activities” for the process “Incident Management”.
Figure 6.1: MACBETH judgments matrix and numerical scale for criterion “Activities”.
The numerical scales were anchored on the value scores 0 and 100 which were assigned to the two
reference levels “neutral” and “good”, respectively. Those scales were proposed by the M-MACBETH
decision support system based on the set of judgments made by the DM, who then analyzed and
validated them. Using the validated value scales, M-MACBETH computed their value functions.
To weight the criteria, neutral-good swings were ranked by the DM for all the criteria by their overall
42
attractiveness. Then, the DM used MACBETH semantic categories to judge the differences in attrac-
tiveness between each two of them as shown in Figure A.1 (Appendix A).
Finally, with those judgments, the M-MACBETH created a weighting scale that was validated by the
DM and shown in Figure 6.2.
Figure 6.2: Weighting scale for the criteria for each process or data source presented in Table 6.1.
6.1.3 Test the Tools and Analyze their Documentation
To test the tools, free trial versions were used, since their purpose is to show some functionality to help
the DM make his/her decision. Complementing that, tools’ documentation was also analyzed since trial
versions have limitations on what can be tested.
With this information and looking to ITIL recommendations for each criterion, a mapping between all
criteria and ITIL recommendations was made, obtaining the performances for all the four selected tools.
The results are presented in Table 6.2.
Table 6.2: Mapping between evaluation criteria and ITIL recommendations for the selected processes and datasources.
43
6.1.4 Analyze the Results
The performances obtained in the third step were inputted in M-MACBETH. Using the value functions
built in the second step, this software transformed the performances into value scores and calculated
the overall scores for all selected tools (see Figure 6.3). JIRA SD ranked first with 73.03 overall units
followed by ServiceNow with 72.24 overall units. BMC Remedy became third with 69.46 overall units
and ZenDesk was the worst with 68.26 overall units. The results clearly show that none has a good
performance in all the criteria, since all scores are below 100 overall units. However, JIRA SD has the
closest score to the overall score of the hypothetical alternative “Good at all”.
Figure 6.3: Overall value scores of the alternatives.
JIRA SD does not have the highest score in only three criteria: “Metrics/KPIs” for Incident Manage-
ment process, “Metrics/KPIs” for Change Management process and “Exporting Formats” for reports. A
sensitivity analysis on the weight of criterion “Metrics/KPIs” for Incident Management showed that the
weight of this criterion needed to be raised up from 3.17% to 4.2% to see ServiceNow be ranked first
and to 9.0% to see ZenDesk on top. The same analysis showed that for the criterion “Metrics/KPIs”
for Change Management, the weight needed to be raised up from 3.17% to 9.0% to see ZenDesk be
ranked first, and for the criterion “Exporting Formats” for reports the weight needed to be raised up from
1.59% to 4.6% to make ServiceNow the first choice; to 5.1% to put BMC Remedy on top; and to 17.4%
to see ZenDesk be ranked first. However the DM opted to not change the weights. All the analysis here
detailed is shown in Figure B.1 (Appendix B).
Robustness analyses were also made with M-MACBETH. In the first robustness analysis, only ordinal
data in local and global information was considered, concluding that this information was insufficient to
select the best alternative as shown in the left side of Figure 6.4.
The second robustness analysis was made using MACBETH judgments. There were no changes to
the obtained results of the previous analysis.
Finally, the third robustness analysis was made using simultaneous variations of ±1% on the weights
of all criteria, not allowing negative weights. This analysis showed that JIRA SD continues to be the best
alternative within these variations on the criteria weights. The right side of Figure 6.4 shows the results
44
of this analysis, where the green crosses in the cells mean that the alternative in row, JIRA SD, additively
dominates all the other alternatives in columns BMC Remedy, ServiceNow and ZenDesk.
Figure 6.4: Robustness analyses (left uses ordinal scale for local and global information, and right uses ordinal,MACBETH and cardinal with ±1% of global uncertainty).
Taking into account all the defined criteria and the judgments of attractiveness made by the DM,
JIRA SD was recommended to the company, since it is the best alternative considering the overall value
scores and the sensitivity and robustness analyses.
6.2 Evaluation
In this section, the evaluation methodology is applied to the ITIL tool selection method, starting with the
Design Science Research Evaluation to describe the execution conditions of the evaluation, followed by
the four principles of Osterle to validate the artifact, and finally, the Moody and Shanks quality framework
to evaluate the functionality of the artifact. In this evaluation process, feedback from the DM of the
company was collected during the demonstration of the method along with an interview after applying it.
The DM was a certified systems manager of the company with more than 9 years of experience.
6.2.1 Design Science Research Evaluation Framework
This framework was used to describe the execution conditions of the evaluation of the ITIL tool selection
method. The results were the following:
45
• When did the evaluation take place? The evaluation was ex post, meaning that the method was
evaluated after its construction and demonstration.
• How was it evaluated? The evaluation was naturalistic since it was conducted in a real company
facing real problems.
• What was actually evaluated? The method was considered a design process, being the result
of a particular process and not a final product.
6.2.2 Four Principles of Osterle et al.
The four principles of Osterle et al. [16] were applied to validate the method, with the following results
(see Figure 8.1):
• Abstraction: the method can be applied to any company having doubts on choosing an ITIL tool,
giving the option to add criteria and performance levels to meet all the company’s requirements.
• Originality: the method was seen as an original solution, since the DM didn’t know about a similar
research or product for this purpose.
• Justification: the method is justified by the motivation of the problem and the related work. It is
also described with clear steps and instructions and demonstrated using graphical representations
of its appliance.
• Benefit: the method yields benefit, since provides an easier and complete evaluation of ITIL tools,
confirmed by the demonstration, where it helped the DM select an ITIL tool, leading to its intention
to continue to use this method.
The four principles were achieved, thus showing the validity of the method.
6.2.3 Moody and Shanks Quality Framework
The following results were obtained from the appliance of this framework to the demonstration of the
ITIL tool selection method and the interview with the DM after applying the method. The results were
(see Figure 8.1):
• Completeness: The method is complete since the used criteria contain all the DM’s requirements,
and the DM can include or remove criteria and change their performance levels to customize the
model to his needs.
46
• Integrity: The method combines interviews and observation with literature review to define criteria
and their performance levels. This way, a basis composed by some constraints is introduced upon
which the specific organization’s needs are taken into account to mitigate possible errors without
losing flexibility.
• Flexibility: The method is flexible since the DM can adjust it to his organization’s strategies.
• Understandability: The method uses concepts of the ITIL language, which turns it easier to
understand, but the DM lacks knowledge of the used decision analysis process. Guidance is
needed to overcome this difficulty.
• Correctness: According to DM’s intentions, the method is valid and correct.
• Simplicity: The method is simple since it is easy to follow and apply.
• Integration: The method helps organizations make the best decision, being consistent with the
problem.
• Implementability: The method implementability is dependent on factors such as organization’s
policies and laws. The company on which this method was demonstrated used this as a decision
auxiliary tool.
Almost all the quality factors were accomplished. Only understandability and implementability
were not totally accomplished. The first factor was just half accomplished since the method was not
easy to understand at the beginning due to some unfamiliarity with the decision analysis process itself,
which was solved by a period of adaptation. The second factor was not verified since there were several
bureaucracies to implement this solution, specially in a company of the bank sector. These results show
that this method is suitable for evaluating software tools for ITIL.
47
48
7ITIL Processes’ Performance
Evaluation Method
Contents
7.1 Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
7.2 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
49
50
This chapter is divided in two sections and details the demonstration and evaluation steps of DSRM
for the method to evaluate the performance of the selected ITIL processes.
Section 7.1 explains how experimentation, simulation, case study, proof or other appropriate activity
was used to demonstrate the capacity of this artifact to solve one or more instances of the problem,
corresponding to the fourth step of DSRM: demonstration.
Section 7.2 details how the evaluation methodology explained in Chapter 5 was applied to the artifact
and presents its results, corresponding to the fifth step of DSRM: evaluation.
7.1 Demonstration
This section demonstrates the use of the ITIL processes’ performance evaluation method based on
results-based monitoring and evaluation systems’ building actions, corresponding to the demonstration
phase of DSRM for this artifact.
An IT consulting company that wanted to improve the performance of its ITIL processes was selected
for this purpose. The processes that this company wanted to improve were all categorized as request
fulfillment.
The following subsections explain the demonstration for each step of the method.
7.1.1 Select the Evaluation Criteria and Metrics
In this first step, criteria and its metrics were chosen to evaluate the performance of the selected ITIL
process. To do that, meetings in the company along with literature review were made, combining the
ITIL’s recommendations for the selected ITIL process with company’s strategy and interests. Only one
metric from the recommended by ITIL was not chosen due to not being a main priority to the company
associated with the required complexity to implement it. Furthermore, there were not additional neither
derived metrics from the ITIL ones.
Therefore, all the chosen metrics were selected as recommended by ITIL and mapped with the ITIL
suggested criteria: effectiveness and efficiency. Along with that, another criterion was proposed and
used: load (a control criteria focused on the amount of processes’ instances). This way, all the metrics
became linked to a criterion (see Table 7.1 where green means the metric was implemented and red
means it wasn’t) to then analyze the results in step 4.
7.1.2 Define the Analysis Period and its Metrics’ Targets
In this second step, the analysis period and its metrics’ targets were defined. It was agreed that the
analysis period would be divided in two subperiods, both using the same metrics and criteria defined in
51
Table 7.1: Mapping between selected metrics and criteria and their implementation.
step 1 and lasting two weeks each.
In the first subperiod, the company would be asked to perform the processes with their “as is” metrics
(only having access to their current metrics) and at same time the performance would be externally
analyzed using the “to be” metrics defined in step 1. After that, the values of the “to be” metrics would
be provided to the company as a performance report of that subperiod.
In the second subperiod, the company would continue to perform the same processes but this time,
would have access and use the metrics defined in step 1 to analyze the performance during the two
weeks period. After that, the final results would be analyzed and compared with those from the first
subperiod.
The metrics’ targets were also defined based on the performance condition of the company and the
analysis period. It is with those values that the performance can be analyzed and evaluated in terms of
the distance to the aimed targets. Note that the values for the second subperiod were defined only after
concluding the first superiod and access its performance report. All the values can be seen in Table C.1
and Table C.2 (Appendix C).
7.1.3 Calculate the Metrics in the Analysis Period
To calculate the performance metrics defined in step 1, a support system was used (see Figure 7.1).
This system was created using the database of the company’s ITIL software tool to calculate and present
the selected metrics with the distance to their subperiod target values.
The presented data was periodically updated during the analysis period and the target values changed
according to the respective subperiod of analysis.
The access to this system was only provided to the company during the second subperiod of analysis,
on which had the role of supporting the monitorization of the processes’ performance.
Along with the metrics defined in step 1, their targets and distance to them, more data was provided
by the system such as processes’ instances by assignees, types of processes and historical data to give
a better inside on the processes’ performance.
52
Figure 7.1: Performance analysis support system.
7.1.4 Analyze the Results and Evaluate them According to the Selected Criteria
In this final step the results from both analysis subperiods were analyzed.
First, a performance analysis was made for each subperiod, comparing their values with the re-
spective targets according to the selected criteria defined in step 2 (see Table C.1 and Table C.2 from
Appendix C).
Then, using those criteria, performance evaluation was made comparing both subperiods’ perfor-
mances in terms of value distance to the defined targets, which allowed to identify their strengths and
weaknesses (see Table C.3 from Appendix C). It was concluded that the second subperiod had a bet-
ter performance than the first one with clear effectiveness improvement (one target accomplished and
shorter distance to the one that was not fulfilled in this criterion).
7.2 Evaluation
In this section, the evaluation methodology is applied to the ITIL processes’ performance evaluation
method, starting with the Design Science Research Evaluation to describe the execution conditions
of the evaluation, followed by the four principles of Osterle to validate the artifact, and finally, critical
analysis and the Moody and Shanks quality framework to evaluate the functionality of the artifact. In
this evaluation process, feedback was collected during the demonstration of the method and interviews
53
were made with practitioners after its appliance. The interviewed practitioners were a senior software
architect with more than 15 years of experience, a business analytics consultant with more than 10 years
of experience and a SAP business unit manager with more than 7 years of experience.
7.2.1 Design Science Research Evaluation Framework
This framework was used to describe the execution conditions of the evaluation of the method to assess
the performance of the selected ITIL processes. The results were the following:
• When did the evaluation take place? The evaluation was ex post since the method was evalu-
ated after its construction and demonstration.
• How was it evaluated? The evaluation was naturalistic, being conducted in a real company
facing real problems.
• What was actually evaluated? The method was considered a design process, being the result
of a particular process and not a final product.
7.2.2 Four Principles of Osterle et al.
The four principles of Osterle et al. [16] were applied to validate the method, with the following results
(see Figure 8.1):
• Abstraction: the method can be applied to any company that wants to evaluate the performance of
their ITIL selected processes, giving the option to add criteria and metrics to meet all the company’s
requirements.
• Originality: the method was not seen as totally original since practitioners knew about similar
approaches to evaluate the performance of the processes. However, the formalism and rigor
associated made the difference and were seen as a new and better way to apply an empirical
known method.
• Justification: the motivation of the problem and the related work justify the method which is
described with clear instructions and demonstrated with illustrations of its appliance.
• Benefit: the method is beneficial since provides a rigorous, complete and easy way to evaluate
the performance of the ITIL selected processes, confirmed by the demonstration where it actually
helped the company to evaluate and improve the performance of their ITIL processes leading to
the practitioners’ intention to continue to use it.
54
Almost all the four principles of Osterle were achieved. Only originality was partially achieved since
the method was not totally new to the practitioners. The novelty lied in its rigor and formalism, since it
was an empirically known approach. Besides not being completely original, the method can be applied
to other companies, is well justified and has great benefit, making it a valid one for its purpose.
7.2.3 Critical Analysis
This analysis evaluates the capability of the method to assess ITIL processes’ performance, meaning the
capability to determine the fulfillment of its defined objectives, efficiency and effectiveness and identify
its strengths and weaknesses.
To do that, the results of its demonstration (see Appendix C) were analyzed.
From the analysis of Figure 7.2 a clear improvement of the selected ITIL process’s performance can
be seen as a result of its good evaluation provided by the method.
Figure 7.2: Distances to the ITIL process’s targets from the demonstration of the method. The axis corresponds tothe target and the colors mean target fulfilled (green) or not fulfilled (red). If the distance value is 0, thevalue of the metric is equal to its target. The left bar corresponds to phase 1 and the right correspondsto phase 2.
The metrics with higher distances to the respective target in phase 1 suffered the greatest improve-
ments in phase 2, not only shortening their distances to the target, but in some cases, fulfilling it. Backlog
size and mean handling time are the metrics that best illustrate those improvements. This means that
the method not only allowed the determination of the fulfillment of the defined targets, but also a good
55
identification of what could be improved (the weaknesses) and what was already good (the strengths) in
the effectiveness and the efficiency of the process.
From the analysis of Figure 7.3 the contribution of the method to the improvement of the process’s
performance is more prominent.
Figure 7.3: Prediction’s precision and process’s statuses deviation from the demonstration of the method. The leftgraph shows the percentage of requests bellow or above the predicted total amount. The right graphshows the relative distribution of the process’s statuses between the two phases.
On the left side of the figure, the process’s load on each demonstration subperiod is compared with
its respective prediction. The smaller bar in the second subperiod (phase 2) shows an improvement
compared with the first subperiod (phase 1), meaning that the prediction was more accurate in the
second subperiod (phase 2). This result shows that the method helped to a better analysis of the
variation of the process load, which ultimately contributed to a more precise definition of the performance
targets.
On the right side of the figure, the relative distribution of the process’s statuses from the first sub-
period to the second one is presented. The statuses are organized from the initial ones (“open” and in
“progress”) to the final ones (“resolved” and “closed”). The results evidence a clear shift from initial pro-
cess’s statuses to most final ones as the biggest reason to a better performance. This is complemented
with the values from Figure 7.2 that show problems with the backlog size and specially with the mean
handling time, due to process’s instances stuck in initial statuses.
The improvement on this field clearly supports the contribution of the method to the detection of this
major weakness in the process performance. There is still room for improvement in this company for
56
this particular process, since some targets are not yet accomplished as seen in Figure 7.2, which can
be explained by the increasing amount of process’s instances in waiting statuses like “to test”, “pending
information” and “resolved” as seen in Figure 7.3.
From this analysis, it is clear that the method has a great capability to evaluate ITIL processes’
performance with a big focus on the detection of its strengths and weaknesses as evidenced by the
positive results from its demonstration where it contributed to a big boost on the selected ITIL process’s
performance.
7.2.4 Moody and Shanks Quality Framework
The following results were obtained from the appliance of this framework to the demonstration of the
method to assess the performance of the selected ITIL processes and the interviews with the practition-
ers after applying the method. The results were (see Figure 8.1):
• Completeness: The method is complete since the used criteria and metrics contain all the com-
pany’s requirements and there is the possibility to adapt the model to its needs, including or re-
moving some of the criteria and metrics.
• Integrity: The method combines interviews with literature review to define criteria and related
metrics. This way, a combination between constraints and organization’s needs is made, mitigating
possible errors without losing flexibility.
• Flexibility: The method is flexible since the practitioners can adjust it to their company’s strategies.
• Understandability: ITIL language is the only one used in this method, making it understandable.
• Correctness: The method is valid and correct according to the practitioners’ intentions.
• Simplicity: The method is easy to follow and apply, making it simple.
• Integration: The method helps organizations evaluate the ITIL processes’ performance, being
consistent with the problem.
• Implementability: The implementability of the method is dependent on factors such as organiza-
tion’s policies. The company on which this method was demonstrated used this as a performance
evaluation auxiliary tool.
Almost all the quality factors were accomplished. Only implementability was not fulfilled since there
were some bureaucracies to implement this solution. Besides that, these results reinforce the great
capability of the method to evaluate the performance of ITIL processes.
57
58
8Conclusion
Contents
8.1 Lessons Learned . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
8.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
8.3 Main Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
8.4 Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
8.5 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
59
60
In a world of growing technological evolution, where even more companies face disruption along with
economic difficulties and increased demanding from customers, strategic service quality improvement is
more than just an option. ITIL is a widely accepted methodology to improve service quality [12], having
many benefits [2–5] that led to an increased interest in many countries [4,6–11]. Still, there are barriers
to its adoption [14] that cause mistakes on companies [13], being the difficulties in implementation one
of the most common and impactful barriers [15]. Those are the reasons that make companies abandon
their ITIL investment, revealing a problem: the lack of ITIL adoption.
A lot of research has been done to solve this problem, mainly related with CSFs and their role as
important elements for a successful ITIL implementation. Through literature review, the relations and
classification of those factors were found along with their application in adoption models and roadmap
for successful ITIL implementation.
Following this, the proposal is composed by two methods that through technology and evaluation
focused on people and processes contribute to increase ITIL adoption. To fulfill that objective, the
methods focus on two CSFs: tool selection and monitoring and evaluation of ITIL implementation. For
the first CSF, a method to select ITIL tools based on MACBETH is proposed. For the second CSF,
results-based monitoring and evaluation systems’ building actions are the basis to the proposed method
to evaluate the performance of the selected ITIL processes.
To access the usefulness of the artifacts, two demonstrations were made, one for each proposed
method. The method to select ITIL tools was demonstrated in a company of the bank sector that wanted
to implement four ITIL processes and had doubts about the software to use. For the method to evaluate
the performance of ITIL processes, an IT consulting company that wanted to improve the performance
of its ITIL processes was selected.
To validate and evaluate the artifacts and their results, the following were used:
• The four principles of Osterle et al. [16];
• Critical analysis;
• The Moody and Shanks quality framework [17].
From this evaluation, it was shown that the proposed methods are generic enough to be applied in
different companies that want to invest in ITIL. Both artifacts had very positive results, being able to
improve the two CSFs in ITIL implementations, that they focus. As a consequence, it was concluded
that these methods contribute to increase ITIL adoption.
The methods and their results were communicated to proper audiences through demonstrations
to their practitioners and submission and presentation of a scientific paper in an international confer-
ence [18].
61
In the next sections, the conclusions are detailed, presenting the lessons learned during the research
(Section 8.1), the identified limitations (Section 8.2), the main contributions of the proposed methods
(Section 8.3) and the related future work (Section 8.5). The last step of DSRM: communication,
in which the problem, its importance, the artifacts, their utility and novelty, the rigor of their designs
and their effectiveness are communicated to researchers and other relevant audience is also detailed
(Section 8.4).
8.1 Lessons Learned
During this research, lessons were learned from the related work, construction of the artifacts, demon-
stration and evaluation phases.
From the related work, it was noted a great effort to apply CSFs on known adoption models such
as TAM and UTAUT, leading to the creation of a roadmap to implement ITIL. Still, the problem stays
without a solution. Besides the many benefits that ITIL can provide to companies, they still have doubts
on how to implement it, due to lack of guidelines for that purpose. It was learned that the selection of
ITIL software tools and the evaluation of the ITIL implementation are two of the most important CSFs for
ITIL adoption and must not be underestimated.
During the construction of the artifacts it was learned that there isn’t yet a consensus on the criteria to
select ITIL tools, leading to an even bigger dependence on the companies. Along with the related work
it was also learned the usefulness of the MACBETH to make fundamental decisions and the importance
of results-based monitoring and evaluation systems to provide feedback on the outcomes and goals
of a project, program or policy, comparing its implementation against the expected results. These two
approaches weren’t well known in the companies where they were applied.
Finally, from the demonstration and evaluation phases, the learned lessons were mainly practical.
The accuracy of the ITIL tool selection method is highly dependent on the opinion of the DM. Because
of that, DMs have to know exactly their needs before starting the decision process. Regarding the
method to evaluate the performance of ITIL processes, it was learned that its effectiveness depends
on the evaluation of the company’s situation, since it is with that data that the performance targets can
be more accurate and meaningful. Finally, besides recognizing the value of the proposed methods,
companies showed resistance to change and start using them.
8.2 Limitations
The limitations associated with the proposed methods are related with the demonstrations and the used
M-MACBETH software.
62
Regarding the demonstrations, it is not possible to state that the methods are applicable to every
company with every size in every industry, since the demonstrations were only made in two companies
(one for each method). Besides that, the results and the provided feedback and interviews from those
demonstrations give indications that the method to select ITIL tools can be applied to all organizations
that want to choose a software tool for ITIL besides being focused only on its functionality, and the
method to evaluate the performance of ITIL processes can be applied to all organizations that want to
increase the performance of their ITIL processes, thus giving to these artifacts the potential to be applied
to all the organizations that want to increase their ITIL adoption.
Regarding the second aspect, M-MACBETH has two limitations. The first one is its still old appear-
ance that can negatively impact the method to select ITIL tools and the software learning process. The
second one is the absence of hierarchical analysis support, where there is the need to give weights to
all criteria along a tree. All this lead to the necessary support from a decision analyst in the ITIL tool
selection process, since the DM does not have the necessary knowledge.
Finally, also from the demonstrations, another limitation comes. This one affects the results from the
Moody and Shanks quality framework and the four principles of Osterle. From the Moody and Shanks
quality framework, the factors understandability and implementability were not totally accomplished for
the ITIL tool selection method, but for the method to evaluate the performance of ITIL processes, only
implementability was not due to bureaucracies from the companies. Besides that, all the four principles
of Osterle were achieved by the ITIL tool selection method, contrary to the method to evaluate the
performance of ITIL processes that did not totally achieve the originality principle.
8.3 Main Contributions
The proposed methods can bring a valuable contribution in the context of ITIL adoption. By focusing
on two of the most important CSFs for ITIL implementation, these artifacts aim to increase their positive
effects.
The first one is a method to select ITIL software tools that, using the MACBETH decision analysis
methodology together with ITIL criteria focused on functionality to compare and assess the tools, pro-
vides a complete and original way to make that choice as evidenced by the results of its demonstration
(see Figure 8.1) and the scientific appraisal. That way, this method positively increases the effects of the
“tool selection” CSF.
The second one is a method to evaluate the performance of selected ITIL processes that, using steps
based on monitoring and evaluation systems’ building actions together with ITIL metrics and criteria,
provides an effective and simple way to evaluate and increase the performance of ITIL processes as
shown by the results of its demonstration (see Figure 8.1). These positive results show that this method
63
is capable of increasing the positive effects of the “monitoring and evaluation of ITIL implementation”
CSF.
By increasing the effects of those two CSFs, it is proven that the appliance of these methods can help
improving ITIL adoption, since these two factors are important elements to solve that problem, making
these artifacts important contributions.
Along with that, these methods can also provide detailed guidance to companies that intend to invest
in ITIL, reducing the difficulties in its implementation which is one of the biggest barriers to ITIL adoption.
Figure 8.1: Validation and evaluation profiles of the ITIL tool selection method (blue line) and the ITIL processes’performance assessment method (orange dots).
8.4 Communication
Since the proposed methods have a strong practical component, they were demonstrated to practitioners
in two different companies as detailed in Chapter 6 and Chapter 7.
There was also the need to obtain a more theoretical scientific appraisal of the method to select ITIL
tools due to its strong theoretical nature. To do that a research paper was submitted and presented in
an international conference [18]:
• N. Faria and M. Mira da Silva, “Selecting a Software Tool for ITIL using a Multiple Criteria Decision
64
Analysis Approach,” in International Conference on Information Systems Development (ISD), 2018.
Lund, Sweden, Ranking: A. (Accepted).
Note that due to its rank, the conference on which this method was accepted provides an impor-
tant feedback with prestigious recognition from the scientific community that considered it as a good
appliance of a MCDA approach.
8.5 Future Work
For future work, further research can be performed to overcome the mentioned limitations.
First of all, more demonstrations of both methods have to be made, applying them to more organiza-
tions from different industries and sizes to verify if they really can be used by all kinds of organizations
in all industries.
Along with that, an effort on researching criteria that take into account other ITIL best practices,
like recommended roles and knowledge base components must be done to create criteria catalogs to
expand ITIL tool analysis.
The final aspect is related with the M-MACBETH software limitation that influences the understand-
ability of the ITIL tool selection method. For that, a software tool specific to evaluate tools for ITIL should
be developed and evaluated with support from the DMs.
65
66
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ACriteria Weighting Judgments Matrix
The judgments matrix presented in this appendix is the result of applying the MACBETH semantic cate-
gories to judge the differences in attractiveness between each criterion in the demonstration of the ITIL
tool selection method as explained in Section 6.1.2.
73
Figure A.1: MACBETH judgments matrix for the criteria weighting.
74
BSensitivity Analysis
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75
Figure B.1: Complete sensitivity analysis.
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CPerformance Analysis
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77
Table C.1: First subperiod performance’s results.
Table C.2: Second subperiod performance’s results.
Table C.3: Performances’ comparison between subperiods.
78