knowledge management framework_ibm case study

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Knowledge Management Framework for Process Aligned Organizations: an IBM Case

A research paper for: The International Journal of Knowledge and Process Management

Authors (* corresponding): (1) Dr Stephen McLaughlin School of Business and Management University of Glasgow West Quadrangle, Gilbert Scott Building GLASGOW G12 8QQ Scotland, UK E-mail: [email protected] Stephen McLaughlin is a manager with IBM (UK) Ltd. Most recently his roles within IBM have been related to supply chain optimization and performance management. He has recently completed a PhD, which looks at how complex organizations identify and manage inhibitors to performance related knowledge transfer. As a member of IBM's supply chain organization this is particularly pertinent, and his research areas of interest cover supply chain performance, learning organizations, organizational change, and knowledge transfer. *(2) Professor Robert A Paton School of Business and Management University of Glasgow West Quadrangle, Gilbert Scott Building GLASGOW G12 8QQ Scotland, UK E-mail: [email protected]; Tel: 0141 330 5037; Fax: 0141 330 5669 Robert Paton is currently Professor of Management and Associate Dean with the Law, Business and Social Science at the University of Glasgow. He researches, publishes and lectures in the field of managing change and has collaborated widely with co-researchers and various organisations. At present he is concentrating efforts on examining how best to achieve maximum benefit from the effective knowledge transfer within partnership settings. He has recently published in the Journal of Information Technology, European Management Journal and International Journal of Project Management, in addition, he is also finalising, with James McCalman, the 3rd edition of Change Management: a guide to effective implementation for Sage Publications. (3) Professor Douglas K Macbeth School of Business and Management University of Glasgow, West Quadrangle, Gilbert Scott Building GLASGOW G12 8QQ Scotland, UK E-mail: [email protected] Douglas Macbeth is Professor of Purchasing and Supply Chain Management at the University of Southampton School of Management. He has researched collaboratively with IBM for many years and his research interests include both the operational and strategic impact of Supply Chains, especially in Global businesses.

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Abstract Purpose: Many organizations struggling to capitalise on their knowledge assets tend to let their knowledge management systems emerge from existing information technology systems and infrastructure. Within a complex business environment this can cause a mismatch between how knowledge assets are, and should be managed. The author’s contend that for organizations where inter/intra collaboration is vital to overall end-to-end performance, such as in a supply chain, a bottom-up approach to understanding how the different parts of the organization create and transfer knowledge is a key consideration in the development of the knowledge management system. Approach: The research follows a critical theory approach to identify best knowledge transfer practice across complex organizations. The research is exploratory in nature and a case study methodology is used to support this line of inductive theory building. The findings presented are based on data collated within, and across IBM’s Integrated Supply Chain. Findings: In order to help organizations develop dynamic and effective knowledge management systems the authors’ suggest that organizations need to re-think how they develop their processes. In essences, organizations need to consider first the relationship between what the authors see as four key components. These are knowledge strategy, core process optimisation, core process performance, and knowledge barriers. Originality: Based on how information and knowledge are created and shared along a core supply chain process, and the need to match knowledge management improvement initiatives to end-to-end process performance improvement the authors have formulated a list of six basic tenets organizations should also consider when developing a knowledge management system. Keywords Knowledge Management Systems, Business Process Re-engineering, Knowledge Transfer, Supply Chain Management.

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Introduction

This paper examines a recent event associated with IBM’s Integrated Supply Chain in

Europe. In an effort to further drive end-to-end performance IBM decided to make significant

changes to its core supply chain process. The supply chain organization was hierarchically

structured and initially all changes where assessed and driven at departmental and functional

level. Unfortunately, the implemented changes did not produce the required process

enhancements, so a different approach to process improvement was required.

What in effect happened was the organization moved from a function to process aligned

assessment of the supply chain process, looking in particular at the processes in question

from a knowledge transfer perspective. This paper will provide an overview as to how the

changes where identified. However, although of interest this is not the key value proposition

of this paper. The point, which the authors wish to focus on, is the approach the organization

took in identifying the necessary changes, their relationship to technology, process, culture,

and people (Kakabadse et al, 2001).

Once the changes where implemented over a 4-6 month period significant overall end-to-end

performance was seen to increase significantly (McLaughlin et al, 2006). From the data

collated whilst monitoring this process of improvement, the author’s have identified six basic

tenets which could be used to help similar organizations trying to drive performance

improvements based on effective knowledge capture, and transfer. What is also important

here is not just identifying the key elements that effect knowledge management system

design, as the author’s believe they relate directly to performance, but also how these

elements interact. It is from an understanding of this relationship, based on observation and

interviews, which the authors’ have developed and refined the six tenets presented in this

paper.

It must be pointed out that these tenets are based on the findings of one case study, and are

therefore, presented as ‘inductive’ theory building in nature.

Effective Management of Knowledge

Managing knowledge capture, creation and transfer is vitally important to successful

innovative organizations (Nonaka et al, 1995), indeed knowledge itself is recognised as an

important component of value creation and competitive advantage (King et al, 2003).

However, many organizations tend to develop their knowledge management systems from

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their existing IT strategy. In essence the knowledge management system becomes an

extension or expansion of the existing IT infrastructure. This approach may not necessarily be

detrimental. However, a failure to consider how knowledge, in particular tacit knowledge, is

created, shared, and utilised, as opposed to simply focusing on how explicit knowledge is

created, shared, and stored may seriously impact an organizations ability to innovate and

build a competitive advantage.

Therefore, in order to improve and encourage innovation an organization must understand

how both tacit and explicit knowledge are created, shared, and utilised across the entire

organization. In order to do this, so the authors believe, organizations must take a proactive

approach in developing their knowledge management system, and resist the temptation to

simply let it emerge from existing IT systems. Throughout this proactive approach the

organization should focus on developing an organization wide strategy that looks at managing

both knowledge assets and information flows and repositories.

So how then does an organization determine the best strategy for managing knowledge and

information across its business? The authors content that in order to do this organizations

must consider the way employees create and share both tacit and explicit knowledge.

Therefore, organization must understand what knowledge barriers are present and active

across the organization (Szulanski, 1999; Barson et al, 2000; Darr et al, 2001; McLaughlin et

al, 2006a). Once the barriers have been identified a clearer understanding as to how to

manage the barriers will emerge.

To this end, what this paper proposes to do, based on primary research conducted across

IBM’s supply chain organization, is put forward a ‘knowledge management system

dependency model’ (KMSDM). This model will highlight the key aspects of a complex

operating environment that should be considered when developing a dynamic and effective

knowledge management system. The authors also identify 6 basic tenets that organizations

should be cognisant of before implementing their respective knowledge management

systems. The author’s believe that adherence to the tenets coupled with an understanding of

the KMSDM will help develop knowledge management systems that are better matched to the

demanding knowledge needs of complex organizations.

The authors’ also make the point that an effective knowledge management system cannot be

deployed as a generic approach across the entire organization. For the knowledge

management system to be effective it must take cognisance of the fact that different parts’ of

the organization will have different knowledge needs, and understanding these needs will

ultimately determine the most suitable knowledge management system.

The need for a knowledge management strategy

The term ‘knowledge management strategy’ is used by the authors to denote the focused,

proactive and premeditated development of a long-term strategy. A strategy that

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specifically addresses the management of both tacit and explicit knowledge in a way that best

supports competitive advantage. Due to the emergent nature of many knowledge

management systems the authors believe that the development of an effective knowledge

management system now demands that organizations re-think how they initially identify their

knowledge requirements. So, what should an organization consider when developing a

knowledge management strategy? Through the primary research conducted by the author’s,

that in turn resulted in the re-assessment of tacit and explicit knowledge needs across a core

IBM supply chain process, the authors have developed a framework (KMSDM) which, they

believe, will help organizations reconsider the way they develop their cross-organizational

knowledge management system(s).

The knowledge management strategy must consider the different types of knowledge

required at certain key points across the organization, and the knowledge transfer barriers

that impact across the organization. A fundamental consideration made by the authors in

developing their findings is that an effective knowledge strategy is based around how tacit

and explicit knowledge is created and flows along core business processes. The reason for

this is simple. The performance of core business processes will have a direct impact on

business performance. Therefore, by concentrating on how explicit and tacit knowledge flows

along the core business processes, an organization can better match its knowledge

management improvements more directly to process performance. In a sense these

processes can be viewed as knowledge arteries or pathways. In general terms organizations

can manage their tacit and explicit knowledge through a combination of personalised and

codified systems respectively.

Codified and Personalised Systems

Hansen et al (1999) and Gupta and Michailova (2004) have identified the main aspects that

separate codified/personalised ‘knowledge’ systems. The important thing to remember with

these two approaches is that they are designed to fit different business environments.

Therefore, one is not always better then the other. The suitability of the approach will depend

on the type of organisation (Tiwana, 2000). The key aspects of both approaches are

compared and outlined in Table I. The Table characteristics outlined are supported by Gupta

and Michailova (2004) and are an expansion on the original comparison as put forward by

Hansen, Nohria, and Tierney (1999). The tension between technology dominance and

interpersonal dynamics in knowledge sharing is reflected in the distinction between

codification/personalisation (Hansen et al, 1999; Tiwana, 2000). Codification is based on

technologies, such as intranets, repositories, databases, etc. Personalisation emphasizes

knowledge sharing among individuals, groups, and organizations through social networking

and/or engaging in ‘communities of practice’ or ‘epistemic communities’ ( Hansen et al 1999;

Brown and Duguid, 2000; Wenger, 2000). Social and interpersonal aspects seem to override

technology-based and procedural mechanisms in terms of ‘meaningful knowledge

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management’ (Hansen et al, 1999). McDermott (1999) concluded that the great trap in

knowledge management is using information management tools and concepts to design

knowledge management systems. Hansen (1999) maintained that strong network ties are

important for the sharing of tacit knowledge while non-redundant weak ties play an important

role for accessing explicit knowledge. According to Johannessen et al (2001) there is a real

danger that because of the focus IT solutions have on mainly explicit knowledge this may

relegate tacit knowledge to the background hence a knowledge mismatch.

(Insert Table I here) Research Context and Methodology

The research methodology follows a critical theory approach in identifying best knowledge

transfer practice across complex organizations. The research is exploratory in nature and a

case study (Yin, 2002) methodology is used to support this line of inductive theory building.

The findings presented in this paper are based on data collated within and across IBM’s

Integrated Supply Chain. For the purpose of the research the authors’ surveyed over 150

individuals working across an IBM core end-to-end business process; in this case the supply

chain order flow process was used. The author used a semi-structured questionnaire and

one-to-one interviews to identify the organization’s knowledge habits with respect to a core

business process. The analysis of the data has been used to understand the different explicit

and tacit knowledge sharing habits of the workforce, and the perceived barriers which

influence these habits along a core business process. The analysis also identified where

along the core process the existing knowledge management (KM) approach (codified or

personalised) was at odds with employee tacit and explicit knowledge sharing habits. By

understanding the different knowledge creation and sharing practices along the core process

the authors have been able to develop a picture of the dominant knowledge approaches, not

just by business function but also more importantly by the different parts of the organization

as they relate and interact along the core process.

The information gathered through the primary research allowed the organization to re-focus

on how to improve knowledge and information flows in order to improve process performance

(McLaughlin et al, 2006b). The practical application of the findings across the core business

process helped define both the knowledge management system dependency model and

basic tenets for knowledge management system implementation as presented in this paper.

Although the first author is a manager within the ISC organization the research conducted

also formed the basis for the author’s doctoral research (undertaken on sabbatical from IBM),

which in turn is part of an inter-disciplinary, and multi-sectoral research initiative. As there is

little academic research on actual barriers to information and knowledge transfer along

process pathways the authors relied on pre-understanding (Gummesson, 1991) of the

process and organization as a valid starting point for conducting this research. Objectivity and

academic professionalism was maintained by the need to conform to the rigours of an

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ESRC recognized doctoral programme, as well as the requirement to engage with on going

research initiatives.

Ultimately the aim is to develop an underpinning theory and associated models relating to

improving process performance in complex organizations. The research and analysis

outlined in this paper has been conducted using qualitative and quantitative methods with all

data gathering complying with validation criteria as outlined by Yin (2002).

Considerations in developing a knowledge management system

When developing a knowledge management system an organization should assess how it

wishes to capture, create, and share both tacit and explicit knowledge. In reality how this

happens may vary significantly across different organizations. This problem becomes more

acute when trying to define a knowledge management system for a complex organization. If

an organization decides to opt for a mainly codified approach it needs to consider the amount

of interaction employees will have with the systems involved (Hansen et al, 1999). If the

systems are unstructured and allow data to be input as rich text, context might be difficult to

determine, and the employees will have more control over the amount of information they

wish to share. However, at the other end of the spectrum with highly structured data

formatted systems, gleaming knowledge from a ‘tacit to explicit to tacit exchange’ may be

difficult (Marwick, 2001). Also the systems may become inflexible when trying to meet the

demands of a dynamic and changing market place. To that end the choice of a codified or

personalised approach used to support the way an organization views and manages its

knowledge is important (Hansen et al, 1999; Tiwana, 2000). However, even when

organizations have decided on a knowledge management strategy a successful

implementation is not always guaranteed (Kluge et al, 2001; Grossman, 2006). This paper

contends that this is because the assessment for a top-down, organization-wide knowledge

management system fails to properly consider the cultural aspect relating to how individuals

create and share knowledge. Also, current assessments fail to take into consideration the

complexities of today’s organizations. In particular, the complexities inherent in managing a

supply chain, which by virtue of its complexity may span both multiple business functions and

organizations.

To highlight this point IBM’s supply chain organization was assessed using Tiwana’s

framework for determining a dominant knowledge approach (Table II). However, due to the

complexity of the organization involved in the management of core supply chain business

processes, the assessment was not able to clearly identify a suitable dominant knowledge

approach. What in fact the assessment exercise did show was how varied the organization’s

knowledge management requirements were along the core horizontal order flow process.

(Insert Table II here)

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Knowledge management systems for complex organizations

Tiwana’s (2000) comparison between codified/personalised knowledge approaches provides

a clear understanding of the different strategies organizations can take in developing a

‘knowledge aware’ environment. The comparison between codified/personalised is still valid

when one considered that Table I really refers to how organizations handle information

currency and flow within their boundaries (explicit), whilst understanding the need to engage

human cognitive problem solving and reasoning skills over data availability systems when

operating within a unique problem solving environment (tacit). The differences outlined in

Table I refer to two ends of a spectrum and as such an organization should not use a totally

codified or personalised strategy. The question from the authors perspective is how relevant

is the criteria in Table I in determining a suitable knowledge management approach for a

complex organization such as IBM’s Integrated Supply Chain (ISC) group? The questions

outlined in Table I were asked of the IBM ISC group. Table II shows, in the case of IBM,

Tiwana’s criteria show how the need for a codified or personalised knowledge approach will

vary significantly across a complex organization. Therefore, a complex organization’s

knowledge strategy cannot be easily defined against the questions outlined in Table I.

From Table II it cannot be easily determined which dominant knowledge approach should be

used for IBM’s supply chain organization. It does not mean the existing approach is wrong,

just that the assessment, as it stands, is inconclusive with respect to identifying a suitable KM

approach. Developing a suitable strategy must be based on how employees access, create,

and share knowledge. Gupta and Michailova (2004) believe that an individual’s ability to appreciate new knowledge

is a function of their absorptive capacity (Cohen and Levinthal, 1990; Szulanski, 1996). What

is interesting about Gupta and Michailova (2004) research is that it does not look at the

organization as a single entity but as a collection of departments working together, and the

different demands they place on knowledge creation.

This is an important view as the reality of today’s organization, especially a complex supply

chain, is that roles and expected deliverables will vary between departments/business units.

Therefore, when defining a knowledge management strategy an understanding as to how the

organization’s constituent parts use information and create knowledge must be taken into

consideration.

The reviewed literature suggests that when technology is the primary focus in knowledge

delivery systems they have failed to deliver (Barson et al, 2000; Pawar et al, 2002; Gupta et

al, 2004). The assumption that knowledge management relies heavily upon social patterns,

practices, and processes goes far beyond computer-based technologies and infrastructures

(Davenport and Prusak, 1998; Coleman, 1999). Empirical evidence on inhibitors to

knowledge sharing stresses the importance of behavioural and cultural factors rather than

technological (Skyrme and Amidon, 1997; De Long and Fahey, 2000). The emphasis on the

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role of technology specifically knowledge codification has also been questioned by Spender

(1996) and Tsoukas (1996).

Pawar et al (2002) also question the effectiveness of a purely codified approach to KM. It is

their belief that modern management practice has only tended to focus on centralising,

controlling, and standardising knowledge. Such codification allows the marginal cost of

knowledge acquisition to be reduced by economies of scale (assuming the codified

knowledge is relevant and useful). This underlying philosophy has motivated an immense

interest over the last decade in KM. Pawar et al (2002), at the same time realise the place

technology has within the effective coordination of knowledge. However, they feel that

humans play more of a central role in the identification, acquisition, generation, storage,

structuring, distribution, and assessment of knowledge. It’s interesting that Pawar et al (2002)

views although taking the softer aspects of knowledge management in to consideration, do

not really look at how organizations get their employees to ‘pull’ knowledge (Kluge et al,

2001).

Malhotra (2001) also believes in line with Kluge et al (2001) that there is an overarching need

for the building of a knowledge management culture within an organization, and the

responsibility for developing this culture does not rest with the information technology

specialists. However, in order to achieve this, barriers to knowledge and information transfer

need to be identified and managed (Szulanski 1996; Barson et al, 2000; Argote L, 2005).

Knowledge management barriers

A common theme that has emerged is that KM must be viewed from a holistic perspective

(Malhotra, 2001). Failure to do so will result in an organization’s inability to realise the

potential it has to create and share knowledge (Kluge et al, 2001). Although Barson et al

(2000) provide a comprehensive list of issues that support the findings of previous research;

they do not provide any empirical evidence as to how the barriers impact knowledge creation

and sharing within a complex organization such as IBM’s Integrated Supply Chain activity.

There are also aspects of Pawar et al (2000), Kluge et al (2001), and Szulanski’s (1996)

research that are not taken into account. Of particular interest is the impact an imbalanced

‘push-pull’ knowledge strategy can have on information flow and knowledge creation. Also

Szulanski’s work on identifying barriers which effect knowledge ‘stickiness’ within an

organization need to be considered when assessing barriers in any large complex

organization. Therefore, the findings from the different research papers have been collated

together and assessed for over-lap (McLaughlin et al, 2006a). The barriers identified were

categorised under the TOP headings used by Barson et al (2000) and are shown in Table III.

(Insert Table III here)

This list of barriers identified in Table III was used in assessing the main barriers to

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knowledge creation and transfer along the ‘order flow’ process within IBM’s ISC supply chain.

Barriers impact upon the way knowledge is shared across an organization, and Table III

contains a list of the most commonly identified barriers to knowledge transfer (Szulanski

1996; Barson et al, 2000; Kluge et al, 2001; Argote L, 2005). In order to assess how they

impact across an organization, IBM’s ISC employees, working along a core process, were

asked whether they had any experience of the barriers, and to what degree. From analysis of

their responses it became apparent that the barriers could be addressed by using: technology

(codified), or team building (personalised), or a combination of the two (Hansen et al, 1999).

However, another point to note was that some barriers seemed to have little or no impact

across certain parts of the organization. This does not necessarily mean these barriers do

not exist, but in fact the barriers are already being managed through existing

codified/personalised aspects of the existing knowledge strategy. Table III, in the case of

IBM’s ISC, looks at the identified barriers and matches them to a dominant approach that

minimises their respective impact.

(Insert Table IV here)

What is clear from Table IV is that an assessment of the barriers against an organization

cannot only identify areas where knowledge creation and sharing are impacted, but also how

the organization currently access, value, and share tacit and explicit knowledge. This is

important when defining a KM strategy as the barrier analysis can indicate how individuals

prefer to access and share. It also shows that barriers to information and knowledge sharing

can provide an important control mechanism that prevents the dissemination of

information/knowledge to undesirable locations and recipients (Risk, Self Interest, and

Proprietary Knowledge). Organizations may not necessarily wish to remove such barriers,

but instead strive to understand and manage the barriers as effective information/knowledge

flow control mechanisms. However, before this can be done, one needs to understand how

the barriers manifest themselves across the key business processes.

Table IV also shows how each barrier can be aligned to either a personalised or codified

knowledge approach. Organizations will see differing manifestations of the barriers, and

therefore, the approach chosen will depend upon particular barrier profiles/interactions. That

said, Table IV identifies, in the case of IBM, the dominant approach in managing the barriers

as being a personalised approach. However, one must remember that the barriers may not

always be present, and even when they are their impact may vary.

From Table IV it can be seen that in order to address the identified barriers the main KM

approach is personalised. However, this does not, and should not be taken to mean that

codified implementation methods should be dismissed. The information in Table IV simply

points to the fact that organizations need to:

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1. Identify how these barriers manifest and impact across their key business processes.

2. Understand how information and knowledge sharing happens as a consequence of

the existence of these barriers.

3. Understand whether any of the barriers are important for the operational control of

information or knowledge.

4. Understand and decide on a suitable knowledge management system based on the

existence, and need to manage barriers.

What in effect this means is that the organization more effectively maps its knowledge

management system to how the individuals currently manage knowledge (McLaughlin et al,

2006b). However, it is important to remember the mapping processes must happen along the

defined core business process. That way the barrier analysis across the organization is

assessed against individuals and work groups who are interacting along process pathways.

This is important as the need for performance improvement is dependant on ensuring tacit

and explicit knowledge sharing pathways are managed effectively, not simply within functional

hierarchical structures but along cross-functional process pathways (van Weele, 2005). In the

case of IBM’s supply chain organization the differences in knowledge creation and sharing

practices became apparent when the work groups involved with the order flow process where

questioned about barrier impact. This was done through the on-line questionnaire and a

series of personal interviews with senior management, the analysis of which allowed the

authors to identify where along the core process the barriers existed. By linking a codified or

personalised approach to managing the individual barriers a dominant approach was

identified for the different work groups associated with the order flow process. Figure I

illustrates how the dominant knowledge creation and sharing processes alternate between

codified and personalised in relation to the order flow process.

(Insert Figure I here)

The preference for either a codified or personalised approach will differ from organization to

organization. However, what is important to realise is that along core processes different work

groups will identify with different knowledge approaches. Therefore, because of this the

implementation of an organization-wide knowledge approach will not help effectively

maximise knowledge creation and sharing across core business processes.

Relationship between strategy, barriers, process and performance

From the research findings it became apparent, when looking at end-to-end performance from

a process alignment and KM perspective certain key elements needed to be considered.

These elements are Knowledge Strategy, Process Optimisation, Knowledge Barriers, and

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Process Performance. The elements and their inter-relationships where identified through the

research.

1. Performance is impacted by knowledge strategy alignment – Different parts of the

process require different knowledge approaches (Codified / Personalised / Mixed).

2. Performance is impacted by end-to-end process optimisation – The effectiveness of

the process is dependant on its weakest link. Therefore, the end-to-end process must be

defined in terms of process alignment, and not functional alignment.

3. Performance is impacted by how people / systems create, store, and share information and knowledge – Barriers to information and knowledge sharing will exist in

every organization. What is important is that organizations understand and manage these

barriers.

From the research findings and the mechanisms required to identify and assess barrier

impact across core processes, the authors’ believe the formation of an effective knowledge

management system cannot be developed in isolation of performance, barrier impact, or the

organizational understanding of key end-to-end processes.

(Insert Figure II here)

Figure II is intended to outline the relationships between what the authors’, based on the IBM

case study findings, believe are the four key elements of any knowledge management

system. This relationship between the key elements does not work in isolation but is also

impacted by larger organizational drivers. The elements tie in closely with existing elements

of the overall business strategy; such as organizational structure and culture (Tsoukas, 1996;

Fuller, 2002; Starkey et al, 2004; Simons, 2005). This interdependency illustrates how the

development of a knowledge strategy is dependant on feedback from process optimisation,

barrier analysis, and performance. This identifies the need to develop a real-time system that

is able to monitor its environment for change; change that is to be expected in a complex

customer focused business environment. The relationships between the four elements are

described in more detail in Table V.

(Insert Table V here)

It is this inter-dependant relationship between knowledge strategy, process optimisation,

barriers, and performance that forms the basis for the authors’ proposed theory. It is the

interaction of these four elements that needs to be considered when developing, and

maintaining an effective knowledge management system.

Developing a holistic approach

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Tiwana’s (2000) criteria for assisting in determining suitable knowledge management

approach requires an assessment based on the type of organization, and what the output

goals are. The assessment does not take into consideration structure (functional or process

orientation), or how it is currently operating. In order to define a strategy, an understanding

as to how the existing organization performs, and what barriers (McLaughlin, et al , 2008)

exist to improving end-to-end performance must be understood.

Tiwana’s (2000) assessment of what distinguishes a codified from a personalised system

provides a good starting reference point. However, the questions asked are general and

provide an indicator which points to a recommended knowledge management approach for

the entire organization. Complex organizations view and share tacit and explicit knowledge

differently at different points along core processes. Therefore, any assessment that can

support knowledge creation and sharing across complex organizations must take into

consideration the fact that barriers and enablers to information/knowledge flow do not impact

uniformly.

The main shortcoming with using the assessment (Table I) to determine the most appropriate

knowledge strategy is that it does not consider the specifics of how information is created and

shared, both from a codified and personalised perspective. Should the responses to the

assessment indicate a personalised strategy there is no indication given as to what barriers

might exist and how individuals and teams should be directed and managed in order to

overcome them. For example the importance in developing a ‘pull’ strategy over a ‘push’

strategy, or the impact of barriers such as motivation, reciprocity, or trust are not considered.

If, however, the response indicated a codified strategy, no warning is given as to the

importance of the information and knowledge creating/sharing issues surrounding legacy

system compatibility, system data formats, and system-to-system compatibility across internal

and external boundaries.

In essence, complex organizations should steer away from developing a ‘one strategy fits all’

approach. The danger here is that such a strategy would fail to meet the specific needs at

key points along the core processes based on their information/knowledge creation and

sharing practices. Instead the organization needs to develop a flexible strategy that responds

to how knowledge is created and shared along the core processes; this may mean a

combination of codified and personalised systems. The difference being the strategy is not

matched to how the organization builds/costs/develops products and services, but rather how

employees and teams access, create, and share information/knowledge horizontally and

vertically internally and externally.

Conclusion As part of a process improvement initiative over 100 process, system, and organizational

changes were identified and implemented to the IBM end-to-end order flow process

(McLaughlin et al, 2006b). The changes where assessed to see if they impacted codified or

personalised knowledge transfer, and a dominant knowledge approach could then be

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identified for each process work group. The changes, which were identified by a cross-

functional process improvement team (McLaughlin et al, 2006b), were seen to target barriers

which in turn could be identified as having an impact on the preferred knowledge approach

(Figure I) for each of the different work groups connected with the process. Through the

process improvement initiative’s targeting of identified barriers, the end-to-end order flow

process saw a 20-22% improvement in the time taken to accept, process, build, and deliver

customer orders throughout EMEA. In order to achieve this level of improvement IBM had to

approach the process from a ‘bottom-up’ improvement perspective. Knowledge and

information habits had to be considered not at an organization-wide level, but at a process

work group level, and an understanding as to how barriers impacted along the core process

needed to be developed. This resulted in different knowledge approaches being implemented

across the core business process.

Therefore, the author’s believe any approach to defining a strategy must be based on the

core belief that the effective ‘management’ of knowledge is not dependant on the selection of

an organization wide codified or personalised knowledge management system. It is,

however, dependant on the effective management of the tacit and explicit knowledge ‘creating

and sharing’ work environment. The subtle implication here is that the organization needs to

understand, first and foremost, how individuals create and share intangible assets such as

tacit and explicit knowledge across the organization. Trying to capture and directly control

this process through the use of technology will not work. As the act of creating and sharing

knowledge is dependant on an individual’s innate capability and motivation, to do this

relegates the use of technology to a support role in the dissemination of information and

sharing of knowledge. This is an interesting position considering the high value organizations

currently place on the use of technology in shaping and driving both codified and personalised

knowledge management systems (Bhatt, 2001; Kluge et al, 2001; Smith et al, 2001;

Grossman, 2006).

Therefore, it is the contention of this paper that in order to implement an effective knowledge

management system an organization must not just focus on how information should flow

along deployed IT systems, but how individuals chose to interact with information sources, be

they systems or people. Using this belief as the starting point this paper contends that any

complex organization looking to improve learning and knowledge creation/sharing needs to

consider the following proposed six basic tenets of knowledge management system design

and implementation (Table VI).

(Insert Table VI here) These six tenets should be understood and adhered to, particularly within complex

environments, when developing a knowledge management system. The tenets shape the

knowledge management system by taking a holistic view that incorporates both barriers and

associated solutions. The knowledge management system is not based on a general

15

overview of existing organization wide KM activities. This prevents any preconceived idea as

to whether a codified or personalised approach should be driven across the organization; the

impact of which could create a knowledge management system that tries to manage codified

needs with personalised methods, and vice versa. This is an important point, as different

parts of the organization will exhibit different knowledge and information sharing practices.

16

References Argote, L. (2005) Organizational Learning: Creating, Retaining and Transferring Knowledge. Springer, New York. Arrow, K.J. (1969) Classification notes on the production and transmission of technical knowledge. American Economic Review, No 52. pp29-35. Barson, R, et al (2000) Inter and intra organizational barriers to sharing knowledge in the extended supply chain, e2000 Conference Proceeding. Bhatt. G, (2001) Knowledge management in organizations: examining the interaction between technologies, techniques, and people. Journal of Knowledge Management 5(1). pp 1-2 Bollinger, A.S. and Smith, R.D. (2001) Managing organizational knowledge as a strategic asset, Journal of Knowledge Management, 5(1). pp 8-18. Brandt, D. and Hartmann, E. (1999) Editorial: Research topics and strategies in socio-technical systems, Human factors and ergonomics in manufacturing, 9(3). pp 241-243. Brown, J.S. and Duguid, P. (2000) Balancing Act: How to capture knowledge without killing it, Harvard Business Review, May-June. pp 73-80 Cohan, W.M. and Levinthal, D.A. (1990) Absorptive capacity: a new perspective on learning and innovation, Administrative Science Quarterly, 35. pp 128-152. Coleman, S. (1998) Knowledge management: Linchpin of change, London: ASLIB Darr, E., Argot, L. and Epple, D. The acquisition, transfer and depreciation of knowledge in service organizations. Management Science, 44(11). pp 1750-1763. Davenport, T. (2005) Thinking for a living, Harvard Business Press, Boston. Davenport, T. and Prusak, L. (1998) Working Knowledge, Harvard Business Press, Boston. Day, G.S. (1994) The capabilities of market driven organizations, Journal of Marketing, pp 37-52. DeLong, D.W. and Fahey, L. (2000) Diagnosing cultural barriers to knowledge management, Academy of management executive 14(4). pp 113-127 Diamantopoulos, A . and Schlegelmilch, B. (1997) Taking the fear out of data analysis, The Dryden Press London. Farr, C.M. and Fisher, W.A. (1992) Managing international high technology cooperative projects, RandD Management 1(2). pp 73-79. Fuller, S. (2001) Knowledge Management Foundations, Butterworth-Heinemann Press, Boston. Grossman, M. (2006) An Overview of Knowledge Management Assessment Approaches, Journal of American Academy of Business, 8(2) pp 242-247. Gummesson, E. (1991) Qualitative Methods in Management Research , Sage Publishing: London. Gupta, A. and Michailova, S. (2004) Knowledge sharing in knowledge intensive firms, CKG Working Paper No 12/2004.

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Hansen, M.T. (1999) The search transfer problem: The role of weak ties in sharing knowledge across organizational sub-units, Administrative Science Quarterly 44. pp 82-122. Hansen, M.T., Nohria N. and Tierney, T. (1999) What’s your strategy for managing knowledge?, Harvard Business Review, Mar-Apr. pp 106-117 Hinton, P.R. (2004) Statistics explained, 2nd Ed Routledge, East Sussex. Husted, K. and Michailova, S. (2002) Diagnosing and fighting knowledge sharing hostility, Organizational Dynamics, 31(1). pp 60-73. Johannessen, J., Olaisen, J. and Olsen, B. (2001) The mismatch of tacit knowledge: The importance of tacit knowledge, the dangers of information technology, and what to do about it, International Journal of Information Management. 21(1) . pp 3-21. Kakabadse, N., Kouzmin, A. and Kakabadse, A. (2001) From tacit knowledge to knowledge management: leveraging invisible assets. Knowledge and Process Management 8(3), 137-154. KBMG (1998) Knowledge Management research report 1998. King, A.W, Zeithalm, C.P. (2003) Measuring organizational knowledge: A conceptual and methodological framework. Strategic Management Journal, Vol 24, pp 763-772. Kluge, J., Stein, W. and Licth, T. (2001) Knowledge Unplugged: The McKinsey and Co survey on knowledge management, Palgrave, London. Krogh, G.V., Ichijo K., and Nonaka, I. (2000) Enabling Knowledge Creation, Oxford Press, London. Lucas, E. (2000) Creating a give and take culture, Professional Manager 9(3). pp 11-13 Malhotra, Y. (2001) Knowledge Management for the new world of business, http://www.brint.com/km/whatis.htm. Marwick, A.D. (2001) Knowledge Management Technology, IBM Systems Journal on Knowledge Management. 40(4) pp 814-831. Miller S (2000) Experimental design and statistics 2nd Ed, Brunner-Routledge, East Sussex McDermott, R. (1999) Why information technology inspired but cannot deliver knowledge management, Californian Review 41(4) pp 103-117. McLaughlin, S and Macbeth, D. (2006a) “Identifying knowledge transfer barriers within a complex supply chain organization”, In Mendibil K and Shamsuddin A (Eds), EurOMA: Moving up the value chain. Glasgow: Strathclyde University Press.

McLaughlin, S., Paton, R.A., and Macbeth, D. (2006b) Managing Change within IBM’s complex supply chain, Management Decision, 44(8), pp 1002-1019. McLaughlin, S. and Paton, R.A., and MacBeth (2008) Identifying Barriers that Impact Knowledge Creation and Transfer within complex organisations, Journal of Knowledge Management, Volume 12, No 4 Nonaka, I., and Takeuchi, H. (1995) The knowledge creating company: How Japanese companies create the dynamics of innovation, Oxford Press, London O’Dell, C. and Grayson, C.J. (1998) If only we knew what we know: Identification and transfer of internal best practice, Californian Management Review 40(3), pp 154-174.

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Pawar, K., Horton, A., Gupta, A, Wunram, M, Barson, R, and Weber, F. (2002) Inter-organizational knowledge management: Focus on human barriers in the telecommunications industry, Proceedings of the 8th ISPE International Conference on Concurrent Engineering: Research and Applications. pp 271-278. Porter, M.E. and Millar, V.E. (1985) How information gives you competitive advantage, Harvard Business Review, Jul-Aug. pp 149-161. Quinn, J.B., Anderson, P., and Finkelstein, S. (1996) Managing Professional Intellect, Harvard Business Review. Mar-Apr. pp 71-81 Rajan, A., Lank, E., and Chapple, K. (1998). Good practice in knowledge creation and exchange, Create, Tunbridge Wells. Scarborough, H., Swan, J. and Preston, P. (1999) Knowledge Management: A Literature review, Series: Issues in people management. London: Institute of Personnel and Development. Simons, R. (2005) Leavers of Organizational Design, Harvard Business School Press. Boston. Skyrme, D.J.and Amidon, D.M. (1997) Creating the knowledge based business, London: Business Intelligence. Spender, J.C. (1996) Organizational knowledge, learning and memory: Three concepts in search of a theory, Journal of organizational change management 9(1) pp 63-78 Starkey, K., Tempest, S., and McKinlay, A. (2004) How organizations learn: Managing the search for knowledge, (2nd Ed) Thomson, Cornwall. Swartz, J. (1999) Collaboration – More hype then reality, Internet Week Oct 25th Issue 786. Szulanski, G. (1996) Exploring internal stickiness: impediments to the transfer of best practice within the firm, Strategic Management Journal Vol 17 pp 27-43 Teece, D.J. (1998) Capturing value from knowledge assets: the new economy, markets for know how, and intangible assets, Californian Management review 40(3) . pp 55-78 Tiwana, A. (2000) The Knowledge Management toolkit, Prentice Hall PTR New Jersey Tsoukas H. (1996) The firm as a distributed knowledge system: A constructivist approach, Strategic Management Journal 17. pp 11-25 Van Weele, AJ.(2002) Purchasing and Supply Chain Management, (3rd Ed) Thompson Publishing, London. Wenger E (2000). Communities of practice and social learning systems, Organization 7(2). pp 225-257. Winter, S. G. (1987) Knowledge and competence as strategic assets, In Teece, D. (eds) The competitive challenge: Strategies for industrial innovation and renewal, Ballinger, Cambridge MA pp 147-178 Yin, R. K. (2002), Case Study Research, 3rd Edition, Sage Publications: London Zander, U. and Kogut, B. (1995) Knowledge and the speed of transfer and imitation on organizational capabilities, Organizational Science 6(1). pp 76-92.

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Business Strategy Q i

Codification Approach Personalisation Approach What is the organization business?

Provide high quality, reliable, fast and cost effective services and products.

Provide creative, rigorous, and highly customisable services and products.

How much data is reused to support new projects?

Reuses portions of old documents to create new ones.

Every problem has a high chance of being a “one off” and unique problem. Highly creative solutions are called for.

What is the costing model used for organizations products or services?

Price based competition. Expertise based pricing. High prices not detrimental to business. Price based competition barely (if at all) exists.

What are the organisations typical profit margins?

Very low profit margins; overall revenues need to be maximised to increase net profits.

Very high profit margins.

How best can the role IT plays be described?

IT is a primary enabler; the objective is to connect people distributed across the organization with codified ‘knowledge’ such as reports, documentation, code etc that is in some reusable form.

Storage and retrieval are not the primary applications of IT. IT is used to enable communication and better contact. Conversations, socialization, and exchange of tacit knowledge are considered to be the primary use of IT.

What are the reward structures?

Employees are rewarded for using and contributing to databases such as Notes discussion databases.

Employees are rewarded for directly sharing their knowledge with colleagues and for assisting colleagues in other locations/offices with their problems.

How is knowledge/information transferred?

Employees refer to a document or best practices database that stores, distributes, and collects codified knowledge.

Knowledge is transferred person to person; intra-organizational networking is encouraged to enable sharing of tacit knowledge, insight, experience and intuition.

Where do the organizations economies of scale lie?

Economies of scale lie in the effective reuse of existing knowledge and experience and applying them to solve new problems and complete new projects.

Economies rest in the sum total of expertise available within the organization; experts in various areas of specialisation are considered indispensable.

What are the typical team structure demographics?

Large teams; most members are junior-level employees; a few project managers lead them.

Junior employees are not an inordinate proportion of a typical team’s total membership

What do the organization services resemble?

Accenture Consulting, The Gartner group, Delphi Consulting, ZDNet, Delta Airlines, Oracle.

Boston Consulting Group, McKinsey and Company, Rand Corporation.

What do the organization products resemble?

Pizza Hut Dell Computers, Gateway, Microsoft, SAP, People Soft, Baan, America On-line (AOL), Bell South, Lotus, SAS Institute, IBM, Hewlett-Packard, Intranetics, 3Com

A custom car, or bicycle manufacturer, Boeing, a contract research firm, a private investigator.

Table I. Codified and Personalised Systems Source: Tiwana (2000)

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Business Strategy Question IBM ISC Position Approach What type of business is the organization in?

Providing high quality, cost effective service. Codified.

How much data is reused to support new projects?

Reuse contract templates and reporting metrics and formats.

Codified.

What is the costing model used for organizations products or services?

Price based competition. Cost efficiency – driving cost out of the business…

Codified.

What are the organisations typical profit margins?

Supply Chain seen as a way of taking cost out of the business.

Codified.

How best can the role IT plays be described?

IT used to store and retrieve information. Also to automate generic / standard processes.

Codified.

What is the organization’s reward structure like?

Employees are rewarded for sharing knowledge directly with peers, and helping problem solve in other parts of the organization.

Personalised.

How is knowledge/information transferred?

Employees refer to documents of best practice, and use databases for storing common information. However, also encouraged to share person to person.

Codified and Personalised.

Where do the organizations economies of scale lie?

Economies lie in the effective reuse of information. However, subject matter experts within key areas of the process support information sharing.


What are the typical team structure demographics?

Matrix organization with varying sizes of teams. Organization invests in MBA’s, Post-grad, and PhDs within supply chain specialisation.

Personalised.

What services do the organizations resemble?

IBM services sections moving to a personalised services setup.

Personalised with strong IT support.

What products do the organizations resemble?

Core supply chain process is process driven. However, supply chain used to support project type customer requirements.


Table II. Best-fit strategy for knowledge enablement

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Source Cross category BarriersBarson et al(2000) Existing Resources (Money, time, technology, skills, Barson et al(2000) / Kluge et al(2001)

Rewards (individuals rewarded for sharing/creating K)

Szulanski(1996) Arduous Relationship Barson et al(2000) / Kluge et al(2001)

Culture (K Strategy)

Technology BarriersBarson et al(2000) Available Technology (Does IT support K requirement) Barson et al(2000) Legacy Systems (Are Legacy systems impacting K Organizational BarriersGupta and Michailova(2004) Knowledge Strategy Implementation Szulanski(1996) Causal Ambiguity Barson et al(2000) Poor targeting of knowledge Barson et al(2000) Knowledge Cost Barson et al(2000)/ Pawar et al(2000)

Proprietary knowledge

Barson et al(2000)/ Pawar et al(2000)

Distance (Geo, Culture, language, legal)

Szulanski(1996) Unproveness (Is knowledge rated as being of value) Szulanski(1996) Organizational Context Szulanski(1996) Info not perceived as reliable Szulanski(1996) / Kluge et al(2001)

Lack or Motivation (Knowledge as power syndrome)

People BarriersBarson et al(2000) / Kluge et al(2001)

Internal Resistance (Protect interests of Org/BU)

Barson et al(2000) Self Interest (expose Knowledge to competition) Barson et al(2000) Trust (Trust for individuals sharing Knowledge with) Barson et al(2000) Risk (Fear of penalty, losing profit) Barson et al(2000) / Pawar et al (2000)

Fear of exploitation

Szulanski(1996) Lack of Motivation (Not invented here syndrome) Kluge et al Fear of Contamination Szulanski(1996) / Gupta and Michailova (2004)

Lack of Retentive Capacity

Szulanski(1996) Lack of Absorptive Capacity Table III. Concise list of barriers Source: McLaughlin et al (2006a)

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Cross category Barriers Preferred approach to managing barrier.

Existing resources (Money, time, technology, skills, data transfer)

Codified or Personalised – In the case of the ISC the resources that were mainly impacted are personnel, training and time. However, technology might also be a contributing factor in other organizations.

Rewards (individuals rewarded for sharing/creating Knowledge)

Personalised – The Rewards system is based on developing a ‘team-working’ approach to improving overall organizational performance.

Arduous relationship Personalised – Arduous relationships are improved through personal contact and regular meetings

Culture (K Strategy) Personalised – As a ‘Pull’ culture is the desired option this cannot be achieved through technology. Individuals need to be motivated to seek and use information.

Technology Barriers

Available technology Codified – This barrier specifically looks at technology as an impact on information / knowledge sharing. Legacy systems Codified – This barrier specifically looks at technology as an impact on information / knowledge sharing. Organizational Barriers

K Strategy implementation Codified or Personalised – This is a key barrier as it looks at how individuals access valuable information. Causal ambiguity Personalised – It is more desirable to develop within individuals a better understanding of the E2E process and how the failure to

share information may impact performance at different stages in the process. . Poor targeting of knowledge Codified or Personalised – When looking to provide answers to unique queries the individual can either target data sources such

as Databases, or they can refer to subject matter experts. Knowledge cost Funding – This barrier refers to the ability of the organization to finance the necessary codified or personalised initiatives for

improving information / knowledge creation and sharing. Proprietary knowledge Personalised – Although this refers to how parts of an organization share information / knowledge, it refers to more the intent to

share (trust) than the mechanisms for sharing (technology. Distance (Geo, Culture, language, legal) Codified or Personalised – Technology may impact the communication and transfer of information between separate work groups

/ individuals. Unproveness Codified or Personalised – This depends on whether individuals value information / knowledge more highly from systems over

people, or vice versa.

Organizational context Personalised – This refers to how the organization is aligned. Does it’s structure create, or remove barriers to information / knowledge sharing.

Info not perceived as reliable Codified or Personalised – This may be dependant on the perceived quality and reliability of the existing IT systems in delivering information in a timely and accurate manner. Or it can depend on how individuals rate the reliability of fellow employees with whom they have little, or no contact

Lack of motivation (Knowledge as power syndrome)

Personalised – Reducing this barriers impact is about improving individual’s openness to sharing information and knowledge.

People Barriers

Internal resistance (Protect interests of Org/BU)

Personalised – This depends on how strongly an individual feels the need to protect their dept, function, organization by restricting the flow of information / knowledge.

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Self interest Personalised – This barrier refers to how individuals will restrict the flow of information / knowledge to vendors or business partners in case the information / knowledge is then passed on to a competitor.

Trust Personalised – This refers to how one individual trusts another to use the information provided in the manner intended.

Risk Personalised –This barrier exists when individuals restrict the flow of information / knowledge based on potential loss of earnings, customer dissatisfaction, or incurred penalty payments.

Fear of exploitation Personalised – This refers to information / knowledge reciprocity. If individual shares information how important is it they get information back.

Lack of motivation (Not invented here syndrome)

Personalised - Reducing this barriers impact is about improving individual’s openness to accepting information and knowledge that has been created elsewhere.

Fear of contamination Personalised – Information and knowledge sharing is related to the level of competence / professionalism experienced by the individual who maybe looking to share.

Lack of retentive capacity Codified – This refers to how well an organization can store new information or knowledge.

Lack of absorptive capacity Codified or Personalised – How does the organization ensure the individual gets access to the right information / knowledge, and knows what to do with it

Table IV. Approaches to Managing Barriers.

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E2E Customer E2E Re-Engineering E2E Admin Support

Senior Management

Order Order Order Order

Order Flow Process

Manufacturing DeliveryFulfi lment Scheduling

Order Management

Personalised

Personalised

Personalised Personalised

Codif ied

Codif ied

Codif ied / Personalised

/ PersonalisedCodif ied

Figure I. Dominant knowledge approaches across core supply chain process.

Knowledge

ProcessOptimisation

Knowledge Create / Transfer

Barriers

ProcessPerformanceStrategy

Desired Performance

Shape / Prioritise

Impact

Impact

Target / Reduce

Identify

Identify

Actual Performance

Impact

Culture

Org Structure

Org Strategy

(KS)

(PO)

(KB)

(PP)

Prioritise barriers

Targ

et Impact

Figure II. Knowledge Management System Dependency Model (KMSDM) with defined relationships.

25

Relationship between Elements.

Description.

KS to PO Shape / Prioritise – Knowledge strategy will shape and prioritise changes and improvements needed across core processes in order to meet overall strategic objectives.

PO to KS Impact – The operation of key core processes, and how they are structured will impact the decisions which will shape the overall knowledge strategy; such as existing technology and how it will support / hinder desired strategy, and the alignment of processes, and how flexible they are at supporting new product / customer requirements.

KS to PP Desired Performance – The knowledge implementation strategy needs to be developed in order to support and drive to achieve the desired business performance for core processes.

PP to KS Actual Performance – When shaping the knowledge implementation strategy consideration must be given to the actual performance of the core process. This feedback mechanism is necessary in order to ensure the strategy implementation methods are targeting key performance issues.

KS to KB Target / Reduce – The knowledge implementation strategy must target barriers which adversely impact the way information or knowledge sharing across the organizations key processes.

KB to KS Impact – In order for the knowledge implementation strategy to ensure information and knowledge flow efficiently across the organization, the implementation strategy must take full consideration of how barriers impact across key processes.

PO to PP Impact – Effective process optimisation will improve overall end-to-end efficiency of the processes being optimised. However, in order for optimisation to successfully improve efficiency the process must be optimised from an end-to-end perspective regardless of inter/intra-organizational boundaries.

PP to PO Identify – As processes are being optimised the impact of any change must be understood, and fed back into the optimisation process.

KB to PP Impact – Information and knowledge sharing barriers will impact end-to-end process performance if they are not checked and managed.

PP to KB Prioritised barriers – As processes are optimised and barriers identified end-to-end performance will help identify which barriers are impacting performance.

PO to KB Target – Process optimisation looks to implement changes which don’t just consider information technology considerations, but also look at how barriers impact information and knowledge creation and sharing.

KB to PO Impact – As the process is optimised key barrier impact must be monitored to ensure the dynamic effect of reducing / removing one barrier has on other key barriers are understood.

Table V. Knowledge Strategy Model breakdown.

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Basic Tenets for Designing and Implementing Knowledge Management Systems.

1. Knowledge, in itself, cannot be directly managed. However, how knowledge is created and shared can be influenced through the identification and management of knowledge barriers.

The creation and sharing of knowledge is a human function. As such technology can only be used to facilitate the dissemination and storing of information. Concerning the human ability to create and the desire to share knowledge, a knowledge strategy must focus on environmental aspects that in turn shape an individual’s beliefs, capability and desire to create and share knowledge.

2. Effective development and implementation of a knowledge strategy is dependant on end-to-end (horizontal) process awareness.

Within a complex organization, such as a supply chain, effective management of process performance is dependent on an end-to-end understanding of the total process. If an organization does not clearly define ownership and connectivity between business unit processes performance issues will be difficult to identify, agree on, and finally resolve.

3. Complex organizations need to develop their knowledge management strategies along core business processes.

Current strategy development looks to define a knowledge management systems based on broad aspects of the organization’s business structure, and type of industry. However, for a knowledge management system to be effective it must look at how the business manages its service and product delivery to its end customers. By focusing on the core processes the knowledge management system can be more accurately configured to support improved performance by targeting information and knowledge flows along the core processes.

4. Knowledge management systems should be linked to directly improving core process performance.

Knowledge management system needs be linked to operational performance. Many knowledge initiatives are developed in order to ‘improve data / information storage and retrieval’ or ‘improve cross-organizational communications’. These initiatives are usually organization-wide, and not focused on actual barriers that impact specific parts of core processes. The Knowledge management system should identify and target known barriers to performance. This way knowledge management initiatives can be directly related to process performance improvements.

5. The development of a knowledge management system is a dynamic process that needs to be constantly reviewed irrespective of process change.

Knowledge flow barriers impact the creation and sharing of information and knowledge that in turn can impact process performance. However, the barriers themselves can be impacted by changes to organizational strategy, culture, organizational structure, external business environment, and other barriers. Therefore, the knowledge management system must constantly scan and understand how the barriers are interacting with the core processes, and with other barriers.

6. To ensure process development takes consideration of existing barrier impact, organizations should develop core processes from a bottom-up perspective.

By developing processes using end-user input, a more accurate alignment can be made between how the process users create and share knowledge and information, and the performance requirements of the core process. The bottom-up approach also helps develop employee engagement and buy-in early on in the processes development.

Table VI. Tenets of Knowledge Management System Development.

knowledge management framework_ibm case study

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