Knowledge Management Framework_ibm Case Study 3ssh

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] 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.

1

Knowledge Management Framework for Process Aligned Organizations: an IBM Case

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

2

Knowledge Management Framework for Process Aligned Organizations: an IBM Case

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

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

3

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

4

specifically addresses the management of both tacit and explicit knowledge in a way that best s 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 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 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 ed 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 of ‘meaningful knowledge

5

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 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

6

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 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)

7

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

8

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 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 . 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

9

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 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:

10

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 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

11

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 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 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

12

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

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

13

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

14

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.

15

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 sociotechnical 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, istrative 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 3752. 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.

16

Hansen, M.T. (1999) The search transfer problem: The role of weak ties in sharing knowledge across organizational sub-units, istrative 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), 137154. 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.

17

Pawar, K., Horton, A., Gupta, A, Wunram, M, Barson, R, and Weber, F. (2002) Interorganizational 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.

18

Business Strategy Q i the organization What is business?

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

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

How much data is reused to new projects?

Reuses portions of old documents to create new ones.

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

Price based competition.

Every problem has a high chance of being a “one off” and unique problem. Highly creative solutions are called for. 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. 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. Employees are rewarded for using and contributing to databases such as Notes discussion databases.

How best can the role IT plays be described?

What are the reward structures? How is knowledge/information transferred?

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

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. Large teams; most are junior-level employees; a few project managers lead them. Accenture Consulting, The Gartner group, Delphi Consulting, ZDNet, Delta Airlines, Oracle. Pizza Hut Dell Computers, Gateway, Microsoft, SAP, People Soft, Baan, America On-line (AOL), Bell South, Lotus, SAS Institute, IBM, HewlettPackard, Intranetics, 3Com

What are the typical team structure demographics? What do the organization services resemble? What do the organization products resemble?

Table I. Codified and Personalised Systems

Very high profit margins. Storage and retrieval are not the primary applications of IT. IT is used to enable communication and better . Conversations, socialization, and exchange of tacit knowledge are considered to be the primary use of IT. Employees are rewarded for directly sharing their knowledge with colleagues and for assisting colleagues in other locations/offices with their problems. Knowledge is transferred person to person; intra-organizational networking is encouraged to enable sharing of tacit knowledge, insight, experience and intuition. Economies rest in the sum total of expertise available within the organization; experts in various areas of specialisation are considered indispensable. Junior employees are not an inordinate proportion of a typical team’s total hip Boston Consulting Group, McKinsey and Company, Rand Corporation. A custom car, or bicycle manufacturer, Boeing, a contract research firm, a private investigator.

Source: Tiwana (2000)

19

Business Strategy Question What type of business is the organization in? How much data is reused to new projects? What is the costing model used for organizations products or services? What are the organisations typical profit margins? How best can the role IT plays be described? What is the organization’s reward structure like?

How is knowledge/information transferred?

Where do the organizations economies of scale lie?

What are the typical team structure demographics?

What services do the organizations resemble? What products do the organizations resemble?

IBM ISC Position Providing high quality, cost effective service.

Approach Codified.

Reuse contract templates and reporting metrics and formats. Price based competition. Cost efficiency – driving cost out of the business… Supply Chain seen as a way of taking cost out of the business. IT used to store and retrieve information. Also to automate generic / standard processes. Employees are rewarded for sharing knowledge directly with peers, and helping problem solve in other parts of the organization. Employees refer to documents of best practice, and use databases for storing common information. However, also encouraged to share person to person. Economies lie in the effective reuse of information. However, subject matter experts within key areas of the process information sharing. Matrix organization with varying sizes of teams. Organization invests in MBA’s, Postgrad, and PhDs within supply chain specialisation. IBM services sections moving to a personalised services setup. Core supply chain process is process driven. However, supply chain used to project type customer requirements.

Codified. Codified. Codified. Codified.

Personalised.

Codified and Personalised.

Codified and Personalised.

Personalised.

Personalised with strong IT . Codified and Personalised.

Table II. Best-fit strategy for knowledge enablement

20

Source

Cross category Barriers

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

Existing Resources (Money, time, technology, skills, Rewards (individuals rewarded for sharing/creating K) Arduous Relationship Culture (K Strategy)

Barson et al(2000) Barson et al(2000) Gupta and Michailova(2004) Szulanski(1996) Barson et al(2000) Barson et al(2000) Barson et al(2000)/ Pawar et al(2000) Barson et al(2000)/ Pawar et al(2000) Szulanski(1996) Szulanski(1996) Szulanski(1996) Szulanski(1996) al(2001)

/

Kluge

et

Barson et al(2000) / Kluge et al(2001) Barson et al(2000) Barson et al(2000) Barson et al(2000) Barson et al(2000) / Pawar et al (2000) Szulanski(1996) Kluge et al Szulanski(1996) / Gupta and Michailova (2004) Szulanski(1996)

Table III. Concise list of barriers

Technology Barriers Available Technology (Does IT K requirement) Legacy Systems (Are Legacy systems impacting K Organizational Barriers Knowledge Strategy Implementation Causal Ambiguity Poor targeting of knowledge Knowledge Cost Proprietary knowledge Distance (Geo, Culture, language, legal) Unproveness (Is knowledge rated as being of value) Organizational Context Info not perceived as reliable Lack or Motivation (Knowledge as power syndrome) People Barriers Internal Resistance (Protect interests of Org/BU) Self Interest (expose Knowledge to competition) Trust (Trust for individuals sharing Knowledge with) Risk (Fear of penalty, losing profit) Fear of exploitation Lack of Motivation (Not invented here syndrome) Fear of Contamination Lack of Retentive Capacity Lack of Absorptive Capacity

Source: McLaughlin et al (2006a)

21

Cross category Barriers

Preferred approach to managing barrier.

Existing resources (Money, time, technology, skills, data transfer) Rewards (individuals rewarded for sharing/creating Knowledge) Arduous relationship

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. Personalised – The Rewards system is based on developing a ‘team-working’ approach to improving overall organizational performance. Personalised – Arduous relationships are improved through personal 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 Legacy systems Organizational Barriers

Codified – This barrier specifically looks at technology as an impact on information / knowledge sharing. Codified – This barrier specifically looks at technology as an impact on information / knowledge sharing.

K Strategy implementation Causal ambiguity

Codified or Personalised – This is a key barrier as it looks at how individuals access valuable information. 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. . 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. 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. 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. Codified or Personalised – Technology may impact the communication and transfer of information between separate work groups / individuals. Codified or Personalised – This depends on whether individuals value information / knowledge more highly from systems over people, or vice versa.

Poor targeting of knowledge Knowledge cost Proprietary knowledge Distance (Geo, Culture, language, legal) Unproveness

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

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.

22

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 ed 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.

23

Senior Management Personalised

E2E Customer Order Management Personalised

E2E Re-Engineering

E2E

Codified / Personalised

Codified

Order Flow Process Order Fulfilment

Order Scheduling

Order Manufacturing

Order Delivery

Codified

Personalised

Personalised

Codified / Personalised

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

Org Structure

p Sha

Org Strategy

nti f Ide

Ide n

Process Optimisation

e i ti s i or r P e/

(PO)

y

Imp a ct

Desired Performance Target

(KS)

Actual Performance

Imp a ct Tar get /R

edu ce

Process Performance

Impact

Knowledge Strategy

ti fy

Knowledge Create / Transfer Barriers (KB)

(PP) a ct Imp

ri er bar e s i t ori Pr i

s

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

24

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. 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 / hinder desired strategy, and the alignment of processes, and how flexible they are at ing new product / customer requirements.

PO to KS

KS to PP

Desired Performance – The knowledge implementation strategy needs to be developed in order to 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 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. 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 endto-end perspective regardless of inter/intra-organizational boundaries.

PO to PP

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-toend 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.

25

Basic Tenets for Deg 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-toend (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 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- input, a more accurate alignment can be made between how the process s 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.

26