Knowledge Matters™

What is a Model?

A model is an intellectual construct in artefact form that provides an abstract, highly formalised, often visual, yet simplified representation of a phenomenon and its interactions (Coffey & Atkinson 1996; Despres & Chauvel 2000). Broadly there are three types of model: mathematical models, descriptive models, and graphical models (Satzinger, Jackson & Burd 2000). Mathematical models explain the technical aspects of a system and can be either prescriptive or predictive (Miller 2006; Ragsdale 1998). Descriptive models are narrative in form and often use symbolic or mathematic elements to aid understanding. Descriptive models are rarely predictive, but can be prescriptive. Graphic models use diagrams and symbols to illustrate simple and complex relationships. They can be predictive or prescriptive. Typically a model only includes those variables that are sufficient to represent the phenomena in question. For example if colour is irrelevant then the model will not, and should not, include it as a variable. However these simplifications may result in prediction and description errors if not considered carefully. Accordingly all models should be treated with caution. They are useful so long as the underlying assumptions are explicit, and it is recognised that they are an abstract representation of reality that may, or may not, be objective (McAdam & McCreedy 1999, p. 94). Models in the social sciences tend to be descriptive and graphical rather than mathematical, although mathematical models have their place. In the knowledge management literature almost all models are descriptive and graphical.

Models of Knowledge

Much of the academic literature deals with high level abstractions which are presented as knowledge management models, but are actually models of knowledge. Suh, Sohn and Kwak (2004, p. 6) make the point that:

‘While the importance of KM is safely established, the received literature has yet to provide an integrative model of various factors associated with KM activities. … At the risk of oversimplification, generic knowledge models typically focus on KM from knowledge life cycle perspectives. These models are important in enriching our understandings on the essentials of KM activities; yet do not provide an integrative perspective for actual KM implementation’.

That said there are many knowledge models. These include:

• Popper’s ‘Knowledge Worlds’,
• Ackoff’s ‘Pyramid to Wisdom’,
• Firestone and McElroy’s ‘Knowledge Life Cycle'
• Lundvall and Johnson’s 'Six Knows',
• Nonaka and Takeuchi’s ‘SECI Process’, and
• Snowden's 'Cynefin Model'.

My intention is to add a detailed analysis of these models to the website in due course, and to include other knowledge models as they come light. To this end I welcome your suggestions . In the meantime should you wish to see diagrams of the models please view slides 28 to 31 inclusive in my Research Proposal for the Award of Doctor of Philosophy .

Knowledge Management Models

Four publications that do provide an integrative perspective for a knowledge management implementation are worthy of singling out. The first is Tiwana’s (2002) book ‘The knowledge management toolkit : orchestrating IT, strategy, and knowledge platforms’. This book provides a 10-step road map to implement a knowledge management initiative, with each step being explained in detail. Unfortunately I can find no evidence that this model has been applied in any one company or the public-sector.

The second is Frid’s (2002) ‘A pragmatic guide to building a knowledge management program’, and the third is Frid’s (2003) ‘A common KM framework for the Government of Canada: Frid framework for enterprise knowledge management.’ Both of these publications provide a broad five-step framework that is well explained. Each step has five management indices, which together provide a structured method to measure the knowledge management initiative. However, I have been unable to locate any evidence that this model has been applied in any one company, or even the Canadian public-sector!

The fourth is the Stankosky model as published in Stankosky (2005) ‘Creating the discipline of knowledge management: the latest in university research’. This model appears to be a developing methodological framework, rather than a single model, and is the subject of continuing doctoral research at the George Washington University.

Again it is my intention is to add a detailed analysis of these models to the website in due course, and to include other knowledge management models as they come light. To this end I welcome your suggestions . In the meantime should you wish to see diagrams of the models please view slides 32 and 33 in my Research Proposal for the Award of Doctor of Philosophy .

References

Ackoff, R 1989, 'From data to wisdom', Journal of Applied Systems Analysis, vol. 16, pp. 3-9.

---- 1996, 'On learning and systems that facilitate it', Center for Quality of Management Journal, vol. 5, no. 2, pp. 27-35.

Coffey, A & Atkinson, P 1996, Making sense of qualitative data, Sage Publications, Thousand Oaks, California.

Despres, C & Chauvel, D 2000, 'Thematic analysis and design of knowledge systems and processes ', in C Despres & D Chauvel (eds), Knowledge horizons: the present and the promise of knowledge management, Butterworth Heinemann, Boston, pp. 55-86.

Firestone, J & McElroy, M 2003, Key issues in the new knowledge management, Butterworth Heinemann, New York.

Frid, R 2002, A pragmatic guide to building a knowledge management program, Canadian Institute of Knowledge Management, Ontario.

---- 2003, A common KM framework for the Government of Canada: Frid framework for enterprise knowledge management, Canadian Institute of Knowledge Management, Ontario.

Lundvall, B & Johnson, B 1994, 'The learning economy', Journal of Industry Studies, vol. 1, pp. 23-42.

McAdam, R & McCreedy, S 1999, 'A critical review of knowledge management methods', The Learning Organization, vol. 6, no. 3, pp. 91-100.

McElroy, M 2003, The new knowledge management: complexity, learning, and sustainable innovation, Butterworth Heinemann, New York.

Miller, R 2006, 'Model-driven projects in the chemical industry: why using knowledge models is becoming more popular', Knowledge Management Review, vol. 8, no. 6, pp. 28-31.

Nonaka, I & Konno, N 1995, The knowledge creating company: how Japanese companies create the dynamics of innovation, Oxford University Press, New York.

Nonaka, I & Takeuchi, H 2004, 'Theory of organizational knowledge creation', in I Nonaka & H Takeuchi (eds), Hitotsubashi on knowledge management, John Wiley and Sons, Singapore, pp. 47-91.

Satzinger, J, Jackson, R & Burd, S 2000, Systems analysis and design in a changing world, Thomson Learning, Cambridge.

Snowden, D 1999, 'A framework for creating a sustainable programme', in Knowledge management: a real business guide, Caspian Publishing, London.

Stankosky, M (ed.) 2005, Creating the discipline of knowledge management: the latest in university research, Elsevier Butterworth-Heinemann, Oxford.

Suh, W, Sohn, J & Kwak, J 2004, 'Knowledge management as enabling R&D innovation in high tech industry: the case of SAIT', Journal of Knowledge Management, vol. 8, no. 6, pp. 5-15.

Tiwana, A 2002, The knowledge management toolkit: orchestrating IT, strategy, and knowledge platforms, Prentice Hall, Upper Saddle River.