Complexity and Clarity: The Knowledge Strategy Dilemma – Some Help from MaKE

Complexity and Clarity: The Knowledge Strategy Dilemma – Some Help from MaKE

Peter Sharp, Alan Eardley, Hanifa Shah
DOI: 10.4018/978-1-60566-701-0.ch018
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Abstract

Organisations face a great problem. How can they create a knowledge management (KM) strategy that takes account of the complexity of knowledge issues in their organisation and be able to clearly communicate it? This issue, called here the Knowledge Strategy Dilemma, is the main theme of this chapter and is vital for KM success in practice. The authors argue that literature reveals that the Dilemma is one that can be tackled. They also argue that whilst the literature reveals approaches that help address different parts of the Dilemma, the best approach to address it in a coherent way is a KM method called MaKE. MaKE is presented and two of its principles—Traceability and Transparency— are explained. Also visual tools that help implement these principles in practice are critically discussed along with feedback from industry. The principles, when applied, are helpful in tackling the Dilemma with some success. Also, the authors argue that different forms of communication (including face-to-face meetings with visual aids) should be used to address the Dilemma. The question that remains is: are organisations willing to devote the time to do these things in practice?
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Knowledge Strategy Dilemma: Complexity And Communication

There is no doubt that the area of KM and its application to organisations is littered with complexity. The concept of ‘knowledge’ is enough to generate a plethora of different definitions (Sharp, 2006b) and an enormous range of different concepts and approaches (Sharp, 2003). There are a wide range of different viewpoints on the subject which has led some to argue that the field of KM is a bankrupt in the very disciplines (e.g. Information Systems) in which it was originally applied (Galliers & Newell, 2001). Others have argued that the area of KM related to how people think and learn, is so intangible that it is beyond definition. Polanyi (1967) wrote a lot about the subject of personal knowledge at the human-oriented end of the spectrum, but in doing so, provided no definition of knowledge for his readers. This may have been because he believed that by defining it, he may oversimplify the concept and support an unsophisticated approach. The issues relating to tacit knowledge, its meaning, and the whole notion of what can be made explicit, raises dilemmas in KM about implementation and there have been calls for a reconsideration of KM methods in organisations (Vasconcelos, 2008).

Although the issue of defining knowledge is seen as a stumbling block by some, the majority of people working in the field have moved on from that issue by either not defining it or discussing it in the context of different concepts and practices they write about. In doing so, authors have used many different approaches and have created a wide variety of KM concepts (e.g. Wiig, 1993; Machlup, 1980; Bontis, 2000; Malhotra, 2000; Stewart, 2002; Tobin & Snyman, 2008). The KM frameworks that exist range considerably. Some focus on a particular aspect of organisations while others take a more comprehensive view of knowledge in organisations (Holsapple & Joshi, 1999). Some frameworks emphasise the process of knowledge creation and innovation (e.g. Nonaka & Takeuchi, 1999) whereas others focus on knowledge as a resource to be evaluated (e.g. Sveiby, 1997; Edvinsson & Malone, 1997). Some authors argue that complexity itself should be embodied in KM frameworks and that management is best done by creating organisational environments in which these complex processes take place (Snowden, 2002). Others adopt a very different argument. They suggest that by creating unified generic frameworks that synthesise the thinking in the domain, organisations can categorise, process and evaluate their knowledge and intangible assets in a more structured way (e.g. Holsapple & Joshi, 2001a and b).

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