HomeTRY THE ONLINE TRAINING FACILITYSection 2 - Analytical tools for auditing knowledge, corporate culture and knowledge linking with strategy2.1 Business Strategy and Knowledge Strategy – An Overview2.1.4 Knowledge Strategies

(B) I-Space



In another well-known application, Boisot proposes a model of knowledge asset development along similar lines to that of Nonaka and Takeuchi. In Boisot's scheme, knowledge assets can be located within a three dimensional space (“Information Space” or “I-Space”) defined by three axes from "uncodified" to "codified", from "concrete" to "abstract" and from "undiffused" to "diffused". He then proposes a "Social Learning Cycle" (SLC) that uses the I-Space to model the dynamic flow of knowledge through a series of six phases: 

1.       Scanning: insights are gained from generally available (diffused) data

2.       Codification - Problem-Solving: problems are solved giving structure and coherence to these insights (knowledge becomes 'codified')

3.       Abstraction: the newly codified insights are generalised to a wide range of situations (knowledge becomes more 'abstract')

4.       Diffusion: the new insights are shared with a target population in a codified and abstract form (knowledge becomes 'diffused')

5.       Absorption: the newly codified insights are applied to a variety of situations producing new learning experiences (knowledge is absorbed and produces learnt behaviour and so becomes 'uncodified', or 'tacit')

6.       Impacting: abstract knowledge becomes embedded in concrete practices, for example in artefacts, rules or behaviour patterns (knowledge becomes 'concrete')

Fig. 2.1(2). Boisot's I-Space I

In his model, Boisot develops an interesting application of the laws of thermodynamics. This thermodynamic analogy points to the elusive and dynamic nature of knowledge. It seems that what is happening is a cycle in which data is filtered to produce meaningful information and this information is then abstracted and codified to produce useful knowledge. As the knowledge is applied in diverse situations it produces new experiences in an uncodified form that produces the data for a new cycle of knowledge creation.   



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