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Snowden adds the further heuristics that ‘‘knowledge can only be volunteered; it cannot be conscripted’’ and ‘‘we only know what we know when we need to know it’’ for managing knowledge, in contrast to the pure economic argument. Looking back to the BPM context, we could extend the analogy further to ‘‘we can write down more than we can write in BPML’’. Put succinctly, ‘‘we know far more than we can effectively automate’’, the gap arguably being attributable to business practice. Clearly some license has been taken in defining a business practice as the gap between what a human might know and use and what knowledge can be effectively converted for execution within a BPM system.
1, pp. 82-111. , Porter, D. and Taylor, R. (1989), Analysis for Knowledge-Based Systems: A Practical Introduction to the KADS Methodology, Ellis Horwood, Chichester. , Lorenz, E. ’’, Industrial and Corporate Change, Vol. 11 No. 2, pp. 245-62. Johnson, W. (2002), ‘‘Leveraging intellectual capital through product and process management of human captial’’, Journal of Intellectual Capital, Vol. 3 No. 4, pp. 415-29. , Slovic, P. and Tversky, A. (1982), Judgement under Uncertainty: Heuristics and Biases, Cambridge University Press, Cambridge.
The role of computer-based technology in knowledge work Neither the exclusive perspective, nor the inclusive perspective, gives a clear vision of the KM-CBT boundary. They do no offer insight into what is needed along this boundary. They do not offer hindsight about what has been accomplished at the KM-CBT frontier. They do not offer foresight into possibilities about how CBT can assist KM. To better understand the role of computer-based technology in knowledge work, consider a different perspective.