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Kingsley Tagbo

How a corporation handles knowledge is an indicator of how it is positioning itself for growth or leadership in its industry.

Collecting, analyzing and interpreting knowledge is still an expensive proposition ... because:

1.) Knowledge workers are a scare resource and are expensive to hire. Only corporations with deep pockets seem to have the funds to hire talented but scarce knowledge workers.

2.) Knowledge Mining tools are still expensive ... data mining tools provided by corporations like Microsoft, SPSS, SAS still require considerable skill, expertise and training ... SO, WHAT GIVES?



you're spot on - the big task is to make sense of the "knowledge" as it is held today, an almost insurmountable task when it comes to the "web".

The issue, the source of the problem is how "knowledge" is kept, the data model, how it's represented. Today it's kept in document or form format which mashes up knowledge while giving very little context at the same time - a lose-lose proposition.

Cutting up the mashed-up data holders or representation is too costly and not very precise.

The only way to go about it - in my humble opinion - is to keep the "knowledge" from inception in a better data-model (as described). This does not help much for existing "knowledge" but it does the trick for new "knowledge".

Not a practical proposition for the word-processor-using world at large, but it is doable on the micro level within an organisation. If it works there it might spread over time, hopefully :)

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