KM in Practice 2.0

Miguel Cornejo just posted his paper on Visions of KM 2.0 (here), which he was kind enough let me preview and comment on.  The tenor of our exchanges are fairly represented by his post introducing he paper:

For quite a while now, I’ve felt that most business managers were not getting a clear message about knowledge management. There is a lot of academic debate that not even the academics can make practical sense of, a lot of discredited methods still trying to prove themselves, quite a lot of smoke about social software and enterprise 2.0… and a cart load of vendor-talk about all sorts of technology or services solutions. No wonder KM has a fame as a perplexing discipline.

And it shouldn’t. Managing knowledge is a practical part of business management, an essential good practice. Every organization does it, at least by default, and it can bring great benefits if done well.

If you have trouble w/ the emekaeme link above, Miguel’s paper is posted at the Macuarium here.  We’re PC vs. Mac agnostic here.  Of course, that’s the one thing the Borg and Apple can agree on — they both run SAP :-)


One Response

  1. “Knowledge” (a noun or entity) in section 2.1 is described in terms of its creation (a verb or work). This seemingly trivial distinction is really important for clarity. Also, listing the ingredients or attributes of something is a description (what it looks like), not a definition (what it is). You know that you understand a thing when you can define it; description implies observation, not understanding.

    Instead of using the word “context” to imply a capacity that enables interpretation, analysis, or synthesis of data or information, why not stick to the word knowledge. In my models, I refer to knowledge assets (what is known) as well as the capacity to create new knowledge

    One of the issues that I’ve wrestled with over the years is getting past “Oh, it’s all information, anyways!” Unless we clearly distinguish between the two, there is no counter to that argument and KM simply becomes a subset of IM. I particularly like Patti Anklam’s 3 generations of KM (artifacts, tacit, and emergent) as a way of distinguishing IM and KM.

    Knowledge is not simply something in people’s heads. It also exists in explicit form. When I write F=M * A, I am expressing a cause and effect relationship that enables me to predict the consequences of changing either M or A. That is knowledge or understanding, just as much as my experience and mental models that enable me to get through my day. Information would be things like what are force, mass, and accelleration, while data would be the numbers that you use for calculation.

    Some of these (and other) ideas can be found in:

    I’ve wrestled with various definitions of knowledge and KM over the years. The one thing I’ve learned is that any definition must be context-sensitive. That is, it must work in the environment in which it is intended to be applied. So, even though coming from a science-based organization, I use understanding and prediction as my central elements, I have seen things as simple as “something you need to know to do your work.” This is a lot like your definition, except that it isn’t couched in the word information (although knowledge as something that you know is somewhat circular).

    Oh well. I hope these thoughts are of some use to you.

    Al Simard

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