Managing Knowledge: Responding to Hagel III and Brown
In A Better Way to Manage Knowledge, Hagel and Brown offer thoughts on differentiating notions of knowledge management systems from knowledge creation spaces, and wonder what issues need to be overcome to gain wider adoption of creation spaces as an alternative means of creating and capturing knowledge. While I’ve always been an admirer of Dr. Brown’s work, I’m a little surprised by this post–mostly because I’m having trouble figuring out what is ‘new’–but also because he has been pretty good at identifying the effects of only valuing certain kinds of knowledge and knowledge creation spaces over others. I attribute failures of existing knowledge management systems to a lack of habitability: they fail to support work that people do and tasks that they want or need to accomplish in ways that are familiar and useful.
I attribute failures of existing knowledge management systems to a lack of habitability: they fail to support work that people do and tasks that they want or need to accomplish in ways that are familiar and useful.
I’m convinced that the act of sharing/propagating knowledge (one element of knowledge management) is also an act of knowledge creation. I may have created and captured in my head the knowledge that stoves are hot by putting my hand on one and getting burned, but if I don’t propagate that knowledge to the two year-olds conducting an experiment by moving toward the hot stove, I haven’t done a good job managing it, and they’ll painfully recreate that knowledge for themselves.
Knowledge, from our perspective (and by our I’m referring to me and my colleagues Greg Cuppan and Rhonda Steele at McCulley-Cuppan, LLC), is information with some value added. Often this added value is an interpretation (what the information means) represented in a document–and here I’m using a very broad definition of document–but it could also be some other tool that helps someone get to and interpret information. Knowledge management consists of practices and tools that help people add value to information and thus create knowledge. How does it benefit those who are trying to help people and organizations usefully know what they know through knowledge elicitation, capture, propagation and reuse (our characterization of the core elements of knowledge management) to redefine this work and to emphasize one element as a knowledge creation space?
We have a tough time convincing people working int the pharmaceutical and medical device industries that managing knowledge is not the same thing as managing data and information, and that doing science is more than the work scientists and technicians do to design experiments and collect data. For example, people actually have to interpret the data, assign significance, and write the report that presents their interpretation and explains the significance. To do that well it helps to know what the study was designed to test and why–but if that knowledge wasn’t captured, and, as often happens, if the people who conceived the study aren’t around to explain their motivation, it becomes more difficult.
Telling these people that what we’re really doing is something other than knowledge management, and adding a layer of complexity by explaining that what we need or want to add is a “knowledge creation space” may not be helpful. While not untrue (and maybe more accurate), I fear this would produce a new cognitive bottleneck–in the same way that descriptions of what it is to “do science” and the term ‘informatics’ may confuse things.
In “Laboratory Life,” Bruno Latour and Steve Wolgar described the laboratory as a kind of knowledge creation space where scientists design and execute experiments and use technology (inscription devices) to collect data. But in their description they fail to notice some critical elements of life in the laboratory: scientists must do several kinds of work to turn the output of their inscription devices into usable knowledge–as embodied by documents that represent their interpretations of the output, and thus make further work (the creation of more new knowledge) possible. Their description separates knowledge from the artifacts that embody and convey it–and the artifacts appear as if by magic after the experiment has run.
Informatics–another hot label–sees technology as the path for creating new knowledge. Informaticians see themselves as the bridge between practice and technology because their knowledge of practice (in this case science) informs the design and use of technology to support practice. In the life sciences, for example, informatics projects involve finding ways to help scientists collaboratively collect, share, visualize and analyze scientific data. Thus, informaticians see their role as one of creating knowledge creation spaces. This perspective also treats knowledge as an artifact that we can obtain through the appropriate use of technology, and with ideal technology we might not even need the scientist. I use the term informatics because it resonates with some of the people I work with, and helps them understand some of the work I do. But the systems I seek to design are more–they are habitable knowledge management systems.
Scientists we work with often see generating and visualizing data, and creating knowledge as one in the same. They are usually quick to remind me that their experimental design and their collaborative informatics tools are their knowledge creation spaces (and their PhD is in biochemistry, and mine isn’t). Their request for help is: “Help us see the data in a new way, and we’ll worry about writing it up later.” By elevating the notion of knowledge creation spaces, we marginalize the roles of knowledge capture, propagation and reuse because the value of knowledge elicitation and capture isn’t readily apparent as important to the creation of new knowledge.
Unless we do a good job capturing and communicating what we think we know and why, we leave others to either reinvent work we’ve done to know what we think we know (to recreate our knowledge), or, worse, we lose the opportunity to learn why what we think we know might not be quite right, or leave others scratching their heads wondering what the hell we’ve been doing. This doesn’t seem particularly effective or efficient.
It is difficult to for me to imagine knowledge creation in a vacuum, which is what the name “knowledge creation space” seems to represent. The scientific method requires knowledge of something we don’t understand but want to and a possible explanation that we can explore. It is this knowing what we think we know and don’t know that helps us direct our efforts to solve problems. Capturing that knowledge in ways that can be shared helps communities of practice create new knowledge. My sense is that communities of practice are an emergent property of people who have some things in common–but that is a different problem (but one that becomes more apparent as we distinguish ourselves by our labels).
I’m still okay with knowledge management as the term of art, and knowledge management systems as tools that help us manage knowledge, and I won’t argue against the belief that these are practices that help people create knowledge–and more! And I’m pretty sure we’ll see wider adoption of knowledge management systems when we design systems that are habitable. But I don’t see how focusing on one element of knowledge management–knowledge creation– and calling the system a ‘knowledge creation space’ will do this.
What do you think?
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Tufte has a collection of bad visualizations of data – cute graphic USA type bar charts, tons of skewed scale charts, so if you can’t prove that knowledge arenas have to been learned to be used, you can show that arenas can be manipulated to be useless.
PublicSpam isn’t up yet. Just the mailing list.
MM