I enjoyed a pleasant email exchange recently with someone who referenced an earlier (infamous?) blog posting regarding what I witnessed as the death of Knowledge Management in the U.S. Department of Defense. Without rehashing that work, I was interested to see that the post was circulating again. I’m happy to be updated on what I saw in 2009, and welcome any opportunity to update that observation.
Within the email exchange, I was asked a question – what do I see as the difference between Information Management and Knowledge Management? I thought I would share that answer here, offering it up to the gods of Google, in case I need it again someday.
The difference between IM and KM is the difference between a recipe and a chef, a map of London and a London cabbie, a book and its author. Information is in technology domain, and I include books (themselves a technology) in that description. Digitizing, subjecting to semantic analysis, etc., are things we do to information. It is folly to ever call it knowledge, because that is the domain of the brain. And knowledge is an emergent property of a decision maker – experiential, emotional framing of our mental patterns applied to circumstance and events. It propels us through decision and action, and is utterly individual, intimate and impossible to decompose because of the nature of cognitive processing. Of course, I speak here of individual knowledge.
First principles, don’t lose sight of how we process our world.
The difficulty is applying this understanding to organizational knowledge. Knowledge is only in the brain, but organizations have a shared understanding (referred to as ‘knowledge’) as well – humans gathered in groups fit themselves into artificial decision constructs (“collaboration,” “consensus”) in order to leverage the collective individual knowledge to make decisions for the group. My approach is to understand cognitive science, organizational theory, and information science to understand ways to improve group behaviors.
Nice post John. I would have just said ‘tacit’ and not been nearly as eloquent as you
And to hopefully add to your comment on the First Principle, I think one the problems I see in my work is that people want to treat our senses as purely physical systems, while they are in fact interpretive systems open to the strains and limitations of their residence in a larger, organic system.
Ray
Thank you for the kind words, Ray. I agree completely with your addition – this has been framed in the past as “brains have bodies.”
jb
Hi AJ – thanks for that graphic. I find it comprehensive, but confusing. What would you say is the central message there?
Thanks, Robert. I’m reminded of someone (I think it was Davenport) who pointed out that what we call “structured data” is actually information in that there is purposeful metadata that represents the crafting of the data base (domain values, fields, etc.). A similar rabbit hole comes when you use the term ‘unstructured data,’ in that virtually all data has some structure (semantic language structures, syntactic metadata, etc.). These concepts do not lend themselves to either a linear continuum (the DIKW mistake) nor mutually exclusive categories. I don’t have an easy bright line between data and information as a result, but increasingly I’m beginning to wonder if the level of machine understanding is a useful descriptor.
…and I am reminded often that these definitions don’t help the person trying to “do their job.” While I respect that we lose people with long discussions of the theoretical, I also believe much of the failure in our field comes from moving too quickly to solutions without any sense of context, how organizations work, how decisions are made – either individually or in groups, etc.
I like to say (and I know I heard this from someone else) that knowledge comes from within people and between people.
Have you had anyone ask you what is the difference between knowledge and wisdom?
That’s funny, Bill. I actually haven’t. I know others have tried to turn “wisdom management” into another branch for consultancy, but I don’t see the utility for my work and my clients. I get accused of being too academic often enough, if I start talking about organizational wisdom – I will be run out of town on a rail.
Organizational Wisdom (Applied Knowledge) is the summit of the Information Management (Organized Information) hierarchy, as Self Actualization is the summit of Mazlow’s motivation theory. Organizational Wisdom enables/empowers/achieves/sustains operational excellence (i.e. productivity, efficiency, performance, innovation, compliance, risk mitigation, discerning the known-unknown, etc.) through a collaborative knowledge foundation and work culture. KM drives Organizational Wisdom, as Information Management drives KM.
Your analogy of the recipe and chef is interesting … and really helpful for someone like me who is just starting to struggle with the concept of KM in an organization. This, and the comments below, were especially helpful. Thanks!
@AJ, with respect, what does the notion of “Organizational Wisdom” add to the conversation (not this conversation, but the overall field)? The goals implied by the graphic represent KM aspirations. “Knowing what we know” is something out of the KM field, so your graphic confuses me. Frankly, It’s not enough to assert that KM ‘drives’ organizational wisdom, please share the handoff point that encourages you to believe there is a need for this additional discipline. Can you characterize what is “done” in the field of organizational wisdom, or how you would describe it such that it sits apart from organizational knowledge?
(I also have problems with the notion that organizing information is the summit achievement for our practice – I consider decision making and innovation as the end points for applied KM.)
@AJ, I almost wish I had a nifty graphic in response. Oh, wait – I do. This below is from Poindexter, as rendered by Snowden. Notice how the definitions lead to action – of interest to the practitioner. You posit that only wisdom is action-oriented, which just doesn’t square with science nor observation.
I don’t mean to make this a graph-off, but your latest graphic does some violence to the language and science. Listing “complexity” under wisdom makes no sense – is that the only place that complex system dynamics exist? Listing “experience” next to wisdom flies in the face of cognitive science and the role of individual experience in knowledge. We apply new inputs to the world as we have experienced it. Basically, everything thrown into the Wisdom bucket applies below – unless you believe that knowledge does not include heuristics, values and beliefs, etc.
Your definition for “information” seems to encapsulate Shannon Information Theory, by equating information with “message.” Also, connectivity only applies to Information? Not data or the rest?
I apologize, but while we can throw consultancy graphics at one another, I would prefer a conversation. We can subdivide the problem and add “wisdom” but I don’t yet see what problem that solves.
Best deliniation of KM vs IM I’ve seen yet.
Reading this post has been in my cue for weeks. So glad I finally got to it. Thanks John!