In this post I’ll complete my analysis of Dave Snowden’s seven principles of Knowledge Management.
— “Tolerated failure imprints learning better than success. When my young son burnt his finger on a match he learnt more about the dangers of fire than any amount of parental instruction cold provide. All human cultures have developed forms that allow stories of failure to spread without attribution of blame. Avoidance of failure has greater evolutionary advantage than imitation of success. It follows that attempting to impose best practice systems is flying in the face of over a hundred thousand years of evolution that says it is a bad thing.”
I agree that best practices systems are bad news. Some years ago, a friend of mine, Mark Notturno, said that Knowledge Managers should not be concerned with making knowledge maps, but should, instead, be creating error maps, because what our experience really teaches us is where our knowledge has failed and needs to be replaced. Rather than best practices systems, we need lessons learned systems, where the lessons learned are the errors we have made in the past.
Even though I agree with the above, I think, two points really need to be added. The first is that humans have devised ways to learn from error, without personally having to experience the painful consequences of it, as Dave’s young son did. One of these ways is scientific experimentation, which is a type of “safe-fail” experiment, an idea that Dave is very familiar with. Second, even though we learn best when 1) there is no attribution of failure, 2) we also have to experience its consequences, I don’t think we learn very well, when we organize human social institutions in such a way that we escape both attribution of failure and personal experience of the consequences. In the international financial system we are currently seeing a process unfold, where our political leaders are allowing financial managers to escape the personal consequences of their failures, including the public attribution of failure to their previous activities. This is the worst of all possible situations, where the lessons financial leaders seem to be learning is that they are “too big to fail,” and there will be plenty of opportunities to continue to receive huge compensation, no matter how badly they have performed in the past, due to their indispensability in helping to solve the problems they themselves have caused. These, of course, are the worst possible lessons, and they bring into high relief the idea that human evolution shaped us to perform best when we are faced with the personal consequences of those of our bad ideas that have survived our evaluations of them, and that one of these personal consequences is the unmistakable attribution of failure, or at least error, when it has occurred.
— “The way we know things is not the way we report we know things. There is an increasing body of research data which indicates that in the practice of knowledge people use heuristics, past pattern matching and extrapolation to make decisions, coupled with complex blending of ideas and experiences that takes place in nanoseconds. Asked to describe how they made a decision after the event they will tend to provide a more structured process oriented approach which does not match reality. This has major consequences for knowledge management practice.”
I entirely agree with this one. Our narratives about how we’ve made a decision, are bad theories about how we’ve actually made it. But this not only has consequences for KM practice; it also has consequences for knowledge processing and KM theory, as well, since both of these need more realistic theories of decision making.
— “We always know more than we can say, and we will always say more than we can write down. This is probably the most important. The process of taking things from our heads, to our mouths (speaking it) to our hands (writing it down) involves loss of content and context. It is always less than it could have been as it is increasingly codified.”
I agree with the principle here, but not with the statements amplifying it. Specifically, the idea that we lose “content” when we express ourselves using language or other cultural instruments is true only because it is the mental knowledge “content” and subjective experience of context that is lost in the process of creating codified knowledge. In its place however, linguistic content and context, which is something entirely different, is created and gained. The linguistic content and context constituting codified knowledge, unlike mental knowledge, is “objective knowledge” in the sense that it is sharable and criticizable.
What’s often not pointed out about “objective knowledge” is that in an important sense, it is, in Bartley’s words, “unfathomed knowledge.” In saying this he was pointing to the well-known idea that the logical content of any non-trivial knowledge claim is open-ended. New logical consequences of any of our theories or models may appear at any time, and we cannot know, in general, what those consequences will be. Neither Newton nor Einstein understood the logical consequences of their theories. Nor does Dave (or anyone else for that matter) know very much about what logically follows from a commitment to the propositions of Cynefin. It may well be true, as Polanyi said, that: “we know more than we can tell.” But it is just as true that in stating and committing ourselves to a knowledge claim, we also tell more than we know. So there is further mystery, and potential for discovery, in both mental and codified knowledge, and if we want to increase our understanding, we need to explore both, and their dynamic relationship over time.
Looking beyond each individual principle, I think it’s important to ask to what extent the principles, viewed collectively, present a coherent picture about KM practice. The first principle clearly suggests that KM should not use coercive approaches to knowledge sharing. The fifth, suggests that best practices systems shouldn’t be used. The sixth suggests that KM needs to develop more realistic knowledge about how we come to know things. The other principles seem to refer to various aspects of knowledge processing, and Dave doesn’t make clear their implications for KM. This is especially clear with the last principle: “We always know more than we can say, and we will always say more than we can write down.” Dave also says: “This is probably the most important.” But he doesn’t lay out its implications for KM. Finally, the principles come across as isolated “fragments” themselves, rather than as aspects of a coherent picture of how to approach KM practice. Keeping this in mind, and also the previous comments on each of the individual principles, I conclude that some of these aren’t principles of KM at all, and even if some are, they only scratch its surface, and are far from a set of principles that might be used as a guide to the subject.