KM Today …Posted: August 12, 2009
Nancy Dixon has written a very interesting, three-part series on the journey KM has been through till now, and the direction she thinks it is taking. Part 1 refers to Leveraging Explicit Knowledge (all those document repositories), part 2 refers to Leveraring Experiential Knowledge (tacit knowledge?), while part 3 refers to Leveraging Collective Knowledge.
Part 1 is something most of us would be comfortable with, and probably define as the cornerstone of any KM initiative. Part 2, on the other hand, is probably where a lot of us are now. This is the place where the idea that expertise is not necessarily focused with a few people, but rather, everyone has a certain level of expertise on specific things, and an organization can benefit by surfacing this. This can be seen in the idea of blogs, wikis, social networks, and so on. As Nancy says, this difference is like the difference between a warehouse, and a network. I put the difference as being one between a reservoir of water, and a stream.
The part where Nancy talks about leveraging collective knowledge is illuminating. First of all, it is quite a tricky thing to try and define collective knowledge. I agree with Nancy that this cannot be the way it has been … a summation of all knowledge available. Rather, collective knowledge must be about the creation of new knowledge from existing components. As i have written before, i think new knowledge is created at the intersection of existing knowledge. So what are we talking about with collective knowledge? An important aspect here is to get these different knowledge “sets” together, so that the intersection could be leveraged to generate new knowledge. What gets generated could be quite different from any of the sources from which it got created, and this is where the power of collective knowledge is.
The example i would like to give for the value of collective knowledge is that it is similar to the way colours can be combined to create different colours. Like, how, yellow and blue can be combined to create white. In this example, the result of the combination of the components gives us something which is different from either of them, and yet, contains the inherent characteristics of those. Why is this valuable? In the business scenario of today, where the dynamics of the world of business are such that most of the variables keep changing on a regular basis, an organization cannot simply look at existing knowledge to manage the business. Existing knowledge cannot be totally relied upon to solve problems which the organization probably hasnt faced before. In other words, continually changing problems need continually changing solutions. Question is, why do we assume that the tools of leveraging experiential knowledge, tools which the web 2.0 toolkit has brought, like blogs, networks, may not work in this direction? Actually, thats not what we are assuming. The network is going to continue to be vital to the surfacing of existing knowledge, as well as to the creation of new knowledge. As will blogs, wikis, and the web 2.0 toolkit. Having said that, however, we need components which can bring the thoughts which emerge using some of these tools together, in a way that their direction can be merged to build a direction for creating new knowledge. For example, as i have written before, tools which can help us search for opinions rather than keywords.
Another aspect which comes out of the line of thought, is that rather than being facilitators, going forward, KM has to be more active in terms of achieving business goals. Today, most organizations look at KM as the facilitator for knowledge sharing in the organization, while what Nancy talks about is KM as a tool which can be leveraged to achieve specific business objectives, and solve specific business problems, rather than a facilitator, maybe passive, as a lot of organizations seem to think.
Would like to have a discussion about what you think the nature of collective knowledge should be. Do write back, never know, it could create something something.