A discussion is currently taking place on the ActKM mailing list about the theoretical underpinnings of knowledge management. Joe Firestone, reaching into the language of philosophy, has consistently taken the view that KM only makes sense when related to the need to improve underlying knowledge processes:
I see [knowledge management] more as a field defined by a problem, with people entering it because they’re interested in some aspect of the problem that their specific knowledge seems to connect with.
Unfortunately, in more quotidian language, the word ‘problem’ suggests difficulties that need to be overcome, but sometimes KM is actually not dedicated to overcoming difficulties but to taking maximum advantage of opportunities. When Joe refers to a ‘problem’ I think he means it as a puzzle or conundrum: “how do we fill this knowledge gap?” Stated thus, I think this is a less objectionable aim for KM.
What about the nature of the conundrums that face organisations? Rightly, in linking to an earlier post of mine, Naysan Firoozmand at the Don’t Compromise blog suggested that there was a risk of vagueness in my suggestion (channelling David Weinberger) that KM might be about improving conversations in organisations.
Which is all true and good and inspiring, except I want to wave my arm about frantically like the child at the back of class and shout ‘But Sir, there’s more … !’. There’s a difference between smarter and wise that’s the same difference as the one between data and information: the former is a raw ingredient of the latter. And – when it comes to organisational performance and leadership (which is our focus here, rather than KM itself) – simply being smarter isn’t the whole story. Clever people still do stupid things, often on a regular (or worse, repeated) basis. Wise people, on the other hand, change their ways.
This is a fair challenge. Just improving the conditions for exchange of knowledge is not enough on its own. (Although I would argue that it is still an improvement on an organisation where conversations across established boundaries are rare.) There are additional tasks on top of enabling conversation or other knowledge interactions, such as selecting the participants (as Mary Abraham made clear in the post that started all this off), guiding the interaction and advising on possible outcomes.
Those additional tasks all help to bring some focus to knowledge-related interactions. The next issue relates to my last blog post. In doing what we do, we always need to ask where the most value can be generated. The answer to that question, in part, is driven by the needs expressed by others in the organisation — their problems or conundrums. However, not all problems can be resolved to generate equal value to the organisation.
The question, “what value?” is an important one, and reminds us that focus on outcomes is as important as avoiding vagueness in approach. How can we gauge how well our KM activities will turn out? Some help is provided, together with some scientific rigour, by Stephen Bounds (another ActKM regular) who has created a statistical model for KM interventions using a Monte Carlo analysis. His work produces an interesting outcome. It suggests that on average, the more general a KM programme, the less likely it is to succeed. In fact, that lack of success kicks in quite quickly.
To maximise the chance of a course of action that will lead to measurable success, knowledge managers should intervene in areas where one or more of the following conditions hold:
- occurrences of knowledge failures are frequent
- risks of compound knowledge failure are negligible or non-existent
- substantial reductions in risk can be achieved through a KM intervention (typically by 50% or more)
Where possible, the costs of the intervention should be measured against the expected savings to determine the likelihood of benefits exceeding KM costs.
So: simple, narrowly defined KM activities are more likely to succeed, all other things being equal. Success here is defined as it should be, as making a contribution to reductions in organisational costs (or, potentially, improving revenue). Stephen’s analysis is really instructive, and could be very useful in encouraging people away from a “one size fits all” organisation-wide KM programmes.
In sum, then, our work requires us to identify the conundrums that need to be solved, together with the means by which they should be addressed, and to define the outcomes as clearly as possible for the individuals involved and for the organisation. We cannot hope to resolve all organisational conundrums by improving knowledge sharing. So how do we choose which ones to attack, and how do we conduct that attack? Those are questions we always need to keep in mind.
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