4 Popular mistakes Knowledge Managers make
Do you make any of these assumptions?
1. Knowledge Management should set out to capture and store critical knowledge, and make available to anyone who needs it, at the time they most need it. Knowledge generalised, categorised, labelled, ordered and made available to anyone who needs it, whenever they need it. Sounds great, but, if this is your strategy, you will fail.
People have hidden (discrete) knowledge that they take for granted; this is potentially the limiting knowledge that differentiates them from their colleagues. They don’t realise they have this knowledge until they need it - so, if you assume that people can tell you what critical knowledge they hold, you are wrong. Critical knowledge is defined by time and place, which causes problems - exit interviews, for example, are not the time and place to identify critical knowledge.
Ask yourself, how does this knowledge get captured, unless you ask the right questions, in the right environment to expose it? Also, Knowledge Managers often fail to consider that "expert" knowledge is not necessarily about the knowledge itself, but the ability to acquire, share, deploy and develop it. This leads to Knowledge capability, which is a totally different focus from traditional Knowledge Management.
2. Critical thinking is for academics! Too many Knowledge Management reports are built upon poor science that has a negative impact on the Knowledge Manager and the wider KM function. Data (big or small)/information is only as useful as the question you ask in the first place - rubbish in, rubbish out, that simple. Not only this, but you have to accept that data is subject to the bias of the consultant/Knowledge manager/expert that produces it – you cannot avoid this (ask a question and you have to consider the bias that led you to ask the question in the first place)!
You often see this in surveys produced by KM consultancy companies, the results contain a heavy bias toward outcomes that they want you to buy in to. Want to sell a KM service? Run a survey that channels (nudges) people into your service offerings. How do you do this? Limit the question set to conform to your view of the world and produce quantitative outputs that don’t allow people to discuss anything to do with “why” they feel a particular way – then make inferences based on your limited data set. Limited input, limited output value. This is work so poorly crafted, from a research perspective, the outputs are almost worthless!
Is this really the type of data you want to base your next decision upon? Is this the type of data you generate?
3. Size is everything. Knowledge Managers often think of knowledge in terms of the vastness of the repositories they create - the bigger the store, the more knowledge available, the better the KM 'solution'. This is incorrect. Knowledge Capability is governed by the "proposition of the minimum" and the sustainability (resilience) of any organisation is at risk if it is ignored:
An organisation’s ability to adapt, to sync to its environment, is not contingent on the total resources available to it today. Its ability is constrained by the scarcity of the limiting data, information, knowledge, skills, behaviours, experience, time, finance and technology available when people sense change and need to act.
Is your organisation at risk if you only focus on traditional technology-led Knowledge Management 'solutions' and you ignore the capability that activates knowledge?
4. Knowledge resources are assets, just like any other organisational asset. Knowledge resources are not assets in the traditional sense. You cannot audit or benchmark a person the way that you would a marine terminal. Knowledge resources are governed by the ability to activate them (people cooperate and compete); they sit in a complex, interconnected environment and cannot be optimised in isolation. If you want to optimise knowledge resources, you have to be prepared to make adjustments across the whole KM environment and not only a small part of it - see the K-Core model below for areas you should be exploring.
“Perhaps we all have a rather Victorian fetish for reductionist explanations about the world….We have somehow made behavioural phenomena feel connected to larger explanatory systems, the physical sciences, a world of certainty, graphs and unambiguous data. It feels like progress. In fact, as is often the case with spurious certainty, it’s the very opposite” (Goldacre, 2008)
What does the knowledge environment look like in your organisation? If you do not know, if you assume you know, you will find your projects limited and/or failing? Do you want to get lucky by design or do you want to leave your Knowledge Management projects to the whims of pure chance?
