Of Numbers and Knowing

Social Group Size and Knowledge Management Concerns

Numbers have a curious way of popping up in the most unlikely places. Think of social groups and their optimal dynamics and you’re likely to imagine somewhat fuzzy amounts. Large groups might be difficult to manage, but that shouldn’t be the case for small groups. This has been important for me lately as I’ve argued against the need for knowledge management in self-organising systems. But one number I’ve missed might well make a difference, and it’s rather precise.

Debating me on a range of issues under the broad rubric of knowledge management today, Patrick Lambe mentioned what is often described as Dunbar’s number: 150. It seems dubiously even, but it’s rounded up from 148 and is only then the upper limit of individuals with whom you’re likely to maintain close personal relations.

Robin Dunbar is an evolutionary psychologist who studies the size of the neocortex in primates – that part of the brain governing consciousness, sensory perceptions and language – and relates it to optimal group size. It turns out that our brains might be hardwired to work best in smaller organisations.

Actually, I should have known that. Malcolm Gladwell mentions Dunbar’s number in Tipping Point, which I read a few months ago, and I remembered the subsequent discussion about W.L. Gore and Associates (of Gore-Tex fame). Gore has broken itself into small units of what it calls “multidisciplinary teams” with largely horizontal staff structures to counteract organisational inefficiency. When I raised this issue today, Patrick recognised it as a “good example of organising to meet cognitive constraints”.

In that light it might also be an alternative to knowledge management, disaggregating a large organisation that’s cutting too many links between its members. Patrick thinks “even those optimal size tea[m]s need to coordinate with each other if the organisation is to operate as a coherent whole”. Yes certainly, and it will be interesting to find out exactly what form of coordination would be needed, given that employees would be neurologically more capable of doing the inter-group organising for themselves.

Another interesting number came up when Stephen Bounds joined the discussion. Of Ray Sims’ 53 definitions of knowledge management, it appears 4 are not relevant to the field. Stephen has posted his analysis in a wikigroup, and it’s worth considering because his comments tend to break the field down even further into bases and types of action.

I can identify 3 bases of action in knowledge management from Stephen’s efforts: specific processes, day to day management and, though not as often, individual skill sets. From these wellsprings of action come collaboration, learning and codification, all with the aim of improving organisational efficiency.

The only problem I have with this schema is codification, because it embodies the expectation that implicit knowledge can be made explicit, that the nuances of the workplace can be fitted together into a list of rules, regulations or organisational norms.

For now I’ve agreed to disagree on this point, but it brings me to something that’s equally important to mention. In my last post I implied that knowledge management was hiding behind barricades of ambiguity because it failed to use the common definition of knowledge. But Stephen and Patrick’s responses indicate that what appeared to be ambiguity is actually the complexity of a field not fully formed, so I retract my remark.

Still, my concerns about knowledge management remain, and thanks to Patrick’s reading suggestions I’ll be able to pursue them further. For now, the pointer to Dunbar’s number has come at a very fortuitous time. I’m just preparing a post on monkey behaviour and learning for tomorrow. I want to throw poo at Andrew Keen’s Cult of the Amateur.

It’s back to the puzzles of the world for me.