Analysing social networks and knowledge transfer: What we learnt from some Oxfordshire blue tits

We are not called brainybirdz for nothing. We love birds. So when many months ago we found a tweet (!) from @biotweeps citing a 2012 study into the foraging behaviour of blue tits, great tits and marsh tits in woodlands in Oxfordshire, we were naturally interested, especially when we saw that the researcher scientists involved had been using social network analysis and specifically a model called NBDA (Network based diffusion analysis) as part of their method. They wanted to establish whether frequency of contact between individual birds accounted for which birds then found new food ‘patches’, that is, random locations within two controlled areas, where overnight the researchers placed new bird feeders. We have been using social network analysis for some time to investigate frequency and perceived usefulness of interactions within office environments and determine how much these are affected by the design of the physical workspace. The bird study at one level is very similar to this, in that it is measuring the connections between individuals (birds in this case) in terms of frequency of co-location. What makes this study so interesting, is that it directly measures actual information transfer between individuals in a social network. Knowledge sharing has been seen as a business imperative for a long time. Striving for faster innovation, greater creativity, less wasted effort through duplication, through greater collaboration is a legitimate concern.

Reading the bird study, we were struck by the relative simplicity of studying birds compared with humans in an office. Finding food is a pre-occupation for birds, so if birds arrive at a new food source they either found it by chance or they found out from another bird. Nevertheless, we think there are some lessons to be had here for us humans.

The bird researchers showed that indeed the patterns of food discovery were explained best by social connections between the birds. After the first bird found the new food site by chance (although great tits seemed to be particularly good at this), those who subsequently found it, were birds which had greater centrality in the overall social network. That is, sociable birds were more likely over time to find more new food than other less sociable birds. The findings also showed that random chance meetings of birds after initial food discovery did not explain the spread of information. The bird social network of one of the woodland areas is shown below. The researchers couldn’t say whether the birds had a specific call to alert each other or whether birds just took other visual or verbal cues from birds they had regular contact with – but we like to think they sang to each other!

bird-network

Social bird network from Aplin et al 2012. Dark nodes represent birds who found food patches; numbers inside nodes indicate how many patches they found. For details see the original paper.

Of course with humans we know that we do communicate with each other (though not usually by singing!) and that we might well tell other people if, say, we found out there was some free cake on offer in the office that day. If the bird theory holds true in an office, it would be fair to say that (in the absence of an all staff email) the most networked people will get to know about the cake pretty quickly. That is, seeing the cake by chance or simply randomly being told by the next person you see, irrespective of whether you know them, are probably not the main mechanisms at play when it comes to office cake. Furthermore in the bird study, even with the power of social networks, each time only about 60% of the networked birds ever found the new food sources, which would mean in an office, some people would never find out about the cake.

So clearly, since information flow in offices is important (not just to find the cake!), social networks can help us explain how exactly information spreads. This understanding is also crucial for office designers, yet many will advocate a simple open space, where it is assumed that people can easily meet each other and ‘collaborate’. But how social networks and knowledge transfer actually works is way more complicated than that, as the blue tits who fly freely around the Oxfordshire woodland, demonstrate.

In business, we have the potential to analyse the communication or social network in an office setting using the same analytical tools. Then and only then, should we be trying to make a link back into the world of office design to better understand the complex effects of spatial settings on interaction and knowledge transfer.

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