I realized the other day that we haven’t said anything on the blog about small worlds and how they help innovation. This is odd because it is a major research project for us so today I’ll summarize some of the current thinking and evidence in this space.
I grew up on the small island of Tasmania, which has a population of around half a million people. Now half a million is actually quite a lot but I always had a sense that we were closely connected. If I didn’t know somebody then there was always a strong chance that I knew someone who knew that person. For those of you who live in bigger population centers, I’m sure that you still have the experience of meeting someone who is an unexpected friend of a friend (although this might not happen as often as it did for me in Tasmania).
This ‘small world’ experience has also been called ‘six degrees of separation’ and it has been puzzled social scientists for decades. Many years ago, a US sociologist by the name of Stanley Milgram popularized the six-degrees idea by getting people to send a letter to someone they had never met in another US city. The senders had to do this by sending the letter to people they knew who might know the final receiver. The amazing finding was that the average number of steps was a little over 6- hence the six degrees of separation.
The Milgram experiment has been repeated internationally with similar findings and the Kevin Bacon game works on the same principle. The fact that small worlds ‘work’ is a bit harder to explain. We don’t have that many contacts and we mostly prefer to be with people who are culturally or professionally similar to ourselves. This would suggest that the world is organized into distinct clusters of people and yet we have this idea that we are six network steps from anyone on the planet. Surely both clustering and few steps through the network can’t work together? Or can it….
One of the really interesting breakthroughs in network science over the past 10 years is an understanding of why small worlds work – and this has some pretty big implications for managing innovation (which I’ll explain later). Most of what follows here is taken from Six Degrees: The Science of a Connected Age by Duncan Watts. This is a really interesting account of networks and the six degrees problem and it’s very readable.
Watts introduces small world networks as being in between highly structured networks with organized clusters and networks with completely random links
The ‘regular’ sample network is highly structured with everyone connected to their immediate neighbors but count how many steps it takes to get from one side of the network to the other. On the other hand, the random network has few steps between anyone in the network but has no organization to it. The small world trick is that a few random connections across the network creates shortcuts and turns an organized structure into a small world.
Now, I suspect that many of you are thinking about the possibility of having organization structures together with an efficient way of transferring ideas and expertise. The small world network shows us that this is possible and there is a lot of good evidence that it can support innovation. I won’t go into great detail (and you can read a more technical review from Tim and me here) but my favorite evidence comes from the Broadway Musical industry. Using collaboration networks of score-writers, choreographers and librettists, this study showed that block-buster musicals were more likely to occur in the small-world environment.
So small-worlds can help innovation, but I also think that the network science has some serious management implications.
Try to foster a bit of randomness in the organization
-It only take a few random links to turn a structured network into a small world. Encouraging different people to talk to each other can have big payoffs, even if very few of these contacts turn into lasting collaborations.
Understand who is making the network small and look after them
-the flip side of the small number of random links creating a small world is that they can easily be accidentally removed or overloaded. Many of the firms we work with on the research are surprised to learn who these critically important links are.
We need to continue the research into small worlds and innovation but the early evidence in encouraging enough to share with business. Network analysis has a big future in the management of innovation.