Innovation’s initial slow pace!

Some interesting thought from the preface of the book ‘The Slow Pace of Fast Change’.

It argues that the more connected the network is, the more it would experience the initial slow pace of innovation diffusions even with those with the highest degree of break through.

This goes against the common sense where the more connected, the higher degree of of diffusion. Similarly to the premise outlines in those popular book such as the Tipping point which simply concludes that it is possible to find the CONNECTOR who will spread the news/meme/innovation like a wild fire.

Of course, this paradoxial knowledge is not new, especially if one follows the recent development of network sciences, especially the role of social network threshold in innovation diffusion.

The idea is simple really, most people don’t try or accept new thing unless many of their close friends do. Each person have their own threshold on exactly how many friends it takes to accept new thing. The problem is, as your close friends grow rapidly with the growth of ICT-enabled social networks, the threshold even with the same ratio (such as 2/3) will result in the lower probability for you to accept new stuff. If you are in a room with 100 friends, it will take two third of those people to be convinced before you would. Actually, the more people adding into the social network, the threshold ration tends to change also for the worst. Of course, it would take much longer time before the diffusion happens, but once it does,

This argument is a basic stuff from social network sciences.

Now, this new book ‘the slow pace of fast change’ put forward the same arugment but using Game theory, it basically argues that the decision to accept new innovation depends on the move of so many people in the games, sort of the Nash equilibrium we learned during Econ 101, where everyone tries to maximize their payoff matrix. And exactly because of this, the more connected the game / network, the more time it will take for people to reach their innovation-acceptance decisions, especially in reality people don’t know other people’s moves. When people works on imperfect information, they tends to reserve their move in the safest manner. This can, of course, lead to something like prisoner dilemma where everyone is worst off because of their fear for others.

Anyway, this is quite insightful for people trying to create innovation diffusion or cascade over the Internet, especially those working on web2.0. The initial phase can be slow but once it picks up, the fast chagne could come. The key is to look very very closely to the development of intial responds of various players in your innovation game. Exactly how, once I read the book, I will blog more about this 🙂