Jack, Valdis and I had a wonderful lively discussion about networks and innovation diffusion a few weeks ago and I’d like to capture some of what we talked about here.
First, we continue to try to clarify the different kinds of networks. We three often use the term networks in the social network analysis sense of sets of relationships and the patterns they generate. However, most people use networks to describe
intentional networks -- networks that have some awareness of the set of relationships and incorporate that awareness into their strategies. But there are considerable differences in the nature of that intentionality.
Jack came up with a nice way to represent some of those differences, see the chart above.
Some networks actually look like and function like organizations, or an organization of organizations. These tend to be intentionally focused on a particular goal or purpose, i.e. a housing network committed to increasing housing units available to low-income residents. Such networks are often structured like organizations in that they have membership and rules about how decisions are made. They tend to spend considerable time arriving at consensus and developing plans of action. These networks have had considerable success working on specific initiatives, such as advocating a specific piece of legislation but are often expensive to maintain over long periods of time.
This is in contrast to networks that are self-organized. In self-organized networks, the organizations or individuals may never all meet in one room and don’t decide on anything as a group. They move forward when individuals identify others with similar or overlapping interests and do something together. Generally, many small joint actions are generated and fewer large actions. The many groups involved in
Regional Flavor initiatives are an example of self-organized networks.
Meet-ups is another example.
Another quality of networks is their ideological stance. For some networks a specific ideology shapes the boundaries of the network, determining who is in and who is out. Such networks can generate tremendous energy (for example, the Right to Life network or some environmental networks). However, their homogeneity can sometimes limit their reach and innovativeness.
Networks that are driven by pragmatism and experimentation tend to shun specific ideologies. Individuals and organizations in such networks are looking for solutions to intractable problems that require massive innovation; or, they are trying to figure out new ways of organizing economic activity. Such networks tend to have many opportunities that encourage people to move out of silos and meet people different than them. They encourage lots of reflection about what has worked and what hasn’t. Scrum software development teams and hospital networks working to eliminate MRSA are an example of this type of network.
Where would your networks fit on this chart? Is this chart useful?
