How social networks control your company

Photo by Belinketeneghe

Brokerage and Closure by Ronald Burt is a must-read for anyone interested in innovation and social networks. He’s a sociologist with the Chicago Graduate School of Business who’s spent years mapping and analyzing the patterns of relationships in large companies like Raytheon. This book describes how new ideas, trust and power flow directly from these networks.

The title refers to the two forces that shape who you talk to. Closure is the technical term for how insular a group of peope are, measured by the strength of relationships between all the insiders, and the weakness of ties with outsiders. If you draw a graph of the communications within a group with high closure, you see a lot of lines between the members, and few contacts with others:
In everyday language, a cluster of people with high closure would be called a clique. They form because they have some big advantages. It’s a lot easier to trust someone you’ve no experience with if you share mutual friends, because the risk to their reputation will be severe if they let you down. The dense pattern of communications also makes sure that practices and beliefs get spread and standardized quickly throughout the group.

Large organizations are made up of many of these self-contained teams, each with their own shared experiences, ideas and ways of doing things. Brokerage is the act of bridging the gaps, or structural holes, between these groups in the network. People who have connections with multiple groups that would be otherwise unconnected are known as brokers or bridges.


They play an important role in innovation because they have the chance to introduce good ideas from one team into another, or combine partial insights from multiple groups into a new approach to a problem. They also have political advantages because they have more information about the motivations and goals of other teams, and can use that knowledge to help steer decision-making to avoid conflicts and gain support for initiatives.

Where Burt really shines is the application of this general model to the wealth of data from sociological studies within companies, together with his own personal experiences of working with large businesses. He sets out to prove 4 ‘stylized facts’ about how brokerage and closure works in practice:

Brokers do better. He uses network analysis together with personnel records to show that people who have strong connections outside their immediate team get paid more, and promoted faster.

Brokers have better ideas. Analyzing the ranking of improvements for a supply-chain management department together with the connectedness of the people suggesting them, he builds a case that the reason brokers do better is because of the quality of the ideas they come up with.

Brokerage is useless without closure. This is less of a slam-dunk, but he gathers evidence that brokers don’t help when the teams themselves are fragmented and poorly coordinated. Intuitively this makes sense, groups who can’t communicate internally won’t be able to execute even given the best ideas.

The echo chamber amplifies closure. Treating networks as information circuits ignores the primate biases that actually guide our social behavior. In particular, etiquette demands that we avoid contradicting a conversation partner when possible. This and similar habits mean that reputations are exaggerated in a feedback loop through gossip, since people you talk to will tend to agree with your assessment of someone, even if they don’t hold the same opinion. This gives the illusion of corroborating evidence for your views, and tends to tighten the bonds that bind a group together and more strongly exclude outsiders. This is a tough one to tease out from the data, but he shows that the more mutual contacts you share with someone, the stronger your opinion of them, even if that opinion disagrees with the assessments of your shared contacts.

This is vital reading for anyone dealing with social networks because of the applications of these theories to the design of our tools. At the start he talks about the delusion that having lots of contacts in a network adds value, when instead the really valuable connections are those outside your immediate group, and how this is where businesses like LinkedIn and Tacit should be focusing their efforts.

I’m particularly interested because most of my work has been aimed at making brokerage easier and faster. Defrag Connector was about establishing initial trust between conference attendees by revealing mutual friends. I’m analyzing email to reveal the existing communication networks, and identify good candidates for brokerage contacts because they’re experts in a helpful area, or have external contacts that would be useful. Most of his data comes from self-reported surveys of who people talk to, I’d love to run some of his work against my large company email data sets. He mentions Valdis Krebs in the foreword, but I was disappointed I didn’t see any references to his work deriving networks from implicit communication data.

Burt is writing for an academic audience, so he presents a lot of the primary data backing up his arguments, which can make it a tough read for generalists like me. He’s got a readable style though, and I love some of the anecdotes that pop up throughout, such as the quote from a manager explaining that when analyzing improvement ideas "that were either too local in nature, incomprehensible, vague or too whiny, I didn’t rate them."

4 responses

  1. wow, that’s a compelling title…I definitely opened it from google reader just because of the title.
    Great analysis of the interpersonal effects of social networks. I guess the big question is how do we accomplish using our tools — a web browser ui?

  2. I loved this book because it gave me a mental model to describe patterns I see all the time in my professional life.
    As the saying goes, every science starts off as stamp-collecting, and Burt has his hands full trying to describe reality. He doesn’t offer any suggestions on how to use this information, but I took away a few insights that could be useful for designing tools:
    Reputation is the currency that flows around networks. You make new connections and take action based on what you hear from mutual contacts. That implies that you should base a network around recommendations and other signs of approval, rather than just the existence of a connection between two people. At the moment ‘friending’ is an implicit recommendation, but it would be powerful to have that recommendation step explicitly be the primitive used to build networks.
    Volume is far less important than variation in your contacts. To help promote brokerage, we should make contacts outside your usual circle more prominent and accessible, possibly by expertise location or something similar.

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