Network analysis – Open space outcomes

As part of the Enterprise2.0 Summit 2010 in Frankfurt, we held an open space session on network analysis, facilitated by Alpesh Doshi. In the following post I try to summarize the results. If you have any additions or corrections, please leave a comment.

We’re all part of multiple networks. Even more: relationships change, so our membership of networks changes over time. If you start mapping, visualizing and analyzing these formal and informal networks in organizations, you can do all kinds of interesting things. Thing such as:

  • asking questions to your network – to reveal the experts,
  • recommendations from your network – “you might also be interested in…”
  • find shortest path to colleagues – How are we connected?
  • identify relevant people for an innovation project,
  • find patterns in the network to identify experts, connectors, influencers,
  • and even: who to contact for a 360 degree appraisal round of a colleague.

But if you start mapping, visualizing and analyzing networks, all kinds of privacy issues arise. We had a good discussion on that, but no uniform solution. Transparancy seems key: knowing (and being able to control) what information about your network is in the system seems crucial.

And then, how do you prove the business case of social network analysis? If you start from a real, specific, measurable problem, you have a good chance of explaining the ROI. Otherwise, you might have to collect success stories, and sometimes use KPIs around communication & knowledge flow.

Further readings on, where Rob Cross publishes interesting information on this topic.

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