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Years
Sensemaking
This description of sensemaking makes the most sense to me.
Sensemaking involves turning circumstances into a situation that is comprehended explicitly in words and that serves as a springboard into action. (Weick et. al 2005)
I’ll tell you why.
When I run lessons learning sessions I’ll often start the session by asking, “So, what did you learn from this project?” The typical response is, “Hmmmm, let me think … Nup, didn’t learn anything really.” Then we timeline the project, identify key events, retell stories of what happened and then this happens: “Remember how we got the funding? It was a shocker. We had to get the Commissioner to move money to the large projects vote and as a result we never really had a project sponsor. I would never do it that way again.” It’s this point of putting the idea into words, usually as a story, that the lessons are identified (not sure they’ve been learned yet).
The same think happened to me last week. We (I’m working with Patti Anklam and Bruce Hoppe on this one) are running a social network analysis for a global community of practice of chocolate experts. When we presented the first SNA charts the immediate response from the client was, “Nothing new here really.” After a number of discussions the response was, “Wow! Heaps of insights.”
Weick, K. E., K. M. Sutcliffe, et al. (2005). “Organizing and the Process of Sensemaking.” Organization Science 16(4): 409-421.
About Shawn Callahan
Shawn, author of Putting Stories to Work, is one of the world's leading business storytelling consultants. He helps executive teams find and tell the story of their strategy. When he is not working on strategy communication, Shawn is helping leaders find and tell business stories to engage, to influence and to inspire. Shawn works with Global 1000 companies including Shell, IBM, SAP, Bayer, Microsoft & Danone. Connect with Shawn on:
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Re sensemaking with social network analysis data, I find it useful to get participants to make a prediction about the aggregated results, then show the actual aggregated results to them, then get them to compare their prediction with the results. I do this by presenting network data in matrix form (e.g. actors x actors)via a spreadsheet shown with an overhead projector. You can easily add a summary row and column to the matrix, showing how many outward and inward links each actor has (or is expected to have).
I find it is a good way to proceed with almost any survey data. The resulting discussion is usually lively, and can involve questioning both the survey method as well as initial expectations.
rick davies
Thanks Rick. Great ideas regarding sensemaking. Oh BTW, Stuart (Zahmoo techical lead) called me today to tell me that the Zahmoo alpha was ready and we are keen for you to check it out.