Minding data’s pedigree

Does it seem to you like data analysis is busting out all over the place? It might become another fun game like chess or Chutes and Ladders — so this might be good time to recall an old admonition: Don’t just consume data, mind its pedigree.

Repeating the warning, though, makes you look like a party-pooper. In 2007 at the TDWI conference in Las Vegas, a keynote speaker raised it one morning. Jonathan Koomey — author of Turning Numbers into Knowledge and one of those voices the BI world needs more of — did his best. But I could see the unfolding disaster from my banquet table, as attendees glanced at each other in scorn. When the lights went up, not one person raised a hand with any question or comment.

Now Sex, Drugs, and Body Counts: The Politics of Numbers in Global Crime and Conflict, edited by Peter Andreas and Kelly M. Greenhill, tries it again.

You may wonder what sex, body counts, and politics have to do with data analysis, but try to keep an open mind here. The book promises to let us spit out the usual cud of business intelligence, data quality, and get to the real spice: the politics of data. I can’t wait to read it. For now, see Jack Shafer’s review on Slate.

I won’t be surprised if the book points out how each organization’s core group subtly chooses the stories its data tells. I’ve just finished Art Kleiner’s Who Really Matters, which goes into detail on these groups’ formation and influence, including how they define who’s in, who’s out, and why. It’s the essence of politics.

Though core-group members may not ever lay their smooth palms on any data, data is nonetheless coiffed to suit these people. Through layers of managerial interpretation and re-interpretation, their influence cascades all the way down to tiny decisions about how data’s summarized, what’s measured, how it’s measured, and who measures it.

Like other forms of expression within an organization — speech, email, jargon, attire, hair style, suit or T-shirt — data is part of the politics. Though this has a big effect on decision making, it seems rare that I find it on a BI-event agenda. BI’s scope needs to widen.

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