Data Ethos -

Examing competitive advantage and the associated ethical challenges of the Big Data Revolution.

Sunday, October 31, 2010

Squirming: its Not Just for Halloween Anymore.


Remember those nameless horror films of your adolescence where three kids whip out a Ouija board for fun. With the onset of creepy music, the films protagonists eye’s widen as the planchette spells out “HE’S IN THE HOUSE AND IS GOING TO EAT YOUR BRAINS!”

If directed effectively, the audience will squirm in their seats and implore the actors to “Get the hell out of there!” Its that feeling, the one that tells you something isn’t right, and that whispers in your ear in a raspy voice “Get out while you can!”

These are the feelings I sometimes feel as I watch the Data Revolution unfold, and that I have labeled the Squirm Factor. As we unleash tools to help us derive insight and value from gargantuan data sets, I expect there to be a corollary rise in Squirm Factor amongst big data stakeholders.

In a recent blog post Edd Dumbill mentioned the Squirm Factor, and whether it could, or should, be codified. Given the vast spectrum of people involved in the Data Sphere, and individual Squirm Tolerances, it may impossible to arrive at empirical measures of “Squirmishness”.

However, we can look for visceral clues to recognize the Squirm Factor in ourselves and in others that might help us build a foundation for “data culture”, or what is and isn’t acceptable for this emerging community. Here are a few examples to start the discussion:

1. The Alien Probe Trade Off Squirm (Consumer) - aka the mortgage application. If you have been through this you’ll have the muscle memory vaguely reminiscent of being microscopically examined by faceless banking creatures. You will, however, endure the procedure, in order to obtain the funding for your new dwelling. Later hypnosis may reveal the details of your “encounter”, but do you really want to remember?

2. The Algorithm Development for Energy Trader Squirm (Data Scientist). This is squirm produced when a data scientist creates a sublime algorithm generating profit maximization trading schemes, only to hear the energy trader say “We like to create a monopoly, then induce volatility”. How can something so beautifully derived and crafted be twisted into something so desperately evil?

3. The “We’ve Tapped into Something Dark and Supernatural Squirm” (Management). This is the squirm felt by a business leader, generally an MBA, when presented with a magical analytic treasure trove by his data science Magi. However, he doesn’t understand or trust his Magi’s mysterious powers. And as a my former colleague Eric Bonabeau said, “Managers would rather live with a problem they cannot solve than accept a solution they don’t understand.”

When it comes to data, whether you are a consumer, data scientist or management, what makes YOU squirm? Go ahead, scare us all, please share you data Squirm Factors in the comments section.

Then you can return to your Ouija Board just in time for Halloween. Remember, its just a silly game. Really. Just ignore that man in the hockey mask...........

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