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September 14, 2007

Smart enough to be Lucky

Along with confusion about "business intelligence" comes similar uncertainties about "predictive analytics".

Aside from the very entertaining irony of not being able to predict the value of predictive analytics, is this another case of managers and markets just making things harder than they need to be?

The very notion of analyzing one's way to a "correct prediction" is so provocative, it's hard to even make a comment about it that stays on point instead of swinging freely between paranoia and irrational exuberance... But let's look at the enthusiasms, this way:
- everyone wants predictive analytics;
- a subset of everyone wants to pay for it;
- a subset of that payers' group is willing to trust it;
- and a subset of that trusting group is willing to depend on it.

Meanwhile, the difference between what makes predictive analytics successfully marketable versus successfully useful is a gap just as large as between the whopping percentage of enthusiasts versus the miniscule percent of dependents.

Useful? To figure out where you ought to be within that gap, you have to decide whether you need, or not, to bet on change in order to get what you insist on gaining. The more you need to bet on change, the more you're ready to rely on predictive analytics.

But "predictive analytics" is confusing to people because it makes them think of "calculation" which makes them think of "facts" -- and in other words encourages the idea that there's science leading to certainty. The problem is that it isn't the kind of certainty they suspect! The real point of prediction is not to identify certain future outcomes; it is to identify certain future possibilities. If you're only interested in one possibility, you're not looking for analysis, you're looking for accounting.

(Timo Elliott's BI Questions Blog is the most recent location of discussion that provoked these comments.)

Posted by Malcolm Ryder at September 14, 2007 10:16 PM

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