I almost couldn't get myself to purchase a book called Super Crunchers. The thinking was that such a title is more indicative of a Fox News Channel special investigation piece than a book on business intelligence (BI). Rupert Murdoch the new BI guru? It just doesn't seem right. Fortunately, you can't always judge a book by its title. Turns out there's a lot to like about Super Crunchers - and lots of lessons for BI, including several noted in previous OpenBI Forums. Turns out as well that the author eats his own dog food, with even the Foxian title the result of "super crunching."If Competing on Analytics offers a solid foundation and conceptual framework for analytics in business and Smart (Enough) Systems provides painstaking detail on how to use analytics, decision rules and optimization techniques to automate routine decisions, Super Crunchers provides breadth of exposure to the current state of analytics in business, government, education and health care, offering incisive commentary on both developments and direction. Indeed, a dilemma for reviewers of Super Crunchers is deciding just what to exclude from consideration.

A law professor and econometrician at Yale, Super Crunchers author Ian Ayres begins the discussion of predictive analytics with, appropriately enough, a modeling "application" developed by an economist that illustrates many of the issues surrounding super crunching. Orley Ashenfelter, Princeton professor and wine aficionado looking to optimize his selection of Bordeaux for purchase, developed a regression model to determine characteristics associated with vintage auction prices. His final equation reduced to three factors related to the growing season in France: winter rainfall, average temperature and harvest rainfall. The beauty - and the source of controversy - with this approach is that it allows Ashenfelter to predict the future quality of a vintage year before the wine is sold. And his predictions, published in a semiannual newsletter, have proven quite accurate - thus roiling the wine critics' community. One expert decried Ashenfelter's work as "rather like a movie critic who never goes to see the movie but tells you how good it is based on the actors and director." Fortunately, many who at first scoff at such unsophistication grudgingly relent to co-existence in time. The theme of predictive models versus resistant expert opinion or intuition is a recurring one in Super Crunchers.

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