Super Crunchers: Why Thinking-By-Numbers is the New Way To Be Smart

An international sensation—and still the talk of the relevant blogosphere—this Wall Street Journal and New York Times business bestseller examines the “power” in numbers. Today more than ever, number crunching affects your life in ways you might not even imagine. Intuition and experience are no longer enough to make the grade. In order to succeed—even survive—in our data-based world, you need to become statistically literate.

Cutting-edge organizations are already crunching increasingly larger databases to find the unseen connections among seemingly unconnected things to predict human behavior with staggeringly accurate results. From Internet sites like Google and Amazon that use filters to keep track of your tastes and your purchasing history, to insurance companies and government agencies that every day make decisions affecting your life, the brave new world of the super crunchers is happening right now. No one who wants to stay ahead of the curve should make another keystroke without reading Ian Ayres’s engrossing and enlightening book.

Customer Reviews:

CRUNCHING on Empty, CRUNCHING Blind (Apologies to Jackson Browne)

By Steve Koss - November 11, 2007

Is it a new brand of cereal? Or maybe it's a granola bar, or a chunky peanut butter spread? Then again, could it be the latest infomercial exercise device designed to give you the six pack abs you've always dreamed of but know in your heart of hearts you'll never achieve? Actually, it's a book - the title a product of the very methods the book describes. Here's what SUPER CRUNCHERS says.

(1) Mathematical regression models generated from large datasets often generate better predictions than human experts, and they provide supporting information on the predictive weight and reliability of each explanatory variable.
(2) Well-crafted experiments using randomized trials and control groups provide good market research and behavioral analysis results.
(3) Technological advances - the Internet, massive data storage devices, rapid computation, broadband telecommunication - are making it possible to share more sources of information and create ever-larger databases for... read more

Disappointing

By William Addington "William Addington" - October 6, 2007

I read a blurb on this book in the Economist and bought it for that reason. When I read it however, it failed to deliver. It is similar to the Tom Peter's "Search of Excellence" type book with anecdotal stories with little substance. It is overgeneralized and overhypes the models it discusses. The models Ayres discusses are also NOT NEW. I personnally have been creating these types of system for nearly 30 years. What has changed over the years, of course, is greater accessibility of data and a greater capacity to process that data economically. But we still struggle with quality of data issues and appropriateness of model issues -- especially when the models begin to be used by people other than the model creators. The book glosses over this, only providing an example of how Choicepoint used a poor matching algorithm when eliminating felons from Florida's voting roles and even then the author minimizes the problem.

There is no discussion of how these models become abused... read more

Outstanding Information and Very Interesting!

By Loyd E. Eskildson "Pragmatist" - August 30, 2007

"Super Crunchers" provides a very readable summary of what can be done to improve performance using the incredible volumes of data accumulated in business, government, health care, and education. Why now? One reason is that the massive amounts of data now available make randomization (essential to valid conclusions) much more achievable than in the past; the other is the low and continually falling costs of computers and storage media.

The bulk of Ayres' work consists of examples (names both companies and the software involved) within each of the sectors previously mentioned. Capital One has been running randomized tests since at least 1995 - tests include page layout, and type and size of offers. Google uses data analysis to fuel its web accelerator (uses your past browsing history to predict pages to be called up next), Wal-Mart's analysis of responses to various employment questions is used to rank potential employees, and Continental Airlines follows up on its own... read more