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| Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart | 
 enlarge | Author: Ian Ayres
Publisher: Bantam
Category: Book
List Price: $25.00
Buy New: $12.40
You Save: $12.60 (50%)
New (40) Used (28) Collectible (2) from $8.76
Avg. Customer Rating:  71 reviews
Sales Rank: 7820
Media: Hardcover
Edition: 1
Number Of Items: 1
Pages: 272
Shipping Weight (lbs): 1
Dimensions (in): 9.1 x 6.1 x 1.1
ISBN: 0553805401
Dewey Decimal Number: 519.5
EAN: 9780553805406
ASIN: 0553805401
Publication Date: August 28, 2007
Availability: Usually ships in 1-2 business days
Condition: READY TO SHIP!!!!
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Product Description
Why would a casino try and stop you from losing? How can a mathematical formula find your future spouse? Would you know if a statistical analysis blackballed you from a job you wanted?
Today, number crunching affects your life in ways you might never imagine. In this lively and groundbreaking new book, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers. From internet sites like Google and Amazon that know your tastes better than you do, to a physician's diagnosis and your child's education, to boardrooms and government agencies, this new breed of decision makers are calling the shots. And they are delivering staggeringly accurate results. How can a football coach evaluate a player without ever seeing him play? Want to know whether the price of an airline ticket will go up or down before you buy? How can a formula outpredict wine experts in determining the best vintages? Super crunchers have the answers. In this brave new world of equation versus expertise, Ayres shows us the benefits and risks, who loses and who wins, and how super crunching can be used to help, not manipulate us.
Gone are the days of solely relying on intuition to make decisions. No businessperson, consumer, or student who wants to stay ahead of the curve should make another keystroke without reading Super Crunchers.
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| Customer Reviews: Read 66 more reviews...
 Disappointing October 6, 2007
170 out of 205 found this review helpful
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 when implemented as tools where the user of the tool has no knowledge of its limitations, when the model provides suboptimal solutions or what "outliers" are and how to deal with them (although you know immediately when you ARE the outlier and are trapped dealing with a company using a model designed for a population you don't belong to).
This leads us to becoming a nation of people who read off a screen and do what the computer says to do, while turning off our brain. Any wonder you can get outsourced in that scenario? But it must be right -- we Super Crunched it!
 Outstanding Information and Very Interesting! August 30, 2007
68 out of 82 found this review helpful
"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 data to design follow-up programs for complaining fliers. Capital One's approach has also been used to evaluate various charity donation-matching programs, and could also be used to evaluate potential billboard and magazine ads. (Similarly, TiVo is now being used to evaluate various TV ads, using the same approach and measuring the relative frequency with which various ads are fast-forwarded through.)
"Offermatica" software not only automates randomization (format, type of offer) for a number of firms, it also analyzes the responses in real time, dramatically cutting the cost of experiments. Thus, no more waiting for hyper-controlled experiments in universities and laboratories that conclude, ALL OTHER THINGS BEING EQUAL (that never happens), eg. red is preferred to blue.
Randomized tests are also increasingly being used to evaluate various government programs, finding eg. that additional job location assistance more than paid for itself for those receiving unemployment benefits, guiding HeadStart programs to target those most likely to benefit.
"Super Crunchers'" health care examples were the most impressive. Don Berwick's "100,000 lives" campaign saved 122,342 lives in an 18 month period through persuading about 3,000 hospitals representing 75% of all beds to focus on six areas of improvement identified through data analyses. These included antiseptic placement of central line catheters in ICUs, elevating heads and washing the mouths of those on respirators, adoption of the latest heart attack treatments, and rapid response teams to patent beds.
Bottom Line: "Super Crunchers" is an exciting vision of what is already possible!
 The horse versus the locomotive September 1, 2007
44 out of 54 found this review helpful
Ayres argues that decisions in business and government should be made through the creative utilization of data analysis rather than as the result of anecdotal observation. While this may seem to be almost a truism, Ayres begins by demonstrating how older enterprises like the wine industry and professional baseball both rely more on feeling and experience than on the quantitative method. Both also rejected initial efforts to move towards a more data centric model.
The difference in the two approaches is not just a matter of managerial preference according to the author: "We are in a historic moment of horse vs. locomotive competition where intuitive and experiential expertise is losing out time and time again to number crunching." Examples include hedge fund experts who create value by finding empirical correlations between unrelated factors and the consumer lending business where front line loan officer judgement has been replaced by more reliable centralized formulas.
I have long worked in the telecommunications business in which a surprising number of important decisions such as constructing channel line ups or marketing products is based to a large degree on experience or feeling. As we have moved to a more data-based model, we continue to struggle to achieve the balance Ayres describes as comfort with both numbers and ideas.
Ayres discusses some of the institutional and ideological barriers to such a transition. The shift to Direct Instruction in primary schools, for example, pits "the brute force of numbers" against the professional experience of teachers and the philosophical inclinations of education professionals. In the commercial lending business, super crunching (defined simply enough as "statistical analysis that impacts real-world decisions") has effectively shifted discretion from front line employees to centralized experts, has deflated salaries and has created the potential to export jobs overseas.
Overall, this is a useful discussion of the challenge of blending science and art in management. It brings a wide range of examples into play and achieves balance in its conclusions. Aside from the pure reading experience, I left with some definite plans to explore the use of randomized trials in my business in place of focus groups and simple historical analysis.
 CRUNCHING on Empty, CRUNCHING Blind (Apologies to Jackson Browne) November 11, 2007
31 out of 33 found this review helpful
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 analysis.
(4) Today's companies engage in multiple forms of market research by creating and using large databases and large-scale randomized trials.
(5) Many phenomena conform to normal distributions in which 95% of the population will be found within two standard deviations of the mean, the5% balance generally divided evenly in the two tails.
That's it. I just saved you $25.00 U.S. and a half-dozen or more hours learning how a guy from Yale named Ian Ayres collected a bit of information about applied mathematical techniques that have been in practical use for decades, packaged them up, palmed them off as something new, and cooked up the ridiculous name Super Crunching to describe an ostensibly new technological development. Yet "Super Crunching" is nothing more than the author's marketing hype for a couple of standard mathematical methodologies, a creation of nothing from something. There's no new breakthrough here, no new paradigm.
Yes, the anecdotal information about the future prices of wine vintages, Capital One's teaser offerings, and evidence-based medical diagnosis are interesting (hence the two stars rating). The rest, however, is neither prescriptive nor sufficiently critically analytical. Should we go out shopping for a Super Cruncher tomorrow? Should we delight in the increased accuracy of data-driven modeling and prediction, or should we fear the implied manipulation of our desires and the incessant, single-minded drive toward maximum profit at the expense of creativity? Do we really want movies and books to be developed from mathematical models like Epagogix? Do we really want our every keystroke on the Internet to be fodder for market research that manipulates us in response? John Kenneth Galbraith, among others, warned of exogenous, manufactured demand decades ago.
SUPER CRUNCHERS is part business tome, part econometric paean, and part sociology book, but not fully any of the three. No matter how many time the author uses words like "cool" and "humongous" and "amazing," it's still regrettably a "No Sale" even for someone like me who enjoys reading about applied mathematics.
Not impressed September 19, 2007
28 out of 41 found this review helpful
I picked up this book after seeing it in Wired magazine. Being a computer programmer specializing in databases, I figured this was a great book to read.
Right from the introduction I had issues. The first 2 words of the intro are "Orley Ashenfelter", who we learn loves wine and has done statistics on wine. Right away, he's called Orley, then Ashenfelter, then Orley again, then Ashenfelter... When Robert Parker is mentioned, he's just referred to as "Parker" after that. Reading through that section of the book: Orley, Parker, Ashenfelter, Orley, Parker, Ashenfelter, it feels like he's talking about 3 people. The next section of the intro is about Bill James. After finding out his first name, curiously he's only "James" there on out. I guess "Bill" is not as exciting as "Orley"... When you disregard the common writing style of introducing a person by first and last name, then referring to them by last name only after that, it's only going to confuse the reader and remove them from just being able to enjoy the book.
The next thing I noticed is that the terms "Super Crunchers", "Super Crunching", etc are used about once a paragraph. OK. We get it. You want to coin a new word. Really, really, really badly. But while you're spending all this time bashing this word into my head, you're losing me from enjoying your book again. There's no need to have it repeated ad nauseam. It's distracting.
If I wasn't distracted enough, he spends a few pages talking about John Lott, who's also a number cruncher. There's no love lost between the two of them, and the whole section comes across as "Ha ha. I'm writing about you in my book and everyone can see it. Nanny nanny, boo boo." Maybe that's not what was intended, but that's how I came away from that section.
The last reason that made me write this review was that I wish there was more meat in the book. A lot of the time I felt I was watching a review of a movie, not watching the movie itself. (Hopefully that makes sense.) He does get into specific details once in a while, but most of the time it seems like he's talking around the topic, not about it.
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