Personal Branding Blog – Dan Schawbel

Today, I spoke with Ian Ayres, who is an author and law professor at Yale. He shares insights as to why you really need to learn about statistics and how companies are using these so-called “Supercrunchers” to conduct business.

Why do we need to understand numbers to succeed and survive in our world? Should every college student have to take a statistics class before they graduate?

Every college student should definitely take statistics before graduation. I’d even think we should mandate it in high school. Only about 2% of college students use calculus in their subsequent lives. But 100% of college graduates can use statistics to understand the meaning of political polls or of medical studies or to understand advice about how to invest for retirement.

There’s some progress here. I’m heartened to see that many Algebra and Pre-Algebra text books are sneaking in statistics (often by brute force). But it is an afterthought and not clear that teachers actually teach these sections or those students come away knowing how to compute for example a test of statistical significance in the difference of two means.

Which companies are looking at databases to find unseen connections to predict human behavior? Do you know any specific people who are “stand-out” number crunchers?

Virtually every Fortune 500 company now is doing some kind of data mining. The difference is in the quality of the number crunching that is being done. The book “Competing on Analytics” does a good job of giving an idea of some of the best companies (including Harahs for example). A lot of companies are stuck at just doing descriptive statistics. They are only pulling cross tabs and using dashboards. The next level up is doing more sophisticated scoring. The next phase is to improve quality of scoring prediction and pay more attention to the precision of the predictions. One of the coolest things about regressions is that the same technique that makes a prediction, simultaneously tells you the precision of that prediction.

What is a “super cruncher” and how do we become one? How does that differ from an “intuitivist”?

Super crunchers are using traditional tools of regression and randomization but they are applying them to mammoth datasets and they are having impacts on a scale that we’ve never seen before. So size, speed and scale are the hallmarks of super crunching. Super crunchers still use their intuitions, but they are willing to put their intuitions to the test. To become a super cruncher, you need to be trained in the techniques of randomization and regression. If your organization is not using BOTH of these techniques, you’re presumptively screwing up.

Can you explain how the “super cruncher” phenomenon will impact the workplace, recruitment and how we manage our personal brands?

Super Crunching tends to take discretion away from line employees. The front-line tasks tend to become more scripted.

Ian, please list the top 5 skills that you would recommend we all work on.

You need to learn how to:

• 1) generate testable hypotheses
• 2) run randomized tests
• 3) run regressions
• 4) analyze the results of the regressions and randomized trials
• 5) use the results to generate more testable hypotheses

I’d recommend starting with running randomized tests. The new chapter that’s been added to the paperback editions, talks about free software that Microsoft and Google are giving away to help you start regressing and randomizing. It’s really easy and free to run randomized tests on your own websites. Finally, checkout my prediction tools if you want to start generating some predictions about things in your own life.

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Ian Ayres is a lawyer and an economist. He is the William K. Townsend Professor at Yale Law School and a Professor at Yale’s School of Management.Professor Ayres is a regular commentator on public radio’s Marketplace and a columnist for Forbes magazine. His research has been featured on PrimeTime Live, Oprah and Good Morning America and in Time and Vogue magazines. Professor Ayres has published 9 books and over 100 articles on a wide range of topics. In 2007, he published Super Crunchers: Why Thinking-By-Numbers is the New Way to be Smart.