In a win for the social sciences, Fast Company has put Nate Silver in the top slot of their 100 Most Creative People in Business list for 2013. Silver is best known as the former baseball stats genius who applied his modeling skills to predicting likely outcomes in political races. His coldly analytical approach proved much more instructive than all of the bluster and narrative of the omnipresent punditry. And his work contains a lot of useful lessons in how to apply data across all sectors. Fast Company's Jon Gertner:
Silver is by no means the first to mine interesting conclusions from big data sets. Nor is he the first to become known for using statistical models as an innovative tool. Depending on how you define it, big data has been around for a while. It was a crucial element in tracking patterns in early epidemics (such as the black plague in London in the 1600s) as well as trends in the U.S. census (beginning in the late 1800s). You might consider the D-Day invasion at Normandy, or even the Apollo lunar missions, as strategic triumphs of complex problem solving and big-data analytics. In the early 1970s, a group of academics published a book called The Limits to Growth that used a fairly sophisticated statistical model to test the sustainability of Earth. (The planet and society are likely doomed, the program concluded.) In his book and in conversation, Silver is quick to point out that the most familiar, and arguably most successful, applications of big data involve National Weather Service predictions and hurricane warnings, which rely on huge data sets and wizardly models and have become increasingly accurate and precise. But other familiar examples abound too. The quants on Wall Street have been helping hedge funds interpret complex trading data for years. Watson, the IBM computer that won at Jeopardy! and is now being applied to medical treatment and financial planning, is a success with a certain kind of big data--"unstructured data," as IBM likes to call it, which describes information formatted as natural language rather than numerical figures. Palantir, a willfully obscure company that crunches big data in the name of national security, is another. Above all are Amazon, Facebook, Google, and Twitter, which stand as the foremost practitioners at making informed conclusions from customer data. By vacuuming up the exhaust from web users, such companies have made extraordinary gains in efficiency, trend-spotting, sales, and--at least in Google's case--research that sometimes translates into societal rather than corporate advantages. "Google is doing a better job predicting the flu than the CDC," observes D.J. Patil, the former chief data scientist at LinkedIn, who now works at venture capital firm Greylock Partners.
Silver is taking on such challenges as a solo practitioner, though he places his work more in the realm of "medium data," involving, say, hundreds of thousands of data points rather than the millions or billions mined by researchers at Google or Amazon. But the size of the information pile matters less than the measure of clarity it can yield. As a kid in East Lansing, Michigan, Silver grew up a sports fanatic but wasn't much of an athlete. "I played soccer up through eighth grade," he tells me. "It was my least worst sport." After earning a bachelor's degree in economics at the University of Chicago, he took a job with a consulting company that left him frustrated and unfulfilled. So he began to work on his PECOTA statistical system in the evenings. The choice of baseball, a sport unusually rich in statistics and measurement, was fortuitous (this abundance is why the sport also lent itself, more famously, to Billy Beane's predictive calculations chronicled in Michael Lewis's book Moneyball). After gaining a reputation for expertly dicing baseball stats, Silver wondered whether he could do a better job of predicting political elections than the Beltway pundits. In 2007, he started sifting through poll data and posted his analyses anonymously, at first on the Daily Kos blog under the name Poblano. (A fan of Mexican food, he once created a website to rate Chicago's burritos.) Eventually Silver revealed himself as the author, set up the independent FiveThirtyEight blog (named after the number of voters in the electoral college), and became a minor celebrity outside the insular world of baseball statistics. A few years later, the editor of The New York Times Magazine ran into Silver on a train platform in Boston and invited him to bring his now high-traffic blog to the Times, which is where he remains, for the moment.
Read the Silver profile and access the full list here.