Andrew Zatlin is a Silicon Valley economist who has figured out how to forecast official economic data releases more accurately than the institutions that have made it their business for much longer than he has. He uses better data and better algorithms, and his underdog firm is starting to upset the forecasting incumbents in ways the tech industry cherish.
The Wall Street Journal has a catchy headline for that: "Moneyball for Economics." Of course.
Michael Lewis's canonical Moneyball, about the Oakland A's use of statistical modeling to make the most of a tiny payroll, has become perhaps the most overused literary reference of our generation. There's Moneyball for advisors, marketing, job-seekers, startups, judges, finance, lawyers, law, investing, managers, crime, prisons, art, software engineering, fantasy leagues, and of course, government (whether or not it could actually work).
In other words, anything that uses rigorous data analysis to improve upon intuition, conventional wisdom, and traditional logic in making decisions. Which is how all smart industries, businesses, and government entities ought to operate.
Perhaps back in the 1990s it was difficult to understand why, or how, someone could outmaneuver wise elders with vast resources just by futzing with spreadsheets. And I understand that it's an eye-catching headline for what might otherwise just be...a story about spreadsheets.
But really, the novelty's worn off. Now, if you're not "data-driven," using analytics to exploit inefficiencies created by a lack of the right information, you might as well give up and go home. The fact that we still cling to a sports story to explain that principle -- even a great sports story! -- is a troubling indication that America still hasn't quite gotten the message.