Playing Moneyball with your start-up

December 5, 2013
Dan Katcher

Playing moneyball worked for Billy Beane’s Oakland As, but will it work for start-ups? A growing number of investors and entrepreneurs think it might.
Last time, we took a look at some of the business-savvy and psychology that went into LinkedIn’s Series B pitch to Greylock Partners. Today, we focus on the cold, hard math.
In both business and baseball, it all comes down to the data.
First, the baseball: Beane was always skeptical about the ability of conventional wisdom and standard scouting reports to build the best team. So, with the help of some serious statisticians, he found new ways to parse the vast archives of baseball stats to figure out the best predictors of baseball success. Then he went out and found bargain-priced players who matched these profiles. Author Michael Lewis chronicled the success of this strategy in his bestselling 2003 book Moneyball.
Newly re-launched software tool Compass (formerly Startup Compass) applies this concept to the start-up world, letting entrepreneurs compare their growing companies to others on dozens of metrics including user growth, customer acquisition cost, and funding per employee. The tool, the company says, compares your numbers to data from thousands of other companies, letting you see what numbers really matter to enterprises like yours and where your stats fall against these crucial benchmarks.
Entrepreneur-academic Steve Blank (author of the must-read start-up classic The Four Steps to the Epiphany) also argues that this stats-driven baseball management approach is relevant in the business world, according to a recent article by PandoDaily’s Erin Griffith. Blank points to the Innovation Corps, an accelerator for companies arising from National Science Foundation-funded projects. NSF tracking data discovered that start-ups that came through the Innovation Corps program got funded five times as often than those that received grants but no incubator training.
Griffith says:

The data, which includes details like the number of hypotheses tested, the number of customers met with, and the number of “pivots” from 300 teams, proved that the Innovation Corps had figured out what to teach startup founders to get them to the next step of commercialization. It was the first time anyone had gathered quantitative evidence on the methods of accelerators, Blank says.

The numbers showed the “investors” what was working and what wasn’t; the NSF made the incubator program mandatory.
The Moneyball metaphor can also offer a useful way for investors to think about their funding strategy. Beane determined that home runs were less important that getting players on base as much as possible.
“The idea is that not every tech startup needs to have a billion-dollar IPO — a well-negotiated acquisition can yield a decent return,” writes Christina Farr at VentureBeat.
What do you think? Can data replace intuition or is there still room for gut feelings? Let us know in the comments.

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