Thomas Thurston says we’ve entered “the era of the Moneyball VC,” and no less a name than investment banking pioneer Bill Hambrecht is placing a bet on this Northwest-based data scientist’s formula for picking winners.
Over the last seven years, Thurston (pictured) has been developing algorithms—first at Intel Capital, and later in collaboration with Harvard professor Clayton Christensen, and under his own shingle at Growth Science in Portland, OR—to model markets and business behavior, and thereby predict the success or failure of a given innovation.
Now he is joining Hambrecht-led venture fund Ironstone Group as a partner to try this method in a venture capital industry increasingly open to data-driven approaches.
“It’s sort of this data scientist’s dream to find some amazing patterns and then get to put them out into the real world,” says Thurston, 35.
Since launching Growth Science five years ago, Thurston has used algorithms as the basis of a corporate consulting practice, helping large companies evaluate acquisitions, investments, and strategy shifts. He has also collaborated with Hambrecht—founder of investment bank WR Hambrecht + Co, and leading proponent of the OpenIPO method used most prominently by Google in 2004—who, Thurston says, has used the algorithms to inform his investment decisions. One of these includes a 2010 investment in Palo Alto, CA-based mobile video communications company Tango.
A Hambrecht representative confirmed that Thurston has become a partner in Ironstone, but offered no additional comments. “In a couple of weeks, we’ll have more information about the fund,” the representative tells Xconomy.
Ironstone Group, currently structured as a public Hambrecht holding company, will be focused on seed and early-stage investments up to a “few million dollars,” Thurston says. He would not disclose the amount of capital at the San Francisco-based fund’s disposal.
“We’re not raising $100 million from a pension fund that we have to deploy in three years,” Thurston says. “There’s no unhealthy pressure to do deals. Instead, if we see awesome, disruptive companies, we’ll do a deal.”
The fund has no specific geographic focus—though Thurston says he would love to do more deals in the Northwest, having lived in Oregon on and off since 1994—and will invest in sectors including technology and healthcare.
Thurston joins the chorus of those finding fault with what he describes as the traditional intuition- and personal-relationship-driven approach to VC investing. “That’s wrong 70 to 80 percent of the time,” he says.
And he is not the first to apply the Moneyball moniker in venture capital. In fact, the term is coming up more frequently. (Michael Lewis’ 2003 book Moneyball, and the 2011 Brad Pitt movie by the same name, chronicles Oakland Athletics’ GM Billy Beane’s use of obscure statistics and data analysis to upend the old way of scouting baseball talent.)
In June, Xconomy profiled Correlation Ventures, a $165 million fund based in San Diego using analytics software to decide more quickly whether to co-invest in potential deals. Others pursuing a data-centric approach to investing include Matt Oguz, who last summer announced Palo Alto Venture Science, with a mission to chase the “cognitive biases and hype investing” out of VC with “data-driven analytical models.”
Since Moneyball, data-driven decision making has gained
