We noticed you're browsing in private or incognito mode.

To continue reading this article, please exit incognito mode or log in.

Not an Insider? Subscribe now for unlimited access to online articles.

Business Report

An Algorithm to Pick Startup Winners

A venture capital firm throws out intuition and uses computer models to determine investments.

Aldea Pharmaceuticals, a biotechnology startup developing an emergency treatment for alcohol poisoning, seemed like an attractive investment to venture capitalist David Coats. But he didn’t rely on a hunch—he consulted the computer model he’d built.

Investment model: Wenjin Yang, research vice president at Aldea Pharmaceuticals, got funding thanks to software suggesting that his company’s method for speeding up alcohol metabolism was a good investment.

Two weeks and a few phone calls later, he cut the company a $1.25 million check. “A decision like that would have normally taken a minimum of three months,” says Tim Shannon, a partner with Canaan Partners, the firm that had led Aldea’s $7 million fund-raising round.

The $1.25 million was a follow-on investment from Correlation Ventures, which calls itself a “new breed of venture capital firm”—one driven by predictive analytics software built over the last six years by founder Coats and his partner Trevor Kienzle. The effort adds efficiency to the investment process. And for entrepreneurs, it means far faster answers: rejections come in as little time as two days.

This story is part of our September/October 2012 Issue
See the rest of the issue

To run its model, Correlation Ventures, which is based in San Diego and Palo Alto, California, asks startups to submit five basic planning, financial, and legal documents. It enters these into a program similar in function to credit rating software.

A top-ranked score leads to a 30-minute interview with both the startup CEO and the outside venture firm leading the investment, plus a quick legal review and background check. As a co-investor, Correlation Ventures always relies on some vetting by the primary investor.

Correlation Ventures will then often deliver a check from its $165 million fund, closed last November, in less than two weeks. “That’s unheard of in the venture industry,” says Coats.

Once it makes an investment, Correlation backs off and doesn’t take a board seat. That policy is itself data driven: the firm’s analytics show that companies with more than two VCs on the board are less likely to be successful.

What’s not yet clear is whether this system works. Correlation Ventures has so far invested in 26 companies in diverse sectors but says it is too early to report successes or failures.

None of this might have been possible a decade ago. Harvard Business School professor Matthew Rhodes-Kropf, who advises Correlation Ventures and is now an investor in the fund, says the venture capital industry has only recently worked through enough business cycles to look for subtle trends.

There was also no complete, accurate, public set of venture capital data, so Correlation Ventures hustled for it. To build and maintain its database, it partnered with Dow Jones, scoured the Internet, signed nondisclosure agreements with more than 20 venture funds to see their internal statistics, and called hundreds of companies.

While so-called Big Data companies have attracted plenty of investors, the reputation-driven venture capital industry itself has yet to embrace their tools. (There are exceptions, such as Google Ventures, which uses quantitative analysis to help guide decisions.)

Rhodes-Kropf says venture capitalists are good at identifying companies that will have the best chances at success but not as good at predicting which will be the next Facebook. And one finding from Coats’s research is that while top-tier firms do invest in a disproportionate share of “winning” companies, the majority of successful investments are led by firms that don’t even crack the top 50. So it makes logical sense for Correlation Ventures to focus equal time and energy on many companies and co-invest with a diverse set of venture capital firms, he says.

To explain his project, Coats cites Moneyball, the book and movie about how Oakland Athletics general manager Billy Beane rejected the conventional wisdom on evaluating baseball players and built a winning franchise by letting a computer tease out variables that others overlooked. He believes the averages will work out. “We’re not claiming to have a magic crystal ball,” he says. “We’re tilting the odds a little in our favor with each investment.”

Tech Obsessive?
Become an Insider to get the story behind the story — and before anyone else.

Subscribe today
Next in this Business Report
The Future of Work

The future of automation: how businesses are putting algorithms and robots to work.

Want more award-winning journalism? Subscribe to Insider Plus.
  • Insider Plus {! insider.prices.plus !}*

    {! insider.display.menuOptionsLabel !}

    Everything included in Insider Basic, plus the digital magazine, extensive archive, ad-free web experience, and discounts to partner offerings and MIT Technology Review events.

    See details+

    Print + Digital Magazine (6 bi-monthly issues)

    Unlimited online access including all articles, multimedia, and more

    The Download newsletter with top tech stories delivered daily to your inbox

    Technology Review PDF magazine archive, including articles, images, and covers dating back to 1899

    10% Discount to MIT Technology Review events and MIT Press

    Ad-free website experience

You've read of three free articles this month. for unlimited online access. You've read of three free articles this month. for unlimited online access. This is your last free article this month. for unlimited online access. You've read all your free articles this month. for unlimited online access. You've read of three free articles this month. for more, or for unlimited online access. for two more free articles, or for unlimited online access.