Can Big Data Pick a Winning Startup?


Can you predict whether a startup will collapse or succeed? Wall Street and Silicon Valley would certainly like to think so. According to Wired, a handful of independent entrepreneurs and big companies are using data analytics to better forecast whether that hot startup will become the next Uber, or merely the next

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Thomas Thurston, who runs a research firm called Growth Science, told the magazine that his algorithmic simulations accurately predict 88 percent of the time whether a startup will implode within the next five years. He also claims a 66 percent success rate when it comes to guessing which startups will survive during that same time period.

Despite Thurston’s reliance on algorithms, his model still requires a certain amount of old-fashioned intuition—a human being needs to decide whether a company qualifies as a fast follower or a first mover, for example—but his team is working on making everything as scientific as possible. He’s also not the only one working on a startup-prediction project: Google Ventures and other investment funds rely on their own formulas.

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Google Ventures’ track record is pretty impressive, with investments in Cloudera, Uber, Nest (eventually acquired by Google), and other name-brand companies; but given the firm’s secrecy, it’s difficult to tell how many of those investments hinged to whatever degree on a predictive algorithm. California-based Correlation Ventures, another fund, boasts of making “algorithm-driven investments” in startups, which often results in funding companies well outside of the traditional tech-power corridors of Silicon Valley and Silicon Alley.

And no matter how advanced the math becomes, at least a subset of investors and advisors will always argue that their gut is superior to an algorithm when it comes to choosing startups in which to invest.

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