The company maintains that the tool isn’t meant to take the place of human expertise. “By scoring a startup, we give the first indication of its potential,” says Goodson. “We never expect to completely replace humans.”
Even so, some experts question how useful an automated system like this can truly be.
David Robinson, an associate professor of entrepreneurial finance at Duke University, says that the success of a startup is inherently difficult to predict: “Even if you give me smart people and a good idea and ample funding, there’s still scope for it to fail.”
Others are blunter with their criticism. Entrepreneur and investor Brad Feld says that quantitative predictive models cannot work for innovation or entrepreneurial success because “factors like this dramatically oversimplify the drivers of success (and failure) in entrepreneurial ventures.”
YouNoodle plans to make money by licensing more in-depth information to VCs and other investors. The company also claims to have 150,000 members on its social network.
Josh Lerner, a professor at Harvard Business School, has published research showing that an entrepreneur’s second startup has slightly better odds of succeeding than her first, and that having one successful startup makes a second startup more likely to succeed. “That suggests there are definitely patterns out there that work,” Lerner says. “I’m sure if you were really to punch the data, you’d find there were many other patterns.”
However, Lerner is cautious about relying on prediction tools too much. “So far, it’s hard for me to believe there isn’t an important element of randomness that constitutes a successful entrepreneurial venture,” he says.