Google’s VC arm focuses on science of deal,not art of deal

Google Ventures and its take on investing represent a new formula for the venture capital business,and sceptics say it will never capture the chemistry — or,perhaps,the magic — of Silicon Valley. Would computer algorithms have bankrolled David Packard or Steve Jobs? Foreseen the folly of Pets.com?

The data provide one answer to those questions,at least for now: Since its founding in 2009,Google Ventures has stood out in an industry that,for all its star power,has been dealing its investors a bad hand. In recent years,an investor would have done better with a ho-hum mutual fund that tracks the stock market than with some splashy VC fund. Venture capital funds posted an annual average return of 6.9% from 2002 to 2012,trailing major stock indexes,according to Cambridge Associates.

Google Ventures,like all venture funds,does not publicly reveal returns. But its partners can count on one hand the number of its 170 investments that have failed,though it is too early to know how many will succeed,and it has missed investing in some superstar companies. Its successes include companies that have gone public and start-ups sold to Google,Yahoo,Facebook and Twitter.

Whether Big Data — that label for technology and decision-making that is upending so many businesses — can truly transform the industry that helped spawn it remains to be seen. Few deny that crunching data is increasingly important. But some insist that those old intangibles,like instinct and luck,are still paramount.

Google Ventures was the first major firm to rely heavily on data. Since then,established funds like Kleiner Perkins Caufield & Byers,Sequoia Capital and Y Combinator have followed suit,and new firms like the Ironstone Group and Palo Alto Venture Science have been created to test the strategy.

Google Ventures has $1.5 billion under management — a pittance in the wider world of Google,which made $50 billion in revenue last year. It employs seven people who gather data,analyse it and present the results to the investors. Jerome Friedman,a prominent statistician at Stanford who writes papers with names like “Data Mining,Inference and Prediction”,consults for a few hours a week.

The firm feeds its algorithms data gleaned from academic literature,past experience and due diligence about start-ups and their founders. Even college drop-outs who have never started a company have a quantifiable track record. Google declined to reveal its secret sauce — the algorithms it uses to parse the data. But it has learned a few lessons.

Here’s a riddle from Graham Spencer,a general partner at Google Ventures who oversees its data work: Is it better to invest in someone who started a company in a mediocre year for returns and did well,or started one in a good year with mediocre results?

Most people say the first case. But results from studies show it is the second,because that indicates the founders have a better sense of market timing,Spencer said. Some of the lessons seem obvious. An entrepreneur who has started a successful company is more likely to do it again. But the key,Spencer said,is to be able to understand which elements are most important,as opposed to coming up with black-and-white rules.