It’s Science, Not Art, In Google’s Deals
谷歌投資學 是科學非藝術
By Claire Miller

SAN FRANCISCO – A friend calls a friend who knows a guy. A meeting is taken. Wine is drunk. A business plan? Sure, whatever. But how does it feel?
一個朋友打了通電話給一個認識某傢伙的朋友。他們會了面，喝了酒。一項商務計畫？無論是什麼，當然。問題是，感覺如何？

That may be how the venture capital game used to be played here, but it is decidedly not how Google wants to approach the high-stakes business of investing in, say, the next Google. The company’s rising venture capital arm focuses not on the art of the deal, but on the science of the deal. Data is collected, collated, analyzed; only then does the money flow.
這可能是創投遊戲曾經在舊金山進行的方式，谷歌卻不希望以這種方式進行諸如建立下一個谷歌之類的高風險投資。谷歌的新設創投部門著重的不是交易的藝術，而是交易的科學。它收集、整理、分析數據。然後才會把錢放出去。

Skeptics say the new formula will never capture the chemistry – or the magic – of Silicon Valley. Would computer algorithms have bankrolled David Packard or Steve Jobs? Foreseen the folly of Pets.com?
懷疑的人士說，這種新方式斷無可能掌握矽谷的化學或魔術。電腦運算可能為已故惠普公司共同創辦人帕卡德或已故蘋果公司執行長賈伯斯提供資金嗎？有無預見寵物網站的不智？

The data provides one answer, at least for now: Since its founding in 2009, Google Ventures has stood out. In recent years, an investor would have done better with a mediocre mutual fund that tracks the stock market than with some splashy V.C. fund. Venture capital funds posted an annual average return of 6.9 percent from 2002 to 2012, trailing major stock indexes, according to Cambridge Associates.
至少就目前而言，數據提供一個解答。谷歌創投公司自2009年成立以來，一直表現突出。近年來，投資人如果押寶一支專門注意股市動態但表現平平的共同基金，投資報酬必定高過押注某些有口皆碑的創投基金。劍橋聯合研究顧問公司說，2002至2012年，創投基金的報酬率每年平均約6.9%，不及主要的股價指數。

Just a few of Google Ventures’ 170 investments have failed. Still, it is too early to know how many will succeed, and it has missed some superstar companies. Its successes include companies that have gone public, like Home-Away for vacation rentals, and start-ups sold to Google, Yahoo, Facebook and Twitter.
谷歌創投出手的投資共170筆，只有少數幾筆失敗。儘管如此，欲知幾筆會成功還為時太早。還有，谷歌創投曾經錯失一些巨星級的公司。它成功的實例包括部分已經上市的公司，例如假期房屋租賃網站Home-Away，以及一些已經賣給谷歌、雅虎、臉書與推特的新公司。

Few deny that crunching data is important. But some insist that those old intangibles, like instinct and luck, are still paramount.
很少人會否認處理數據很重要。然而部分人士堅決認為，直覺、運氣等不可見的因素還是最重要。

Google Ventures was the first major firm to rely heavily on data. 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.
谷歌創投是第一家高度仰賴數據的大公司。凱鵬創投資金、紅杉資本、Y Combinator等基金已經跟進。鐵礦石集團與帕拉奧圖風險科學等新公司也已相繼成立，實驗這項新策略。

“If you can’t measure and quantify it, how can you hope to start working on a solution?” said Bill Maris, managing partner of Google Ventures. “We have access to the world’s largest data sets you can imagine, our cloud computer infrastructure is the biggest ever. It would be foolish to just go out and make gut investments.”
谷歌創投管理合夥人馬里斯說：「無法衡量並量化，怎能指望開始找出解決方法？我們可以接觸舉世最大的資料庫，我們的雲端電腦基礎設施更是歷來最大的。單憑直覺投資愚不可及。」

Google Ventures has $1.5 billion under management; Google made $50 billion in revenue last year.
谷歌創投管理15億美元資金。谷歌去年營收約為500億美元。

Along the way, Google has learned a few lessons. For example, 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?
谷歌一路上學到了些經驗。例如，究竟該投資在平凡時期設立公司但表現不錯的人，還是在好年冬創立公司卻表現平平的人？

Most people say the first case. But studies show it is the second, because that indicates the founders have a better sense of market timing, according to Google Ventures partner Graham Spencer.
谷歌創投合夥人史賓塞說，多數人選擇前者，然而研究顯示後者才是上策，因為它顯示創辦人比較擅長掌握市場時機。

Google’s algorithms have shown that while location matters, for instance, past success is much more important. But investing only in experienced entrepreneurs would have meant overlooking Mark Zuckerberg, as well as Larry Page and Sergey Brin.
谷歌的運算顯示，位置誠然重要，以往的成功卻更重要。只押寶有經驗的創業家意味會遺漏祖克柏、佩吉、布林等人。

Google says intuition and chemistry still play a crucial role, and can even override the data.
谷歌說，直覺與化學仍然扮演重要角色，甚至可能凌駕數據。

“We would never make an investment in a founder we thought was a jerk, even if all the data said this is an investment you should make,” Mr. Maris said.
馬里斯說：「即使所有數據全都顯示應該投資，我們也絕不會押注在我們認為是個討厭鬼的創辦人身上。」

Other firms are at further ends of the spectrum. For some, like Kleiner and Sequoia, data-driven venture capital means simply tracking how many times a startup is mentioned on Twitter, or where it ranks in the App Store. For those like Ironstone, it means relying almost solely on algorithms. Ironstone’s algorithms have produced conclusions that are heretical to traditional venture capitalists. They say, for instance, that a start-up’s founding team has only 12 percent predictive value, even though most investors rank that as one of the most important factors.
另有些公司更極端。對凱鵬創投、紅杉資本等公司而言，以數據為本的創投意味，只留意人們在推特提到一家新公司幾次或它在應用程式商店上的排名。對鐵礦石等公司來說，它意味幾乎只依賴運算。鐵礦石的運算結論被傳統創投資本家視為異端。例如，他們說，一家新公司的創辦團隊只有12%的預測價值，而多數投資人卻視它為最重要的因素之一。

Thomas Thurston of Growth Science, which uses data science to make predictions for companies, welcomes the uproar.
成長科學公司以數據學預測一家公司的表現，該公司的屠斯頓對批評聲浪表示歡迎。

“Some people fear a world where algorithms can do this,” he said. “Usually entrepreneurs are worried their flash of genius can’t be captured, and the investors are very afraid that this will somehow diminish their value. ‘If an algorithm can do better at picking than me, will that put me out of a job?’ ”
他說：「有些人害怕面對運算可以做到這一點的世界。創業家往往擔心他們的才幹火花稍縱即逝，投資人則非常擔心這可能減損他們的價值。『如果運算法選擇的本領勝過我，我會不會失業？』」

原文參照：
http://www.nytimes.com/2013/06/24/technology/venture-capital-blends-more-data-crunching-into-choice-of-targets.html

2013-07-09聯合報/G9版/UNITEDDAILYNEWS 陳世欽譯 原文參見紐時週報七版左