两年前，我投身风险投资行业，重点关注清洁技术类初创公司。这就像是通过观看八年级学生（译注——相当于中国的初二学生）打篮球来发掘未来的NBA球员：他们还需要很多年的时间来成长，一旦他们真的成长起来，情况就会大不一样。选择的关键之处在于出色的模式识别——早在成功到来之前就找到相应的征兆。

    清洁技术风险投资领域里的同行大多来自于其他领域，通常是半导体或通信行业，他们在模式识别方面的偏好也带着这些行业的烙印。我不禁想问：“要是大家的偏好都错了，该如何是好？”要是我们在选拔苗子的时后看走了眼，该怎么办？

    我曾从事于技术分析工作，因此我希望找到一种基于事实的方法来找到这个问题的答案。于是，我选择了一批成功的、获得风险投资的初创公司，试图找出他们的共同点。我所选择的初创公司：

    • 已经取得了明显的成功。我将“成功”定义为在大型股票交易所上市。我知道，这个标准远远称不上完美，但至少是清晰明确的。

    • 在2000年之后上市。这是为了把那些在1998-99年互联网泡沫时期搭便车上市的能源公司排除在外。

    • 得到了风险投资机构的支持。请注意，绝大多数的清洁技术上市公司实际上都没有得到风险投资。

    到目前为止，我选择了18家公司作为样本：

    I entered the venture capital business two years ago, focusing on cleantech start-ups. It's kind of like picking a future NBA draft by watching eighth graders play basketball: There are many years worth of development to go, and the subjects will look a lot different once they're all grown up. The key is excellent pattern recognition – identifying the antecedents of success long before it happens.

    Most of my fellow cleantech VCs came to this field from some other domain – often semiconductors or telecom – and brought their pattern recognition biases along with them. The question I found myself asking was "What if everyone's biases are wrong?" What if we're picking the wrong eighth graders?

    Coming from a career in the tech analyst business, I wanted to find a fact-based way to answer the question, so I assembled a set of successful VC-backed start-ups and looked for what they had in common. I picked companies that:

    • Had achieved unambiguous success, which I defined as an IPO on a major exchange. That's far from a perfect criterion, I know, but at least it's clear-cut.

    • Went public after 2000, to rule out the boomlet of '98-'99 energy IPOs (when the Internet bubble's rising tide lifted all boats).

    • Were backed by institutional VC. Note that the majority of public cleantech companies have, in fact, not been venture-funded.

    As of today, this sample consists of 18 companies:

    上面这份名单能告诉我们什么？平均来看，这些清洁技术初创公司的好苗子：

    • 通过发行股票筹集了1.22亿美元。其中不包括补贴和债务。融资规模相差很大，但如果把Q-Cells公司和REC公司作为特例排除在外，它们的融资规模都不低于3,000万美元。如果某份新的商业计划提出了比这个数字更低的生命周期资金需求，必须有无懈可击的理由来加以证明。

    • 上市时估值达到9亿美元。估值差别也很大。假如投资者在这些公司上市时持有80%的股份，这些股份将带来5.9倍的投资回报率。

    • 从成立到上市需要8.3年。清洁技术公司从成立到上市大概需要10年时间。但请注意，那些在2010年后上市的公司所需时间较短，平均为6.7年。这类初创公司在成立时或成立后不久就获得了风险投资；相比之下，前者常常在自力更生了数年之后方才得到风险投资。

    • 在1/50的成功率中幸存下来。这18家公司在1995年至2007年间首次获得风险投资。风险投资行业追踪机构风险资源（VentureSource）的资料显示，清洁技术行业在此期间共进行了986次种子融资或首轮融资。毫无疑问，今后将有更多的初创公司获得成功，尤其是最近几年获得了风险投资的初创公司。但到目前为止，得到风险投资支持的初创公司成功率仅为18/986，也就是1.8%。

    如果将某些财务标准考虑在内，我们可以了解到更多情况。平均来看，这些获得成功的清洁技术公司：

    What can we learn from this? The average NBA draft pick of cleantech:

    • Raised $122 million in equity financing, which excludes grants and debt. The distribution is pretty broad, but I'd note that if you remove Q-Cells and REC as special cases, the floor is ~ $30MM. If a new business plan poses a lower lifetime cash requirement, there should be an airtight argument to justify that claim.

    • Went public at a ~ $900 million valuation, also with a broad distribution. If you assumed that investors owned, say, 80% of these companies at the IPO, the lot would have delivered a 5.9x return on capital invested.

    • Took 8.3 years from founding to IPO. If you're signing up to build a cleantech winner, reserve a decade. Note, however, that this elapsed time has shortened for companies that have gone public since 2010, where it averages 6.7 years. Start-ups in this later group received venture financing either right at their founding or soon after it, in contrast to earlier companies which often bootstrapped themselves for years before taking venture capital.

    • Survived a 1-in-50 success rate. These 18 companies received their first venture investment between 1995 and 2007. A quick VentureSource search indicates 986 seed/Series A rounds done in cleantech during that period. While there are doubtless further successes to come, particularly from start-ups funded in the later years, the yield so far is 18 / 986 or a 1.8% of start-ups funded.

    If we include some financial metrics, we learn a bit more. The average cleantech winner also: