黑天鹅效应:大智若愚的赢者通吃

黑天鹅效应

“创业投资之所以如此吸引我,很大程度上是因为其反直觉的特性。生活中的大多数时候,我们都在学着躲避风险,只追求那些“好主意”(比如做律师,而不是去做摇滚明星)。对创业公司,我经常需要去关注那些可能是蠢主意,但是也可能是伟大的想法的公司。这些也许不适用于所有人,但是对那些敢于追梦的人来说,上路开始冒险吧。”

——Paul Graham

这些年来我做过不少类型的工作,其中最同直觉相悖的非创业投资莫属。

要想理解创业投资这门生意,有两件事你需要明白:其一是几乎所有的回报都是由很少的几个大赢家带来的;【1】其二是那些最好的主意起初看起来都傻透了。

第一条我起初只是知道而已,但是直到亲身经历后我才真正明白是怎么一回事。我们投资所有公司大概值100亿美元,但是Dropbox和Airbnb这两家的价值就占了总额的四分之三。

那些创业公司中的大赢家赢得是如此彻底,完全颠覆了我们的预期。我不清楚这些预期是先天还是后天形成的,但是不管怎样,我们的确没料到在创业公司的回报上存在着如此大的差距。

这也促成了一系列奇怪的后果。比如单从财务上看,YC的一期孵化班中至多只有一家公司能够真正给我们带来大量收益,其余的都是瞎忙活。我还不太能接收这个事实,一方面是因为它是如此的同直觉相悖,另一方面是因为我们做YC不单单是从金钱的角度去考虑问题,毕竟如果每期我们只投一家公司的话,YC得多寂寞啊。不过话说回来YC也的确是个寂寞的地方。

要想在一个同你的直觉相悖的领域获得成功,你需要在某些时候关掉自己的直觉,就像飞行员在飞过云层时做的一样。【2】你得去做那些你的理智告诉你该做的事,即使它们感觉起来不对。

敢于去持续不断的冒险对我们来说是挺困难的。当你看到一家创业公司并觉得“他们看起来会成”的时候,很难不去投资他们。然而,至少从财务上来说,真正的成功只有一种:这些创业公司要么会成为大赢家,要么就不会,如果是后者的话你投不投都没有太大关系,因为即使他们成功了,也不会对你的收益产生多大影响。反倒是有时候你会碰到一些18、9岁的小伙子,很聪明,但是他们甚至都不知道自己要干嘛,这些人成功的概率似乎很小。但是真正重要的不是他们成功的概率,而是他们成为真正大赢家的概率。任何一个团队要想真正做大机会都小的可怜,但是这帮19岁小伙子真正做大的概率可能会比那些看起来更安全靠谱的团队更高。

创业公司做大的概率并不仅仅是做成的概率的简单累加。要不然你就可以采用广撒网的策略,投资每家你认为可能做成的公司,这样你就肯定不会漏过那几条大鱼。可惜的是抓大鱼要远比这样做困难。你得学会忽略掉眼前的“大象”——这些创业公司做成的概率,集中考虑更为关键但也更不可捉摸的问题:他们能不能做大。

更难的是

之前我就写过类似的内容:如果某个好主意大家都觉得好,那么肯定已经有人做出来了。因此那些最成功的创业者会倾向于去实现那些只有他们觉得好的主意。有时候这些主意可能在别人看来跟疯了差不太远,直到你到了那个点才能看到成效。

在“听起来很蠢”的主意和好主意之间就是机会

Peter Thiel第一次在YC演讲的时候,画了一副维恩图来解释这些。他画了两个相交的圆圈,其中一个叫“看起来挺傻的”,另一个叫“好主意”,两个圆圈交汇的区域,就是创业公司应该发力的地方。

道理很简单,但是用维恩图的形式来表现还是很有启发性的。你会发现两类主意是有交叉的——有些好主意初看就是挺傻的,你还会发现其实那些看起来挺傻的主意中,大部分的确挺傻的。

那些最好的主意可能看起来挺傻,这一事实让“捉大鱼”这一游戏更难玩了。因为这意味着一家创业公司做大的概率越大,初看起来做成的概率反倒会越小。我一直记得自己初次听说Facebook时觉得这个主意简直是废材。一个供大学生浪费时间的网站?几乎完美贴合一个烂点子的特点:1市场小众,2 没有钱赚,3 做的事根本不重要。

苹果和微软也不例外,你完全可以给出“傻逼主意”的判断。【3】

难上加难

等等,还有更坏的情况呢。不光要解决之前提到的这些难题,在解决的过程中你得不到任何你是否做对了的指示,两眼一抹黑。就算你挑到了一条大鱼,不过个三五年你是不知道自己挑到的到底是啥的。

更糟的是,在这个过程中,你能感知到的指标却是非常有误导性的。我们可以详细跟踪Demo Day之后每家创业公司的融资情况,但是我们也清楚这个指标非但没有意义,还会产生很多负作用。我们需要去挑出那些看起来不怎么样的异类,因为那些大鱼能带来一万倍的回报,所以即使我们签下了一千家失败的初创公司,最终还是能拿到10倍的回报。所以如果有一天YC Demo Day之后所有的初创公司都拿到了融资,那只能说我们变得太保守了。

我不清楚现在有多少公司在Demo Day之后能拿到更多融资,我可以不去关心这些,因为我知道一旦开始留意我就会想着优化这个数字,而我知道优化是一个错误的决策。不论好坏,我们是不可能真的去试着投很多看起来太冒险的项目的,我们承受不起。我可以列出那些我清楚的知道是正确的事情,但是依然不会去做。投太多很冒险的公司可能会伤害YC的品牌(至少对那些不懂数学的人),还可能会稀释YC校友会的价值,最令人信服的原因可能是过多的失败会让大家泄气。但是我知道真正的原因是我们就是没法接收回报率天差地别这个事实。

也许我们永远做不到正确处理创业投资中的风险和收益分散问题。我们能做的就是在见创业者后想着“似乎是个不错的团队,但是投资者到底会怎么看这个疯点子呢?”的时候,可以对自己说“管那帮投资人怎么想呢!”这就是我们在见Airbnb时的想法,如果希望看到更多这样的公司的话,我们就应该继续保持这种态度。

注释:

1.并不是说只有那些大赢家才有意义,只是说从金钱角度说这些大赢家才对投资者有意义。因为我们做YC并不单是为了钱,所以我们不单关心那些大赢家。比如我们就很高兴曾经投资了Reddit,虽然没有挣到多少钱,但是Reddit对这个世界产生了很大的影响,而且还让我们认识了Steve Huffman和Alexis Ohanian两位好朋友。

2.没有参照物(比如地平线)时你很容易混淆地心引力和机身的加速力。这意味着当你穿越云层时,很难弄清飞机到底在怎么飞。也许感觉告诉你你正在水平前行,但事实上你的飞机正在螺旋下降。解决办法是无视身体告诉你的信息,完全依照仪器的指示来驾驶。当然说起来容易做起来难,人类是很难做到拒绝身体的暗示的,所以虽然每个飞行员都知道这个问题,每年还是会有很多这类事故。

3.也不是所有大鱼都遵循这个模式。比如Google,它看起来是个坏主意的原因就是已经有太多的搜索引擎,市场上似乎已经没有足够的空间来容纳下一家公司。

I’ve done several types of work over the years but I don’t know another as counterintuitive as startup investing.

The two most important things to understand about startup investing, as a business, are (1) that effectively all the returns are concentrated in a few big winners, and (2) that the best ideas look initially like bad ideas.

The first rule I knew intellectually, but didn’t really grasp till it happened to us. The total value of the companies we’ve funded is around 10 billion, give or take a few. But just two companies, Dropbox and Airbnb, account for about three quarters of it.

In startups, the big winners are big to a degree that violates our expectations about variation. I don’t know whether these expectations are innate or learned, but whatever the cause, we are just not prepared for the 1000x variation in outcomes that one finds in startup investing.

That yields all sorts of strange consequences. For example, in purely financial terms, there is probably at most one company in each YC batch that will have a significant effect on our returns, and the rest are just a cost of doing business.[1]?I haven’t really assimilated that fact, partly because it’s so counterintuitive, and partly because we’re not doing this just for financial reasons; YC would be a pretty lonely place if we only had one company per batch. And yet it’s true.

To succeed in a domain that violates your intuitions, you need to be able to turn them off the way a pilot does when flying through clouds.?[2]?You need to do what you know intellectually to be right, even though it feels wrong.

It’s a constant battle for us. It’s hard to make ourselves take enough risks. When you interview a startup and think “they seem likely to succeed,” it’s hard not to fund them. And yet, financially at least, there is only one kind of success: they’re either going to be one of the really big winners or not, and if not it doesn’t matter whether you fund them, because even if they succeed the effect on your returns will be insignificant. In the same day of interviews you might meet some smart 19 year olds who aren’t even sure what they want to work on. Their chances of succeeding seem small. But again, it’s not their chances of succeeding that matter but their chances of succeeding really big. The probability that any group will succeed really big is microscopically small, but the probability that those 19 year olds will might be higher than that of the other, safer group.

The probability that a startup will make it big is not simply a constant fraction of the probability that they will succeed at all. If it were, you could fund everyone who seemed likely to succeed at all, and you’d get that fraction of big hits. Unfortunately picking winners is harder than that. You have to ignore the elephant in front of you, the likelihood they’ll succeed, and focus instead on the separate and almost invisibly intangible question of whether they’ll succeed really big.

Harder

That’s made harder by the fact that the best startup ideas seem at first like bad ideas. I’ve written about this before: if a good idea were obviously good, someone else would already have done it. So the most successful founders tend to work on ideas that few beside them realize are good. Which is not that far from a description of insanity, till you reach the point where you see results.

The first time Peter Thiel spoke at YC he drew a Venn diagram that illustrates the situation perfectly. He drew two intersecting circles, one labelled “seems like a bad idea” and the other “is a good idea.” The intersection is the sweet spot for startups.

This concept is a simple one and yet seeing it as a Venn diagram is illuminating. It reminds you that there is an intersection—that there are good ideas that seem bad. It also reminds you that the vast majority of ideas that seem bad are bad.

The fact that the best ideas seem like bad ideas makes it even harder to recognize the big winners. It means the probability of a startup making it really big is not merely not a constant fraction of the probability that it will succeed, but that the startups with a high probability of the former will seem to have a disproportionately low probability of the latter.

History tends to get rewritten by big successes, so that in retrospect it seems obvious they were going to make it big. For that reason one of my most valuable memories is how lame Facebook sounded to me when I first heard about it. A site for college students to waste time? It seemed the perfect bad idea: a site (1) for a niche market (2) with no money (3) to do something that didn’t matter.

One could have described Microsoft and Apple in exactly the same terms.?[3]

Harder Still

Wait, it gets worse. You not only have to solve this hard problem, but you have to do it with no indication of whether you’re succeeding. When you pick a big winner, you won’t know it for two years.

Meanwhile, the one thing you?can?measure is dangerously misleading. The one thing we can track precisely is how well the startups in each batch do at fundraising after Demo Day. But we know that’s the wrong metric. There’s no correlation between the percentage of startups that raise money and the metric that does matter financially, whether that batch of startups contains a big winner or not.

Except an inverse one. That’s the scary thing: fundraising is not merely a useless metric, but positively misleading. We’re in a business where we need to pick unpromising-looking outliers, and the huge scale of the successes means we can afford to spread our net very widely. The big winners could generate 10,000x returns. That means for each big winner we could pick a thousand companies that returned nothing and still end up 10x ahead.

If we ever got to the point where 100% of the startups we funded were able to raise money after Demo Day, it would almost certainly mean we were being too conservative.?[4]

It takes a conscious effort not to do that too. After 15 cycles of preparing startups for investors and then watching how they do, I can now look at a group we’re interviewing through Demo Day investors’ eyes. But those are the wrong eyes to look through!

We can afford to take at least 10x as much risk as Demo Day investors. And since risk is usually proportionate to reward, if you can afford to take more risk you should. What would it mean to take 10x more risk than Demo Day investors? We’d have to be willing to fund 10x more startups than they would. Which means that even if we’re generous to ourselves and assume that YC can on average triple a startup’s expected value, we’d be taking the right amount of risk if only 30% of the startups were able to raise significant funding after Demo Day.

I don’t know what fraction of them currently raise more after Demo Day. I deliberately avoid calculating that number, because if you start measuring something you start optimizing it, and I know it’s the wrong thing to optimize.[5]?But the percentage is certainly way over 30%. And frankly the thought of a 30% success rate at fundraising makes my stomach clench. A Demo Day where only 30% of the startups were fundable would be a shambles. Everyone would agree that YC had jumped the shark. We ourselves would feel that YC had jumped the shark. And yet we’d all be wrong.

For better or worse that’s never going to be more than a thought experiment. We could never stand it. How about that for counterintuitive? I can lay out what I know to be the right thing to do, and still not do it. I can make up all sorts of plausible justifications. It would hurt YC’s brand (at least among the innumerate) if we invested in huge numbers of risky startups that flamed out. It might dilute the value of the alumni network. Perhaps most convincingly, it would be demoralizing for us to be up to our chins in failure all the time. But I know the real reason we’re so conservative is that we just haven’t assimilated the fact of 1000x variation in returns.

We’ll probably never be able to bring ourselves to take risks proportionate to the returns in this business. The best we can hope for is that when we interview a group and find ourselves thinking “they seem like good founders, but what are investors going to think of this crazy idea?” we’ll continue to be able to say “who cares what investors think?” That’s what we thought about Airbnb, and if we want to fund more Airbnbs we have to stay good at thinking it.

Notes

[1] I’m not saying that the big winners are all that matters, just that they’re all that matters financially for investors. Since we’re not doing YC mainly for financial reasons, the big winners aren’t all that matters to us. We’re delighted to have funded Reddit, for example. Even though we made comparatively little from it, Reddit has had a big effect on the world, and it introduced us to Steve Huffman and Alexis Ohanian, both of whom have become good friends.

Nor do we push founders to try to become one of the big winners if they don’t want to. We didn’t “swing for the fences” in our own startup (Viaweb, which was acquired for $50 million), and it would feel pretty bogus to press founders to do something we didn’t do. Our rule is that it’s up to the founders. Some want to take over the world, and some just want that first few million. But we invest in so many companies that we don’t have to sweat any one outcome. In fact, we don’t have to sweat whether startups have exits at all. The biggest exits are the only ones that matter financially, and those are guaranteed in the sense that if a company becomes big enough, a market for its shares will inevitably arise. Since the remaining outcomes don’t have a significant effect on returns, it’s cool with us if the founders want to sell early for a small amount, or grow slowly and never sell (i.e. become a so-called lifestyle business), or even shut the company down. We’re sometimes disappointed when a startup we had high hopes for doesn’t do well, but this disappointment is mostly the ordinary variety that anyone feels when that happens.

[2] Without visual cues (e.g. the horizon) you can’t distinguish between gravity and acceleration. Which means if you’re flying through clouds you can’t tell what the attitude of the aircraft is. You could feel like you’re flying straight and level while in fact you’re descending in a spiral. The solution is to ignore what your body is telling you and listen only to your instruments. But it turns out to be very hard to ignore what your body is telling you. Every pilot knows about this?problem?and yet it is still a leading cause of accidents.

[3] Not all big hits follow this pattern though. The reason Google seemed a bad idea was that there were already lots of search engines and there didn’t seem to be room for another.

[4] A startup’s success at fundraising is a function of two things: what they’re selling and how good they are at selling it. And while we can teach startups a lot about how to appeal to investors, even the most convincing pitch can’t sell an idea that investors don’t like. I was genuinely worried that Airbnb, for example, would not be able to raise money after Demo Day. I couldn’t convinceFred Wilson?to fund them. They might not have raised money at all but for the coincidence that Greg Mcadoo, our contact at Sequoia, was one of a handful of VCs who understood the vacation rental business, having spent much of the previous two years investigating it.

[5] I calculated it once for the last batch before a consortium of investors started offering investment automatically to every startup we funded, summer 2010. At the time it was 94% (33 of 35 companies that tried to raise money succeeded, and one didn’t try because they were already profitable). Presumably it’s lower now because of that investment; in the old days it was raise after Demo Day or die.

Thanks?to Sam Altman, Paul Buchheit, Patrick Collison, Jessica Livingston, Geoff Ralston, and Harj Taggar for reading drafts of this.

英文原文:Black Swan Farming
中文基础译文:Paul Graham谈YC的黑天鹅效应:大智若愚的赢者通吃