Why There Aren't More Googles

"The low cost of starting a startup means the average good bet is a riskier one, but most existing VC firms still operate as if they were investing in hardware startups in 1985."

I don't understand the idea behind this sentence. In this context what is a good bet, a company with certain traits or does this refer to a certain type of portfolio strategy, say one that expects most startups to fail and a few to win big? Also, how does the falling cost of startups make the average good bet riskier? Is it because it lowers the barriers for competitors? Or is it because any idiot can say they're doing a startup so it's harder for investors to know which ones are good and which ones are bad? Also, what was investing in hardware startups like in 1985? Are you saying that VCs today evaluate companies with low capital requirements and high risk as if they are capital intensive with low risk? This has multiple implications, and which one(s) was in your head when you wrote this is not entirely clear to me.

EDIT: Rewrote the last few sentences

this article makes the good point that the mba types who are running vc funds are fundamentally ill-suited for identifying and investing in technology startups. paul graham identified this as true for managers of startups as well; and this is a defining feature of yc--investing in technology people vs. investing in mba types who hire programmers. of course, the logical extension is that the people doing the investing themselves should be technology people because they alone can recognize value in the technology sector. whatever value mba vc types did bring to the table, understanding of business management and such, is becoming less relevant with smaller startups and less money to be allocated.

"Why are VCs so conservative? ..."

I just read a fascinating book - Gut Feelings by Gerd Gigerenzer. It's by the guy who did most of the research that Malcolm Gladwell's Blink is based upon. The central thesis was that people have evolved heuristics for decision making that let them quickly make snap decisions more effectively than gathering full information, but a couple chapters were on an interesting corollary: in the absence of hard data on their performance, most people's decision-making heuristic falls back to "Will I be blamed for this decision?"

He provided a bunch of examples from different professions. For example, doctors' decisions often aren't based on solid evidence-based medicine (which is often contradictory), but rather on "Will I be sued if I do or don't perform this treatment?" If you want the doctor's actual opinion, you should ask "If it were your own mother, what would you recommend?" instead of "What would you recommend I do?" - the former shifts the doctor's perspective so that they're thinking "How can I provide the best care?" rather than "Will this person sue me?" A study of UK magistrates found that 92% of their bail decisions could be predicted by the following heuristic: "Did any of the prosecution, police, or previous court recommend bail?" If not, and the defendant commits a crime, it falls into the category of unforeseeable events and the magistrate can't be blamed for it.

A similar effect may be at work with VCs. It's usually impossible to know, even with hindsight, what the opportunity cost of a lost deal was. If a VC turns down the next Google, chances are nothing happens and the company just fizzles. If a VC invests and it goes bust, however, everyone knows. So it pays for the VC to invest like everyone else does: then they can blame any failure on "Well, this was completely unforeseeable: everyone else was sure they'd be a success too." It's the combination of risk aversion, self-interest, and lack of feedback that drives this. If VCs actually had solid conceptual frameworks and good data for evaluating possible opportunities, they could rely on that rather than on their peers' evaluations. (Maybe this explains Sequoia...)

It's great to hear discussion around Umair's thought patterns that add even more depth...

I think what he was trying to say might be a little different from PG's interpretation...

Umair might have said, "every company that had the potential to be economically revolutionary over the last five years sold out [to an acquirer devoid of strategic imagination or the capabilities to discontinuously continue their trajectory]," ergo ending the disruption gravy train.

That is, it's not necessarily "selling out" that blows things up; it's selling out to companies only driven to "increase market share", etc.

Or something like that.

I also think it is really interesting how your view of how the GOOG acquisition/IPO story played out vs. Umair's version:

"If all Larry, Sergey, and Google's investors had wanted to do was to sell out fast to the highest bidder, they could have done so at any time. But they didn't: they chose to revolutionize something that sucked - and so a tsunami of new value was unlocked."

That clearly doesn't square with how you saw it (even though it's an inspiring revision). I unfortunately lost my copy of Battelle's book before I got this far in the story, otherwise I would weigh in.

Clearly PG, Fred, Umair, and other smart ones agree on the need for more, smaller risks and purposeful management.

At any rate, whoever these "new investors" are that are going to fill the void between bottstrapping at Series A are going to make a FORTUNE. And they can't show up soon enough!

The article makes some good points on the effects of funding on startup success, but it doesn't mention one the "other" reasons there aren't more Googles (or Microsofts, or Ebays): huge markets that startups can disrupt so successfully are rare. Facebook, for example, which is probably the biggest startup success story since Google, could be doing everything right but it may never be as big as Google because it's playing in a smaller market.