Reaction Wheel

Twice in the past week I have had pre-product entrepreneurs tell me that they were raising seed rounds at an approximately $10mm pre-money. In both cases I had to pass, despite the merit of the management teams. Both companies told me that they have other early-stage investors ready to fill their rounds, and I’m glad. I am generally of the opinion that if an entrepreneur can get a better valuation while still getting value-add investors, then they should.

Plenty has been written recently by venture capitalists about venture capital to help entrepreneurs. Not much has been written to help newer venture capitalists. I think, in a way, this is because VCs don’t care so much if those new to the industry succeed or not. If a new angel loses his shirt, well, one less competitor for me down the line.

I don’t believe that, though. I think we need more investors. But smart ones, investors who make some money on their investments and so feel confident reinvesting it in a new round of entrepreneurs. Investors, like everyone else, get smarter and more helpful the more experience they have. Smarter investors is better for the ecosystem.

So, valuation.

Valuation in venture capital is tough. The amount of uncertainty between investment and exit is immense. But that doesn’t mean that you shouldn’t try to pay the right price. Valuing a startup correctly means estimating risk, not contemplating the unknowable. The idea that was briefly tossed around that valuation doesn’t matter because a startup either goes big or dies is wrong. Ludicrous, in fact. There’s a range of outcomes for every fund. The cliche that out of each ten investments, two are winners, three are failures and five go sideways shows this. The two winners determine whether the fund is an overall winner or loser, but how sideways the five go determines whether it’s a good return or a great return. What happens to the second tier of investments matters.  And, for the math challenged, even if startup returns were binary, when you invest in many of them you get a binomial distribution, so expected value matters.

I look at valuation this way. For every company,

• I think about what the expected exit would be if the entrepreneurs were right: if they are right about the problem, about what their customers want, about their ability to execute, right about everything. 
• I figure out how much dilution I expect before the exit.
• I decide how likely it is they are right and multiply by the expected exit to get an expected value.
• I divide by three, because I’d like my investments as a whole to return 3x*. 

This is the post-money valuation.

An example. Company X is an amazing data-driven adtech company. It’s going to disrupt some existing companies and if it does it should sell for $400mm in five years. I think, given the risks, that there’s a one in ten chance they will succeed.

But I know they will need to raise a Series A to commercialize the product once it’s ready, and a Series B to ramp sales once they have product-market fit, and a Series C to expand the product line. The Series A will be 33% of the company, the Series B will be 25%, and the Series C 20%. My stake will be diluted down to 40% of my original ownership.

So my post-money expected value of the company is $400mm * 10% * 40% = $16mm. I would be looking for a post-money of $5mm. If the company is raising $1mm in the seed round, the pre-money valuation would be $4mm.

You can see the difficulty in the $10mm pre-money. If the company is raising, say, $2mm at a $10mm pre, then the expected exit value would have to be $12mm/(10% * 40%) * 3 = $900mm.

Billion dollar exits are the sine qua non of the venture business. But they are rare. Rarer than you think.

I made a list off the top of my head of some 125 business-to-business advertising exits. I may be missing some obvious ones, but there were only a handful of $500mm plus exits in the last ten years, even fewer billion dollar ones (M&A exits, I didn’t count IPOs, so I probably undercounted by one or two.) Here are the $500 million and up exits I have.

Of the 125 exits, five were more than a billion, seven were between $500 million and a billion, 20 were between $200 million and $500 million, and 15 were between $100 million and $200 million. The rest were sub-$100 million. Remember, these were all exits–companies that didn’t make it weren’t counted. There’s also a bias in the list because I am more aware of the large exits; I would be surprised if I missed too many billion dollar exits but I am sure I missed many $10mm exits. Also note that only a couple of the billion dollar exits here were as straightforward as my model: aQuantive was built through acquisition (and thus had substantially more dilution), Doubleclick had gone through several owners including the public markets, etc.

In fact, all else being equal (a priori, that is) billion dollar exits returned less overall than $500mm-$1bn exits, because there were fewer of them. Exits between $200mm and $500mm probably returned slightly more than $500mm-$1bn exits (also because there were more of them). The $100mm-$200mm range and less than $100mm range each return less than the $200mm-$500mm range**. Here’s my estimate of what each of these ranges returned.

The sweet spot in adtech, the “average” expected exit value, seems to be around $400mm.

Every industry is different, you need to know yours. Make a list of exits over the last ten years, all exits not just the good ones. Then try and figure out how many companies were funded in your industry. This will inform your expected exit values in the success case as well as help you decide what percentage of funded firms get to an exit. Conditions change all the time, of course, but looking at the last ten years will probably keep you reasonably conservative.

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* I asked an engineer friend of mine how comfortable he is being in the buildings he helped design. “Pretty comfortable”, he said. “You never worry?” I asked. “Look”, he said, “There’s a lot of math and experience behind choosing exactly how much steel and concrete the building needs to bear its load. I do the work carefully, run the calculations twice and make absolutely sure the answer I am getting is the right one. Then I multiply by three.” [Edit: For those for whom anecdote is not analysis, I’ll point out that a 25% IRR compounded annually for five years is 3x].

** The list I made is up here. Click on the headers to sort. I think all of the #N/As are sub $50mm exits except the two bolded ones, which I think are ~$200mm exits. [Edit: Wow, the sorting on the linked table was all screwy. Sorry. Fixed it.]