Why VCs are obsessed with size
“How big do you think this can get, and where do you see yourself in terms of size in 5 years?” If you’ve spoken with a VC before, you have likely heard these questions uttered by every one of them, probably several times. If you haven’t spoken to a VC before, you should make sure to give these questions a lot of thought before meeting them.
He first started his career with an internship at Goldman Sachs in the US, and then worked as a strategy consultant in Kaiser Associates' London office. Prior to obtaining his MBA from INSEAD, he spent a year as an associate in Athene Capital.
“How big do you think this can get, and where do you see yourself in terms of size in 5 years?” If you’ve spoken with a VC before, you have likely heard these questions uttered by every one of them, probably several times. If you haven’t spoken to a VC before, you should make sure to give these questions a lot of thought before meeting them. And if you are wondering whether you should try raising money from a VC, read on for a better understanding of what sort of answers they are looking for.
Most companies have a traditional business model: they have developed a product or a service, which they sell for more than it costs them. They make a margin, generate a profit, reinvest this into the next product or service (or distribute it to the owners of the business), rinse repeat. However, these are not the businesses that VCs invest in. Or should I say, this is not enough for a VC to base its investment on.
VCs invest in hyper growth and scalability. The reason almost every VC backed business is tech-enabled (read: most reliant on software in one form or another) is not because they have a weird fascination for innovation, although having a weird fascination for innovation is probably a trait found in most VCs. It is because software is infinitely scalable. Once you have paid for the cost of development, there is virtually no additional cost, other than the marginal costs of maintenance and customer support, whether you sell one ‘unit’ or thousands. This, in turn, enables hyper growth, once the miraculous ‘product market fit’ has been found.
VCs invest in hyper growth and scalability.
However, what this doesn’t mention is how risky investing in this type of business is. Most businesses will run out of money before they find that market product fit. You can look at it in two ways.
Number one: barriers to entry in trying to create a software product are really low. Many will try, competition will be fierce, and the likelihood that you are the only one with that genius idea is almost zero. Think of it as many candidates entering the funnel.
Number two: it is really hard to convince someone to give you money for something. People will only fork out cash for something that satisfies one of their Maslow pyramid needs. Even then, many of the web 2.0 economy consumers have become used to receiving services for free. Think of it as few making it out of the funnel.
Succees in a big way
So with that in mind, one has to realize that many VC investments FAIL. Zip, nada, the money is gone. But a VC has its own ‘customers’, the LPs who lent money as an investment, typically over a period of 5+5 years, and who expect a return on the money they’ve been investing. And therefore, to succeed, the VC needs those investments which succeed, to succeed in a big way. To any normal investor, a project which aims to get twice or three times the money back would seem attractive, but not to a VC; not with the level of risk involved in its investments. This works if you are reasonably convinced that the investment will deliver according to plan. But remember, most of the VCs’ investment will lose money because of how hard it is to make it out of that funnel. Therefore, the ones that succeed need to pay for the ones that have failed, and more, to ensure that the fund overall earns money.
A VC, to be considered successful, needs to return more than 2-3 times the initial fund. So now let’s do a quick back of the envelope calculation on how to get there, when most of your investments fail. For simplicity’s sake, let’s imagine a virtual $100m fund, making 100 investments of 1m. The table below compares the final money multiple, how many times the sum invested was returned, depending on the portfolio success mix.
VC Portfolio 1 would be considered a failure. Over the life of the fund (10 years), the VC was only able to return 1.4x. As a comparison, $100m invested in a conservative investment plan returning 5% per year would be worth $163m (i.e. 1.6x) by then, taking compounding into account.
Most VCs would be very happy with VC Portfolio 2, returning 2.8x, with 20% of its investment performing well and 20% performing according to plan. Remember all these investments are made with a plan to deliver great returns.
VC Portfolio 3 however is closer to a real, successful fund. Most investments have failed, few have delivered, but 2 out of the 100 have delivered exponentially and made up for all the failures. As a result, the overall fund returns 2.6x and can be considered successful.
VC will look for the ones with a plan to deliver 10x, ideally more.
So going back to our original question “How big do you think this can get, and where do you see yourself in terms of size in 5 years?”, you can now see what type of answer the VC is looking for. Plenty of businesses can generate 3x and would find themselves willing investors. But a VC will look for the ones with a plan to deliver 10x, ideally more. He knows that most will fail, and yet, if he is able to find the few that perform beyond expectations, he will generate attractive returns for his backers.
Examples of VCs portfolio
|Non VC Portfolio
|VC Portfolio 1
|VC Portfolio 2
|VC Portfolio 3
|The business failed and lost the money
|The business failed but the investor at least managed to get its money out
|The company grew a lot but not deliver up initial expectations
|The company was a great success, as hoped for in the investment thesis
|The company outperformed and delivered incredible returns
|Money Multiple Returned
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