99 VC Problems But a Batch Ain’t 1 (2024)

99 VC Problems But a Batch Ain’t 1 (1)

Abstract: Most VC funds are far too concentrated in a small number (<20–40) of companies. The industry would be better served by doubling or tripling the average # of investments in a portfolio, particularly for early-stage investors where startup attrition is even greater. If unicorns happen only 1–2% of the time, it logically follows that portfolio size should include a minimum of 50–100+ companies in order to have a reasonable shot at capturing these elusive and mythical creatures.

Like startups, most venture capital firms fail — at least in terms of returns.

Historically, 1/2 of all VC funds fail to return 1X initial capital. Another 1/4 fail to beat the (much more liquid) public market. Of the remaining “top-quartile” VCs that actually do perform, most can’t do it consistently across multiple funds. Yet we still view most VCs as pseudo-divine interpreters — powerful wizards who peer into their palantir to see the future, tell us what new companies or trends will disrupt existing incumbents, and write big checks to amazing founders who create the next Insanely Great startup.

Except most of the time this is just a big bunch of baloney, and they don’t.

For the few firms that by luck or skill get those predictions right, a strategy of very big bets on a very small # of companies can pay off handsomely. In fact, the more concentrated the portfolio, the better the returns will be for investors, assuming the portfolio still contains one or more big winners.

However in its most extreme form, this strategy devolves into betting all one’s money on a single turn of the roulette wheel, or buying a single ticket in a lottery. Surely winners of such games of chance should not be viewed as financial geniuses. Yet we still worship concentrated portfolio strategy as an industry best practice — when clearly, longitudinal performance of the venture capital asset class has yielded less than stellar results in the average case, and only consistent, frequent success for very few (~5–10%).

In the past five years of investing in over 1,000 companies at 500 Startups, we have found a few companies in our portfolios perform extremely well, but they occur very infrequently. Most of our investments (likely 50-80%) don’t ever get to any kind of exit, or return less than 1X invested capital. Perhaps 15–25% of portfolio companies succeed and result in a small exit of 2–5X. Another 5–10% might attain valuations of over $100M (which we call “centaurs”) and achieve exits of 10–20X. And if we’re lucky, 1–2% attain valuations of over $1B ( “unicorns”) and result in very large returns of 50X or more invested capital. In summary: most investments fail, a few work out ok, and a very tiny few succeed beyond our wildest dreams.

While these numbers might be unique to our own experience and process of investing at 500 Startups, most people in the industry would not disagree that large outcomes happen infrequently, or that a few big investments tend to dominate returns (re: Peter Thiel / power laws, etc). If this is true, then a more prudent VC investment strategy would be to construct portfolio size based on # of investments required to generate at least one big outcome (or ~3–5 large outcomes, to be on the statistical safe side).

Currently most larger VC funds ($200M+) doing Series A/B investments rarely invest in over 30–40 companies, and most micro-funds (<$100M) doing Seed & Series A investments rarely invest in over 50–75 companies.

We believe the current VC fund industry average portfolio construction is inherently & critically flawed, and undersized by a factor of 2–5X. We believe a more rational # of investments is ~50–100 companies for later-stage funds, and at least ~100–200 companies for early-stage funds.

Let’s presume that even for the average khaki-wearing VC — tall, smart, good-looking, went to all the right schools, and likely very white & male — that their portfolio distribution looks something like this

99 VC Problems But a Batch Ain’t 1 (4)

Looks pretty doable, right? With only 7% big wins, a VC fund could theoretically return almost 2.5X — hey, we should all become VCs!

But given the frequency of centaurs & unicorns (5% and 2% respectively in this model), let’s look at three portfolio sizes of 15, 30, and 100 companies.

99 VC Problems But a Batch Ain’t 1 (5)
99 VC Problems But a Batch Ain’t 1 (6)

What is excruciatingly clear from this model is that returns are dramatically based on the # and % of unicorns (& possibly also centaurs) that occur in a portfolio. If portfolio size is too small, you risk finding ZERO big wins.

In the model above, if we assume Unicorns occur only 2% of the time, then with portfolio size of less than 50, you might not find any. In fact, given the drama that occurs with many startups and VC funds, you might come to the conclusion that you really don’t feel statistically “safe” without constructing a portfolio that gives you a decent shot at 3–5 unicorns. So unless you think you’re going to pick unicorns at a rate of 5–10 % instead of the 1–2% industry norm, you are essentially GAMBLING with LP money by selecting a portfolio size of less than 50–100 companies.

Depending on how often the average VC is able to find & invest in unicorns, we believe a minimum safe # for most large funds is 50–100 companies, and for early-stage seed funds (where company attrition rates are even higher), we believe a “right-sized” portfolio requires at least 100-200 startups, and possibly up to 500 startups. (hmm, what an interesting number/name ;)

Note: we acknowledge this is a very simple example — management fees and other expenses are not included, nor have we modeled any follow-on capital typically reserved for 2nd/3rd check investments in winners (which might or might not improve overall performance), nor have we modeled the timing of deployment and return of capital, nor any recycling / re-investing of capital.

However, the basic argument remains: portfolios too highly-concentrated in small # of companies risk missing out on ANY unicorns whatsoever.

Ok, it’s a Saturday & since I’m overdue to take the kids to the pool, I’ll skip a more in-depth debate on why VC portfolios are so typically under-sized — my guess is it’s due to the mistaken belief by traditional VCs that they need to serve on boards directly, rather than simply securing the necessary voting rights and control they want that usually come with board seats.

Or maybe they think they’re just better than the rest of us who aren’t tall, white, male, or didn’t go to the right schools. Or who don’t wear khakis.

Or maybe it’s due to all those tee times, I’m not quite sure.

Regardless, we will be sure to discuss this in more detail at PreMoney.

Hope to see you there.

99 VC Problems But a Batch Ain’t 1 (2024)
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