VC 201 - the VC Success Equation

This post was originally published on martinkrag.substack.com. Want to read more of Martin's thinking? Subscribe to his Substack here!

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This is a continuation of my last post on Cultivating a Venture Mindset, intended to be a primer for people new to the venture capital industry. We’ve now graduated freshman year and are ready for sophomore and VC 201.

Today, we’re diving deeper into what it (presumably) takes to succeed in VC. I believe there are three necessary (yet not sufficient) conditions in the VC Success Equation.

Variable #1 – Optimism

“If I can be optimistic at 99, almost dead, surely the rest of you can handle a little inflation.”
–Charlie Munger

The majority of great investors I know in venture are optimistic about nature. You have to be if you want to stay sane in an industry with such a high failure rate as startups have.

In general, though, it is easier to default to pessimism, and for every outlier startup success, pessimists have probably outweighed the optimists 100:1 or 1000:1. Every founder can attest to the number of rejections they’ve had on their journey – also the immensely successful ones.

But while pessimists may sound smart, optimists are the ones making the money. Why? They tend to make fewer of the most expensive mistakes you can make in venture: the mistake of omission.

A mistake of omission is if you had the chance to take a swing at the ball but chose not to do so. In other words, if you had the opportunity to invest in a company but decided not to, and the company turned out to be successful.

The opposite of a mistake of omission is a mistake of commission – when you take a swing at the ball but miss – you make the investment but the startup ends up failing.

Ask any VC and they will give you the horror story about a mistake of omission — that time they could have and should have but didn’t. It’s the name of the game and it happens to the best out there – Bessemer famously showcases some of their misses, while Benchmark arguably missed out on both Google, Skype, and Facebook.

Such mistakes are the most expensive ones because you can "lose" potential outlier returns that would have made all your other decisions and investments inconsequential (remember the power law).

Mistakes of commission, on the other hand, have a capped loss at 1X the invested capital. As a venture investor, these losses should be expected and somewhat frequent, otherwise you're not investing in risky enough (and thus highly enough rewarded) opportunities.

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Mistakes of omissions are unavoidable (you will pass on a great investment) but they can be somewhat mitigated by having an optimistic lens on the world and technology’s place in it.

You should not invest in everything that comes through the door. But in those difficult situations where you are on the fence, it probably pays to be leaning in rather than leaning out.

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Variable #2 – Probabilistic Thinking

If you don't get elementary probability into your repertoire, you go through a long life, like a one-legged man in an ass-kicking contest
- Charlie Munger

The world of venture is probabilistic, not deterministic.

Deterministic thinking assumes that outcomes can be predicted with a high degree of certainty, while probabilistic thinking acknowledges that uncertainty is inherent in many situations.

Determinism works well in simple, well-defined systems with known rules and conditions, while probabilistic thinking is more applicable to complex systems with many unknowns and a high degree of variability. Startups and early-stage investing are examples of the latter, not the former.

As a VC, you’re better off adopting the probabilistic approach when evaluating investment opportunities. Outlier outcomes cannot be predicted based on extrapolations of past data, instead, you should view your job as trying to invest in multiple possible futures, each with a tiny chance of playing out but with a sufficiently large upside if they actually do.

To think in more probabilistic terms, you want to move from first-level thinking (simplistic, superficial, deterministic) to second-level thinking (complex, convoluted, probabilistic):

• “I don’t believe in…” → “What is the range of future outcomes?”
• “This is too risky/difficult/impossible because…” → “What is the outcome in a scenario where it actually does work?”
• “I’m sure that… “ → “How sure am I? 100%? 80%? 60%?”
• “This can’t work because…” → “What is the probability of me being wrong? And what is the consequence if I am?”

Another simple way to think about probabilities in investing is around valuations and Expected Value. Simply put, if your fund model requires €1B outcomes for a company to return the fund, you are implicitly assessing the startup’s probability of achieving such an outcome through its valuation.

For a €10M valuation to have a neutral expected value there needs to be a 1% probability of a €1B outcome (€1B x 1% = €10M).

Naturally, you want Positive Expected Value (+EV) on your investments and to achieve that you would either need to believe there is a higher than 1% chance of an €1B exit or that the exit outcome is higher than €1B.

This line of thinking also (partly) explains the latest years of ZIRP investing. When everyone starts believing outcomes are 10x larger than previously thought (narrator: they weren’t), it becomes somewhat rational, at least mathematically, to invest at 10x higher valuations.

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Variable #3 – Contrarianism

“Whenever you find yourself on the side of the majority, it is time to pause and reflect” ‍
‍- Mark Twain

If you’ve spent more than 10 minutes in VC-land, chances are that you’ve met a self-proclaimed contrarian investor. You’ve probably also heard that it is important to be non-consensus and right. And you most likely have seen this 2x2 matrix:

Memes aside, and before diving into the actual merits of contrarianism, let's first understand the the nature of averages in an asset class all about the outsized outliers.

The Actualisation of the Average VC

I’ll let you in on a little secret. The Average VC Fund™ is not performing that well and is not a particularly good investment for its LPs. Even among the top 25% of all funds, the average performance is mediocre: historically, the top quartile of all funds is on average returning less than 2X to their LPs, despite many having had the advantage of investing through the last decades of extreme technological innovation and a sustained bull market.

With more and more funds popping up over the years, the absolute number of average funds has been increasing. I’d say four factors are driving this Actualisation of Average:

1. Commoditisation of venture capital → Returns regressing to the mean

There are so many VC funds chasing not-so-many outlier companies (and this ratio has probably gotten worse over time) that we simply are witnessing a regression to the mean in terms of performance. The Law of Large Numbers (and the Power Law) suggest that venture capital, on average, is perhaps meant to be a not-above-average asset class (but: the return profiles of the outlier funds more than make up for the mediocre performance of the middle of the pack).

2. Proliferation of Playbooks → Consensus-driven behaviour

How-to-VC content and thought leadership have proliferated in recent years, and while we all have become smarter because of it (I surely have), it has also formed a consensus around best practices and fundable companies. And consensus leads to average behaviour, which leads to average returns and average funds.

3. Human Nature → It pays to be in-group

Herd mentality and tribalism are prevalent in most fields, especially in ones with a high degree of uncertainty, where it pays to signal that you’re in the know and in-group by backing the current hot thing or the well-credentialed founders. Truth be told, most investors are investing like most investors, and if you act like most people, you end up looking like, well, most people.

4. The Business Model of VC Funds → Short-term incentives

The lifespan of an active VC fund investing in new companies is around 3-4 years, while the feedback cycle (getting returns) often is at least twice as long. This timing discrepancy creates a misalignment between short-term incentives and long-term results, leading to average outcomes. A VC firm trying to raise its next fund could be swayed to optimise for early signals (which turns out to be noise) and the smaller, obvious win rather than the larger, patient one.

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How not to be average

"Rules direct us to average behaviours. If we're aiming to create work that is exceptional, most rules don't apply. Average is nothing to aspire to. The goal is not to fit in."
- Rick Rubin

Since average is clearly not good enough, VCs looking for outsized returns should be willing to break from the pack. If you want to beat your peer group, the first thing you need to do is not look like your peer group.

The logic is as follows¹:

1. You can’t take the same actions as everyone else and expect to outperform
2. In order to outperform, you have to be above-average which means doing something different than average
3. In order to do something different, you have to dare to do something that could potentially be wrong
4. In order to potentially be wrong, you have to break from norms and "best practices" and move from conventional to unconventional behaviour
5. Behaving unconventionally means that you have to accept the risk of looking stupid, and survive the instances where you actually turn out to be stupid

Cultivating contrarianism

I believe there are three areas you can explore to cultivate contrarianism: ideas, timing, and judgment.

IDEAS

A good place to look for the difference between consensus and contrarianism is in the intersection between good and great ideas.

Most people recognise good ideas but not great ideas because great ideas often look like bad ideas.

“Good ideas are influenced by the status quo, the current configuration of society, cultural norms, internalised beliefs and first-order thinking. Great ideas break with norms, deviate from belief systems, ignite discussion and disagreement, and require second-order thinking.”

There is a reason for many VCs admitting that their best investments were the ones igniting the most discussion and disagreement and that it only seemed obvious in hindsight.

Good ideas seem a priori good to most people, while great ideas are prospectively unclear to all but a few people but retrospectively obvious to everyone.

TIMING

There is an advantage in being able to discern great from good faster than your peers. Following the crowd rarely leads to outsized outcomes, but leading the crowd does – true alpha comes from spotting value before others do.

However, being too far ahead of your time is indistinguishable from being wrong, so you want to be ahead of the curve of a crowd that eventually catches up, spots the value and agrees with you. And the value needs to be durable if you are to be right rather than look right².

“Why Now?” is one of the most important questions you can ask a founder when investing in startups but it is equally important to ask that of yourself as an investor. Where am I on the slope of the contrarian curve vis-a-vis the position of my peers? What are the potential inflection points that will flip the curve from contrarian to consensus?

JUDGEMENT

Being contrarian is tautological to thinking for yourself and trusting your own judgement.

In investing there are no easy answers or obvious truths. If there were, those advantages would be arbitraged away by the market:

“This all leads me back to something Charlie Munger told me around the time The Most Important Thing was published: “It’s not supposed to be easy. Anyone who finds it easy is stupid.”
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Anyone who thinks there’s a formula for investing that guarantees success (and that they can possess it) clearly doesn’t understand the complex, dynamic, and competitive nature of the investing process. The prize for superior investing can amount to a lot of money. In the highly competitive investment arena, it simply can’t be easy to be the one who pockets the extra dollars.”
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- Howard Marks

Jeff Bezos talks about two different kinds of decisions: math-based decisions and judgment-based decisions. For the former, data and analysis do the heavy lifting, while judgment and debate are the prime ingredients in the latter. In Bezos’ view, “any institution unwilling to endure controversy must limit itself to the decisions of the first type, while innovation and long-term value creation comes from the second type.”

Trusting your judgment to act on little or no data - or acting contrary to what the data suggest - requires conviction. And having conviction in spite of evidence requires a unique insight or edge that points you to the right even if others are turning left.

Any early investor in a generational venture company has had to look past certain off-putting elements of the business and be willing to take on risks other investors weren’t.

The ones who did earn the grand price in investing: being right and being paid for it.

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This post was originally published on martinkrag.substack.com. Want to read more of Martin's thinking? Subscribe to his Substack here!

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¹ I recommend Howard Mark’s ‘Dare to Be Great’ and ‘I Beg to Differ’ if you want to read more about averages and outliers in investing

² Finn Murphy has written a great post on the difference between looking smart (for a while) and making money