The Case for More Adventure in Venture Capital
Peter Thiel’s Zero to One opens with the maxim that “it’s easier to copy a model than to make something new”. This is true. I can now make fire in a matter of seconds. I can calculate the length of the hypotenuse with relative ease, and record audio with the push of a few buttons. These are all things which I have copied others’ models to accomplish. Accordingly, I don’t get as much praise for doing them as Pythagoras or his colleagues might have.
The value which the inventors of these methods delivered to society completely dwarfs that which imitators like myself deliver. Each time we copy them, we are essentially awarded zero credit by comparison. This is — as Thiel tries to impress upon us — the corollary to his original maxim; just as “the act of creation is singular”, the reward is too.
For business in particular, novel and innovative companies claim a significantly higher portion of the spoils than their derivatives. It’s hard to quantify the scale of this, but a bit easier if we focus on one industry. For me, it’s most interesting to consider the material impact of technological novelty on venture returns.
The most basic point to begin at is by acknowledging the historically extraordinary returns of VC versus other financial services:
This graph demonstrates the pretty rudimentary fact that those who invest in companies early on receive higher aggregate returns than those invest later on. What it doesn’t prove is that the superior returns of early-stage investing are not simply the result of a meaningless jump in valuation — one that occurs usually at IPO.
Equally, this graph only shows the results of successful companies. Early-stage investments usually involve very small commitments of cash — commitments so small that many losses are made negligible by the success of a unicorn. It is the results of these “winners” which the graph is depicting, rather than the “losers” for whom returns never materialize. Essentially, the data demonstrate that investing in companies early on is a good idea, but they don’t tell us which companies to invest in. To help with this, we can look at two separate examples.
Many people now tend to agree that quality trumps timing, hence why I am not claiming that first-mover advantage is the trick to VC. Rather, I’m claiming that being the first good mover in early-stage VC is everything. Whilst true failures are forgotten, the first successful iteration of a product or technology becomes so revered that countless mimics try to follow it. The reward of investing in these copycat companies, however, pales in comparison to that of investing in the original success — if you want great returns, you can’t just sit around and wait for a true innovator to prove the concept before you invest. The boldest and bravest investors who commit capital before success is evident (at the earliest stages) are rewarded with the largest multiples. An excellent example of this can be seen in the success of Zoom versus its followers:
Of course, Skype was founded before Zoom, meaning it was not the technical first mover. But Zoom successfully expanded on Skype’s offerings whilst timing marketing (somewhat luckily) to reach a true critical mass of users. Breakout rooms, participant polling, meeting size, and COVID are all partially accountable for making Zoom the first-good-mover over Skype. Here, “good” is the operative word.
Currently, Zoom is valued around $25 Billion. Not a single other company in that graphic is publicly listed. At its most basic, this is because the value of those companies — once Zoom already existed — drastically diminished in comparison. In short: the most lucrative startup investments are those which don’t simply imitate something that already exists in their market. Don’t just be the first mover; be the first to move well.
Snowflake, when it went public, doubled in value within the first 24 hours. CNN referred to it as the biggest tech IPO ever. The stock is now down, but the return to Snowflake’s VC investors was still astronomical. Here, we are concerned with the rate of return over the earliest time horizon: from private launch to public offering.
If, like Sutter Hill Ventures, you had led Snowflake’s $5m Series A, your stake in the company at the end of opening day would have been just north of $12bn. The multiple of this payout obviously diminishes the later one decides to invest in a startup. If, like Wing VC, you had been part of Snowflake’s tiny $900k seed round way back in 2012, your shares at IPO would be worth more than 1500 times what they were back then.
The vital and seminal lesson to take, though, is one that Wing VC recalls themselves when speaking about their investment:
“At the time, there were several not-so-obvious aspects of our initial investment in Snowflake. They highlight the scale of the challenges the Snowflake team has overcome. They also illustrate some of the persistent biases that have a way of creeping into investment decision-making to this day.”
In other words: the potential upside from early-stage VC is massive. Small startups can become global corporations. Valuations can skyrocket from when a company is pre-revenue to when they finally IPO or sell to an incumbent. Innately, the companies for which this will happen are those who do not always seem surefire bets. If they were surefire, then the valuation would be massive from day 1. Rather, the startups that provide extreme payouts do so because early investors spotted something unusual and unique which others did not. Delivering extraordinary returns requires investing in contrarian ideas.
Back to the earlier point, however — does this mean that all other cloud data startups are doomed to failure? If lightning has struck here already, then should we abandon all hope? Yes and no. There are now dozens of Snowflake imitators, complements, and competitors out there in the market. Some of these (Amazon Redshift, Databricks) have hordes of customers. They’re certainly not failures (right now) but, in the case of the latter company, aren’t close to Snowflake for rate of return. Databricks was founded in 2013, a few years after Snowflake, is now at its Series H, has received more than $1bn in funding than Snowflake did, and has not yet IPOd. (To really drive this point home, just take a look at Snowflake’s Startup Challenge. Snowflake is so much bigger than all of the nascent startups in its industry that the company can afford to bankroll their inception, then profiting from potential success as those startups build on Snowflake’s own tech stack.)
A number of these startups will fade into obscurity. More and more pop up every year, attempting to add another layer to the tech stack for data engineers. Some may make use of genuine innovations. Those that are simply trying to hop on the bandwagon of Snowflake’s initial innovation, however, are perfect examples of the fact that both the act and reward of creation are singular. When someone has already moved well, potential upside from investing in competitors will diminish.
These parables, therefore, teach us about a kind of “negative rule” — what we should not do, rather than what we should do. Some of the “positive rules” are well established, though, which leads us to a kind of half conclusion as we attempt to find proverbial needles in haystacks. Of course it’s good to invest in innovative ideas. Of course we want to find groundbreaking technologies. But then there’s what is seemingly becoming less obvious in VC: stop investing where lightning has struck before.
Moving beyond this and defining hard and fast tricks for VC is near impossible. If those rules existed in any concrete format, then someone more clever than me would have figured them out by now. In the next few paragraphs, I’m not going to try and state the definitive rules of good VC. Instead, I’ll attempt the far less lofty task of using the writing and thoughts of these cleverer people to construct a map for where great investments might lie.
Clarke’s third law — that “any sufficiently advanced technology is indistinguishable from magic” — is a beautifully intuitive definition. Put most simply, technology allows us to do more with less. It severs the connection between input and output. In the case of the Wizard of Oz the charlatan politician appear to be an indomitable wizard. Through engineering, Oz takes one thing and multiplies its powers and abilities. Technology does the same and, in the right hands, allows us to build more prosperous, healthy, good societies — permitting safer and quicker ways of getting things done.
This marriage of technology and magic is also the reason why novel innovations are so hard to spot. It is all too easy, in VC, to run towards what is shiny and prestigious; we are often attracted to the things which we know work precisely because we’ve seen these technologies work their magic before. For a VC, this removes some level of risk. But the technologies that we are currently seeing get attention are by no means those which we should be giving attention to. Ursula K. Le Guin, another science fiction writer, explains this phenomenon as it relates to social psychology:
“Its technology is how a society copes with physical reality: how people get and keep and cook food, how they clothe themselves, what their power sources are (animal? human? water? wind? electricity? other?) what they build with and what they build, their medicine — and so on and on… Technology is the active human interface with the material world… We have been so desensitized by a hundred and fifty years of ceaselessly expanding technical prowess that we think nothing less complex and showy than a computer or a jet bomber deserves to be called “technology “ at all. As if linen were the same thing as flax — as if paper, ink, wheels, knives, clocks, chairs, aspirin pills, were natural objects, born with us like our teeth and fingers — as if steel saucepans with copper bottoms and fleece vests spun from recycled glass grew on trees, and we just picked them when they were ripe...”
Le Guin’s account here is a far more sophisticated way of saying that we — humans, VCs — are too quickly distracted by prestige and shine. Consequentially, we’re quite slow at actually spotting real innovation. Of course, we must then ask ourselves what innovation really is. A quick and functional definition I offer (building on Le Guin, Thiel, Clarke etc…) is that true technology is how society copes with physical reality by learning to do more with less.
Importantly, Le Guin also acknowledges that “the enormously complex and specialized technologies of the past few decades [have been] supported by massive exploitation both of natural and human resources.” This is somewhat true. Of course, some technologies have given us hope for the future: more efficient renewable energy and mRNA vaccines, for example. But the ceaseless combusting of hydrocarbons and occasional misuse of the internet demonstrate human ability to take powerful technologies and direct them towards a practical evil. These things delineate between good, true technology, and innovation for innovation’s sake.
As to whether better returns are driven by investing in more pious, noble, sustainable technologies, the jury is still out. I would argue that sustainability is inseparable from long-term growth. This argument is based on common sense. If we want continued growth and positive returns, we must invest in companies that are going to still exist in 10, 20, or 30 years time. Sure, in the VC model, many of our investments will be offloaded before these time horizons. If, however, investments are so destructive as to degrade markets and natural environments for any potential new inventions, then timespan is irrelevant anyway. In other words: if we want to be able to invest at all, we must build a world that allows us — as a species — to stick around for while.
Similarly, the benefits of investing in “true tech” are hard to quantify, but somewhat instinctive. It would be nice to pull up a graph depicting just how much better these “true-tech” investors perform than their mimics, but that graph doesn’t really exist. It’s incredibly hard to categorize investments (definitively) in one bucket or the other, so equally hard to categorize investors in one of these buckets too. The good news is that the general principle holds so readily that we don’t need a graph. Invest in more innovative companies, and you’ll be better off!
One counterfactual to note, however, is that many VCs seem to be transitioning away from this model in favor of higher-probability returns for the “mimics” I mentioned. Sure, they say, investing once in Snowflake is a bigger payoff if you’re right, but the probability of being right is much higher when you invest in the companies who follow Snowflake once their success has been established. This might very well work, but it is certainly not in the spirit of VC. (Will Quist talks about this idea at length on a recent episode of 20VC). More generally, it is also not in the original spirit of American capitalism, but that is a point for another time.
The point is to look down the tech stack. Find foundational technologies. Invest in products that fundamentally sever the link between required inputs and given outputs. Do this, because you cannot capture carbon with enterprise SAAS. Have conviction in contrarian ideas. Back businesses that will make the world prosper and your portfolio flourish. These are all simple concepts — so much so that our disregard for them is both surprising and worrying. To summarize them all into three, quippy rules:
- Any sufficiently advanced technology is indistinguishable from magic
- If a technology is distinguishable from magic, it is insufficiently advanced
- If a technology is distinguishable from magic, then it is probably not ambitious enough for Venture Capital
