Luck in Venture Land

Succeeding as a venture capitalist can be the result of carefully researching startup companies and experience in the financial markets, but venture capitalists admit that it can also be about being lucky.

According to Bella, a venture capitalist,

“Luck is probably the most under-estimated resource; it plays a huge role. With all of these companies—there are so many opportunities for failure. It is not just incredible execution that gets you there—there is a lot of luck involved. In hindsight, people make it look like execution …. Even for us, we were so lucky so many times to get started—a chance encounter over here, an introduction over there—but it comes back to why do we invest in people. It is because there are certain people that have a tendency to become luckier over time than others.”

Bella, a partner in a highly lauded Silicon Valley venture capital fund that was an early investor in some of the most famous gig economy companies, tried to explain to me what makes success in startup investing. She was not, like so many other investors and commentators, talking up her own success as something for which she was alone responsible. Bella believes that investing in early-stage ventures and running them is not just a matter of “good execution.” In fact, she admits that the meritocratic story many people like to tell about their successes is often a retrospective narrative. The component that these stories underestimate is luck.

Rationality, objectivity, and accountability are usually seen as the key success factors to make economic decisions. The preferred way to achieve results is by constructing an abstract mathematical model and consequently, since the late 1990s, economic reality has often been measured against what Carrier calls “virtual models.” We have come to a point where many economic decisions based on models are now ultimately processed directly by machines. Not only do algorithms decide which rank websites have on Google-search (i.e. how easily they can be found and generate revenue), they also execute up to 80 percent of all orders on the US stock market. With credit scores, Amazon’s recommendation engines, and dynamic airfare pricing, economic “authority is increasingly expressed algorithmically,” as Frank Pasquale argues in The Black Box Society. More generally, quantification and the cult of metrics, of measuring things in numbers, have taken over big swathes of social life, too. From general self-tracking (e.g., for fitness purposes) and collecting likes and hearts on social media, to stars for and from Uber drivers, and China’s social credit score, a numbers-based economic measurability, comparability, and rationality is increasingly the only acceptable way of thinking about and governing noneconomic, even intimate social spheres. Luck and uncertainty are supposedly minimized with this calculability. So, what do Bella and other venture capital investors I spoke to really mean when they talk about luck?

Image description: Numerous people sit near each other in a room, all facing in the same direction. A whiteboard hangs on the wall. Across the top of the whiteboard, orange letters spell out “Startup Day,” and the board is filled with various phrases written in marker. Most of the writing is not completely visible, but in the middle of the board the text reads “You and your startup.”Venture capital investors are early investors in startup companies. Frank V./Unsplash

I observed more broadly that how investors gave money to early-stage startups in Silicon Valley, New York, London, and Berlin contradicted this trend of quantification and modelling in curious ways. This is not altogether surprising. Because many of the companies these early-stage investors focus on might neither have a product nor generate revenue, venture capitalists do not yet have data that could be plugged into a model. Still, venture investors are ultimately financial intermediaries. They are responsible (bound by so-called fiduciary duty) to the limited partners (pension funds, endowments, family offices, and the like) to increase their investments as much as possible and pay back more money to these investors. They have every incentive to decrease risk and make it calculable.

Often, there is data about market size and growth, where there would be experts, customers, employees, and possibly competitors for venture capitalists to talk to. But these data points are insufficient for making final decisions. Mostly, they only help to identify red flags and decide against a startup. As many of the more than 180 interviews I conducted with venture capitalists makes clear, they “form beliefs” based on different kinds of data. One important type is experience. Seeing hundreds of deals every year and meeting hundreds of teams helps investors to train their intuition. Many venture capitalists claim that they know what a good company, led by a strong team in sector X, looks like because they have encountered it before. The decision is, then, made based on the kinds of people the founders and co-investors are and their narratives. While Leins’ monograph on financial analysts focuses on the narratives used to persuade investors, he returns to the analysts’ “embodied experiences of past success and failure” to understand their decisions. He also observes the role which feelings play when “affect and calculation become closely intertwined when analysts aim to predict the future”. In my world of venture investors the jockey (the startup team) trumps the horse (the business and the market as such) for many venture investors.

For the most part, venture capitalists’ decisions are not based on quantifiable measure or models. Following the same trend, some venture capitalists support their decisions with AI, but these tend to be marginal and unsuccessful or fragmentary. Many early-stage startup investors don’t even write down their analyses and thinking processes in systematic ways. In the moment of making their decision, they are often influenced by hunches based on excitement and passion, as I describe elsewhere, leaving uncertainty and failure unaccounted for. Here, luck figures prominently.

To return to Bella, she doesn’t exactly ascribe sheer luck to investors’ decisions. It is slightly more targeted if not exactly planned. She believes that luck figures into having the right relationships, especially with people who were themselves lucky in the past. The importance of curating one’s social network is central here. Bella also considers the importance of timing, something another investor who made his first money with Skype emphasizes: “In 2001, when we started, very good deals started happening because the market was so bad. We were early in Skype with 1300x [return] in 36 months…. Once you got some luck, people think you know what you are doing… and better deals came to me afterwards.”

Luck multiplies in Silicon Valley. Sean, a former partner in a decades-old Silicon Valley firm, explains in greater detail that luck is a “critical skill to identify an unforeseen opportunity and grab it when it appears” and he claims that “preparing for and managing luck is itself a best practice,” an “art form.” In his eyes, it is clear why many people, particularly in the United State, are hesitant to attribute too much power to luck and timing: “The myth of the self-made person.… This myth defends the huge economic disparity we suffer in this country…. And in society more broadly, the contribution of so many unrecognized hard-working people with little access to luck is overlooked.…”

By accepting how important luck and intuition are to venture investing and more broadly to economic practices, we can challenge established narratives about hard-earned meritocratic achievements and wealth creation in the first place. Then, we can even pave the way to find ways to counteract underlying structural inequities, because not everyone is equally likely to be lucky.

Johannes Lenhard is the centre coordinator of the Max Planck Cambridge Centre for Ethics, Economy and Social Change. His current academic work concerns the ethics of venture capital. His recent edited volume based on prior work around homelessness is entitled Home – Ethnographic Encounters. You can follow him on Twitter (@JFLenhard) and write to him at [email protected].