Taking a broad view, it seems that ethnography can help innovate the VC model in four main ways:

1. Gaining meaningful insights and understanding in new markets and domains
2. Developing a more holistic and proactive process to evaluate ideas and teams in which to invest
3. Providing richer data sources for making funding decisions, and
4. Reflecting on and considering values and broader impacts

In the following sections, I delve a bit deeper into some of these issues and highlight the ways in which ethnographic thinking and ethnographic methods can help create a more meaningful process to support innovation.

Meaningful Insights into Different Markets and New Domains – Across the industry, a variety of factors inhibit VCs from identifying areas of opportunity for investment and new paths for finding innovative startups. Most VC firms have some general guiding theses about what they aim to invest in, though they are very similar from firm to firm. They also keep an eye on current investment trends based on what leading firms are doing or what Silicon Valley pundits say the current trends are, making the focus between different firms even more analogous. That is to say, there is much more opinion guiding the way partners identify areas of opportunity for investment, and not much research. Within the firms themselves, this is exacerbated by the self-reinforcing perspectives that emerge from Silicon Valley insularity and from the virtuous cycle that magnifies a focus on certain types of trends. These limit both the markets and the domains that VCs set their sites on.

Paul Graham of Y Combinator has equated the rise of startups as a significant revolutionary force on the scale of agriculture or industrialization. But unlike other revolutions, he argues, the startup revolution does not need local producers. Anyone can create software, Graham says, but “it’s most likely going to come from an ecosystem like Silicon Valley” (Stross 2012, p. 237). This insular view is limiting in a number of ways. While there are certainly innovative startups emerging out of Silicon Valley, there are clearly many others in many other places. Rather than technology being created by Silicon Valley startups for the rest of the world, VCs have the potential to help foster entrepreneurs all over the globe. Yet over a quarter of worldwide VC investment is in Silicon Valley companies, and a whopping 70% in US-based companies. This reinforces the cycle, as those who receive investment generally come from US markets, and Silicon Valley in particular. If successful, they go on to invest in the areas they know and understand.

Beyond that, the herd mentality effects the rest of the world by setting the trends for “me-too” products to be developed. One VC firm I observed in Buenos Aires was a particularly strong example of this. They suggested there were 3 different types of startups there were interested in: 1) concepts that were successful elsewhere that could be adapted for a LatAm market, 2) local solutions with the potential to scale in LatAm, or 3) something completely new. In the general partner session I observed, however, only the first type was discussed. The partners took turns presenting startups they had seen covered in media or heard mentioned elsewhere that were getting funded in Silicon Valley. They discussed each and debated how well it would do if they copied it in a LatAm environment. For instance, Sendah, an online gift remittance payment platform from the Philippines, was interesting and drove a long conversation. But ultimately, the partners thought there wasn’t enough of a remittance market outside of Peru and Bolivia. By contrast, Talkspace, a real-time messaging service connecting users with therapists, they thought would be fabulous in LatAm. After all, one partner suggested: “everyone in Buenos Aires goes to a therapist,” where it was not only socially acceptable, but you were seen as odd if you didn’t. They thought this concept showed promise, and noted it down as one to evaluate further and potentially find a team to pursue. There was no research backing up these assumptions—either about the various markets or how these potential products might be meaningful for users.

It seems there’s great potential for ethnographic research to play a role in expanding the horizons of this focus, certainly beyond US-based markets. An ethnographic approach emerges from both emic and etic perspectives, giving a richer picture of the cultural system being studied. It’s not just about observation, but also interpretation– in what ways is a market changing. It supports a process of discovery, of inferring things and generating deeper questions. This is a natural area of exploration for ethnography, wherein the research can focus on emic validity, and provide a richer picture of areas to explore that might be misunderstood from the perspective of a VC partner. And this extends beyond the focus on new markets, to new domains as well.

One of the major changes in the startup realm in recent years is the shift from tech innovation being centered in information-technology-specific startups to other industries where software is fundamentally transforming the business model. Or, as Elad Gil, a serial entrepreneur, has put it, its a change characterized as a move from “software-driven” to “software-aware” (2016). As prophesized by venture capitalist Marc Andreesen and others: “software is eating the world.” This has been an ongoing trend for several years, but there still a lack of knowledge in the domains in which these transformations are happening. While many investors stick to making bets in areas they understand, others do venture into such new domains, but without much insight. One of the ways of dealing with this lack of insight is to “spray and pray.” That is, investors make lots of bets all over the place to increase the odds of finding a good bet.

An ethnographic approach provides a much better way to approach this— to explore and understand these domains of interest. Having an ethnographer to research the domain would help uncover traditional beliefs and ask the obvious questions to challenge those beliefs– to understand what would be disruptive, and if and how that disruption would help solve certain problems. It would provide insight into the business cultures and trends, representing a domain more close to reality. It would give some contextual understanding to software-aware domains, like IoT, but also potentially to entirely new domains of investment for a firm, like bio-tech.

Importantly, doing comprehensive research can help identify areas of opportunity connecting new domains and markets– areas for positive disruption. Take virtual reality technology (VR) as an example trend. There are engineers who build cool VR stuff, without necessarily having a target market or application area or who focus on the major application of the technology– consumer gaming. Both entrepreneurs and investors think VR can change the world, that it will be a trend. But they often seek solutions that scratch their own itch– they relate it to their own frame of reference because they don’t have knowledge or experience to understand the potential use for the technology in other industries. This is an area ripe for research– to explore such contexts and routines and identify areas of opportunity. To not only discover these areas, but to ask important questions about what matters and why delving into such a domain would be a fruitful realm for innovation.

Finding Teams: A More Holistic Process and Deeper Analysis – The first step in finding, funding, and fostering startups is to be able to identify trends and areas of potential and then connect with entrepreneurs focused in those areas. In current VC processes, there are a number of impediments to creating a “deal flow” that is truly focused on innovation. In identifying opportunities to pursue, VCs are largely reactionary. Most VC’s have an opinion on what is trendy, without necessarily sound reasoning behind it– it typically comes from following other lead investors’ opinions. Moreover, because VC pundits are typically the ones who declare what the trends are, the whole process is self-fulfilling prophecy. If a leading VC says chat bots are the next big thing and invests heavily in them, other investors also pursue the trend of chat bots. Then more entrepreneurs flood into the chat bot trend, seeking funding. The approach the VC firm then takes to choosing from among those startups matters a great deal. Many firms focus on connections, rather than ideas. Andreesen & Horowitz, for example, and many others follow more of a “Hollywood talent agent” model, where they focus on talented teams, rather than ideas. Moreover, finding talent typically happens through networks that VCs navigate, so the startups that ultimately get funded are the ones who already had connections to begin with. The decision making process ranges depending on the firm, and may be a consensus vote, a majority, or a decision made by a single partner, but are generally informed by opinion, not a research-informed, systematic process.

The teams I followed at both NXTP and JFDI in 2013 and 2014 were chosen in a similar fashion. It was heavily influenced by who the specific team members were. Did they fill the necessary roles—or as JDFI put it: did they have a hacker, a hipster, and a hustler? Had they known each other a long time? Were they already familiar with the market? As for the idea—was it in a trendy area, either in terms of domain, like bit-coin was at the time, or similar to ideas being funded in Silicon Valley? Teams looking to dive into more obscure realms or with riskier ideas were often left by the wayside.

An ethnographic approach seems valuable here in several ways. First, it can help in developing a more systematic, grounded process for identifying trends that is anticipatory, not reactionary. Taking a holistic approach to looking at a technology from a historical viewpoint, and then analyzing trends in systematic way, we can look at the deltas and anticipate some of the changes and the directions of those changes. And we can utilize rich anthropological theory in conducting such analysis. Anthropological theories can help us frame, understand, and assess behaviors to inform analysis of these dynamics. And in moving from trends to teams, an ethnographic approach seems most valuable in terms of the rich context it provides.

Funding Choices: Richer Data for Making Decisions – Following from the process of finding to funding startups, the main area of focus for VC’s is performance metrics. The main metrics VC’s look for include: retention (also referred to as churn), growth (in terms of revenue), acquisition growth (number of users), daily and monthly active users (DAU/MAU), amount of time spent (depending on product), lifetime value of a user (in dollars), acquisition cost (how much it costs to acquire a customer), profit margin, and potential market size, which is more of a (usually inflated) estimate, rather than a metric. This forces startups to focus on these metrics to survive; Lean principles instill in startups a very metrics-driven focus that relates back to funding mechanisms. In order to build, measure, and test their ideas, founders must focus on metrics to benchmark progress and make sense of it.

Metrics play a large role not only for VC’s, but for the teams they scout, informing their decision-making process and shaping their understanding of their product and its use. But where metrics provide direction, they can also add pressure for the teams to perform and compete, without questioning the goals. For instance, teams try to optimize for things like conversion rates before they are even certain of their business direction. When a team is too eager to move forward to obtain a milestone, they may not be optimizing for the right thing.

Another common issue is that these benchmarks are often one-size-fit-all. Metrics tend to be overly-simplistic representations of a complex system. The emphasis on metrics can pose a danger by giving false reassurance of progress and growth. Or, on the other hand, can force abandonment of an idea —a pivot— prematurely. The problem therein is that metrics provide minimal meaning or insight. They focus on linear growth and projections to measure progress, and they only act as a scale to measure how successful or not one potential solution has been. And even at that, they are often not indicative of anything beyond a binary. That is to say that we may know that users returned. But we do not necessarily know why. Metrics don’t expand one’s insight around solving a particular problem or developing potential solutions. Over several conversations with one of the startup teams I studied, an advisor repeatedly suggested they really needed to “measure engagement.” The team worked to do more analytics, but they never talked with potential users, so they didn’t really know what was actually engaging about the product. This was common among a lot of teams, who deferred to metrics, rather than getting insight from their users. As a result, founders approach continuing development of their idea assuming they know and understand the complex system in which they are introducing the product.

Lastly, and perhaps the most frustrating aspect for startups, is that metrics can add bureaucratic overhead. One team I followed in Argentina, Gorsh, wanted to move into Brazil as a market for a number of reasons, but an advisor said they needed metrics, numbers to show they should move into Brazil. He suggested they talk to a mentor who was particularly adept at analytics to figure out what to measure. These metrics force teams to work within that specific structure to show progress, rather than following their own journey. Metrics thus become a form of currency. Investors and founders nod and fire off questions based on their perception of how well, or how poorly, a startup is doing, based on such metrics. With the right metrics, a startup can garner more funding; without, it’s unlikely. Metrics mean survival.

It seems that despite using data and doing their due diligence, VCs are not necessarily selecting truly innovative startups, but rather ones that provide immediate quantitative rationale. But growth metrics don’t tell the whole story, particularly in early stage startups. And they may in fact be misleading if something truly has the potential to be disruptive. Reliance on metrics is not going away, but an ethnographic approach would provide an opportunity to extend and enhance the story and complement or contradict these limited data sources. These quantitative metrics don’t tell you why people are using something, how they’re using it, or what underlying needs are addressed. They don’t provide meaning. Ethnographic data would provide deeper focus, and richer context. Within a VC setting, having someone to consult with on qualitative data would be beneficial to both the firm and the startups to get a fuller picture to how the metrics relate to the bigger picture. And would help firms and teams make better, more informed decisions that incorporate metrics into a richer understanding.

Influencing Startups: Reflection and Values – Finally, once a startup receives funding and becomes part of a VC’s portfolio, the firm’s role is to advise the startup and foster their growth and success. A VC partner typically takes an important advisory role for the startup or sits on the board, making strategic decisions to shape the startup’s direction and growth. The firm also draws upon service providers in their networks to help their portfolio companies succeed (Hochberg et al 2007). But, at the same time, the structure of limited and general partners’ investment is such that about 99% of a fund is limited partner dollars; the general partner commits only about 1%, which insulates the general partner from feeling the effects of a poor fund return. These economics encourage the VC general partners to aim for generating high returns in the short term by “flipping” companies, instead of focusing on long-term, scale growth of their portfolio startups (Mulcahy et al 2012). Regarding the majority of startups funded, this part of the process tends to be an afterthought, particularly in considering the startups’ core goals as they relate to broader impact, values, and sustainability. It is here that the most critical assets of ethnographic thinking, as Hasbrouck outlines (2015) would have the most impact—relativism, interpretation, deconstruction, and reflexivity.

In the nascent companies I have observed, VC’s have an outsized impact in shaping their direction, and unfortunately, that is often fueled on how they can gain traction most rapidly and scale, for the benefit of returns. This, then, often has the effect of dramatically changing the focus and vision of the startup itself. Startups focused on smaller or more niche markets are encouraged to jump to bigger, more lucrative ones. Founders with an intense passion for solving a specific problem reorient to other problems that VCs suggest are more worthwhile to pursue. And in the end, there is a distinctive shift in values—a shift that moves teams from doing something potentially meaningful and of value for a particular type of end user to doing something that potentially leads to value for the VC firm.

One poignant example of this is Obatech, whose founders joined JFDI’s program with the grand vision of developing a technological solution to eradicate fake drugs in Indonesia. At the beginning of the program, Obatech’s focus was to create “a mobile-based validation platform connecting good pharma to patients in an emerging market.” But the consistent feedback they received in pitching their idea forced them to reconsider how this solution would work in reality. Would users really be motivated to scan their own drugs? Would they have the ability to, considering the low smartphone penetration rates in Indonesia? Still lacking the resources to develop a pilot study with a prototype, the team began exploring other possibilities. At the suggestion of some VC advisors, they reached out to two regional pharmaceutical companies. The team built a relationship with an Indonesian pharmacy chain and modified their vision; pharma ultimately became their customer. The outcome was a mobile application to “patients with chronic disease buy medicines more cheaply and take them more regularly” by providing data analytics to help pharmaceutical manufacturers. This shifted the focus from creating value for marginalized patients who feared for their safety to creating value for large pharmaceutical manufacturers. Obatech did not last long enough to see this vision either. But their brief existence and dramatic shift in aims highlights some important questions centered around value.

We’ve focused a bit on what it truly means to be disruptive. Disruption suggests radical change in meaning alongside wide diffusion… but this perspective should also reflect on values, sustainability, and impact on the end user. Innovation is an important driver of the economy, but as much research has noted, this does not mean it is necessary or positive (Abrahamson 1991). The types of “value” inherent in a new concept or product need to be unpacked; that is not easy or straightforward, as Graeber has shown (2001), but ethnographic reflexivity can help us get to a more fruitful place. Reflexive thinking needs to be a part of the innovation process, and this extends to the roles that VC’s play in fostering startups as well. VCs would benefit from a broader perspective, that gets them out of their affluent, educated, and mostly white male bubble. They, and their startups need to understand what people—and not just early adopters—value. Otherwise, they are imbuing values into the product without understanding their impact on the end user.