Emerging Markets Need Investors to Get Over Their Blind Spots

November 17, 2017

8:30 am

Anyone following the world of venture capital sees first hand that a disproportionate amount of capital is going to just a few people in a few places.

Let’s put numbers on that:

  • More than half of all venture capital in the world goes to just three US states: California, New York and Massachusetts
  • Just 10 percent of private equity investments goes to emerging markets
  • Women-led companies made up less than 5 percent of all venture deals in 2016

Of course, no one reading this believes that any one place, population, or sector has cornered the market on good ideas that make great businesses. And yet, the capital markets are disproportionately leaving emerging markets and its entrepreneurs on the sidelines.

So what’s happening here? The question we need to answer is: Why “Pattern Recognition” can be both a blessing and a curse.

I’m certain we’ve all heard the same series of responses from investors when it comes to backing new ideas in emerging markets:

  • “There’s just not enough deal flow”
  • Emerging market entrepreneurs “lack experience”
  • Local founders simply “don’t understand how to take on capital”

Putting aside for the moment that many of these comments are extremely condescending, let’s take a closer look. The reality is that investment in promising new ideas that come from currently overlooked places is being held back by significant blind spots. Blind spots in how we invest, who and what we invest in, and why we invest in the first place — blind spots that are created by mental shortcuts that we all take. Another way to put it: blind spots caused by a reliance on pattern recognition.

Finding Patterns for Good and for Bad

The concept of pattern recognition, or pattern matching, is often touted by venture capitalists as a badge of honor — this idea that, based on past successes, they’ve developed a unique ability to identify traits of a business that predicate success.

And in theory, this is not necessarily a bad thing — particularly when you have a deep data set that will help you understand ingrained patterns and inform a decision.

I’ll go a step further and say that pattern recognition is downright lazy. And it’s particularly problematic when it comes to investing in early-stage emerging market entrepreneurs.

The Pattern Recognition Problem: Some Entrepreneurs Are 0–3

This starts with a concept that a Village Capital alum, Jerry Nemorin, first shared with us: the 0-for-3 problem.

In the wake of the 2008 financial crisis, Jerry started LendStreet, a company based in Charlottesville, Virginia focused on helping lower-income individuals who found themselves in significant debt — due to unforeseen circumstances like a major illness or natural disaster — refinance that debt at more affordable rates.

But after a series of frustrating meetings with potential investors, it dawned on him: Jerry didn’t look like most entrepreneurs — in 2015, less than 1 percent of venture capital in the US went to African Americans. Also, he was solving a problem that didn’t resonate with the average venture capitalist, who typically haven’t had first-hand experience with expensive and unexpected debt. And as a first generation immigrant, Jerry lacked the network and the “pedigree” that the highly relationship-driven innovation economy is based on.

Or as he put it: “When it comes to pattern recognition, living far away from VC funds in Central Virginia, as a black guy, solving a problem for poor people, I was 0 for 3!”

LendStreet Founder Jerry Nemorin

So how does this relate to entrepreneurs in emerging markets? First, today, they sit geographically far from most of the capital going into new ideas.

For example, I was in Kenya recently with an entrepreneur, let’s call her Rita, who spent a week in Northern California looking to raise money for a Series A round.

Rather than pitch her business and product, she spent most of her time educating investors on the basics of the Kenyan market, and lost the opportunity to fully explain why her company was a good investment.

Second, as demonstrated in a recent study by the Global Accelerator Learning Initiative, emerging market entrepreneurs are disproportionately addressing problems in sectors like agriculture, energy, and health, that generally don’t resonate with the lived experiences of investors.

And third, let’s just address the elephant in the room — most emerging market entrepreneurs don’t look like Mark Zuckerberg, Steve Jobs or Sergey Brin.

In other words, entrepreneurs in emerging markets in many cases are 0-for-3.

And when the dollars do come in to these overlooked geographies, we still see the negative impacts of pattern recognition. Investors are looking for a classic Silicon Valley tech company pattern.

Case in point — at Village Capital, we recently conducted research on digital financial services companies in East Africa and India. Here’s what we found:

  • In the past two years, only three companies have received a whopping three-quarters of the venture capital going into new startups in the sector within East Africa.
  • More than 90 percent of funding for East African startups went to expat, and not local founders.

To be clear, we think these are good businesses and good founders — but they can’t be the only good businesses and founders in the region’s burgeoning fintech ecosystem.

So What Can We Do?

How do we reduce the negative impacts of pattern recognition? First, we have to change the way we find entrepreneurs.

  • As investors, let’s hire more diverse teams, including being more intentional about engaging local founders and investors in the markets we’re investing in. The data (and human nature) show that we tend to invest in who we know, understand and identify with. If we bring more perspectives to the table, we’re likely to find a more diverse set of great entrepreneurs.
  • Let’s create a common Myers-Briggs type system to evaluate entrepreneur potential, creating an environment where people and ideas can be evaluated using a data-driven approach based on what works? We’re doing just that with our STAR Survey to evaluate founding teams — more on that here.
  • Let’s bring more transparency and self-awareness on both sides of the table to what is currently an opaque process for raising capital, thanks in large part to investors who default to a version of pattern recognition that relies on gut more than specifics. What might happen if we developed a framework that introduces a “common language” — similar to the common app that many universities use — to ensure that investors and entrepreneurs are speaking from the same song sheet and using specific business metrics rather than vague gut instincts to evaluate a business, ultimately putting everyone on a more even playing field. We’re exploring this at Village Capital with our VIRAL Pathway.

startup team

In addition to changing the way we find entrepreneurs, we have to change the paradigm on how we invest.

  • Let’s start by ditching the Demo Day. Pitchfests are packed with implicit bias that cut many people out. Laura Huang at Wharton, for example, found that men were fifty per cent more likely to raise money pitching the same business as women, and all sorts of data shows that even well-meaning people have unconscious bias toward people of other races.
  • Let’s look at what’s already working. Already folks like Freada Kapor Klein, Ellen Pao, and Project Include have done incredible work looking at strategies and technology that mitigate bias in all sorts of investment decisions. At Village Capital, we’ve developed a unique process to change the paradigm, flipping the tables and putting our investment decisions in the hands of entrepreneurs using a peer review model. We’re seeing a very different result — our portfolio represents more geographic, sector and demographic diversity than peer funds of our size.
  • Let’s stop thinking that the Silicon Valley equity-only investment structure is the only option. Ditching the hunt for so-called unicorns in favor of another animal — zebras — that represent solid, but more realistic investments. And instead explore alternative investment structures like revenue share.

The most important thing we can do to mitigate blind spots is to be self aware — know that we have them, that we’ll keep having them and that we have to constantly experiment with ways to get around them.

Some of those experiments will succeed, and some will fail — but inevitably those efforts will bring more great ideas off the sidelines, into the spotlight, and unleash a new generation of entrepreneurs who no longer have to look or talk a certain way or live in a certain place, backed by capital markets who believe that hard problems are worth the patience it takes to solve them.

Read more about diversity initiatives and what investors are doing about it on TechCo

Allie Burns is Managing Director of Village Capital, a venture capital firm that finds, trains, and invests in overlooked entrepreneurs solving real-world problems. Learn more about Village Capital here.

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Allie serves as the Managing Director at Village Capital, bringing more than 16 years of experience working with entrepreneurs and innovators at the intersection of tech and social change. She previously served as a senior executive at Revolution and the Case Foundation, the venture capital firm and private family foundation created by former AOL executives Jean and Steve Case, where she led the organizations' communications and marketing teams. She also held positions at Discovery, AOL and Atlas Venture among others. Allie is a graduate of Boston University and holds an MBA from Thunderbird School of Global Management.

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