Gauging Impact: A Closer Look at Entrepreneurial Density

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Last week, I wrote about a new groundbreaking report by Dane Stangler and Jordan Bell-Masterson, offering policymakers ways to better assess and measure the impact they are having on their local entrepreneurship ecosystem. The report proposes four baseline indicators — density, fluidity, connectivity, and diversity — as a starting point for evaluating and measuring entrepreneurial vitality. This week, I look at entrepreneurial density.

The effect of entrepreneurial density can be dramatic: when talented makers and innovators interact regularly, new successful ventures are likely to emerge.

As AnnaLee Saxenian, the dean of UC Berkeley’s School of Information and an expert on the subject has explained, “Proximity facilitates the repeated, face-to-face interaction that helps to sustain competition and collaboration, as well as speed the continual recombination of knowledge and skill.” If the process of new firm formation requires constant iterative testing, face-to-face communication can only be an asset.

Brad Feld, who runs a VC firm in Boulder, Colorado, was struck one day by how often he ran into entrepreneurs he knew while running errands in town. This led him to explore the idea of entrepreneurial density, a term he may have coined. He defined it as, “the number of entrepreneurs plus the number of people who work at entrepreneurial companies per capita.”

Or, as a formula:

entrepreneurial density = (# entrepreneurs + # people working for startups or high growth companies) / adult population

The resulting sum is a fraction, the closer to 1, the higher the density. For policymakers interested in innovation and job creation, the higher the level of entrepreneurial density, the better.

Naturally, the entrepreneurial places we can name off the top our heads are also those that are most dense – Palo Alto near Stanford, Kendall Square near MIT, Union Square in New York City, SoMa in San Francisco, and it turns out, Brad Feld’s environs, a 10x5 block area of Boulder, Colorado that churns out remarkably high rates of new firms.

Fortunately for those Coloradoans who live outside Boulder, who like to say it is 25 square miles surrounded by reality, Boulder does in fact have one of the highest entrepreneurial densities in the country.

Prompted by Feld, Richard Florida, who writes about startup communities in The Atlantic’s CityLab, analyzed venture capital investment dollars per 100,000 people by city or metro area. He confirmed Feld’s sense about Boulder. On a per capita basis, Boulder places third in the nation.

Granted, this is looking at one type of new firm, those in the tech-sector that have the potential to scale quickly, which as I discussed two weeks ago, is an important, but still partial set of all new firms.

Nonetheless, the example of Boulder speaks loud and clear about entrepreneurial density as an indicator of an ecosystem’s fertility for innovation and new firm formation, and shows how policymakers and practitioners can use this metric to gauge impact of their interventions and investments in the ecosystem.

To gain a deeper understanding of entrepreneurial density, the new Kauffman study presents three different approaches to capture it across time

  1. The number of new and young companies per 1,000 people in a given geographic area, be it a city or a region. This metric will indicate how well the local economy is fostering entrepreneurial activity.
  2. Capturing the number of people impacted by new and young companies (i.e. founders and their employees).
  3. The density of new and young companies within specific sectors (high-tech or any sector of interest to the local ecosystem). Here again population is the denominator.

Tracking density over time could help us more closely establish a link between programs and actual outcomes. While silver bullets will never exist, we might soon be able to finally prove the effectiveness of programs.

The good news is that increasing density has been popular with policymakers for some time — albeit motivated by different reasons including the fact that our elected officials are politically incentivized to focus on small geographic areas.

While I think cluster theory has perhaps exaggerated the value of “industry clusters”, an increasing number of cities have used it to focus their efforts – seeking to generate growth by creating areas specifically designed to support research and innovation.

According to the National Bureau of Economic Research, “the first step in cluster development is to identify the candidate cluster by geography, industrial composition, and existing networks.”

Of equal if not more impact in my view has been the emergence of startup hubs like 1776 highlighted in the Washington Post yesterday that provide a place for entrepreneurs to work and connect to supporters, such as mentors and possibly investors, through on-site programs, events, and meetups.

The increase in attention to hubs has emerged at the same time as rising caution about the performance of accelerators and incubators. Hubs seek to invent new and more comprehensive models of startup support that can better quantify what network assistance has impact and if necessary pivot faster.

Universities have also been at the density game although only recently adopting more sophisticated evidence-based models to facilitate free-flowing pipelines of university research and startup spin-offs. Silicon Valley was always the model in terms of its connection to Stanford University just as Cambridge was the model on the East Coast with its connection to MIT.

What is exciting is that universities in towns across the country are adopting much smarter strategies than before in helping foster stronger local startup communities often under pressure from Governors struggling to deliver more in terms of local economic impact from their public universities.

Efforts to boost entrepreneurial density, however, have been one of the most financially-burdensome. Openness to policy experimentation has infused the field with new program and policy designs and implementation approaches.

Even in 2015, regional hubs, especially through universities and accelerators, remain arguably the biggest financial investment by the federal government in promoting startups. Two weeks ago for example the US Department of Commerce announced a new round of support for startups. What has changed is a healthier appreciation of the need for more diligence in collecting performance data around whether such efforts result in increased rates of new firm formation in order to test such formulas and guide future policymaking.

As always, your comments are welcome. Next week I look at entrepreneurial fluidity.

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