I'm happy to say my newest paper has just been published in Small Business Economics. You can read the (open access) paper here. "Examining the cohesiveness and nestedness entrepreneurial ecosystems: evidence from British FinTechs" looks at an important question in the research on entrepreneurial ecosystems: do regions have several nested ecosystems based around particular sectors or do they have a single, cohesive ecosystem linking all different types of founders. I look at this question by studying the founders and top managers at British FinTech firms in order to answer a pretty basic question: are they (a) Fin, (b) Tech, (c) Both, or (d) Neither. If it's A or B, that would suggest that regions have separate ecosystems for finance founders and technology founders, leading to little intermixing. If it's C, that would suggest that there is a cohesive ecosystem combining both. If it's D, well, we'll get to that.
The Question
Before I get to the answer, let's think about why this question matters. Nested vs cohesive ecosystems isn't just a minor conceptual quibble, it speaks to what ecosystems are and why they matter. Nested ecosystems mean that the most important resources for founders to grow is sector specific: industry knowledge, niche technology, and insider networks with specialist financiers. If there is a single, cohesive ecosystem in a region then the most important resources are more generic: knowledge about the scale-up processes, sales and marketing skills, or a broader investment community. So, being able to tell if a region has a single, cohesive ecosystem or if it has several distinctive ecosystems is an important way to really understand how ecosystems actually work.
To tackle this issue I looked at the world of FinTech. FinTech is digital technological solutions to problems facing the finance sector. The very word FinTech speaks of two worlds: finance and technology. Both have their own norms, structures, rituals, and cultures. In the platonic ideal of entrepreneurship, you would have someone with a deep finance background who os able to observe opportunities in that market that would be hard for an outsider to see connect with a technology expert who can develop a solution to that problem. I call this the 'You Got Peanut Butter in My Chocolate' outcome.
The Method
So, how do we figure out if this actually happens? To do this, I turned to my old friend, LinkedIn. I've previously used LinkedIn data to track the career mobility of engineers laid off from Blackberry to see if they stayed in the Waterloo ecosystem or not. In this project, I gathered the profiles of the founders and top managers of FinTech firms in the four largest FinTech clusters: TechCity in London, the City of London, Edinburgh and Leeds. Firms and people were identified by Beauhurst Business Intelligence, a great business information site that I've used in the past.
However, for this project I'm not interested in where they are, I'm interested in who they are. I needed to develop a way to classify people as being Finance people, Technology people, or something else. That's a bit harder since it's a classification task that requires making judgements about people's backgrounds, experiences, and career trajectories.
To deal with this, I worked with four amazing PhD students as research assistants. After I collected and cleaned the data (and that was a whole ordeal, believe you me), we had a database of 1570 people from 380 FinTech firms consisting of their their LinkedIn descriptions, their education, and their prior seven jobs. That is, if they included all that info. There was a lot of missing info. Many people had much less info and some people had a lot more. But, anyways. We developed a coding guide to look at people's prior jobs to classify them as Finance, Technology, Management, or Other. So, someone with a lot of jobs as an investment manager would be classified as finance, someone who had lots of jobs as a programmer tech, and someone who has spent most of their career as a marketer or salesperson would be management.
After doing this, I saw that people's job histories aren't enough to classify them alone, we also need to look at their employers as well. Because a human resources professional working for Goldman Sachs might be able to spot problems facing the finance world as well as any investment banker. So, we went through again, classifying more than 2,400 firms listed as prior employers as being technology firms, finance or other. In general, the coders agreed about 70% of the time and I resolved any conflicts. But this was still a months long process with a lot of back and forth and arguments over who was what.
Venn, veni, vidi (I came, I saw, I made Venn Diagrams)
After this classification process was done, I was left with a huge table of people, the firms they founded or worked at, and their classifications. How do deal with this? A bunch of Venn Diagrams!
What I found was actually pretty interesting. There was actually very little overlap between tech founders and finance founders. Only about 7% of FinTech firms had teams with both fin and tech experience. The most common figuration was actually just a management background, no Fin or Tech needed to start a FinTech firm!
Very little overlap between Fin and Tech!
You can see the same thing looking at founders employment background: fairly low levels of overlap between Fin and Tech
A bit more overlap, but still very low!
There are some interesting regional patterns. Leeds, the least developed of the four ecosystems being studied, had the lowest rates of overlap between backgrounds while the larger finance centers of London and Edinburgh had higher rates.
Questions, answered
So, what does this tell us. The data show that entrepreneurial ecosystems are fairly nested. The data show big disconnects between the technology and finance communities of all four case study sites. While there is some overlap in London, it's still far from the norm. I don't think this is either a good or bad thing, it's just a reflection on the nature of how communities form in advanced economies.
But for me, the biggest finding is that 'generic' business knowledge and entrepreneurial know-how is really important to FinTech. It's not just being able to solve Black-Scholes models in your head or being a blockchain ninja hacker. It's knowing how to manage diverse workforces. It's about knowing how to sell products and manage innovation processes. People with these skills are most likely to be the founders of high-growth FinTech firms. They hire people with the finance insights and tech skills that they need. Knowledge about the entrepreneurship process is as critical as more specializes domain knowledge in supporting the creation of high-growth FinTech ventures.
What does this mean for ecosystems researchers and builders? I think it means that we need to pay attention to managers as much as we pay attention to tech folks. Maybe this is my bias as someone in a business school, teaching business skills, but I think they're pretty dang important! We know that managerial know-how is important to firm success, but sometimes that gets lost in the shuffle with the focus on young tech entrepreneurs. Don’t neglect your middle-age middle-managers, they often make the best entrepreneurs!
Finally, I just want to thank the Frank H. Kenan Institute of Private Enterprise and their Frontiers of Entrepreneurship Research Grant for their support in this research. The paper required skilled and thoughtful PhD students in order to classify thousands of people and firms and they deserved to be paid top dollar for their work!