Social Network Analysis (SNA) and Start-Ups: An Interview with Murat Ünal

Beyond traditional investment analysis and the relatively modern analysis of environmental, social, and governance (ESG) issues lies social network analysis (SNA), which promises to help inform investment decisions. But what is SNA and how and why can it inform investment decisions in start-ups?

To answer these questions CFA Institute interviewed Murat Ünal, DBA. Based in Germany, Ünal is the executive director of SONEAN, which provides asset managers and owners with complementary SNA insights related to investing in start-up and listed companies in Europe. Ünal earned his doctorate in SNA and is a member of the International Network for Social Network Analysis (INSNA). Together with his team, he has recently produced a research report, “Going Beyond Financial Data — The Crucial and Complementary Role of Social Network Analysis (SNA) for Investments in Start-Up Companies.”

CFA Institute: What is social network analysis (SNA)?  

Murat Ünal: The answer really depends on your perspective. For us it is a means to go beyond financial and non-financial (ESG) data and provide unique insights for investors when it comes to making investment decisions. With SNA we don’t focus on organizations in which our clients invest in isolation, but analyze, among others, prior and existing social ties of executive and non-executive directors to understand the networks in which the people that run these organizations are embedded and how these ties can potentially affect corporate governance and performance of those institutions. What interests us are the people behind organizations which embody those institutions.

How can SNA help in investment decisions regarding start-ups? Give us examples of how an investment decision in a start-up is influenced by SNA.

It can help along the entire investment process, from sourcing investments, as part of the due diligence, throughout the portfolio monitoring process, or even the exiting of investments.

Let us give you three relevant examples, among many others:

1. As an investor you either invest in start-ups directly or you entrust, for example, VC managers to do it on your behalf through a fund. Knowing in which co-investment clusters other investors are embedded and how it affects, even limits, their decisions where to invest is of great importance. We track already over 4000 start-ups in Europe and their over 1000 investors from across the world, knowing exactly who invests where and whose portfolios correlate greatly with others. Investors are not aware of how co-investment clusters can greatly affect decision making and even valuation of start-ups they invest in.
2. When it comes to prior and existing ties between investors — for example, VC funds — and start-ups, we know that it can greatly affect the due diligence process. The social capital that people derive from being connected to specific networks has a tremendous effect on sourcing but also the exiting of investments and the opportunities and risks along with it. In one case it turned out that a start-up company and a board member (founder) had family ties with a specific VC fund and the start-up even filed for bankruptcy after substantial investments had gone into it. For the investor who entrusted the VC fund with the money, this should have been transparent right from the start.
3. SNA and our way of implementing it allows us to define all relevant actors within the ecosystem (investors, start-ups, the central people, and institutions behind it) and develop automated and optimized as well as tailored screening processes to monitor almost real-time developments across all relevant sources (publications, social media, and other electronic sources) which have a potential impact on our clients’ portfolios. Recently a rumor emerged with regard to the CFO of a start-up company which we picked up in a New York-based blog and provided instantly to a client which led to a divestment in time.

So these three examples show the importance of the co-investment cluster–related work, the social capital behind organizations, and the crucial role of dynamic screening across multiple sources where network analytic thinking and methodologies play an important role.

How do you collect information to perform SNA? 

We have a multiple tie and multiple source approach. We thus look at all relevant ties between people across all relevant institutions (university, company, military, associations, NGOs, politics, government, and many other ties) and across all relevant data sources (more than 2000 publications, all relevant social media outlets, legal registries, video streams, etc.). This allows us to get a much better picture. We hereby have developed clear and rigorous standards for data that we will use or not, and in the last 13 years have been able to create a very unique way of spotting risks and opportunities dynamically.

How did you go about performing SNA in your research on start-ups?

In our current universe we cover, as mentioned before, over 4000 start-ups in Germany and Europe and their ties to over 1000 investors from across the world. By analyzing thousands of sources over six months, we identified who invests where across which stages, sectors, countries . . . and using a snowball approach also identified a significant and representative portion of the European start-up ecosystem. By knowing who — what type of investor and institution/person — invests where, we transformed the network data in one-mode matrices, which allowed us to analyze correlations between start-ups and investors, getting the co-investment clusters — who correlates most highly with whom — for investors, but also understand which start-ups are embedded into which co-investment clusters. We furthermore looked at the social capital of investors and founders alike to see how being connected to each other affects investment outcomes. From empirical research we have many insights into social network analytic measures that affect certain outcomes and also can apply these. One should definitely highlight the predictive power of the data as you can say with great [certainty] where money will be invested based on co-investment cluster ties, for example, and how being connected affects investments.

What were the key insights that you gathered by performing this analysis?

As shown in my own doctoral dissertation, SNA helps you to go beyond financial data and explain much more of the variance that exists. We even ask ourselves how investors still focus mainly on financial factors knowing that social ties and network configurations count. It also showed us that we need to create greater awareness for SNA and its ability to provide measures which affect governance and performance outcomes greatly. Just take the two simple examples from the listed space:

1. There are about 117 so-called independent directors in the top 50 European companies, and it turns out that almost one third hold prior or existing ties with the executive directors (the management of the company) based on our network data. How do these ties affect governance and how do the regulators need to react in this regard?
2. Furthermore, in times of financial crisis we know from institutionalization theory that companies close to governments will fare much better (who is going to be bailed out?). Our data allows us to quantify government ties of executive and non-executive directors and reweight their company’s position in a given portfolio. There is a huge difference between Barclays and Nordea when it comes to government ties. Furthermore, by identifying network heterogeneity of entire boards and their members, we can develop measures which, in the long run, can add great value to company innovation and thus performance-affecting portfolio outcomes.

What’s your take on the future of SNA and investment decisions into start-ups?

We already looked into ESG-related factors in 2002, developing very relevant projects around environmental, social, and governance-related factors. However, SNA-related insights on top of financial and ESG factors help us to explain much more of the variance and thus better understand the real dynamics. Furthermore, social network analytic measures have substantial predictive power. From our point of view, SNA will be the third main dimension along [with] financial and ESG factors in 10 years time. It is the same process as with ESG. When we pushed the importance to include ESG factors in 2002, not many people really cared but this has changed now. Social network analysis will strive in tandem with greater awareness and thus become a crucial and fundamental pillar in analysis and investments. It helps us to understand financial and ESG data better but, above all, provides unique insights on top of them.

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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: Courtesy of Murat Ünal