Benchmarking VC Investment Ecosystems: A Data Model
Ajit Deshpande, Class 17
For early-stage entrepreneurs, one of the first tasks is to sell their vision to capital providers—venture capitalists, angel investors, and the like. In fact, today there is much public-domain content addressing ways and means for successfully raising venture capital as an entrepreneur. Founders want to know how VCs evaluate businesses and teams, what trends VCs currently see as interesting, how entrepreneurs should prepare an elevator pitch or a full-blown slide deck, and so on, throughout the VC process. Yet, the venture-funding process is just the starting point for a new company, paving the way for the crux of the startup’s mission: ongoing business execution and value creation.
The Challenge of Assessing Ongoing Performance
Execution brings its own unique challenges specific to the startup’s location, sector, team-capabilities, business model, and competitive dynamic. Recruiting, product-market fit, customer acquisition, customer retention, and partnerships all bring their own hurdles. While public-domain content addresses some of this, for the most part, the leadership team must anticipate, evaluate, and act based on its own circumstances.The same execution challenges also apply to VC firms! Compare a venture capitalist’s journey to an entrepreneur’s journey.VCs themselves fundraise every few years from their Limited Partners (LPs). VC firms sell their investment strategy when raising money from their LPs, across various dimensions such as geography, stage, sector, industry segment, approach, and so on. This strategy is a function of both the skillsets and the interests of the VC firm’s general partners (GPs) themselves, as well as the prevalent trends within their ecosystem. Once the funds are raised, the GPs are accountable for their execution and eventual outcome (maximizing cash-on-cash returns is their fiduciary duty to their LPs). There are a few thousand VC firms worldwide, generally co-located in a few urban clusters such as San Francisco, Boston, New York, Tel Aviv, and London. Competition to fund promising entrepreneurs is significant. Venture capital is a relationship business to an extreme extent, and networking relationships die off if there is any drop in the VC’s effort and execution.Going back to the lifecycle of a startup, all new businesses must determine how to measure success in their ongoing execution. Depending on the business model, various growth metrics can be used, such as top-line, number of net new customers, margins, impressions, regulatory milestones, sales cycles, deal sizes, and so on. Using the chosen metrics, one can examine a startup on a yearly basis and get a reasonable measurement of whether a startup is executing well.Again, VCs have the same pressing question—how can they measure ongoing execution success? It’s a tricky question because a ten-year fund might not see any outcomes for five years, and the true, significant successes may not happen until seven to nine years down the road. Using internal performance metrics cannot work for a VC firm—venture is an illiquid asset class with limited nuggets of activity (investments, follow-ons, exits) within any given firm. Therefore, VCs need to determine a way to aggregate activity in their surrounding venture ecosystem and use that as an ongoing benchmark to measure their own performance.
Introduction to Opus Capital
Based on our own objectives, we at Opus Capital have developed a simple way to benchmark our performance against our peers. Opus Capital is an early-stage, IT-focused VC firm with an office in Menlo Park, CA. We focus on investments primarily in the United States and in Israel. The approach at Opus is to lead or co-lead early-stage rounds, and to be actively involved with portfolio companies all the way through to a successful acquisition or IPO. The partners have all been successful entrepreneurs or senior executives in enterprise IT companies, and thus bring strong domain knowledge and business connections to help portfolio companies succeed.Given Opus’s focused approach across sector, geography, stage, and investment style, it is critical for the firm to know how the VC community evolves across each of the following:
- Are VC firms gravitating more toward seed investments or toward later-stage?
- Is enterprise IT, which is our main sector of interest, gaining greater or lesser investment interest compared to consumer IT?
- Are our local peer VC firms becoming more active or less active in recent times?
- Are our peer VC firms changing their strategy? If so, is the change due to some structural reason that we need to incorporate into our thought process in adjusting our own approach?
The Opus Capital Benchmarking Process
Like many other firms, at Opus we have had a qualitative process for many years wherein on a quarterly basis we review investments made by 25-30 peer VC firms to get a feel for industry trends. More recently, however, we added a quantitative piece to our review, which despite its simplicity has turned out to be a powerful analytics tool.First, we selected a “peer group”: 25-30 “competitor” VC firms, initially chosen based on their similarity with Opus from an overall investment thesis standpoint. The current mix of firms that Opus monitors is shown in figure 1.
Fund SizeFirmsTracked$0 - $100M1$100M - $500M13> $500M13Figure 1. Peer Group VC Tirms Monitored by Opus Capital. Author's figure.
For these chosen firms, Opus obtains quarterly investment data from multiple sources (currently PitchBook, Crunchbase, and Twitter). The data include new investments as well as follow-on investments, ranging from Seed to Series B, within the United States and Israel, across the Information Technology spectrum—all of these being elements of Opus’s investment approach. Typically, we have seen 100-200 investments per quarter across our selected universe of “competitor” VC firms.Next, we take the list of companies invested in by our peers, and perform quick reviews of each startup on the list. We determine whether from our standpoint it would have been a
- Yes, we would have loved to invest (100% compatibility)
- Maybe, but would have needed additional information (50% compatibility)
- No, not a fit for Opus (0% compatibility)
Using the above simple categorization of portfolio companies, we create a blended “Compatibility with Opus” percentage for each peer VC firm, based on the number of investments that firm made during that quarter and on our categorization of these investments as described above.We then sort the peer VC firms based on this compatibility index, to create a Compatibility Table (figure 2). In the same table, we also build a cumulative compatibility index based on data across multiple quarters (our preference is to use five previous quarters of data).As shown in figure 2, Opus internally reviewed 155 investment instances from Q4 2013 across 27 competitor VC firms (since some are co-investments within this group of 27 firms, the actual number of startups reviewed is lower). Correspondingly, over a cumulative period (in this case, five previous quarters), Opus reviewed 718 investment instances for the same 27 VC firms. Firms in the figure are stack-ranked in descending order of cumulative compatibility.
The Value of a VC Benchmark
The obvious question is, what has a simple analytical approach like the above been able to tell us? What have we learned, beyond the usual qualitative insight into what is (and is not) deemed to be hot for investment? As it turns out, we have learned quite a lot!
Better Understand Co-Investment Scenarios
The compatibility index in figure 2 helps Opus Capital understand which competitor VC firms are consistently the closest to, and which have the most divergence from, Opus’s investment philosophy. We assume that firms with a cumulative compatibility rating of more than 60% operate very similarly to Opus from an investment standpoint—these are the firms that our GPs could focus on building stronger deal-sharing and networking relationships with. Additionally, when we have deal flow that comes from or is in concurrent due-diligence with these VC firms, Opus needs to make a point of doing deep due diligence as well.On the other hand, firms rated less than 30% on the compatibility index are considered to have a quite different investment approach—these are the firms that Opus tracks mainly to understand the “other side” of the early-stage IT investment fence. Within this list, if there are firms that consistently make head-scratcher investments, which a year or a few months later turn out to be duds, then we choose to stop tracking the firm and replace it with other, more interesting (to us) VC firms.
More Insight into Emerging Short-Term Investment Trends
For any individual quarter, a quick comparison of the compatibility rating for the quarter versus the cumulative five-quarter rating for any specific competitor firm tells us whether there might be a widening strategy gap for us with that specific VC firm. In the compatibility matrix in figure 2, for example, it can be seen that 11 firms were diverging away from Opus (as highlighted grey), whereas only 5 firms were getting closer to Opus (as highlighted blue). We feel it is abnormal to have more than 10-20% of firms getting closer, or more than 10-20% firms diverging away from Opus in any given quarter. So, having more than a third of our peer group diverge away from us in this case indicates either a strategy drift within Opus itself (unlikely over such a small timeframe as a quarter), or, more likely, a new trend emerging that Opus is not yet sold on, but that other VC firms are starting to bet big on—something for us to stay on top of.
2013 Q4 InvestmentsPast 5 QuartersOpus CompatibilityFundSizeYesMaybeNoaTotalYesMaybeNoTotalQ4’13Cumulative1100-500M112220475%75%2100-500M1238231333%63%30-100M11321650%67%4>500M2246621425%64%5>500M513916593061%62%6>500M246101252767%59%7100-500M112312625%58%8>500M4371511113757%55%9>500M21251312103550%54%10100-500M14511492420%54%11>500M5319139113372%53%12>500M3137101193050%52%13100-500M11606120%50%14>500M2417138143557%49%15100-500M3257682130%48%16>500M437142529379139%43%17100-500M2136911143442%43%18100-500M2244371450%39%19>500M11133261150%36%20>500M1121470%36%21>500M12691110244522%36%22>500M21811811203923%35%23100-500M2133581633%34%24100-500M21337102033%33%25100-500M489211425438238%32%26100-500M1122471325%31%27100-500M32543121960%29%Distribution29%28%43%15531%28%41%718Figure 2. Peer Fund Compatibility Index, Q1 2014. aIndicates that the investment opportunity is not a fit for Opus Capital. Author's figure.
Better Identify Structural Longer-Term Shifts in Venture Investment Preferences
Looking at the longer term, we are able to plot the quarterly rating for each VC firm over multiple quarters, to test whether there has in fact been a strategy divergence within that VC firm. If multiple firms show a strategy drift in the same direction over several consecutive quarters, then the broader VC ecosystem is likely moving toward a new paradigm. Such a shift would be structural; for example, the industry as a whole shifting from enterprise IT toward consumer IT, or vice versa.In fact, such a shift did occur toward the second half of 2013, and we were able to see this shift unfold through our data. To visualize this shift, I selected five peer-group VC firms from across the compatibility gamut: Fund 4, Fund 10, Fund 13, Fund 19, and Fund 24. Funds 4 and 10 have been historically highly compatible with Opus, Fund 13 is somewhere in the middle within the compatibility spectrum, and Funds 19 and 24 have had limited compatibility with Opus. Figure 3 shows the compatibility indices for these five firms, and figure 4 shows these same indices as a time-series chart.
FundSize2012Q42013Q12013Q22013Q32013Q4Comments4> $500M88%75%75%75%25%Traditionally enterprise IT-focused10$100M - $500M6350408120Traditionally enterprise IT-focused13$100M - $500M50506733050-50 blend of enterprise and consumer IT19> $500M17050050Traditionally skewed toward consumer IT24$100M - $500M3630303033Traditionally skewed toward consumer ITFigure 3. Selected Funds from Q1 2014 Peer Fund Compatibility Index. Author's figure.
Figures 3 and 4 showed us something quite interesting, which was that Fund 4, Fund 10, and Fund 13—all of which have traditionally had reasonable compatibility with Opus—saw a huge drop in compatibility from Q3 2013 to Q4 2013. On the other hand, Fund 19 and Fund 24, which had traditionally shown limited compatibility with Opus, continued to have low compatibility.
Figure 4. Compatibility Trend for Selected Peer Group Fund. Author's figure.
This data indicated to us that the broader VC ecosystem was diverging away from Opus’s investment philosophy. As it turned out, we were seeing signs of a transition for the VC world broadly, from enterprise IT toward consumer IT (enterprise IT is Opus’s key area of focus). We had a qualitative feeling that such a transition was occurring (based on interactions with our entrepreneurs and with peer VCs around follow-on and new financings), and that feeling was verified when this transition showed up clearly in our analytical exercise.
Limitations and Delimitations
If there is a limit to this analysis, it is just in the resource and time constraints. The raw data is very powerful and can easily be further analyzed to understand trends across dimensions, such as geography, round sizes, partner-level activity, incubator/accelerator emergence, and so on. For now, we have continued to keep our analysis at this level; however, depending on the resources available, larger firms could easily set this system up into a structured, in-depth analytical process that could be reviewable more frequently.All models have limitations, however. We identified three ways this analysis might misdirect us.First, the crux of this analysis is in Opus’s categorization of each of the 100-200 investments reviewed each quarter, which presents the risk of a “categorization drift” from one quarter to the next. A good internal review process can help mitigate this risk, in addition to not carrying more than about five quarters of past investments for the matrix.A second issue arises around investment frequency—some firms make few to no investments in any given quarter or year. One needs to be especially careful in making judgments for such firms.Finally, for sectors or geographies that do not have enough VC firms to create a reasonable compatibility matrix, one would need to brainstorm ways to find outside comparables in order to build up enough of a dataset to drive good analysis. At Opus, our view is that a minimum of 20 firms would be needed to build a reasonable analytical approach.
An Agile Venture Capital Firm
Venture capital is a highly subjective and long-term investment process. While one can never zero in on the “magic button,” a simple data model such as the one described here can go a long way toward keeping a VC firm honest and cognizant of its surrounding landscape. The right balance of product vision and data analysis such as this can help a VC firm become increasingly agile over time—and in the process, help the venture capital industry become better at optimizing its investments.
Ajit Deshpande
Ajit is Director of Marketing Business Planning at Salesforce, where he owns forecasting and ROI for worldwide initiatives run within the CMO’s organization. Prior to joining Salesforce in early 2014, Ajit was Senior Associate at Opus Capital, where he evaluated investment opportunities across enterprise software, infrastructure, and mobility. He holds an MBA from UC Berkeley, and a Master’s and Bachelor’s in mechanical engineering from Stanford University and IIT Bombay, respectively. Kauffman Fellow Class 17. ajit.deshpande@gmail.com
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