Peter is a guardian at the Leslie eLab and an intern at the Entrepreneurial Institute. He is co-president of CASEA and co-chair of the NYU Entrepreneurs Festival. He has started a film production company called Minetta Studios. This is the second piece in Peter's 'Statistical Analysis is Sexy' three-part series, the first of which you can find here.
Now that the scene is set, statistical analysis makes its entrance onto the stage. It seems if a firm could better analyze startup data, it could find ways to capitalize on those companies that are making humble returns as well as increasing the success of getting a high return. In order to get a better understanding of the quantification of venture capital, I talked with Paul Singh of Disruption Corporation and Crystal Tech Fund.
Paul is the founder of Disruption Corporation and general partner of Disruption's post-seed venture capital arm, Crystal Tech Fund. Disruption provides research, investment and advice in the maturing private market. Paul was a partner at 500Startups, an accelerator and venture firm headquartered in Silicon Valley where he oversaw the investments in 450+ companies across 30+ countries. Paul has founded a few of his own startups (two successful exits and a number of failures in between) and spent some time at PBworks, AOL and Symantec. After graduating from Bishop O'Connell High School, Paul attended George Mason University. He lives in Ashburn, Virginia with his wife, Sukhi and daughter Eva. Paul can be reached at twitter.com/paulsingh.
His original plan for Disruption Corporation was to provide data and analysis (this is known as Dashboard and later will add another layer called Indicate) to venture firms and their portfolio companies. They took into account many variables with a focus on secondary signals. Some metrics are twitter followers, events, and slide decks. Secondary signals take the form of this example: lets say a portfolio company is telling you they are doing really well but the system will pick up on the CTO updating their linkedin which can translate to problems in a company since you really only update your linkedin when you are looking for another job. They get their data from AngelList, SEC filings, and 85 other different sources. After gaining traction with their customers, they started getting direct inquiries about making investments.
This is where the Crystal Tech Fund comes in, as it acts as another arm of the total Disruption Corporation package. The Moneyball approach that he incorporates into his data analysis is based on combating conventional thinking about what the necessary investments and returns are in the venture financing industry. According to Singh, the reason why venture firms are looking for those astronomical returns is because their funds are getting much larger. It doesn’t make sense for them to focus on smaller returns if they have a behemoth fund. It is easier to raise $300 million than $50 million because there is promise of a higher return. Singh discusses that small exits can still make money if you don’t have such a large fund to maintain. “Traditional venture firms are always going for homeruns, where as I’m fine with getting singles and doubles and the occasional home run is always nice”, said Singh. Then using data analysis he can figure out how to make fewer bad investments.
He chooses to invest in the gap between seed and Series A (which is associated with the Series A Crunch). However, Singh dislikes the categorizing of rounds and prefers to think about companies based on their specific needs. There are a lot of angel and seed investors and he says that early stage funding is very much available for those companies it just that when getting into higher rounds of financing where it gets tricky. “$2 to $3 million is hard for seed round investors to handle”, said Singh. Those companies that he does fund must have revenue coming in, and have potential to be high growth. He puts a small amount of money in initially and wants to see how a company does, in order to “see how this works”. He has invested in 8 companies so far, and hoping to invest in 50 to 60 companies total in the next 18 months. He makes 40 to 60 early stage investments at about a quarter of a million (which is 25-30% of the fund) and then waits to invest the other 70% of the fund in companies that prove themselves from his initial investments.
Singh elaborates on his supervisory role that shares characteristics to Coats’ approach. Singh says, “at the early stage, the function of the board is governance: making sure money is accounted for, all rules are followed, and the i’s are dotted. Later it will become a sounding board for a CEO, and also the body that decides to fire / hire the CEO”. He doesn’t see the lack of board seats as a disadvantage in instructing a company. He believes that the 70% of the fund that is sitting their for financing is an implicit motivation for the founders to stay on track with Singh’s expectations and advice. At the end of the day he doesn’t see the venture capitalist’s role as the instructor makes that much of a difference, and it is the founder that will turn a company around if needed. He expects on average a 3-5x return over a 5-7 year period. He’s usually getting 5-8% of a company. He says, “80% [of portfolio companies] might be nothing, the next 10% will get 1x return, the next 5% will see a 2x return, the next 4% will see a 3-10x return, and the final 1% will have an outsized return”.
The data is primarily directional, and doesn’t mean that there is an automatic investment. Humans make the decisions, and sometimes they go against what the model is telling them. He views it as a way for him to make better decisions, rather than making them for him. They seem to strictly do co-investments but aren’t shy from doing a few solo investments here and there. Most of their investments are syndicated deals. They differ from Correlation Ventures’ approach of valuing the other investors, because Singh thinks that it isn’t an accurate signal anymore. “You don’t even know if they did correct due diligence”, said Singh. However Singh can still do in depth due diligence faster than most, thanks to their home-made checklist they can get 90% of the information they need right away.
Putting it simply Singh talked about how he wants Disruption Corporation to be the Goldman Sachs of the private market. Goldman provides research and investments, as well as a plethora of other services and products, for the public market. Singh doesn’t see why that can’t be done for the private market. He elaborated on this private vs. public market difference, saying that the private market is where the public market was 30 years ago. The public market back in the day was mostly powered by paper. In order to make a trade, paper orders had to be sent around the trading floors. In fact, they had to close the exchange down on Wednesdays in order to file all the paper orders. Then the 1990s came and a lot of the backend of the stock exchange was advanced with technology, and soon all trades would be processed electronically.
He also talks about how the private market is one of the last remaining ways for someone to generate true wealth. Someone can probably make a 10% return per year in the public market, however that same person has the potential to make 300% in the private market. He talks about how there are 24 hour TV channels devoted to the public market but nothing like that for the private one. Singh tries to apply the same playbooks of the public market and says investors like to see that. Today, the inflection point from a paper to an electronic system has been crossed in the private market. For instance, $20 to $30 million was invested on AngelList last year.
For further insight into venture capital quantitative analysis stay tuned for Part 3, my interview with Paul Singh of Disruption Corporation.