IA Venture Strategies - Working to Build a Better Venture Mouse-trap
As was ably covered by Dan Primack in PEHub, I am starting a new venture fund. However, as my friends and venture colleagues know, I am extremely down on what the venture industry has become. To be clear, it is less an issue of structure (management + incentive fees in a GP/LP structure) and more an issue of size. It is clear to understand how motivations get skewed when venture firms effectively become asset managers, where the management fees alone are sufficient to make the partners rich and investments must become increasingly large and non-venture like. Growth capital is not venture capital in my parlance. Venture capital means funding "ventures" - taking on early-stage risk - and actively helping companies execute their plans and achieve their potential. I have a theory that the largest a true venture fund can be, which means, having a seed-stage investment charter together with a "life cycle" approach to investing (leaning into winners, deploying larger amounts of capital in Series A and B rounds, if necessary) is around $300 million. But I digress...
I decided to start my fund after determining that many of the deals I was seeing were both strategic and thematic, strategic to my trading company and thematic in that they all had a common thread - helping to manage and extract value from massive, often real-time data sets - "big data" in jargon. Rather than prosecute them as an angel, I felt a fund structure would better enable me to "size up" in particular deals and to cast a wider net across the big data domain. I wanted the fund to be small ($25 million stated goal, but with the ability to go a little higher) and I wanted it to be different than most venture funds I know, who have raised money largely from pension funds and endowments. I really wanted the fund to be an extension of my activities as an angel, where I frequently build syndicates of value-added angels and select venture firms to help de-risk the portfolio companies and create a network effect across a particular domain. This approach has helped me win deals from conventional venture firms that couldn't (or wouldn't) bring such a syndicate to the table and generally had terms that were more oppressive than those I offered (less about valuation, more about participation and specific protective provisions). So how to create a fund that achieved my value-added investor objectives and offered the network effects I was seeking...
My answer was to raise money from "non-traditional" investors, e.g., strategic firms and individuals with knowledge of and deep interest in the big data domain, focusing on verticals with particularly acute data problems. Further, my explicit goal was to bring such strategic LPs to the table as part of a "big data ecosystem" I am creating among my Limited Partners, my venture portfolio companies, my trading company, and leading academics and thinkers in the field. Big data problems are, by their nature, big, and substantially benefit from collaboration across a wide array of domains. For instance, this is why there are several open-source database projects currently in operation, because the problems are growing at such a rapid rate and are so complex that discrete teams are often not best equipped to tackle the issues at hand.
So investor engagement, and not just money, is a ticket to play in this game. Funny thing is, they want engagement. They know that the value of the insights on the edge can impact their operating businesses to a far greater extent than any normal investment they could make. Their early involvement can also help to "de-risk" the portfolio companies, giving them early access to real customers with a strong motive to help out. My trading company also acts as a strategic partner, helping to evaluate the technologies of these big data opportunities and, on occasion, to become an early customer as well. Also, the LPs are excited about the network effects of participating in this ecosystem and sharing ideas with the other members of the community. Finally, they are interested in seeing the filtered deal flow and possibly helping with due diligence, becoming an early beta-tester and even a paying customer. It is really an institutionalized form of what I've been doing for the past five years, except with a unique array of people sitting around the table due to their operating companies and ability to test and deploy the tools, technologies and analytics being developed by the fund's portfolio companies. Neat stuff.
I am also extremely excited to be doing this fund in New York City. I have found NYC to be a great place to base my investing activities and couldn't think of a better place to start my fund. Proximity to Wall Street, big Media, the Pharma industry, several major insurers and health care providers, and a short flight to the Defense complex down in Washington D.C./Virginia. Fertile commercial ground on which to launch a big data fund. I already have three deals for the fund, one in the predictive analytics space (closed), one in database architecture (term sheet) and a NYC-based incubation of a new intrusion detection system. I couldn't be more excited to be working with my early companies and syndicate partners. I am also looking forward to working with those domain-expert angels and venture firms as partners in my portfolio companies. I've always believed in having the right people around the table, and having a venture fund won't change this one bit.
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