Responding to a popular request, we are now sharing transcripts of our investor podcast interviews in this new series. The following interview with Curtis Feeny was recorded in April 2018.
Curtis Feeny, Managing Director at Silicon Valley Data Capital, talks about his firm’s investment thesis around Big Data and Machine Learning.
Sramana Mitra: Let’s get our audience introduced to you. Tell us about your fund, investing focus, a bit about your background. Let’s get the audience to know you.
Curtis Feeny: Our fund is an enterprise software-oriented fund in the seed and A round investments. We’ve already done investments ranging from a quarter of a million to $5 million. It’s a range of investment size. The fund size is $60 million. We have a focus on data analytics.
My partner and I had been investing together for four to five years in like-minded enterprise software deals with a heavy enterprise analytics focus. That has given us a lot of time to get to know each other and realize that we can do a fund together to bring analytics solutions to the Global 1000 enterprises who really need to move into real-time processing of high volume, high variety, high velocity data the Googles and the Amazons of the world are doing. The pre-internet incumbents of the world are all getting the same amount of data explosion that everyone else has. They need to build next-generation systems around that.
Silicon Valley Data Capital is a fund exclusively focused on that solution for the enterprise. Our investors are aligned with that. One of our investors is the biggest public company in data analytics. It’s a $17 billion NASDAQ company. They cover seven verticals of enterprise. We are their eyes and ears on early-stage technology companies in that space.
We have very strong relationships with large enterprises who have purchased companies that Jim and I have been involved in. We have some strong enterprise connections that give us a view of what enterprises want and then also help us vet.
Sramana Mitra: You said there are particular industry sectors within that scope of work that your investors have particular expertise in. Would you like to elaborate on what those are?
Curtis Feeny: They tend to be the data-intensive industries that are all in the process of moving along the lines of what our investment thesis is. Insurance is a big one. They also include financial services, retail, oil & gas, healthcare, tech, and real estate. Then we also have an investor that’s one of the largest logistics companies in the world.
Sramana Mitra: Could you also double-click down on what your definition of stage is in terms of seed and Series A? What do you like to see in these kinds of companies that you want to invest in? What level of validation are you looking to see? Are you looking to see MRR metrics or number of customers?
Curtis Feeny: We typically don’t expect much MRR. The reason is, given our size, we come in the sweet spot of around $3 million and get 10% to 20% ownership. We don’t expect the company to have multi-million dollar annual revenue coming in. We expect them to just be getting to revenues. What we look for is the quality of the team.
Particularly in the data analytics space, the quality of the team is a huge differentiator for anybody who’s bringing a solution to market. It attracts the best people, the best customers, partners, and channel. We put a really high bar on quality of the data analytics team bringing the solution to market.
In the enterprise focus, we look at the return on investment that it provides the customer. In bringing change to enterprise, you need a quantum improvement to bring a new product in. We look for strong ROI solution to enterprise whether it’s bringing top-line revenues, reducing costs, or increasing efficiencies.