🔮 I’m doing research in venture capital, AMA

aka Why don’t VCs do research?

“Best case, we’re going to outperform the market by building the best research program in venture capital. Worst case, I’ll spend a lot of time in my armchair mulling over the future of peer-to-peer, decentralized, zero-shot, NFT agent-based simulations.”

Why is research (so)rare in VC?

Research is a luxury. Ain’t nobody got time for that. We’ve got LP cash to spend it as soon as possible in the absolute best companies we can find. Every fund is time-poor. and so the idea of a team that sits around stroking their beards thinking about possible futures seems…like a waste of time? (in the time it takes for me to think about the future of databases, Tiger has led 2 deals) Also, the investment team is super smart and they can do practical research when diligence requires it, right? “Hey look this quantum photonics deal came in, go away and look into the market, would you?” Also I think there’s probably a view that it just doesn’t work. I could make the argument: long-term research is pointless operating under conditions of high uncertainty and when in the end talent is one of the best predictors of success. It’s great to know that privacy-enhancing technologies are ready for investment and we think the market is going to be huge, but the fund lives or dies on its ability to pick the winners right? Well, I dunno.

What is research for?

Research means many things to many people. In fact, it touches on all fund activities. It’s best to discuss it in the context of the objective: diligence, technical, marketing, deals, network, and thesis. Also, there’s research as it relates to data and how a fund manages data, but that feels more like engineering than research, although sometimes the work is described as research or data and research. Francesco Corea at Balderton is a leading light in that domain.

1. Diligence — The most common activity for a research team is to do internal diligence. Either reactively when a deal comes in or proactively to better understand a space or technology for future investments. All researchers are pulled into diligence at some point and it’s the most obvious way to add value to the fund.

2. Technical Diligence — This is common in crypto e.g. Paradigm, Thomas Walton-Pocock at Fabric, InflectionVC, et al. But less common in ‘traditional’ venture capital as GPs typically have experience in the sectors they are investing in e.g. hardware or healthcare. And also typically have a budget for external experts or venture partners for due diligence as required. This technical research especially in crypto extends to operational work like staking tokens or governance.

3. Marketing — Although only a part of what they do, this is the Atomico State of Europe, Mary Meeker State of the Internet, Different Funds State of DeepTech Venture, and Air Street’s State of AI. Good quality research lends itself to easy marketing, although there is a balance between doing research because you want to grow reach versus doing it because you want to grow rich. Research for marketing can easily fall into content marketing. If you have a KPI for number of readers or downloads then you might be sailing too close to the wind…

4. Deals— This was the MMC approach when led by David Kelner with the series on the State of AI State of AI paper. And often the objective behind startup landscape maps. This sort of research is lower down the funnel than the research for marketing and I assume anyone that does this sort of research is measured against inbound.

5. Ecosystem — let’s take Sam Arbesman and Lux case. They don’t have a team of researchers or a function, but rather Sam, who is a complexity scientist, helps grow the Lux ecosystem in ways he thinks will be important. In theory, every member of the fund is growing the network which if used effectively can compound in value. Somebody like Sam has freedom to follow his curiosity and to speak to interesting people without worrying if there is an investment opportunity. That freedom is a great way to develop novel insights.

6. Thesis — Typically a fund is built around an investing thesis. “Hey look, the energy transition is going to generate outsized returns over the next 10 years, I know loads of startups, give me money and I will make good investments.”There isn’t a research function because the thesis is pre-agreed by founding partners to raise the fund. Subsequent funds raised generally invest in different rounds, markets, regions, technologies, etc. The work I did at Outlier Ventures was an exception because we were not a GP/LP fund and so had the freedom to iterate on the investment strategy without being tied to what we promised LPs three years ago. Similarly at Lunar Ventures the thesis is about a lack of technical VCs and can adopt as technology progresses.

The reality is that anyone doing research at a venture fund today might be doing bits and pieces of each of these. Atomico is pretty much doing all 6 of these things bundling research and data into investment products for the business. For others it might be a bit more ad hoc with unclear objectives.

We strongly believe you have to separate the short-term, tactical needs of the investment team with the long-term, strategic needs of research. The main reason is that if you try to do both, the incentive will always be to focus on the short-time. (e.g. we need to do 5 customer calls before the deal closes next week). Also you rarely find the same person to be world-class at both these things. The best investors are out there hustling and writing pithy tweets to attract startups (I assume that’s how it works). But a researcher basically should be reading books, talking to experts, and following curiosity that is likely in the short term to have no practical value. If you find a researcher adding practical value, you should worry. (jk)

So what are we doing at Lunar Ventures?

I’m leading our research program uncovering underpriced theses on the future. We’ve already validated the model a bit with our series on privacy enhancing technologies and collaborative computing (™). We think this allows us to create ‘mini-thesis’ areas in which we understand the direction of a market and can assign some probabilities on future scenarios. So with privacy tech, we looked at the market and said, “hey people aren’t really getting the implications of being able to share information by math rather than law. We think because of X, Y, Z, it’s more likely than not that we will see private and secure compute, so let’s invest in that stuff”. We are looking at post big-data at the moment and asking: will data continue to make machine learning algorithms better? Or is there an underpriced scenario in which it’s the algorithm and not the data that matters? Other stuff bubbling up through our Roam:

• Hardware pluralism: what does a future world look like with analog and digital chips?

• What happens with simulated environments for reinforcement learning agents combined with virtual worlds?

• The intersection of tribes and tools: how does a lens of collective identity rather than the s-curve or surge cycle change the analysis of the future of crypto?

And?

Well research = insights =… profit. But more than that… legacy? Something that will live on after our deaths and make our lives just that little bit more meaningful? Probably not, but look, I just think it’s weird that the rest of finance has research departments staffed with hundreds of people. And VCs are running around doing it themselves? It always seemed a bit off to me.

Obviously this isn’t an AMA (yet) so if you are doing research in VC please get in touch, and if you’re thinking of a career in VC research please AMA. @lawrencelundy

Thanks to Sam Arbesman and Tom Wehmeier for reading drafts of this essay.