"The Beginning of an Asset Class Revolution" with Mike Arpaia (Moonfire)
DDVC #50: Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts, and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
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Data-driven VC Interview Series - Part #2
Following the successful launch of the “Data-driven VC Landscape 2023” and the positive feedback on the first episode of this Q&A series with Pietro Casella from EQT, I’m excited to continue with another high-profile thought leader: Mike Arpaia. Mike joined London-based Moonfire in 2020 as a Partner and is responsible for defining and executing the firm's AI-focused technology strategy.
Thank you for sharing your valuable perspectives below, Mike! 👀
#1 What’s the status of the VC industry in terms of data-driven initiatives and AI?
MA: I think that the VC industry is just starting to embrace data-driven tactics. There are a few firms that have been all-in on this way of working for a while (Moonfire included) and there are increasingly more firms that are starting to make quantitative hires but I really believe that we are just at the beginning of an asset class revolution.
#2 Why should VCs become more data-driven?
MA: We all know that the economics of VC allow for a solo GP or a small firm to make strong returns without any large-scale data infrastructure. But if you're trying to build a financial institution that can outlast any one partner, you need to capture institutional knowledge via technology.
If you want to improve your decision quality at a faster rate, you need to engage with rigorous decision science. Basically - if you want to outperform for a long time, you need to invest in data, science, and technology.