The Full Ratchet (TFR): Venture Capital and Startup Investing Demystified 243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)
Aug 10, 2020
46:07
Jonathan Hsu of Tribe Capital joins Nick to discuss how to Acquire Data, Build Abstractions and Do Research. In this episode, we cover:
- Walk us through your background and path to VC
- What’s the thesis at Tribe Capital?
- How do you define PMF?
- Could you explain what the 8 Ball diligence framework is?
- When is a deal too early -- how much data (or over what time continuum do you need data) in order for the model to assess appropriately?
- Just for evaluation or also sourcing?
- Can you apply this tool to a range of business types (ie. SaaS vs. Maretkplaces vs. User-Growth, etc.)?
- How to avoid false positives? Data looks great for early phase -- early market… How do you know that it isn’t luck and the company didn’t stumble onto something with early signals of PMF but they don’t have the insight or flexibility to evolve the business through growth and scale phases?
- What aspect of early stage investing don’t you use data for?
- Why is this not appropriate to measure with data?
- Loss ratio goes down -- do you think it increases potential outcome size?
- On the evaluating side of things, it seems like Tribe has a big emphasis on using data to understand early product market fit. What is your definition of product market fit?
- Does Tribe conduct portfolio support in a similar way?
- What happens when data and intuition clash?
- Do you always lean one way or another? Examples of either?
- How do you account for exogenous factors?
- Ever been a scenario w/ a company misrepresenting data (fake data)?
- How long did it take to build this out -- what is the current team structure of investors, developers, and data scientists?
- Where do you and the team at Tribe need to improve most?
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