Podchaser Logo
Home
243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)

243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)

Released Monday, 10th August 2020
 1 person rated this episode
243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)

243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)

243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)

243. A Quantitative Approach to PMF, Tribe's 8 Ball for Objective Evaluation, and Approaches to Reduce Talent Biases (Jonathan Hsu)

Monday, 10th August 2020
 1 person rated this episode
Rate Episode

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?

To listen more, please visit http://fullratchet.net/podcast-episodes/ for all of our other episodes.

Also, follow us on twitter @TheFullRatchet for updates and more information.

Show More
Rate

Join Podchaser to...

  • Rate podcasts and episodes
  • Follow podcasts and creators
  • Create podcast and episode lists
  • & much more

Episode Tags

Do you host or manage this podcast?
Claim and edit this page to your liking.
,

Unlock more with Podchaser Pro

  • Audience Insights
  • Contact Information
  • Demographics
  • Charts
  • Sponsor History
  • and More!
Pro Features