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Doxiadis stochastics dec 2018

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Talk at the Greek stochastics conference 22 Decembre 2018

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Doxiadis stochastics dec 2018

  1. 1. Can we pick winners among technology startups? ARISTOS DOXIADIS BIG PI VENTURES
  2. 2. €50 million capital Target: 3x return = €150 million from exits €42 to invest in 20+ companies Average €2m, but initial ticket €1m. Follow-ons in 5-8 cases Fund economics 1/2
  3. 3. To get back €150m, we need: Two exits that will return €50m each Three to eight exits that will return €50m in total Fund stake in each exit: 15% to 20% Valuations: €250m to €350 for stars; €50m for successes Fund economics: exits 2/2
  4. 4. We will receive 500 to 2000 proposals (in 3 to 5 years) We will examine 50 to 100 in some depth We will invest in 20 to 25 We hope to have 3 to 8 successful exits Funnel
  5. 5. Pre-seed and seed stage, therefore: No metrics for the specific venture Data when we decide: people; a prototype; a business plan; (maybe) a few users Is it like: stock picking OR predicting a revolution OR predicting a hurricane? Nature of problem
  6. 6. Scalability Global market Innovation Geography Filters
  7. 7. Team Technology (product) Trenches (defense: IP or network effects) “TAM” = Total Addressable Market Traction (initial sales OR sales growth) Timeline Criteria: Five Ts (plus one)
  8. 8. Experience Age? 30 to 50 (Azoulay et. al.) Complementary skills (2-3 founders) International Degrees and employers Focus Heuristics: Team
  9. 9. Patents (substance) Publications Design Community (basis for network) Heuristics: Trenches
  10. 10. Initial users: quality and engagement If there are numbers of users: retention, monthly growth Heuristics: Traction
  11. 11. Horizontal vs vertical markets (dilemma) Big today, or growing? Heuristics: TAM
  12. 12. Big Pi 12 Π 3 Ts for Research-based teams Defense Patents Trade secret(s) Superior know- how Team Key technology contributor(s) Product vision, ideally from the core team Understand the space FULL TIME! Product A practical problem that affects users At least one large user category
  13. 13. Big Pi 13 Π Targets for research-based ventures Stage 3 Sales growth Operations Stage 1 IP, trade secrets, know- how Minimum Viable Product (MVP) => prototype Relation of IP to MVP Stage 2 Real clients Sales process Business model • tech or product • big or small clients
  14. 14. … and if we can do it systematically: a. Will it change the focus of innovation? b. Will venture capital survive? So: Can we predict winners?

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