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Can we pick winners among
technology startups?
ARISTOS DOXIADIS
BIG PI VENTURES
€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
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
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
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
Scalability
Global market
Innovation
Geography
Filters
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)
Experience
Age? 30 to 50 (Azoulay et. al.)
Complementary skills (2-3 founders)
International
Degrees and employers
Focus
Heuristics: Team
Patents (substance)
Publications
Design
Community (basis for network)
Heuristics: Trenches
Initial users: quality and engagement
If there are numbers of users: retention, monthly growth
Heuristics: Traction
Horizontal vs vertical markets (dilemma)
Big today, or growing?
Heuristics: TAM
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
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
… 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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Doxiadis stochastics dec 2018

  • 1. Can we pick winners among technology startups? ARISTOS DOXIADIS BIG PI VENTURES
  • 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. 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. 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. 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
  • 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. Experience Age? 30 to 50 (Azoulay et. al.) Complementary skills (2-3 founders) International Degrees and employers Focus Heuristics: Team
  • 10. Initial users: quality and engagement If there are numbers of users: retention, monthly growth Heuristics: Traction
  • 11. Horizontal vs vertical markets (dilemma) Big today, or growing? Heuristics: TAM
  • 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. 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. … 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?