Lean Startup Challenge Keynote

Professor Thomas Eisenmann of Harvard Business School delivered his keynote address at the Lean Startup Challenge kickoff event for the 2012 program.

1. Lean Startup Challenge Tom Eisenmann September 21, 2012

2. Ways to Launch Build It and They Will Come… Waterfall Planning Just Do It! 2

3. 3

4. Lean Startup Principles Most startups fail because they waste $$ building and marketing a product that no one wants Instead, formulate hypotheses about business model , then launch early with a minimum viable product , i.e., smallest feature set needed to test a hypothesis Goal: validated learning via rigorous experiments Ries: “It’s not a test if you can’t fail” Pivot when a hypothesis is disconfirmed, i.e., revise hypothesis then rapidly test it with another MVP Repeat process until hypotheses are fully validated and you have product-market fit Don’t scale aggressively until you have PMF 4

5. Lean Startup Myths Lean = bootstrapped Lean = crappy product Lean = driven by customer feedback Lean = new approach Lean = only for web/mobile products Lean = only for startups 5

6. Hypothesis-Driven Entrepreneurship Envision Venture Concept Generate Business Model Hypotheses Test Hypothesis Using Minimum Viable Product Pivot Perish Product-Market Fit : Proceed with Scaling Persevere with Next Test 6

7. Business Model An integrated array of distinctive choices specifying a new venture’s unique customer value proposition and how it will configure activities —including those of its partners—to deliver that value and earn sustainable profits . 7

8. Business Model Customer Value Proposition Problem: unmet needs served Solution: launch MVP; product roadmap Target Customer Segments: early adopters and beyond Willingness to Pay vs. Total Cost of Ownership (“whole product”) Basis for sustained differentiation and/or cost advantage Complements needed: who will provide, under what terms? Penetration vs. skimming price Switching costs Technology & Operations In-house vs. outsourced activities Value proposition for key suppliers, complement providers Intellectual property protection Go-to-Market Plan Mix of direct and indirect channels; margin/rights for partners Mix of free vs. paid c ustomer acquisition methods; cost for each Customer Lifetime Value vs. Customer Acquisition Cost (LTV/CAC) Incentives to race for scale, e.g., network effects, switching costs Profit Formula Size, growth of Total Addressable Market Variable contribution margin Fixed costs; breakeven sales as % of TAM Investment (PPE & WC)/sales ratio Cash flow profile: maximum need; net positive point 8

9. Falsifiable, Specific Hypotheses Falsifiable: can be rejected via test (Ries: “It’s not a test if you can’t fail”) Specific: not “Product will spread by word of mouth”; rather “Viral coefficient > 0.4” Measurable: Ideally, hypotheses require quantitative measures for validation 9

10. Write Down Hypotheses! 10

11. Specify MVP Tests and Launch! Minimum Viable Product : Smallest set of features/activities needed to test a business model hypothesis “Launch early and often” i.e., ASAP, put a real product in the hands of real customers in a real world context Fast cycles/small batches reduce waste by accelerating feedback and making it easier to diagnose/fix problems 11

12. Launch Early? Why? With high uncertainty about both problem and solution, must start learning ASAP Must observe radically new product in use to refine it Corollary: less lean value with “better/faster/cheaper” products Stealth rarely needed Ries: Try to get big company to steal idea Why Not? Disruption of mission-critical activity, e.g., Dropbox Early adopters’ needs do not match mainstream’s Reputational risk, esp. with viral products and concentrated markets Early users = small % total Can use trial brand, e.g., Textbookflix 12

13. MVP Design Reduce product functionality to test hypotheses about “need to have” features before building “nice to have” features Example: foursquare alpha Rely on temporary/makeshift operations if doing so doesn’t impact feedback quality Examples: Aardvark turk testing; RTR PDF test Smoke test: offer product that doesn’t yet exist, via landing page test, video MVP, letter of intent, etc. Better for rejecting hypotheses than validating them 13

14. Partial vs. System Tests Partial test of a single “known unknown” Examples: supplier letter of intent; probation for new hire Give priority to tests that eliminate lots of risk at a low cost, e.g., patent search Issue: run partial tests in series or in parallel? Parallel tests can speed time to market, but this risks wasted effort if H1 must be discarded due to failure of H2 test System test of entire model, at reduced scale Reveal “ unknown unknowns” Explore interactions between variables RTR adoption odds increase sharply after a consumer has had 7-8 interactions with brand, including PR and word-of-mouth referrals Consumer adoption of RTR depends on designer adoption, and vice versa. 14

15. Test Design When does validation require passage of time ? Retention/repurchase/referral rates Mainstream adoption requiring referrals Firms face Catch-22 when validation requires scale, and scale requires validation Cannot test demand if value depends on network size User base determines number of tests possible, which determines feature set, which determines user base… 15

16. Risk : False Positives and N egatives FP : sample only enthusiastic early adopters FN: reaction to badly-built prototype rather than the venture concept If RTR had started with PDF test, it might have offered wrong dress assortment and observed false negative 16

17. Lean Startup Data Sources Qualitative Customer Interviews Focus Groups Concierge MVP Usability Tests Customer Service Interactions Quantitative Customer Surveys Smoke Tests: Landing Pages, Letters of Intent A/B Tests Funnel/Cohort Analysis Viral Coefficient CAC vs. LTV Net Promoter Score 17

18. Pivot Lessons Pivots are NOT a goal ! Pivots are costly , especially with a strong reality distortion field Employees, investors, partners are sold on vision Entrepreneur has ego invested in vision It’s possible to pivot too quickly Post-PMF, pivots continue as market evolves (e.g., Dropbox, Chegg ?) 18

19. Lean Psychology Be ready for surprises , including information not generated by tests Be wary of cognitive biases and remain open to disconfirming data Optimism bias, planning fallacy, confirmation bias, sunk cost fallacy Ego-defensive behavior can keep entrepreneur from acting on disconfirming data 19

20. Some Limitations of Lean Logic Cannot “launch early and often” when: Mistakes must be limited (e.g., pacemaker software) Product development cycles are intrinsically long due to science/engineering challenges (e.g., clean tech, “Chunnel”) Less need to launch early/often with low demand risk Strong unmet demand (e.g., cancer cure) “Me, too” product (but, must still test execution capability) Founder with domain expertise (but, be wary of success-induced biases) 20

21. B2B: Fewer Pivots Less feedback available Longer cycles due to multi-level process Fewer cycles due to costly system integration, training Fewer trial candidates Less feedback needed Failure risks mandate a more fully-evolved product B2B products more likely to serve existing market (?) Issue: Will more B2B products cross over from B2C, like Dropbox (also, WiFi, iPhones )? 21

22. To Learn More… Business model analysis Osterwalder’s Business Model Generation M y posts at http:// bit.ly / oiWqPJ Lean startups Ries’s The Lean Startup; blog Blank’s Four Steps to the Epiphany; blog Startup management practices : my reading lists at http://bit.ly/f9vSyP 22