Lean Startup Challenge Keynote


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

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Lean Startup Challenge Keynote

  1. 1. Lean Startup Challenge Tom Eisenmann September 21, 2012
  2. 2. Ways to Launch• Build It and They Will Come…• Waterfall Planning• Just Do It! 2
  3. 3. 3
  4. 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. 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. 6. Hypothesis-Driven Entrepreneurship Pivot Viable Feasible Perish Desirable Product-Market Fit: Proceed with Scaling GenerateEnvision Test Hypothesis Business Persevere with Next TestVenture Using Minimum ModelConcept Viable Product Hypotheses 6
  7. 7. Business ModelAn integrated array of distinctive choicesspecifying a new venture’s unique customervalue proposition and how it will configureactivities—including those of its partners—todeliver that value and earn sustainableprofits. 7
  8. 8. Business ModelCustomer •Problem: unmet needs servedValue •Solution: launch MVP; product roadmapProposition •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 costsTechnology & •In-house vs. outsourced activitiesOperations •Value proposition for key suppliers, complement providers •Intellectual property protectionGo-to-Market •Mix of direct and indirect channels; margin/rights for partnersPlan •Mix of free vs. paid customer acquisition methods; cost for each •Customer Lifetime Value vs. Customer Acquisition Cost (LTV/CAC) •Incentives to race for scale, e.g., network effects, switching costsProfit •Size, growth of Total Addressable MarketFormula •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. 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. 10. Write Down Hypotheses! 10
  11. 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. 12. Launch Early? Why? Why Not?• With high uncertainty about • Disruption of mission- both problem and critical solution, must start learning activity, e.g., Dropbox ASAP • Early adopters’ needs do• Must observe radically new not match mainstream’s product in use to refine it • Reputational risk, esp. with – Corollary: less lean value with viral products and “better/faster/cheaper” concentrated markets products – Early users = small % total• Stealth rarely needed – Can use trial – Ries: Try to get big company brand, e.g., Textbookflix to steal idea 12
  13. 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. 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. 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. 16. Risk: False Positives and Negatives• 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. 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. 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. 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. 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. 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. 22. To Learn More…• Business model analysis – Osterwalder’s Business Model Generation – My 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