Lean Startup Challenge

Tom EisenmannSeptember 21, 2012

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Ways to Launch

• Build It and They Will Come…• Waterfall Planning• Just Do It!

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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

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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

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Hypothesis-Driven Entrepreneurship

EnvisionVenture Concept

Generate Business Model

Hypotheses

Test Hypothesis Using Minimum Viable Product

Pivot

Perish

Product-Market Fit: Proceed with Scaling

Persevere with Next Test

Desirable

Feasible

Viable

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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.

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Business ModelCustomer 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 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 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

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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

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Write Down Hypotheses!

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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

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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

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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

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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.

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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…

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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

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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

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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?)

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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

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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)

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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)?

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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