Notes on Lean Startup Skillshare Session

I had the pleasure of attending Eric Ries's "Lean Startup Strategies" Skillshare talk last night. I greatly enjoyed his book, and seeing him in person highlight a lot of the key points and bring up many additional examples was really useful.

Below are some of main takeaways  (some are highlights of his main book points and others are more supplementary).

Intro

• Started out as a programmer
• Programmed amazing technology that nobody was using
• Entrepreneurship is a domain of extreme uncertainty

Part 1: Vision

• Entrepreneurial management (photo montage that's usually skipped over in movies)
  
• Different from general management
• Lean manufacturing inspiration
• Difference between value and waste
• Whose eyes do you use to evaluate the product line (when don't know your customer yet)?
• Goal of a startup: figure out the right thing to build (what customers want and will pay for) as quickly as possible
• Was afraid to launch IMVU, but then no one even downloaded the product
• Even though used agile, had to throw away tons of code
  
• "Learning" is oldest excuse in book when fail
• Could've learned the same lesson with 1 landing page or 1 IM network connected instead of connecting to all 6
• Pivot = a change in strategy, not a change in vision
• Change in product = optimization
  
• Startup = human institution designed to create a new product or service under conditions of extreme uncertainty
  
• Validated learning vs. plain learning
  
• Reality distortion field (entrepreneurs and sociopaths)
  
• Cohort metrics
  
• Spent $5/day; bought traffic from Google at $0.05/click
• Consistently saw 1% conversion rate
• Value vs. waste: only things that contribute to learning are valuable
  
• Making money, press, awards: not valuable, just consequence of learning
  
• Audacity of zero: easier to get resources when never tried to get users
  
• From alchemy to science: experiment to test which strategy makes sense and which is crazy
  
• Scientific method vs. product astrology
  
• Eric's law of Google Analytics: no matter how bad you're destroying your company, there is at least one graph in Google Analytics that is up and to the right.
• Goal: not best analytics, but best product (and learning to get there)
  
• Split testing
• Rolling out lean to team: incubate in one small division then roll out to entire group
• Add "validated" column to scrum board
• Kanban: capacity constrain size of each bucket
• Will be painful because team will grind to a halt until everyone gets validated learning; will instill culture of only seeking validated learning

Part 2: Steer

• Build-measure-learn feedback loop
  
• 2 hypotheses: value hypothesis, growth hypothesis
• Beyond "the right place at the right time"
  
• Genchi gembutsu (go and see for yourself)
  
• Basing strategy decisions on firsthand understanding of customers
  
• Minimum viable product: not smallest product imaginable; just the fastest way to get through build-measure-learn loop
• Video MVP (took 2 years to build Dropbox's magic technology)
• Concierge MVP
• Little fear to launching MVP
• Try your best to get your idea stolen; no big company will do it
• innovation accounting
• It's better to have bad news that is true, than good news that we just made up.
• in general management, forecasts and operating plans work because they have long and stable operating history.
  
• 3 learning milestones: establish the baseline, tune the engine, pivot or persevere
• "10% of visitors signing up for free trial" should not be in 2 point font in Appendix B of business plan; it is a leap of faith assumption; it should be a red banner in the office saying, "If 10% of our visitors do not sign up, then our company will cease to exist."
• Metrics: actionable (showing cause and effect), accessible, auditable
• Innovation accounting leads to faster pivots
• Pivot = strategic hypothesis

Part 3: Accelerate

• Small batches in entrepreneurship
  
• Sustainable growth: new customers come from actions of past customers; when you have to buy customers, you trade equity (permanent) for growth (transient)
• Growth through word of mouth
• Growth as a side effect of product usage (viral or publicly shown good)
• Engines of growth: sticky engine, viral engine, paid engine
• Product/market fit: binary; if you're asking if you have it, you don't