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The Lean Startup
                         #leanstartup



           Tokyo Edition
             Eric Ries (@ericries)
http://StartupLessonsLearned.blogspot.com
Most Startups Fail
Most Startups Fail
Most Startups Fail
Most Startups Fail
• But it doesn’t have to be that way.
• We can do better.
• This talk is about how.
What is a startup?
• A startup is a human institution designed to
  deliver a new product or service under
  conditions of extreme uncertainty.



• Nothing to do with size of company, sector of
  the economy, or industry
A Tale of Two Startups
Startup #1
A good plan?
• Start a company with a compelling long-term
  vision.
• Raise plenty of capital.
• Hire the absolute best and the brightest.
• Hire an experienced management team with tons
  of startup experience.
• Focus on quality.
• Build a world-class technology platform.
• Build buzz in the press and blogosphere.
Achieving Failure
• Company failed utterly, $40MM and five years
  of pain.
• Crippled by “shadow beliefs” that destroyed
  the effort of all those smart people.
Shadow Belief #1
• We know what customers want.
Shadow Belief #2
• We can accurately predict the future.
Shadow Belief #3
• Advancing the plan is progress.
A good plan?
• Start a company with a compelling long-term
  vision.
• Raise plenty of capital.
• Hire the absolute best and the brightest.
• Hire an experienced management team with tons
  of startup experience.
• Focus on quality.
• Build a world-class technology platform.
• Build buzz in the press and blogosphere.
Startup #2
IMVU
IMVU
New plan
• Shipped in six months – a horribly buggy beta
  product
• Charged from day one
• Shipped multiple times a day (by 2008, on
  average 50 times a day)
• No PR, no launch
• Results: 2007 revenues of $10MM
Lean Startups Go Faster
• Commodity technology stack, highly leveraged
  (free/open source, user-generated
  content, SEM).
• Customer development – find out what
  customers want before you build it.
• Agile (lean) product development – but tuned
  to the startup condition.
Commodity technology stack
• Leverage = for each ounce of effort you invest
  in your product, you take advantage of the
  efforts of thousands or millions of others.
• It’s easy to see how high-leverage technology
  is driving costs down.
• More important is its impact on speed.
• Time to bring a new product to market is
  falling rapidly.
Customer Development
                             Continuous cycle of customer
                              interaction
                                 Rapid hypothesis
                                  testing about
                                  market, pricing, custom
                                  ers, …
                                 Extreme low cost, low
                                  burn, tight focus
                                 Measurable gates for
http://bit.ly/FourSteps
                                  investors
Customer Development
                         Continuous cycle of customer
                          interaction
                             Rapid hypothesis
                              testing about market,
                              pricing, customers, …
                             Extreme low cost, low
                              burn, tight focus
                             Measurable gates for
                              investors



http://bit.ly/yx8K4
Agile Product Development
              (A tale of two startups, revisited)

• Principles drawn from Lean Manufacturing
  and Toyota Production System

• These examples are drawn from software
  startups, but increasingly:
  – All products require software
  – All companies are operating in a startup-like
    environment of extreme uncertainty
Traditional Product Development
                      Unit of Progress: Advance to Next Stage

                   Waterfall

                  Requirements


                       Specification


                                 Design
Problem: known


Solution: known
                                  Implementation


                                          Verification


                                                Maintenance
Agile Product Development
                     Unit of Progress: A line of Working Code




                      “Product Owner” or in-house customer




Problem: known


Solution: unknown
Product Development at Lean Startup
          Unit of Progress: Validated Learning About Customers ($$$)

                                    Customer Development




                           Hypotheses,
Problem: unknown           Experiments,
                           Insights
                                                                Data,
Solution: unknown                                          Feedback,
                                                             Insights
Minimize TOTAL time through the loop

                IDEAS




      LEARN              BUILD




        DATA
                         CODE


               MEASURE
There’s much more…
                                                        IDEAS


Learn Faster                                                                                       Code Faster
Split Tests
                      LEARN                                                      BUILD               Unit Tests
Customer Interviews                                                                              Usability Tests
Customer Development                                                                   Continuous Integration
Five Whys Root Cause Analysis                                                        Incremental Deployment
Customer Advisory Board                                                      Free & Open-Source Components
Falsifiable Hypotheses                                                                        Cloud Computing
Product Owner Accountability                                                          Cluster Immune System
Customer Archetypes                 DATA                                CODE            Just-in-time Scalability
Cross-functional Teams                                                                             Refactoring
Semi-autonomous Teams                                                                      Developer Sandbox
Smoke Tests                                                                          Minimum Viable Product



                                Measure Faster
                                                   MEASURE
                                Split Tests                          Funnel Analysis
                                Clear Product Owner                  Cohort Analysis
                                Continuous Deployment            Net Promoter Score
                                Usability Tests             Search Engine Marketing
                                Real-time Monitoring              Real-Time Alerting
                                Customer Liaison               Predictive Monitoring
The Lean Startup
• You are ready to do this, whether you are:
  – Thinking of starting a new company, but haven’t
    taken the first step
  – Are in a startup now that could iterate faster
  – Want to create the conditions for lean innovation
    inside a big company
• Get started, now, today.
Thanks!
• Startup Lessons Learned Blog
  – http://StartupLessonsLearned.blogspot.com/

• Getting in touch (#leanstartup)
  – http://twitter.com/ericries
  – eric@theleanstartup.com

• The Lean Startup Workshop
  – June 18 and October 30, 2009 in San Francisco
  – December 10, 2009 in New York
  – http://training.oreilly.com/theleanstartup/
How to build a Lean Startup
• Let’s talk about some specifics. These are not
  everything you need, but they will get you
  started



• Continuous deployment
• Split-test (A/B) experimentation
• Five why’s
Continuous Deployment
                                             IDEAS


Learn Faster                                                          Code Faster
Five Whys Root
                 LEARN                                        BUILD    Continuous
Cause Analysis                                                        Deployment




                              DATA                     CODE




                         Measure Faster
                                             MEASURE
                         Rapid Split Tests
Continuous Deployment
• Deploy new software quickly
   •   At IMVU time from check-in to production = 20 minutes


• Tell a good change from a bad change (quickly)

• Revert a bad change quickly

• Work in small batches
   •   At IMVU, a large batch = 3 days worth of work

• Break large projects down into small batches
Cluster Immune System
What it looks like to ship one piece of code to production:

 • Run tests locally (SimpleTest, Selenium)
     o   Everyone has a complete sandbox

 • Continuous Integration Server (BuildBot)
    o All tests must pass or “shut down the line”
     o   Automatic feedback if the team is going too fast

 • Incremental deploy
     o   Monitor cluster and business metrics in real-time
     o   Reject changes that move metrics out-of-bounds

 • Alerting & Predictive monitoring (Nagios)
     o   Monitor all metrics that stakeholders care about
     o   If any metric goes out-of-bounds, wake somebody up
     o   Use historical trends to predict acceptable bounds

 When customers see a failure:
     o   Fix the problem for customers
     o   Improve your defenses at each level
Rapid Split Tests
                                             IDEAS


Learn Faster                                                           Code Faster
Five Whys Root
                 LEARN                                         BUILD    Continuous
Cause Analysis                                                         Deployment




                              DATA                      CODE




                         Measure Faster
                                             MEASURE
                         Rapid Split Tests
Split-testing all the time
• A/B testing is key to validating your
  hypotheses
• Has to be simple enough for everyone to use
  and understand it
• Make creating a split-test no more than one
  line of code:
         if( setup_experiment(...) == quot;controlquot; ) {
            // do it the old way
         } else {
           // do it the new way
         }
The AAA’s of Metrics
• Actionable
• Accessible
• Auditable
Measure the Macro
• Always look at cohort-based metrics over time
• Split-test the small, measure the large
                       Control Group (A)   Experiment (B)
   # Registered        1025                1099
   Downloads           755 (73%)           733 (67%)
   Active days 0-1     600 (58%)           650 (59%)
   Active days 1-3     500 (48%)           545 (49%)
   Active days 3-10    300 (29%)           330 (30%)
   Active days 10-30   250 (24%)           290 (26%)
   Total Revenue       $3210.50            $3450.10
   RPU                 $3.13               $3.14
Five Whys
                                                IDEAS


Learn Faster                                                            Code Faster
Five Whys Root
                 LEARN                                          BUILD    Continuous
Cause Analysis                                                          Deployment




                              DATA                       CODE




                         Measure Faster
                                               MEASURE
                         Rapid Split Tests
Five Whys Root Cause Analysis
• A technique for continuous improvement of
  company process.
• Ask “why” five times when something
  unexpected happens.
• Make proportional investments in prevention
  at all five levels of the hierarchy.
• Behind every supposed technical problem is
  usually a human problem. Fix the cause, not
  just the symptom.
Thanks!
• Startup Lessons Learned Blog
  – http://StartupLessonsLearned.blogspot.com/

• Getting in touch (#leanstartup)
  – http://twitter.com/ericries
  – eric@theleanstartup.com

• The Lean Startup Workshop
  – June 18 and October 30, 2009 in San Francisco
  – December 10, 2009 in New York
  – http://training.oreilly.com/theleanstartup/

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2009_06_08 The Lean Startup Tokyo edition

  • 1. The Lean Startup #leanstartup Tokyo Edition Eric Ries (@ericries) http://StartupLessonsLearned.blogspot.com
  • 5. Most Startups Fail • But it doesn’t have to be that way. • We can do better. • This talk is about how.
  • 6. What is a startup? • A startup is a human institution designed to deliver a new product or service under conditions of extreme uncertainty. • Nothing to do with size of company, sector of the economy, or industry
  • 7. A Tale of Two Startups
  • 9. A good plan? • Start a company with a compelling long-term vision. • Raise plenty of capital. • Hire the absolute best and the brightest. • Hire an experienced management team with tons of startup experience. • Focus on quality. • Build a world-class technology platform. • Build buzz in the press and blogosphere.
  • 10. Achieving Failure • Company failed utterly, $40MM and five years of pain. • Crippled by “shadow beliefs” that destroyed the effort of all those smart people.
  • 11. Shadow Belief #1 • We know what customers want.
  • 12. Shadow Belief #2 • We can accurately predict the future.
  • 13. Shadow Belief #3 • Advancing the plan is progress.
  • 14. A good plan? • Start a company with a compelling long-term vision. • Raise plenty of capital. • Hire the absolute best and the brightest. • Hire an experienced management team with tons of startup experience. • Focus on quality. • Build a world-class technology platform. • Build buzz in the press and blogosphere.
  • 16. IMVU
  • 17. IMVU
  • 18. New plan • Shipped in six months – a horribly buggy beta product • Charged from day one • Shipped multiple times a day (by 2008, on average 50 times a day) • No PR, no launch • Results: 2007 revenues of $10MM
  • 19. Lean Startups Go Faster • Commodity technology stack, highly leveraged (free/open source, user-generated content, SEM). • Customer development – find out what customers want before you build it. • Agile (lean) product development – but tuned to the startup condition.
  • 20. Commodity technology stack • Leverage = for each ounce of effort you invest in your product, you take advantage of the efforts of thousands or millions of others. • It’s easy to see how high-leverage technology is driving costs down. • More important is its impact on speed. • Time to bring a new product to market is falling rapidly.
  • 21. Customer Development  Continuous cycle of customer interaction  Rapid hypothesis testing about market, pricing, custom ers, …  Extreme low cost, low burn, tight focus  Measurable gates for http://bit.ly/FourSteps investors
  • 22. Customer Development  Continuous cycle of customer interaction  Rapid hypothesis testing about market, pricing, customers, …  Extreme low cost, low burn, tight focus  Measurable gates for investors http://bit.ly/yx8K4
  • 23. Agile Product Development (A tale of two startups, revisited) • Principles drawn from Lean Manufacturing and Toyota Production System • These examples are drawn from software startups, but increasingly: – All products require software – All companies are operating in a startup-like environment of extreme uncertainty
  • 24. Traditional Product Development Unit of Progress: Advance to Next Stage Waterfall Requirements Specification Design Problem: known Solution: known Implementation Verification Maintenance
  • 25. Agile Product Development Unit of Progress: A line of Working Code “Product Owner” or in-house customer Problem: known Solution: unknown
  • 26. Product Development at Lean Startup Unit of Progress: Validated Learning About Customers ($$$) Customer Development Hypotheses, Problem: unknown Experiments, Insights Data, Solution: unknown Feedback, Insights
  • 27. Minimize TOTAL time through the loop IDEAS LEARN BUILD DATA CODE MEASURE
  • 28. There’s much more… IDEAS Learn Faster Code Faster Split Tests LEARN BUILD Unit Tests Customer Interviews Usability Tests Customer Development Continuous Integration Five Whys Root Cause Analysis Incremental Deployment Customer Advisory Board Free & Open-Source Components Falsifiable Hypotheses Cloud Computing Product Owner Accountability Cluster Immune System Customer Archetypes DATA CODE Just-in-time Scalability Cross-functional Teams Refactoring Semi-autonomous Teams Developer Sandbox Smoke Tests Minimum Viable Product Measure Faster MEASURE Split Tests Funnel Analysis Clear Product Owner Cohort Analysis Continuous Deployment Net Promoter Score Usability Tests Search Engine Marketing Real-time Monitoring Real-Time Alerting Customer Liaison Predictive Monitoring
  • 29. The Lean Startup • You are ready to do this, whether you are: – Thinking of starting a new company, but haven’t taken the first step – Are in a startup now that could iterate faster – Want to create the conditions for lean innovation inside a big company • Get started, now, today.
  • 30. Thanks! • Startup Lessons Learned Blog – http://StartupLessonsLearned.blogspot.com/ • Getting in touch (#leanstartup) – http://twitter.com/ericries – eric@theleanstartup.com • The Lean Startup Workshop – June 18 and October 30, 2009 in San Francisco – December 10, 2009 in New York – http://training.oreilly.com/theleanstartup/
  • 31. How to build a Lean Startup • Let’s talk about some specifics. These are not everything you need, but they will get you started • Continuous deployment • Split-test (A/B) experimentation • Five why’s
  • 32. Continuous Deployment IDEAS Learn Faster Code Faster Five Whys Root LEARN BUILD Continuous Cause Analysis Deployment DATA CODE Measure Faster MEASURE Rapid Split Tests
  • 33. Continuous Deployment • Deploy new software quickly • At IMVU time from check-in to production = 20 minutes • Tell a good change from a bad change (quickly) • Revert a bad change quickly • Work in small batches • At IMVU, a large batch = 3 days worth of work • Break large projects down into small batches
  • 34. Cluster Immune System What it looks like to ship one piece of code to production: • Run tests locally (SimpleTest, Selenium) o Everyone has a complete sandbox • Continuous Integration Server (BuildBot) o All tests must pass or “shut down the line” o Automatic feedback if the team is going too fast • Incremental deploy o Monitor cluster and business metrics in real-time o Reject changes that move metrics out-of-bounds • Alerting & Predictive monitoring (Nagios) o Monitor all metrics that stakeholders care about o If any metric goes out-of-bounds, wake somebody up o Use historical trends to predict acceptable bounds When customers see a failure: o Fix the problem for customers o Improve your defenses at each level
  • 35. Rapid Split Tests IDEAS Learn Faster Code Faster Five Whys Root LEARN BUILD Continuous Cause Analysis Deployment DATA CODE Measure Faster MEASURE Rapid Split Tests
  • 36. Split-testing all the time • A/B testing is key to validating your hypotheses • Has to be simple enough for everyone to use and understand it • Make creating a split-test no more than one line of code: if( setup_experiment(...) == quot;controlquot; ) { // do it the old way } else { // do it the new way }
  • 37. The AAA’s of Metrics • Actionable • Accessible • Auditable
  • 38. Measure the Macro • Always look at cohort-based metrics over time • Split-test the small, measure the large Control Group (A) Experiment (B) # Registered 1025 1099 Downloads 755 (73%) 733 (67%) Active days 0-1 600 (58%) 650 (59%) Active days 1-3 500 (48%) 545 (49%) Active days 3-10 300 (29%) 330 (30%) Active days 10-30 250 (24%) 290 (26%) Total Revenue $3210.50 $3450.10 RPU $3.13 $3.14
  • 39. Five Whys IDEAS Learn Faster Code Faster Five Whys Root LEARN BUILD Continuous Cause Analysis Deployment DATA CODE Measure Faster MEASURE Rapid Split Tests
  • 40. Five Whys Root Cause Analysis • A technique for continuous improvement of company process. • Ask “why” five times when something unexpected happens. • Make proportional investments in prevention at all five levels of the hierarchy. • Behind every supposed technical problem is usually a human problem. Fix the cause, not just the symptom.
  • 41. Thanks! • Startup Lessons Learned Blog – http://StartupLessonsLearned.blogspot.com/ • Getting in touch (#leanstartup) – http://twitter.com/ericries – eric@theleanstartup.com • The Lean Startup Workshop – June 18 and October 30, 2009 in San Francisco – December 10, 2009 in New York – http://training.oreilly.com/theleanstartup/

Editor's Notes

  1. Hi, I’m Eric Ries. I wan to talk to you today about one simple fact: that the vast majority of high-tech startups fail. It does not have to be that way.Read the stories of successful startups and, if the founders are willing to be honest, you will see this pattern over and over again. They started out as digital cash for PDAs, but evolved into online payments for eBay. They started building BASIC interpreters, but evolved into the world's largest operating systems monopoly. They were shocked to discover their online games company was actually a photo-sharing site.Each of these companies were fortunate to have enough time, resources, and patience to endure the multiple iterations it took to find a successful product and market. The premise of the lean startup is simple: if we can reduce the time between these major iterations, we can increase the odds of success.
  2. Hi, I’m Eric Ries. I wan to talk to you today about one simple fact: that the vast majority of high-tech startups fail. It does not have to be that way.Read the stories of successful startups and, if the founders are willing to be honest, you will see this pattern over and over again. They started out as digital cash for PDAs, but evolved into online payments for eBay. They started building BASIC interpreters, but evolved into the world's largest operating systems monopoly. They were shocked to discover their online games company was actually a photo-sharing site.Each of these companies were fortunate to have enough time, resources, and patience to endure the multiple iterations it took to find a successful product and market. The premise of the lean startup is simple: if we can reduce the time between these major iterations, we can increase the odds of success.
  3. Hi, I’m Eric Ries. I wan to talk to you today about one simple fact: that the vast majority of high-tech startups fail. It does not have to be that way.Read the stories of successful startups and, if the founders are willing to be honest, you will see this pattern over and over again. They started out as digital cash for PDAs, but evolved into online payments for eBay. They started building BASIC interpreters, but evolved into the world's largest operating systems monopoly. They were shocked to discover their online games company was actually a photo-sharing site.Each of these companies were fortunate to have enough time, resources, and patience to endure the multiple iterations it took to find a successful product and market. The premise of the lean startup is simple: if we can reduce the time between these major iterations, we can increase the odds of success.
  4. Hi, I’m Eric Ries. I want to talk to you today about one simple fact: that the vast majority of high-tech startups fail. It does not have to be that way.Read the stories of successful startups and, if the founders are willing to be honest, you will see this pattern over and over again. They started out as digital cash for PDAs, but evolved into online payments for eBay. They started building BASIC interpreters, but evolved into the world's largest operating systems monopoly. They were shocked to discover their online games company was actually a photo-sharing site.Each of these companies were fortunate to have enough time, resources, and patience to endure the multiple iterations it took to find a successful product and market. The premise of the lean startup is simple: if we can reduce the time between these major iterations, we can increase the odds of success.
  5. Start a company with a compelling long-term vision. Don't get distracted by trying to flip it. Instead, try and build a company that will matter on the scale of the next century. Aim to become the \"next AOL or Microsoft\" not a niche player.Raise sufficient capital to have an extended runway from experienced smart money investors with deep pockets who are prepared to make follow-on investments.Hire the absolute best and the brightest, true experts in their fields, who in turn can hire the smartest people possible to staff their departments. Insist on the incredibly high-IQ employees and hold them to incredibly high standards.Bring in an expert CEO with outstanding business credentials and startup experience to focus on relentless execution.Build a truly mainstream product. Focus on quality. Ship it when it's done, not a moment before. Insist on high levels of usability, UI design, and polish. Conduct constant focus groups and usability tests.Build a world-class technology platform, with patent-pending algorithms and the ability to scale to millions of simultaneous users.Launch with a PR blitz, including mentions in major mainstream publications. Build the product in stealth mode to build buzz for the eventual launch.
  6. By hiring experts, conducting lots of focus groups, and executing to a detailed plan, the company became deluded that it knew what customers wanted. I remember vividly a scene at a board meeting, where the company was celebrating a major milestone. The whole company and board play-tested the product to see its new features first hand. Everyone had fun; the product worked. But that was two full years before any customers were allowed to use it. Nobody even asked the question: why not ship this now? It was considered naive that the \"next AOL\" would ship a product that wasn't ready for prime time. Stealth is a customer-free zone. All of the efforts to create buzz, keep competitors in the dark, and launch with a bang had the direct effect of starving the company for much-needed feedback.
  7. Even though some aspects of the product were eventually vindicated as good ones, the underlying architecture suffered from hard-to-change assumptions. After years of engineering effort, changing these assumptions was incredibly hard. Without conscious process design, product development teams turn lines of code written into momentum in a certain direction. Even a great architecture becomes inflexible. This is why agility is such a prized quality in product development.
  8. This is the most devastating thing about achieving a failure: while in the midst of it, you think you're making progress. This company had disciplined schedules, milestones, employee evaluations, and a culture of execution. When schedules were missed, people were held accountable. Unfortunately, there was no corresponding discipline of evaluating the quality of the plan itself. As the company built infrastructure and added features, the team celebrated these accomplishments. Departments were built and were even metrics-driven. But there was no feedback loop to help the company find the right metrics to focus on.
  9. Do our actions live up to our ideals?
  10. After our crushing failure, the founders of my next company decided to question every single assumption for how a startup should be built. Failure gave us the courage to try some radical things.
  11. After our crushing failure, the founders of my next company decided to question every single assumption for how a startup should be built. Failure gave us the courage to try some radical things.
  12. Based on that experience, and the experience of the other startups I have worked for, I now strongly believe there is a better way to create startups. I’ve called this vision the Lean Startup. It combines three key trends.
  13. Let’s look at those changes schematically.
  14. Webcast: May 1Workshop: May 29Fliers up frontDiscussion in web2open
  15. Take a moment to close your eyes…
  16. Run tests locally:-- Sandbox includes as much of production as humanly possible (db, memcached, Solr, Apache).-- Write tests in every language. We use 8 different test frameworks for different environs. Otherwise you get fear and brittle.-- Example kind of problem is that AJAX updater for site header. Seemingly innocuous change would break shopping experience.CIT/BuildBot:-- Simply don’t push with red tests. Even if the site is in trouble. Example Christmas site outage with memcache sampling.-- Give an idea of the scale. 20 machine cluster, runs 10000 tests and 100,000’s of thousand of assertions on every change.Incremental deploy:-- Catch performance bugs and gaps in test coverageSlow query in free tags. This started to drive database load higher on one MySQL instance due to contention and data size. Detected and rolled back before it affected users and before the database was hosed due to high load.Changed transaction commit logic in foundation of the system. This passed all tests but caused registrations to fail in production due to subtle difference between sandbox and production. System detected drop in business metric in 1 minute and reverted the changeAlerting and Predictive MonitoringExample: Second tier ISP to block our outbound emailExample: Rooms list performance time bombExample: Registration quality, second tier payment methods, invite mail success rates by serviceStory: Anything that can go wrong will, so just catch it then fast.
  17. When something goes wrong, we tend to see it as a crisis and seek to blame. A better way is to see it as a learning opportunity. Not in the existential sense of general self-improvement. Instead, we can use the technique of asking why five times to get to the root cause of the problem.Here's how it works. Let's say you notice that your website is down. Obviously, your first priority is to get it back up. But as soon as the crisis is past, you have the discipline to have a post-mortem in which you start asking why: 1. why was the website down? The CPU utilization on all our front-end servers went to 100% 2. why did the CPU usage spike? A new bit of code contained an infinite loop! 3. why did that code get written? So-and-so made a mistake 4. why did his mistake get checked in? He didn't write a unit test for the feature 5. why didn't he write a unit test? He's a new employee, and he was not properly trained in TDDSo far, this isn't much different from the kind of analysis any competent operations team would conduct for a site outage. The next step is this: you have to commit to make a proportional investment in corrective action at every level of the analysis. So, in the example above, we'd have to take five corrective actions: 1. bring the site back up 2. remove the bad code 3. help so-and-so understand why his code doesn't work as written 4. train so-and-so in the principles of TDD 5. change the new engineer orientation to include TDD