Lean Analytics Overview Webinar

Transcription

1 Lean Analytics Overview Webinar

2 Topics Set the stage: What is Lean Startup? So What s Lean Analytics? Lean Analytics Concepts Innovation Accounting Metrics 2

3 Lean Concepts Relentlessly eliminate anything that isn t adding value Eliminate time spent on what we know we ll need in future Eliminate inefficient ways of working Optimize the whole system People doing the work know best how to do it Mapping processes and improving WoMBaT: Waste of Money, Brains, and Time Lean Start-Up takes a lean thinking approach to developing new products. Lean.org 3

4 What is a Startup? Catalyst that transforms ideas into products Includes Entrepreneurs and Intrapreneurs Examples: New Innovation Scientific discoveries Repurposing existing technology for new use New business model Product/Service to new location Address underserved set of customers New internal service Start-Up: A startup is an organization formed to search for a scalable and repeatable business model. Bob Dorf, The Startup Owner s Manual Start-Ups: Human institution designed to create new products and services under conditions of extreme uncertainty Eric Ries, The Lean Startup 4

5 What is Lean Startup? Application of Lean thinking to the process of innovation Adapts Lean ideas in context of entrepreneurship Principled approach to new product development Guidance on how to make trade-off decisions Focused on Validated Learning 5

6 Lean Startup Principles 1. Entrepreneurs are everywhere 2. Entrepreneurship is management 3. Product Success depends on learning 4. Leverage Build-Measure-Learn Cycle 5. Measure Learning Lean Start-Up is a set of practices to help entrepreneurs increase their odds of building a successful Product. 6

7 What Lean Start-Up Is Not -- Not your traditional way to create new products Not a collection of individual tactics Not a rigid, lockstep process Not a lack of discipline Not a software development methodology Silver Bullet Doesn t fix everything 7

8 So What s Lean Analytics? Advanced work in Lean Startup Focused on Measure phase of Build-Measure-Learn Cycle Measure and Analyze to: Validate problem Find the right customer Decide what to build How to monetize it How to spread word Core Idea: Type business Analytics Stage Optimize One Metrics That Matters 8

9 Types of Innovation Sustaining Innovation Improvements to existing product Serving existing customers Most companies are good but Disruptive Innovation Breakthrough new products New sustainable sources of growth Companies struggle 9

10 Lean Startup Overview Vision Strategy Business Plan Assumptions Experiments Growth Product Iterations Sustain ability? Learnings 10

11 Empathy Lean Analytics Stages Are you solving a problem people care about and will pay for? Identify a real problem and real solution Get out of the Building, Interviews, Surveys Stickiness Will the dogs eat the dog food? Leverage the solution with a small, friendly audience Test before going after the masses Virality Will people spread the word? Acquisition, Onboarding processes Force multiplier for paid promotion Revenue Will they open their pocketbooks? Monetize Product, Can you make money? Focus on maximizing and optimizing revenue Scale Can we grow the market with sustainability? Acquire customers, expand verticals and geographies Channels, ecosystem, sustainability 11

12 Stage Example Restaurant Empathy Owner learns about diners in area Desires, trends, foods not available Gets out of building and talks to diners Stickiness Develops menu Lots of tests on customers, frequent changes High costs, variation, uncertain inventory, giveaways Virality Starts loyalty programs to entice return customers Encourage customers to share with friends, friend coupons Leverages social media Revenue Work on margins Fewer free meals, tighter cost controls More standardization Scale Proven sustainability Spends on marketing and promotion from revenues, broader advertising Launches second restaurant 12

13 Sample Business Models E-commerce: Sell things to customers e.g. Amazon SaaS: Software on demand e.g. Salesforce Free Mobile App: In-game content drives revenue e.g. Angry Birds Media: You create content, make money from advertising e.g. Google s Search Engine, cnet Home Page User-Generated Content: Users create content e.g. Facebook, Wikipedia Two-sided: Buyers and sellers come together e.g. ebay, Dating Sites 13

14 Lean Analytics Concepts 14

15 Build-Measure-Learn Feedback Loop Vital function is learning Learn truth of what works in strategy What customers really want (vs. what they say/think they want) Are we on the path to a sustainable business? Minimum Viable Product (MVP) Fastest full turn of cycle Minimum amount of effort Minimum development Start learning as quickly as possible Answer product design or technical questions Test fundamental hypotheses Usually overestimate needs for MVP Are development efforts leading to real progress Metrics are people, too Represents breathing, thinking, buying individuals Behavior is measureable and changeable Are you making your product better? How do you know? Eric Ries, The Lean Startup 15

16 Lean Analytics Cycle Alistar Croll, Lean Analytics 16

17 Experiments to Test Strategy Leap-of Faith Assumptions: Riskiest elements of startup s plan Identify risks and assumptions before building anything Test those assumptions experimentally Devise experiments: Learn to move numbers closer to those expected in business model Products are an experiment, MVP is a process Once clear of leap-of-faith assumptions, enter Build phase quickly with a Minimum Viable Product (MVP). 17

18 Minimum Viable Product Fastest full turn of Build-Measure-Learn cycle Minimum amount of effort, Minimum development Challenges traditional notions of quality MVPs sometimes considered low quality by customers Start learning as quickly as possible Any work beyond is waste Learn what attributes customers care about Answer product design or technical questions Test fundamental assumptions/hypotheses Usually overestimate needs for MVP 18

19 Early Adopters Visionary early customers First to adopt More forgiving of mistakes Expect, even prefer, an 80% solution Suspicious of anything too polished Features/polish might be a waste of energy for them 19

20 Validated Learning Demonstrated by positive improvements in core metrics Synthesis between vision and what customers will accept Startup Productivity Metric: Not How much stuff we built But How much validated learning we re getting Validate Assumptions (hypotheses) Validate Changes 20

21 Innovation Accounting Leanstack.com 21

22 Innovation Accounting Quantitative approach to view results of tuning product Geared towards measuring disruptive innovation Answers questions like: Are we actually achieving validated learning? Are we learning how to grow a sustainable business? 22

23 Pivot or Persevere Decisions Does progress show our strategic hypothesis is correct? Do we need to make a major change? Pivot: structured course correction designed to test a new fundamental hypothesis Product, strategy, growth engine Keep one foot rooted in learnings so far Persevere: Maintain current path Misguided decisions to persevere can destroy creative potential Product neither growing nor dying, consuming resources 23

24 Choosing the Right Metrics Qualitative versus Quantitative Vanity versus Actionable Leading versus Lagging Correlated versus Casual Key Performance Indicators: Specific metrics that drive the business 24

25 Qualitative vs Quantitative Metrics Qualitative Messy, subjective, imprecise Why Not easily measured Quantitative: Easy to understand What and How Much Ranked, counted, or put on a scale Aggregate, extrapolate, put in a spreadsheet 25

26 Vanity: Vanity vs Actionable Often at a gross up level, makes things look good Ex: Total Signups Actionable: Analyze customer behavior What will I do differently based on this metric? Ex: Percent of users who are active 26

27 8 Vanity Metrics to Watch Out For 1. Number of Hits 2. Number of Page Views 3. Number of Visits 4. Number of Unique Visitors 5. Number of Followers, Friends, Likes 6. Time on Site/Number of Pages 7. s Collected 8. Number of Downloads 27

28 Cohort Analysis Instead of cumulative totals, look at each group of customers Break down these groups A/B Testing Segmentation 28

29 Growth Hacking Data-driven guerilla marketing General technique: Find early lifecycle metric as Leading Indicator (e.g. # friends invited) Understand how that metric correlates to business goal (e.g. driving long-term engagement) Build predictions based on current Leading Indicator (e.g. engaged users in 90 days) Modify User Experience today to improve that outcome (e.g. suggest friends) 29

30 Leading vs Lagging Metrics Leading Metric/Indicator Tries to predict future Relate to early engagement activities Tied to business model e.g. qualified customers in sales funnel Lagging Metric After the fact Indicates that you had a problem e.g. Churn 30

31 Leading & Lagging Indicators Sales Funnel: Sales Team Leading indicator, potential new customers Contracts Signed: Sales Team Lagging Metric, deals closed Finance Leading indicator, potential revenue Revenue Earned: Finance Lagging indicator, revenue Stockholders Leading indicator gains/losses P&L: Stockholder Lagging indicator on company performance 31

32 Correlated vs Causal Metrics Correlate Help predict what will happen Causal Cause of something happening Prove Causality thru Correlation A Correlated, Leading Indicator can predict the future A Causal, Leading Indicator can change the future 32

33 Correlated vs Causal Metrics Correlation is good. Causality is great! Purewater gazette.net 33

34 Summary 34

35 Lean Startup Overview Vision Strategy Business Model Assumptions Experiments Growth Product Iterations Sustain ability? Learnings 35

36 Analytics Lessons Learned Accounting takes on a different role in the uncertain world of Startups Know your customer Numbers can t explain everything Get out of the building Moving targets Define what success looks like then: experiment, experiment, experiment Use quantitative data to what and how much Use qualitative data to understand why 36

37 Thank You!!! I appreciate your time. Robert Tyson Agile Coach & Instructor 37

38 Lean Startup References The Lean Startup by Eric Ries Lean Analytics by Alistair Croll & Benjamin Yoskowitz 38

39 4 Kinds of Information Alistar Crool, B.Yoskovitz, Lean Analytics 39