Managing Innovation

Fccb9ef81d69152b6096ec047428ac2e?s=47 Ian Mulvany
October 12, 2017

Managing Innovation

An overview of using some lean product managment principles to rapidly iterate through a set of opportunities when doing new product development.

Fccb9ef81d69152b6096ec047428ac2e?s=128

Ian Mulvany

October 12, 2017
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  1. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Managing Innovation @IanMulvany Head of Product Innovation
  2. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne SAGE Publishing • Founded in 1965 • Independent • 1,500 employees globally • 5th largest journal publisher & fastest growing STM publisher • Research Methods is at the heart of what we do • Product Management team started in 2011
  3. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Core Adjacent Diversification books / journals SRM / video / data Project Ocean Try innovating!
  4. Time Data Computational Cost • Our vision is a world

    in which big data is used responsibly to improve social outcomes and governance. • Our mission is to equip every social scientist with the skills and tools they need to do big data research. • Do this by creating new products and services Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Existing process, meetings, systems Split roles Too much excitement Too many people wanting to get involved Reality not matching up to expectation Too much or too little sponsor involvement Pigs vs Chickens Challenges of innovating from within a large company CC0 Public Domain
  5. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Innovation Incubator • Establish an incubator initially with 3 people • Product Innovation budget • Test, prototype, fail, test, prototype, build • 2 year limit to identify scaleable commercial proposition for SAGE
  6. Time Data Computational Cost

  7. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne What is our problem domain Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Why Big Data? “The social sciences are undergoing a dramatic transformation from studying problems to solving them; from making do with a small number of sparse data sets to analyzing increasing quantities of diverse, highly informative data; from isolated scholars toiling away on their own to larger scale, collaborative, interdisciplinary, lab-style research teams…”
  8. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne What is our problem domain Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Why Big Data? “The social sciences are undergoing a dramatic transformation from studying problems to solving them; from making do with a small number of sparse data sets to analyzing increasing quantities of diverse, highly informative data; from isolated scholars toiling away on their own to larger scale, collaborative, interdisciplinary, lab-style research teams…” Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Our Problem Domain
  9. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne •Our vision is a world in which big data is used responsibly to improve social outcomes and governance. •Our mission is to equip every social scientist with the skills and tools they need to do big data research. • Do this by creating new products and services
  10. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Image flickr: jacinta lluch valero
  11. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne How do you test many opportunities?
  12. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne You have finite time
  13. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Breadth First? Depth First?
  14. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne When do you move from Discovery to Delivery ?
  15. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Can scale by adding more people ! ! ! ! ! ! ! OR Reducing cycle time to decision Start End
  16. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne flickr: smartsignbrooklyn cc-by VS Flickr: beckysnyder cc-by-nd
  17. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne flickr: Tools
  18. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Lean Discovery Framework Portfolio Product Experiment define refine refine hypothesize test refine hypothesize refine test This is the framework we’re using to learn about potential areas of investment:
  19. 1 2 3 4 MISSION LEVEL LEAN VALUE TREE FRAMEWORK

    GOAL LEVEL BET LEVEL INITIATIVE LEVEL
  20. Lean value tree Our mission is to equip every social

    scientist with the skills and tools they need to do big data research. Mission Goals Bets Product ideas Help researchers gain SKILLS Provide TOOLS Support COLLABORATION Support access to DATA Add collaborations through common PROBLEMS Allow CS and Social researchers to find Problems Help researchers collaborate effectively Help researchers collaborate successfully Matchmaking tool Match open data w/ funding opps Make a collaboration metric for Unis Tie SS proposals and tech needs to nonprofit platforms like KIVA Incentivise tech infra folks to provide infra free if data is open Pitch decks to funders Word/topic meaning suggestion engine Grant evaluation
  21. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Grounded by metrics if you can’t confirm those metrics to begin with, you can use your projections as a feedback mechanism, but you need to have a place to start from
  22. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Population of Social Scientists 50% Year 2M 2M Year 1 Year 10 Interested in CSS 6.5% Population Interest Growth
  23. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne lean Canvas Academic Data Scientist ! Can’t do this myself ! Lack quality question ! Lack right method ! Problem getting funding 
 Industry Data Scientist: ! Talent gone to waste ! Lack of social impact ! Lack of new learning
 ! BD research centre, conferences/seminars, linkedin/Twitter, Uni directory, data.world, blogs, Kagle. ! Hackathonsm meetups, linkedIn, idea marketplace, IDEO Academic Data Scientist ! Find SS researcher (by method, data, topic, funding, problem)
 Industry Data Scientist: ! Find researcher (by data, problem, topic) ! 600 new technical collaborations by mid-2019 Academic Data Scientist ! Enhanced reputation ◦ Output ◦ New opportunities ! Power to affect the world / discipline
 Industry Data Scientist: ! Impact the world ! Confirm my super powers Academic Data Scientist 
 Industry Data Scientist: ! Charge to sign up ! Charge upon starting collaboration ! Institutional subscription ! Funders pay
  24. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Identify Riskiest Assumptions ONLINE CSS COURSE - EXPERIMENT PHOTOS Cycle 1 Lean Experiments: Test Riskiest Assumptions
  25. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Pirate metrics / Factory Model Targets: 
 ! 700 ‘happy’ students/ annum, and
 ! $1M revenue/annum Conv: 10% 1.86M Reached Conv: 10% 18.6K Course Starters Success rate: 30% 5600 New Course Completers Retention: 30% 2400 Retained Course Completers “Premium” Coursera: $100 per course 186K Visitors “At Call” Summer School: $400 per course 90K Visitors 900K Reached Conv: 5% 4500 Course Starters Success rate: 50% 2250 New Course Completers Retention: 10% 250 Retained Course Completers “All you can eat” Coursera: $30 per month 133K Visitors 1.3M Reached Conv: 10% 13.3K Subscribers Renewal rate: 75% 10K New 3-month Subscribers Retention: 10% 1000 Retained 3-month Subscribers “Mini” Degree: $200 per month 75K Visitors 750K Reached Conv: 5% 3750 Subscribers Renewal rate: 50% 1875 New 2-month Subscribers Retention: 25% 625 Retained 2-month Subscribers “At Call” Summer School: $400 per course
  26. Landing Page Experiment

  27. LANDING PAGE EXPERIMENT RESULTS 125K Contacted 12.5K Landed 1250 Left

    email (625) Purchase? 10% 10% (50%) Test Goals (Hypothesis) 12.3% 6.5% 39% (50%) 125K Contacted 1663 Landed 204 Left email (102) Purchase? 6.5% (50%) 125K Contacted 1761 Landed 687 Left email (344) Purchase? 26K Opened 26K Opened No Price (control) $400 21% 21% 1.3% 1.4% 12.3% Results of Landing Page Experiment
  28. Feb Mar Apr May Jun Jul Aug Sep Sign Off

    Partners and Platform Announce Sales Launch > 100 people Taking these courses
  29. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Closing the feedback loop daily standouts toy kan ban stakeholder management Retrospectives Need for Tool usage is inverse proportion to how tight knit the team is Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Lessons Learnt - product and market
  30. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Some examples of what we learnt Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne - People like compelling demos - Our Core assumption around challenges to cross disciplinary collaboration was wrong - Spent some time prototyping a product that didn’t have a business model, and we could have saved that time if we had done the business analysis first - Later this approach led us quickly from designing an offering that we realised would not be aligned with what our users need, or what our goal is
  31. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Rapid prototyping process Mon Tue Wed Thu Fri choose sketch solve build test
  32. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Lessons Learnt - team and process
  33. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Specific project $$ is more powerful for alignment than a general project budget
  34. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Depth First
  35. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne flickr: nsalt cc-by flickr: hommedechevre. Cc-by-nc-sa flickr: cakeinmilk cc-by-nc-sa Pigs vs Chickens vs ???
  36. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Need for feedback cycles is inversely in proportion to how tightly knit the team is
  37. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne Finally Confidence in our team is our most valuable resource
  38. Los Angeles | London | New Delhi | Singapore |

    Washington DC | Melbourne Individuals and interactions over processes and tools The Value of Conversation Working software over comprehensive documentation Early testing, low-fi prototypes 
 Customer collaboration over contract negotiation Co-develop, “Get out of the building” Responding to change over following a plan Evidence based decision making Agile Manifesto Translated for Product Development