[appclub] Shazam mobile apps - Data Driven Project Management

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Presentation given by me over skype on 30.10.2014 for http://appclub.im/events/details/11030 It is a modified version of talk given in Cracow in Poland for Mobiconf 2014 (http://www.slideshare.net/tomaszkustrzynski/092014-mobiconf-2014-v2-39838125) The first report will be on how the data collected on the basis of the company's managers Shazam to make management decisions, evaluate projects and solve other important issues. Participants should be familiar with basic principles of Kanban methodology to better understand the essence of the report. The presentation will take place via Skype in English.

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  • 1. Shazam mobile apps -Data Driven Project ManagementTomasz Kustrzynski, October 2014

2. 2014 ShazamEntertainmentAbout Shazammusic recognition service and appsfounded in 1999launched in the UK in 2002one of the most popular mobile apps500M+ downloads 3. 2014 ShazamEntertainmentShazam technology - then1. call 25802. play the music3. wait for SMS with results(phone you most likely used in 2002) 4. 2014 ShazamEntertainmentShazam technology - nowsince 2008 - iPhone and Android appssince 2014 - integrated with iOS8s Sirimusic streaming, TV ads, live TV,and more 5. Agendaorganisationwhy and what do we measureestimation (and causation bias)handling dependenciesdevelopment patterns 6. Organisation 7. 2014 ShazamEntertainmentThe teams 8. 2014 ShazamEntertainmentTechnical Project Managementthe scientific methodhypothesis experimentanalysedatadrawconclusionsimprove continuously(Kaizen) 9. 2014 ShazamEntertainmentWe use Kanbanvisualised value streamenables detailed metricsJIRA to manage boards 10. Why and what do we measure? 11. 2014 ShazamEntertainmentWhat do we care about100+Users. We now have millions monthly active users. 12. 2014 ShazamEntertainmentData drivendecisions 13. 2014 ShazamEntertainmentData gathering"In God we trust; all others must bring data."Edward Deming"What's measured improves."Peter F. Drucker 14. 2014 ShazamEntertainmentData gatheringinformation radiators acrossthe office 15. 2014 ShazamEntertainmentPresentation matters 16. Estimation 17. 2014 ShazamEntertainmentEstimates are dangerous 18. 2014 ShazamEntertainmentEstimation scale we use1TFB - too f* bigNFC - no f* clue[give me a minute]cards in the photo byLunar Logic (@Lunar_Logic) 19. FAQ 1As a Product Manager, when can I expect this Storyto be completed? 20. 2014 ShazamEntertainmentDisney/Cycle Timestime for a Story to getimplemented and tested(or time from entering queue untilfinishing the ride in Disneyland)having lots of samples wecan use statistics(and talk about probabilities) 21. 2014 ShazamEntertainmentDisney/Cycle Timesparallelstreams ofworkCycle Timestwork donestart of teststart of development 22. 2014 ShazamEntertainmentDisney/Cycle Times - statisticshistogram of DisneyTimes (Cycle Times)(all items, bugs)density function 50th, 85th percentile(50/85% items get finished within this time) 23. 2014 ShazamEntertainmentWhen a Story will get done?1. You can get this story within X days with 85%probability.2. Probability of you getting it within a week is Y%. 24. FAQ 2Ok, so when can we get all these 10 stories done? 25. 2014 ShazamEntertainmentModelling parallel workparallel work is difficult to model with cycle timesits easier with Takt TimesTakt Timesparallelstreams ofworkCycle Timest 26. 2014 ShazamEntertainmentDistribution of average Takt Timescreate set of average Takt Time samples based on similar projectaverageresample andmany times(>1000)distribution of average Takt Times 27. Predicting delivery time for N items 2014 ShazamEntertainmentaverage TT* Nrepeat manytimes (>1000)average TTaverage TTaverage TTdistribution of expected delivery times 28. 2014 ShazamEntertainmentWhen will all the Stories get done?1. You can get these Stories within X days with 85%probability.2. Probability of you getting them within a week is Y%. 29. Dependencies and blockersAs a Project Manager, what should I focus on next? 30. 2014 ShazamEntertainment 31. 2014 ShazamEntertainmentBlockers/dependencies visualise prioritise(what is blocked, for how long) act collect statistics and review them(have any recent changes to the process change amountof blocked items/how long theyre blocked for?) 32. 2014 ShazamEntertainmentWhat should I dofirst? - answersTeam A: finally doing wellTeam B: keeps gettingblocked4 blockers including 1 oldTeam C: doing wellTeam D: 1 new blocker 33. 2014 ShazamEntertainmentBlockers statisticsfocus on thebottlenecktrend of increasingmedian time tounblock 34. Development patterns 35. FAQsWhy did we end up with large number of stories totest at once?Do some types of items take longer to develop than others?Are there times when teams are more productive?Did we split Stories properly or we missed splitting some bigones? 36. 2014 ShazamEntertainmentPatterns and improvementBeing aware of patterns enables us to act on them: introduce better policies(e.g. all UI assets for a Story done before dev commences) change development cycle(e.g. release more often to prevent batching) treat some types of work differently(e.g. allow extra dev time) 37. 2014 ShazamEntertainmentControl chart 38. 2014 ShazamEntertainmentControl chart 39. 2014 ShazamEntertainmentControl chart 40. 2014 ShazamEntertainmentControl chartweekends 41. Thank youtomasz.kustrzynski@shazam.com 42. 2014 ShazamEntertainmentReferences Real Options: commitment-thebook.com, Olav Maassen, Chris Matts Real Options: http://www.infoq.com/articles/real-options-enhance-agility Real Options: http://decision-coach.com/lean-and-real-options/ High level planning using Monte Carlo simulation, Dimitar Bakardzhiev Thinking, fast and slow, Daniel Kahneman http://en.wikipedia.org/wiki/Takt_time