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Live it - or leave it! Returning your investment into Agile

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Keynote at Agile Testing Days Berlin 2013

If you’re involved with software development, there is probably no way you can ignore it anymore: the agile approach. With everyone talking about it, there is a certain pressure to adopt agile methods. This brings with it the danger of introducing a bunch of practices without placing enough emphasis on the two main success factors: continuously improving software and continuously improving teams.

The latter is usually driven more or less automatically by the self-interest of the directly affected individuals – after all, nobody deliberately wants to be inefficient. "Continuously improving software" on the other hand will almost certainly go wrong at first, because trust and feedback are much harder to establish between stakeholders (customers, team) than within a team. This often leads to efficient teams building the wrong product, or, even worse, just investing into iterative delivery without enjoying any of its benefits.

Efficiency is therefore just one component for ensuring a good return on investment when adopting Agile. In this talk, I want to focus on the other part – effectiveness – and how it impacts on the way teams collaborate with their customers. I'll introduce a few techniques (Story Mapping, Specification-By-Example) that support this change and present examples from past projects in the financial and public sector where they proved successful.

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Live it - or leave it! Returning your investment into Agile

  1. 1. 1 CHRISTIAN HASSA (@CHRISHASSA) WWW.TECHTALK.AT Agile Testing Days 2013, October 30th 2013 Live it – or leave it! Returning your investment into Agile
  2. 2. 2 Are we scaling the right thing? The DAD Agile Lifecycle Copyright 2012 – Scott Ambler and Associates Envision the future Identify, prioritize and select projects Production ready Delighted stakeholders
  3. 3. 7 M7 Where’s “Phase 2” in SAFe? M8 Phase 3
  4. 4. 9 The SAP “Business by Design” disaster • Target 2010:10.000 customers, 1bn/year •Started in 2003 •2-3bn investment •Announced for 2007 • “Merged” with HANA in 2013 •First release only in 2010 •<1000 customers by 2013 •<100 Mio revenue / year
  5. 5. 11 Fixed time and budget are NOT the problem – … it’s waiting too long and spending too much before validation!
  6. 6. 12
  7. 7. 13
  8. 8. 14
  9. 9. 15
  10. 10. 16
  11. 11. 17 Your job as developers is NOT to develop software, your job is to change the world. - Jeff Patton
  12. 12. 18 What can we learn from Pinky and the Brain about changing the world? Be prepared that the best laid plans don't work out.
  13. 13. 19 Your job as tester is NOT to verify software, your job is to verify the world is actually changing (fast enough).
  14. 14. 20 Scaling TDD to the enterprise Write a failing unit test Make the test pass Refactor Write a failing acceptance test Set a desired business goal Get feedback on deployable system Measure impact of deployed system Define a desired behavior change Measure impact of behavior changes Refine feature Refine deliverable Refine strategy break down stakeholders break down deliverables break down units extend system
  15. 15. 21 Impact Maps Goal Actors Impacts Deliverables Increase yearly revenue by 3% Keep market share in blockbuster concerts Reduce call-center load from blockbuster concerts Introduce mobile platform for concert tickets web shop Mobile phone shop users Customers calling to order by phone Reduce bounce rate Order blockbuster tickets Hang-up to order online Static info on blockbuster concerts Order one particular blockbuster concert Announcement for mobile order possibility
  16. 16. 22 Influence Control Goal Actors Impacts Deliverables Influence vs. Control Reduce accidents by 50% at cross-roads Car drivers pay more attention drive slower put up stop sign put up speed limit transform to round-about
  17. 17. 23 Influence Control Goal Actors Impacts Deliverables Scaling agile principles Test Goals and Impacts as early and as often as possible • Scale: what to measure • Meter: how to measure • Range: Benchmark, Constraint, Target Define roadmap of goals Smaller deliverable slices to production Easier to parallelize Across systems and departments Prioritized with business sponsors
  18. 18. 24 Delivering flexible scopeStory Maps • Introduced by Jeff Patton • Optimize scope of a deliverable for particular impacts • Provide overview about backlog • Help with collaboration and release planning
  19. 19. 25 Story Map structure Mobile phone shop user Order blockbuster tickets Reduce bounce rate Static info on blockbuster concerts Order one particular blockbuster concert Becomes aware of new concert Tries to buy when sale starts Waits for concert Attends concert Upcoming concert sales Additional artist info Pay by credit card Pay by invoice Print paper ticket Validate using NFC News about concert Likely order of events Priority
  20. 20. 26 walking skeleton Prioritizing slices Mobile phone shop user Order blockbuster tickets Reduce bounce rate Static info on blockbuster concerts Order one particular blockbuster concert Becomes aware of new concert Tries to buy when sale starts Waits for concert Attends concert Upcoming concert sales Additional artist info Pay by credit card Pay by invoice Print paper ticket Validate using NFC News about concert Likely order of events Priority Omitted steps Manual workarnd
  21. 21. 27 Slicing for impacts Mobile phone shop user Order blockbuster tickets Reduce bounce rate Static info on blockbuster concerts Order one particular blockbuster concert Becomes aware of new concert Tries to buy when sale starts Waits for concert Attends concert Upcoming concert sales Additional artist info Pay by credit card Pay by invoice Print paper ticket Validate using NFC News about concert Likely order of events Priority
  22. 22. 28 Team Levels of collaboration Stakeholders Project Sponsor Project Lead Product Owner Other groups that deliver Impact Maps Story Maps
  23. 23. 29 Example: eVoting 83 76 58 78 59 60 61 63 8082 55 54 56 52 48 48.2 48.1 49 50 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  24. 24. 30 Sprint 1 83 76 58 78 59 60 61 63 8082 55 54 56 52 48 48.2 48.1 49 50 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  25. 25. 31 Sprint 2 83 76 58 78 59 60 61 63 8082 55 54 56 52 48 48.2 48.1 49 50 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  26. 26. 32 Sprint 3 83 76 58 78 59 60 61 63 8082 55 54 56 52 48 48.2 48.1 49 50 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  27. 27. 33 Dropped user stories 83 76 58 78 59 60 61 63 8082 55 54 56 52 48 48.2 48.1 49 50 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  28. 28. 34 Added user stories 83 76 89 58 78 59 60 61 63 8082 55 54 56 90 52 48 48.2 48.1 49 50 91 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  29. 29. 35 Sprint 4 83 76 89 58 78 59 60 61 63 8082 55 54 56 90 52 48 48.2 48.1 49 50 91 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  30. 30. 36 Flexible scope 83 76 89 58 78 59 60 61 63 8082 55 54 56 90 52 48 48.2 48.1 49 50 91 77 46 44 42 41 36 34 39 38 32 28 29 25 21 20 23 17 15 13 8 9 11 10 Provision and support Nominate candidates Vote and determine results
  31. 31. 37 Impact Mapping Story Mapping Specification-By-Example Why? Assumption Specification How? Acceptance Criteria Epics Deliverables Impacts Easier to define upfront Harder to define upfront User Activities User Stories Examples Goals Specifications vs. Assumptions Feature Injection 1. Hunt the value: Look at Outputs 2. Inject features: From Outputs to Inputs 3. Find examples: Try to break the model Code
  32. 32. 38 Agile Fluency Build- Measure Learn Impact Mapping Story Mapping
  33. 33. 39 Books Gojko Adzic Impact Mapping Douglas W. Hubbard How to measure anything
  34. 34. 41 Live it – or leave it … • Don’t just focus on delivering larger backlogs with larger teams • Apply principles to next level: focus on impacts and business goals • Elevate your practices: build – measure – learn @chrishassa www.techtalk.at Visit: www.productownersurvivalcamp.com

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