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Slicing and dicing your user stories

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This was a talk given by Jenny Wong and Danilo Sato at Agile Brazil 2011:

Agile teams learned that splitting teams into silos and functional areas is not a productive way to develop software. Having cross-functional teams improve collaboration and enables delivery of value faster. The same arguments can be applied to user stories. The way in which business requirements and features are translated into user stories play an important role on the software delivery process. This session will discuss the benefits of working with small user stories, and present different ways to split requirements into user stories.

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Slicing and dicing your user stories

  1. 1. Slicing and dicing your user storiesJenny Wong ● Danilo Sato morphblade
  2. 2. Why are we here?
  3. 3. Why are we here? As Pedro the product owner, I want to build the system, so that I can have the system As David the developer, I want to migrate the db
  4. 4. Why are we here?
  5. 5. Why are we here? “As product owner, I want to understand how this may help me do planning”
  6. 6. Why are we here? “As product owner, I want to understand how this may help me do planning” “As a developer, I want to have the tools to explain what we are doing”
  7. 7. Why are we here? “As product owner, I want to understand how this may help me do planning” “As a developer, I want to have the tools to explain what we are doing”“As an analyst, I want to learn how to split big chunks into smaller chunks”
  8. 8. What is the real need in slicing and dicing?
  9. 9. What is the real need in slicing and dicing?
  10. 10. Why One Big Chunk does not work LAUNCH
  11. 11. Why One Big Chunk does not work LAUNCH
  12. 12. Why One Big Chunk does not work LAUNCHFEEDBACK
  13. 13. Why One Big Chunk does not work
  14. 14. Why One Big Chunk does not work
  15. 15. Why One Big Chunk does not work
  16. 16. Why One Big Chunk does not work
  17. 17. Why One Big Chunk does not work
  18. 18. Why One Big Chunk does not work
  19. 19. Why One Big Chunk does not work
  20. 20. Why One Big Chunk does not work
  21. 21. Why One Big Chunk does not work
  22. 22. Why One Big Chunk does not work
  23. 23. Why One Big Chunk does not work
  24. 24. Why One Big Chunk does not work
  25. 25. What are the incorrect ways of splitting?STORY Too Big, too small Independent, Negotiable, Value, Estimable, Small, Testable
  26. 26. What are the incorrect ways of splitting? MIGRATE OLD SPLIT DATABASE DATA Not user driven REWRITE REFACTOR ARCHITECTURE JQUERY Independent, Negotiable, Value, Estimable, Small, Testable
  27. 27. What are the incorrect ways of splitting? LOG IN USER PROFILE HOMEPAGE Split per page ACCOUNT SETTINGS Independent, Negotiable, Value, Estimable, Small, Testable
  28. 28. Busting Urban Myths
  29. 29. Busting Urban Myths✤ “Splitting stories result in larger estimates on the feature”
  30. 30. Busting Urban Myths✤ “Splitting stories result in larger estimates on the feature”✤ “Takes longer to develop”
  31. 31. Busting Urban Myths✤ “Splitting stories result in larger estimates on the feature”✤ “Takes longer to develop”✤ “I just see incomplete features”
  32. 32. Busting Urban Myths✤ “Splitting stories result in larger estimates on the feature”✤ “Takes longer to develop”✤ “I just see incomplete features”✤ “Customers will never buy”
  33. 33. See it in Action!
  34. 34. ✤ a running timeline that scrolls in chronological order✤ the ability to distinguish types of event✤ get the data for all genres✤ user can select a genre✤ hover to view detail of event✤ click to view related article on website✤ look and feel, navigation, labels, colours & artistic direction✤ legend to show types of event
  35. 35. Horizontal thinking ... COLOURS LOOK & FEEL PRESENTATION DATA ARCHITECTURE
  36. 36. Horizontal thinking ... COLOURS LOOK & FEEL PRESENTATION DATA ARCHITECTURE
  37. 37. Horizontal thinking ... COLOURS LOOK & FEEL PRESENTATION DATA ARCHITECTURE
  38. 38. Horizontal thinking ... COLOURS LOOK & FEEL PRESENTATION DATA ARCHITECTURE
  39. 39. Does horizontal slicing deliver?
  40. 40. Vertical vs. Horizontal Slicing COLOURS SHOW ALL GENRES SHOW EVENT TYPE SHOW ONE GENRE LINK TO ARTICLE LOOK & FEEL TIMELINE PRESENTATION DATA ARCHITECTUREThe application is split in way that each story can deliver value individually
  41. 41. Does vertical slicing deliver?
  42. 42. Dimensions of splitting
  43. 43. ✤ Business value✤ Risky items✤ Data dependency✤ User interaction and interface✤ Technical implementation, constraints and complexity✤ Stakeholders
  44. 44. Slicing and Dicing
  45. 45. If timeline interaction was most important ✤ Play timeline story first, to test interaction from design ✤ Lightweight Prototyping? ✤ How about a lightweight spike with dummy data?
  46. 46. If timeline interaction was most important ✤ Play timeline story first, to test interaction from design ✤ Lightweight Prototyping? ✤ How about a lightweight spike with dummy data?
  47. 47. Different event types ✤ Different event types have equal priority? ✤ Is all data available for all genres?
  48. 48. Different event types ✤ Different event types have equal priority? ✤ Is all data available for all genres?
  49. 49. If data for a genre is incomplete ✤ Need to fix data for Jazz genre before it can be added to the data ✤ Showcase one other genre first, then add the rest, then add when it is complete ✤ Other genres remain testable. Could we release without Jazz?
  50. 50. If data for a genre is incomplete ✤ Need to fix data for Jazz genre before it can be added to the data ✤ Showcase one other genre first, then add the rest, then add when it is complete ✤ Other genres remain testable. Could we release without Jazz?
  51. 51. Detailed vs. Overview ✤ A little bit of everything? ✤ Or everything in one genre? ✤ A way to release a functional application with incomplete data, whilst allowing enhancements
  52. 52. Detailed vs. Overview ✤ A little bit of everything? ✤ Or everything in one genre? ✤ A way to release a functional application with incomplete data, whilst allowing enhancements
  53. 53. If the user interface was challenged ✤ Lab test interaction ✤ Easy to get lost in timeline ✤ Solve problem by adding a date at the bottom ✤ Proceed development, which may be relatively painless. Think of consequences if we only found out MUCH later...
  54. 54. If the user interface was challenged ✤ Lab test interaction ✤ Easy to get lost in timeline ✤ Solve problem by adding a date at the bottom ✤ Proceed development, which may be relatively painless. Think of consequences if we only found out MUCH later...
  55. 55. Pivoting business direction? ✤ Generate user traffic? ✤ Sell music? ✤ “UGC”?
  56. 56. Pivoting business direction? ✤ Generate user traffic? ✤ Sell music? BUY ✤ “UGC”?
  57. 57. Putting iterative development in perspective
  58. 58. Release planning of ers keep track Help p roduct own split stories
  59. 59. Release planning of ers keep track Help p roduct own split stories
  60. 60. Release planning of ers keep track Help p roduct own split stories
  61. 61. Release planning of ers keep track Help p roduct own split stories
  62. 62. Release planning of ers keep track Help p roduct own split stories
  63. 63. Feature matrix
  64. 64. Feature matrix
  65. 65. Feature matrix
  66. 66. Feature matrix 75% 60% 85%50% 55% 80% 100% 100% 75% 75%
  67. 67. Product management: story mapping time ves over time & How p roduct evol es prior itise featur
  68. 68. Product management: story mapping Id eas times oal G Sto ries ves over time & How p roduct evol es prior itise featur
  69. 69. Product management: story mapping time ves over time & How p roduct evol es prior itise featur
  70. 70. Product management: story mapping✔ ✗ ✔ ✔ ✔ ✔✔ ✗ ✗ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✗ time✔ ✗ ✔ ✗ ✔ ✔ ✔ ✗ ✔✔ ✔ ✔ ✔ ✔ ✔ ✗ ves over time & How p roduct evol es prior itise featur
  71. 71. Our learning journey✤ Benefits of splitting✤ Engineer the power and affordability to change - and change again✤ Keeping track
  72. 72. Questions & Answers
  73. 73. Obrigada!
  74. 74. Jenny Wong @jenny_wongDanilo Sato @dtsato

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