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  • So, before we get started, a little about me. My name is Mike Cottmeyer, I am an agile transformation coach with Pillar technology. Before I joined Pillar I was a trainer and consultant with VersionOne. Before that I ran a pretty large agile portfolio of projects for CheckFree (now Fiserv). Pillar Technology has been around for about 13 years and is just about 100 people strong. Pillar specializes in agile transformation and project delivery. We can bring in agile coaches on the leadership and project management side. We can bring in coaches to help you with TDD. We can spin up teams and help you deliver projects.
  • Explaining the hierarchy of value
  • Explaining the hierarchy of value
  • Explaining the hierarchy of value
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • Story Mapping
  • So, before we get started, a little about me. My name is Mike Cottmeyer, I am an agile transformation coach with Pillar technology. Before I joined Pillar I was a trainer and consultant with VersionOne. Before that I ran a pretty large agile portfolio of projects for CheckFree (now Fiserv). Pillar Technology has been around for about 13 years and is just about 100 people strong. Pillar specializes in agile transformation and project delivery. We can bring in agile coaches on the leadership and project management side. We can bring in coaches to help you with TDD. We can spin up teams and help you deliver projects.
  • Transcript

    • 1. LeadingAgile
      Agile Analysis & Design: Requirements Decomposition
    • 2. Mike CottmeyerLeadingAgilemike@cottmeyer.com 1.404.312.1471www.leadingagile.com facebook.com/leadingagiletwitter.com/mcottmeyer linkedin.com/in/cottmeyer
    • 3. Requirements DecompositionStory Maps and MMF
    • 4. Epics collections of features, typically 1-3 months in duration. Epics span releases. Epics can span more than one team. These are the things the CEO cares about.
      Epic
    • 5. Epics collections of features, typically 1-3 months in duration. Epics span releases. Epics can span more than one team. These are the things the CEO cares about.
      Epic
      Features are smaller than epics, typically 2-4 weeks in duration. Features are contained within releases. Features are contained within a team. These are what the Product Owner Cares about.
      Feature
    • 6. Epics collections of features, typically 1-3 months in duration. Epics span releases. Epics can span more than one team. These are the things the CEO cares about.
      Epic
      Features are smaller than epics, typically 2-4 weeks in duration. Features are contained within releases. Features are contained within a team. These are what the Product Owner Cares about.
      Feature
      User Stores are the smallest increment of value, typically less than a week. User Stories are contained within sprint. These are the things Engineering Management Cares about.
      User
      Story
    • 7. Story Maps visually show the relationship between User Stories and Business Value
      Epic
      Feature
      Feature
      Feature
      Feature
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 8. Story Maps start with the identification of larger, more strategic organizational goals
      Epic
    • 9. Epicsare decomposed into Features that describe the value added into the product
      Epic
      Feature
    • 10. Epicsare decomposed into Features that describe the value added into the product
      Epic
      Feature
      Feature
    • 11. Epicsare decomposed into Features that describe the value added into the product
      Epic
      Feature
      Feature
      Feature
    • 12. Epicsare decomposed into Features that describe the value added into the product
      Epic
      Feature
      Feature
      Feature
      Feature
    • 13. Featuresare decomposed into User Stories that are thin slices of value added into the system
      Epic
      Feature
      Feature
      Feature
      Feature
      User Story
      User Story
      User Story
      User Story
    • 14. Featuresare decomposed into User Stories that are thin slices of value added into the system
      Epic
      Feature
      Feature
      Feature
      Feature
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 15. Featuresare decomposed into User Stories that are thin slices of value added into the system
      Epic
      Feature
      Feature
      Feature
      Feature
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 16. Featuresare decomposed into User Stories that are thin slices of value added into the system
      Epic
      Feature
      Feature
      Feature
      Feature
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 17. Estimating and Planning
    • 18. User Stories are estimated in relative units of measure called Story Points
      Epic
      3
      1
      2
      1
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      5
      2
      3
      2
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 19. Story Points can be added up to size Features
      Epic
      11
      7
      8
      12
      3
      1
      2
      1
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      5
      2
      3
      2
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 20. Feature Points can be added up to size Epics
      38
      Epic
      11
      7
      8
      12
      3
      1
      2
      1
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      5
      2
      3
      2
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 21. Our Goal is to build the smallest system possible to deliver the value in the Epic
      38
      Epic
      11
      7
      8
      12
      3
      1
      2
      1
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      5
      2
      3
      2
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 22. We continuously evaluate the Story Map to determine the Minimally Marketable Feature
      38
      Epic
      11
      7
      8
      12
      3
      1
      2
      1
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      5
      2
      3
      2
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 23. We continuously evaluate the Story Map to determine the Minimally Marketable Feature
      38
      Epic
      11
      7
      8
      12
      3
      1
      2
      1
      User Story
      User Story
      User Story
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      User Story
      User Story
      User Story
      5
      2
      3
      2
      User Story
      User Story
      User Story
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 24. When we focus on Minimally Marketable Features, we deliver Business Value early
      26
      Epic
      10
      4
      7
      5
      3
      1
      2
      1
      User Story
      User Story
      User Story
      Feature
      Feature
      Feature
      Feature
      3
      2
      3
      5
      User Story
      User Story
      User Story
      5
      2
      3
      2
      User Story
      User Story
      User Story
      1
      1
      2
      2
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
      User Story
    • 25. Minimally Marketable Featuresfeed the prioritization of our Sprint Planning
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
    • 26. Identify the User Story most likely to contribute to the MMF and build that one first
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
    • 27. Identify the User Story most likely to contribute to the MMF and build that one first
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      User Story
    • 28. Pull User Stories in priority order focusing on delivering complete MMFs
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      User Story
    • 29. Pull User Stories in priority order focusing on delivering complete MMFs
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      User Story
      2
      User Story
    • 30. It’s okay to work User Stories across MMFs if that is what the Product Owner needs
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      User Story
      2
      User Story
    • 31. It’s okay to work User Stories across MMFs if that is what the Product Owner needs
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      User Story
      2
      User Story
      1
      User Story
    • 32. The team uses its past velocity to determine how many stories go in the Sprint
      Planned Team Velocity = 6 points
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      User Story
      2
      User Story
      1
      User Story
    • 33. The Team breaks each User Story down into Tasks
      Planned Team Velocity = 6 points
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      Task
      Task
      User Story
      Task
      2
      User Story
      1
      User Story
    • 34. The Team breaks each User Story down into Tasks
      Planned Team Velocity = 6 points
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      Task
      Task
      User Story
      Task
      2
      Task
      Task
      User Story
      Task
      Task
      1
      User Story
    • 35. The Team breaks each User Story down into Tasks
      Planned Team Velocity = 6 points
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      Task
      Task
      User Story
      Task
      2
      Task
      Task
      User Story
      Task
      Task
      Task
      Task
      1
      User Story
      Task
      Task
    • 36. And estimates each Task in Real Hours so they can assess if they can make a solid Commitment to Deliver
      Planned Team Velocity = 6 points
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      16
      8
      Task
      Task
      User Story
      8
      Task
      2
      Task
      Task
      User Story
      Task
      Task
      Task
      Task
      1
      User Story
      Task
      Task
    • 37. And estimates each Task in Real Hours so they can assess if they can make a solid Commitment to Deliver
      Planned Team Velocity = 6 points
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      16
      8
      Task
      Task
      User Story
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      Task
      Task
      1
      User Story
      Task
      Task
    • 38. And estimates each Task in Real Hours so they can assess if they can make a solid Commitment to Deliver
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      16
      8
      Task
      Task
      User Story
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      16
      8
      Task
      Task
    • 39. At the beginning of the Sprint, The Team pulls Tasks from the top of the Task Backlog
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      16
      8
      Task
      Task
    • 40. Tasks move across the Story Board until there is a completed User Story.
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      16
      8
      Task
      Task
    • 41. Tasks move across the Story Board until there is a completed User Story.
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      8
      Task
      16
      Task
    • 42. Tasks move across the Story Board until there is a completed User Story.
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      8
      Task
      16
      Task
    • 43. The Team works from the top of the Story Board, Swarming to get User Stories across the board as fast as possible .
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      8
      Task
      16
      Task
    • 44. The Team works from the top of the Story Board, Swarming to get User Stories across the board as fast as possible .
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      8
      Task
      16
      Task
    • 45. The Team works from the top of the Story Board, Swarming to get User Stories across the board as fast as possible .
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      8
      4
      Task
      Task
      1
      User Story
      8
      Task
      16
      Task
    • 46. Until the entire Sprint has been delivered to the Product Owner.
      Planned Team Velocity = 6 points
      Planned Estimated Hours = 98 hours
      Story Done
      In Process
      Task Done
      Task Backlog
      Story Backlog
      3
      8
      Task
      User Story
      16
      Task
      8
      Task
      2
      2
      16
      Task
      Task
      User Story
      8
      Task
      4
      Task
      1
      8
      4
      Task
      User Story
      Task
      8
      Task
      16
      Task
    • 47. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 48. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 49. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 50. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 51. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 52. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 53. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 54. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 55. From a Metrics perspective, we Burn Down hours to make sure the sprint is on track
      38
      96
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 56. From a Metrics perspective, we Burn Down points to make sure the Release is on track
      38
      96
      6
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 57. From a Metrics perspective, we Burn Down points to make sure the Release is on track
      38
      96
      8
      6
      6
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 58. We track Velocity Trend to make sure the team is delivering in a Predictable manner
      38
      96
      8
      6
      6
      5
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 59. When the Release is ready to deliver, The Team has completed the highest priority User Stories, against the highest priority Features ,against the highest priority Epics.
      38
      96
      8
      6
      6
      5
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 60. When the Release is ready to deliver, The Team has completed the highest priority User Stories, against the highest priority Features ,against the highest priority Epics.
      Everyone is focused on delivering value early and often!
      38
      96
      8
      6
      6
      5
      Release Burndown
      Sprint Burndown
      Velocity Trend
    • 61. 10 Patterns for Splitting User Stories
    • 62. Pattern 1 – Workflow Steps
      Identify specific steps that a user takes to accomplish the specific workflow, and then implement the work flow in incremental stages
      As a utility, I want to update and publish pricing programs for my customers
      …I can publish pricing programs to the customers in-home display
      I can send a message to the customer’s web portal
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 63. Pattern 2 – Business Rule Variations
      Some business rules are pretty complex. If this is the case, break the story into several stories to handle the business rule complexity
      As a utility, I can sort customers by different demographics
      …sort by Zip Code
      …sort by home demographics
      …sort by energy consumption
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 64. Pattern 3 – Major Effort
      Sometimes a story can be split into several parts where most of the effort will go into implementing the first one
      As a user, I want to be able to select/change my pricing program with my utility through my web portal
      …I want to use time of use pricing
      …I want to prepay for my energy
      …I want to enroll in critical-peak pricing
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 65. Pattern 4 – Simple Complex
      What’s the simplest version that can possibly satisfy the customers need
      As a user, I basically want a fixed price, but I also want to be notified of critical-peak pricing events
      …respond to the time and duration of the critical peak pricing event
      …respond to emergency events
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 66. Pattern 5 – Variations in Data
      Data variations and data sources are another source of scope and complexity. Consider adding stories just in time after building the simplest version
      As a utility, I can send messages to customers
      …customers who want their messages
      …in Spanish
      …in Arabic, and so on
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 67. Pattern 6 – Data Entry Methods
      Sometimes complexity is in the user interface rather than the functionality itself. Build the simplest possible UI first
      As a user, I can view my energy consumption in various graphs
      …using bar charts that compare weekly consumption
      …in a comparison chart, so I can compare my usage to those who have the same or similar demographics
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 68. Pattern 7 – Defer System Qualities
      Sometimes the initial implementation is not all that hard. Do the simple thing first and then add attributes like scaleability and speed later.
      As a user, I want to see real-time consumption from my meter
      …interpolate date from the last known reading
      …display real time data from the meter
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 69. Pattern 8 – Operations (CRUD)
      Words like manage or control give away that the story might cover multiple operations
      As a user, I can manage my account
      …I can sign-up for an account
      …I can edit my account settings
      …I can cancel my account
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 70. Pattern 9 – Use Case Scenarios
      If use cases have been developed to represent complex user-to-system or system-to-system interactions, the story can often be split according to the scenarios in the use case
      I want to enroll in the energy savings program through a retain disributor
      …Use Case/Story #1 (happy path) Notify utility that consumer has equipment
      …Use Case/Story #2 (alternate scenario) Handle data validation errors
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 71. Pattern 10 – Break Out a Spike
      If the story is too large or overly complex, or if the implementation is poorly understood, build a functional or technical spike to figure it out.
      As a user I want to be able to create reports that have never been created before and we do not have the technology in place to deliver them
      …Research the available technologies for online report delivery
      …Create mockups of reports to show to the customer
      Source: Dean Leffingwell, Agile Software Requirements, Addison-Wesley, 2010
    • 72. Mike CottmeyerLeadingAgilemike@cottmeyer.com 1.404.312.1471www.leadingagile.com facebook.com/leadingagiletwitter.com/mcottmeyer linkedin.com/in/cottmeyer