Your PI Planning Checklist

PI Planning Roadmap

5 Weeks to PI Planning

  • Lean Business cases & Epic Hypothesis communicated (new work) and evaluated (existing work)
  • Solution Management and Portfolio Management aligns on next priorities and socialize with Product Management (PM)
  • Solution Roadmaps are updated & socialized with PM
  • Continuous Exploration workshops conducted to build out features
  • WSJF updated by PM community (PM, Solution Management, Architects, PO’s, SMEs, Agile Team reps., RTEs etc.)
  • ART Vision & Roadmap updated
  • Socialization of Vision, Roadmaps and Features with the ARTs
  • Estimates updated as team refinements pan out

4 Weeks to PI Planning

  • Product Manager Align on the Vision
  • ART Roadmaps are updated based on Solution Roadmaps
  • Personas are associated with features
  • Top features are identified (or created) with Benefit Hypothesis and Acceptance Criteria
  • Features are sized with PMs, Architects, Team leads, SMEs etc. calculate and align on Capacity Allocation
  • Understand what features might slip into next PI

3 Weeks to PI Planning

  • Feature WSJF weighted and sequenced in Program backlog
  • Features are high level estimated
  • Architects update and socialize their Architectural Runway Roadmap
  • Product Mangers and Architects meet on Enabler Features and their WSJF
  • Re-sequence Backlog
  • Ideation / Inception Design Workshops to understand and decompose work to feed team backlogs
  • Feature Acceptance criteria is solid

2 Weeks to PI Planning

  • Features are understood and socialized with Agile Teams
  • Feature requester / Business Owner / PM describes why the feature is prioritized
  • Aligns teams on the benefit hypothesis and the acceptance criteria
  • Where incomplete, PM works with teams and stakeholders to augment them
  • Teams start slicing user stories from the features and populates the team backlogs
  • Teams refine the user stories and enabler stories with acceptance criteria and story points
  • Product Owner and team ensures they prioritize work across the spectrum of the capacity allocation model

1 Week to PI Planning

  • Teams have a good grasp on the user stories to be completed in next PI
  • Continuous refinement on the team backlog for next PI is in full motion
  • Discussions with other teams regarding user story clarity and dependencies (knowledge/skill/technical/build) takes place and is recorded in ADO to solidify the plan
  • User stories are estimated and meets the team’s definition of ready
  • Scrum Master and Team reviews the Team’s metrics and calculates the average velocity for the next iterations / PI
  • Capacity Allocation model is updated if required for upcoming PI

Week of PI Planning

  • Ensure current PI Objectives have their Actual Business Value set by Business Owners
  • Teams participate in Inspect and Adapt (I&A)
  • Scrum Master and Product Owner records the improvement items in the backlog for execution in upcoming PI (with size, acceptance criteria/ outcome on stories)
  • Improvement work earmarked for next PI is linked to Improvement feature on ART and Tagged “Continuous Improvement” item
  • Scrum Masters prepare metrics for current PI and publishes it on Dashboards
  • Scrum Master ensures next PI dashboards are ready for next PI
  • Scrum Master ensures team backlog and next iterations are ready in next PI (in ADO) and works with PO and team to evolve the plan
  • Definition of Done updated for next PI based on current PI learning
  • Closing current iteration, PI Objectives, Iteration Goals
  • Participate in PI Planning

After PI Planning

  • Capture all work in ADO with size of work
  • Link all work according to ADO standards
  • Ensure all PI Objectives have Business Value planned after discussing with Business Owners
  • Program Board updated with feature cards and dependencies
  • Ensure dependencies reflect in all affected teams
  • Risks are captured in ADO with all relevant fields updated (ROAM, Level, Owner (if known), etc.)
  • Agile teams perform their Iteration Planning and teams commit to their first iteration’s delivery

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