TimePerfect8403 describes the challenge of migrating sprint planning to Azure DevOps, emphasizing story point forecasting over task-level estimation, and provides tips for agile, team-centric capacity management.

Sprint Planning and Capacity Management in Azure DevOps Without Predefined Tasks

Author: TimePerfect8403

Migrating your team’s workflow to Azure DevOps can be challenging, especially when it comes to planning sprints and measuring capacity. The scenario discussed here involves:

  • Requests are triaged and estimated using story points.
  • User stories are assigned to team members, who define tasks during the sprint as they work.
  • Hours are recorded post-completion for each ticket.
  • Management wants greater visibility into the progress of individual stories.

Key Challenge

Azure DevOps typically measures sprint capacity based on hours linked to tasks. However, this team’s process creates tasks dynamically during the sprint, not before planning. This creates a disconnect between story point-based planning and hour-based capacity tracking.

Practical Solutions in Azure DevOps

  • Use Backlog Forecasting:
    • In the backlog view, enable the Forecasting feature (found in the backlog’s view options).
    • This predicts how many stories can fit in a sprint based on historical story point capacity, helping you plan sprints even when tasks aren’t pre-defined.
  • Assign Stories to Sprints:
    • During sprint planning, select the user stories you want and add them to the upcoming sprint, using story points and forecast lines as your guide.
  • Granular Progress Tracking:
    • Members can create tasks under user stories during the sprint to represent work steps, making progress transparent for managers.
  • Capacity Tracking by Story Points:
    • Use forecasted story point totals as your main planning metric, rather than hours.
    • Record hours spent at the sprint’s end by aggregating the hours logged on tasks created during execution.
    • This approach aligns with agile best practices and avoids the inefficiency of estimating every task upfront.

Agile Perspective

The discussion highlights:

  • Azure DevOps is optimized for agile workflows (user stories, story points, adaptive planning).
  • Task-level hour capacity is mainly for teams with more traditional or waterfall practices.
  • Teams should avoid the ‘estimation trap’—overemphasizing accuracy in hour tracking can undermine agile delivery and trust (read more).

Summary of Recommendations

  • Rely on user stories and story point forecasting for sprint planning.
  • Add granular tasks during the sprint for progress tracking, not up-front estimation.
  • Use Azure DevOps forecasting tools to visualize sprint capacity and planning boundaries.
  • Focus on flow and value delivery over precise upfront task-hours.

This discussion provides actionable strategies for agile teams transitioning to Azure DevOps, enabling a smoother migration and improved planning outcomes while maintaining agile principles.

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