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How Advanced Roadmaps assigns capacity

This page refers to Advanced Roadmaps, which is a cross-project planning tool only available as part of Jira Software Cloud Premium and Enterprise.

We have a separate section for documentation about the project roadmap that’s included in all Jira Software plans. Go to the documentation for project-level roadmaps in Jira Software.

 

As you assign issues to teams and sprints, Advanced Roadmaps tracks the total amount of assigned work per iteration to help you make a viable plan of attack for your teams. It takes the estimation values (in story points or in hours/days) and subtracts it from the total capacity of your iteration. Learn how to change the capacity of your iterations

In order for capacity management to work, issues need to have an estimate. Learn more about estimating issues in Advanced Roadmaps

The simplest way to manage capacity is to assign an issue to sprint using the Sprint field. Assigned issues consume the estimation value from the capacity, assuming they’re only scheduled to last one sprint.

Advanced Roadmaps can also infer when an issue should consume capacity even if the Sprint field is empty. If an issue assigned to a team is scheduled during one of their sprints, the issue still consumes capacity--even if the Sprint field is empty. These issues are indicated with the label x issues not assigned to sprint in the sprint detail window which you can access by selecting the sprint from the timeline.

Change the capacity of an iteration from your timeline in Advanced Roadmaps for Jira Software Cloud.

Distribute capacity across multiple iterations

Issues in Advanced Roadmaps consume capacity on a first-come, first-serve basis, with priority given to:

  1. an issue’s scheduled end date

  2. issues of lower hierarchy levels (stories or subtasks take priority over epics or initiatives)

  3. issue rank as defined on your timeline

When dealing with issues that span multiple iterations, Advanced Roadmaps uses the assumption that an issue can only be assigned to one person. With that in mind, it distributes that issue based on capacity of one team member, which it calculates this using the following equation:

  • [team’s capacity per iteration]/[number of people in a team] = [capacity of one team member]

This formula assumes that:

  • the capacity of each team member is equal, and

  • only one person will be working on the issue

For example, if a team of five has a capacity of 20 story points, Advanced Roadmaps would calculate an individual team member’s capacity using the formula above to be four points per iteration (20/5=4). With that determined, Advanced Roadmaps would then distribute an issue that spans three iterations with a value of 10 story points as follows:

  • iteration 1: four points

  • iteration 2: four points

  • iteration 3: two points

However, the capacity distribution algorithm in Advanced Roadmaps respects the dates that you set for an issue. If the scheduled duration of the issue isn’t enough for the individual team member’s capacity to handle, Advanced Roadmaps distributes the capacity as outlined above until the iteration where the issue is due. In the last iteration, Advanced Roadmaps allocates all remaining capacity in order to make your deadline.

This is a common source of unexpectedly overbooked sprints.

If the example above was estimated at 16 story points (instead of 10), Advanced Roadmaps would distribute the capacity as follows:

  • iteration 1: four points

  • iteration 2: four points

  • iteration 3: eight points

To change this behavior, you can revise the end dates of your issues as to not exceed the individual capacity of your team members, or adjust your issue’s estimate. You might also break down your work into smaller tasks and assign it to multiple people.

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