How to create Points Committed vs Accepted reports Atl. Analytics using data from Jira Align (EI)

dimitrios_tsiolakis

Hi,

I need some guidance on how to create the following reports in Atlassian Analytics using data from Jira Align:

• Iteration Metrics (M1)
• Planned vs Actual Velocity

I’ve attached screenshots of the reports for reference:

• Story Point Progress by Team
• Iteration Metrics (M1) view

Could you please share the steps or any resources that explain how to build these reports? Any tips on best practices for configuring the data would also be greatly appreciated.

Thank you for your support!

Best regards,
Dimitris

Mohsin Shaikh_tyjrji

Hello Dimitris,

I hope you are doing well.

Here's some information on how to create Points Committed vs Accepted and Planned vs Actual Velocity reports in Atlassian Analytics using data from Jira Align Enterprise Insights (EI), based on the screenshots and best practices:

1. Connect Jira Align Enterprise Insights to Atlassian Analytics

Before building reports, ensure your Jira Align EI instance is connected to Atlassian Analytics:

• Prerequisites: Your org admin must work with Atlassian/Jira Align support to associate your EI instance with your Analytics workspace.

• Connect Data Source:

  1. Go to Analytics → Data sources → Add data source.

  2. Select Jira Align Enterprise Insights.

  3. Choose your instance, name it, and connect.

  4. Connect to Jira Align Enterprise Insights | Atlassian Analytics | Atlassian Support

• Templates: Atlassian provides dashboard templates for EI to help you get started.

  • Dashboard templates for Jira Align Enterprise Insights | Atlassian Analytics | Atlassian Support

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2. Report 1: Iteration Metrics (M1) – Points Committed vs Accepted

Goal: Show, per team and iteration, the % of story points committed vs accepted, and % of stories committed vs accepted.

Structure (based on your screenshot):

• Rows: Scrum Teams

• Columns: Iterations/Sprints (with date ranges)

• Metrics:

  • Stories Committed vs Accepted:
    (Count of Accepted Stories / Count of Committed Stories) * 100

  • Points Committed vs Accepted:
    (Sum of Accepted Story Points / Sum of Committed Story Points) * 100

• Conditional Formatting:

  • Green for 100% or above, red for low percentages.

How to Build in Atlassian Analytics:

1. Data Source: Use the connected Jira Align EI data.

2. Table Visualization:

   • Rows: Group by Team (from the Teams table).

   • Columns: Group by Iteration (from the Iterations/Sprints table), display iteration name and date range.

   • Metrics:

     • Committed Stories: Stories planned for the iteration.

     • Accepted Stories: Stories with status “Accepted” or “Done” in the iteration.

     • Committed Story Points: Story points of committed stories.

     • Accepted Story Points: Story points of accepted stories.

   • Calculated Fields:

     • Add calculated columns for the % formulas above.

   • Conditional Formatting: Use Analytics’ formatting options to color cells based on thresholds.

3. Filters:

   • Filter by Program Increment (PI), team, or other relevant fields.

Best Practices:

• Ensure your EI schema is up to date and you’re using the correct fields for “committed” and “accepted” (these may be custom in your Jira Align instance).

• Use calculated fields for percentages.

• Use color formatting to highlight performance.

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3. Report 2: Planned vs Actual Velocity (Story Point Progress by Team)

Goal: Compare planned vs accepted story points per Program Increment (PI) for each team.

Structure (based on your screenshot):

• X-axis: Program Increment (PI)

• Y-axis: Story Points

• Series:

  • Points Planned: Sum of story points planned for the PI.

  • Points Accepted: Sum of story points accepted in the PI.

• Chart Type: Grouped Bar Chart (Planned vs Accepted side by side for each PI).

How to Build in Atlassian Analytics:

1. Data Source: Jira Align EI.

2. Bar Chart Visualization:

   • X-axis: Program Increment (PI).

   • Y-axis: Story Points.

   • Series:

     • Points Planned: Sum of story points for stories planned for the PI.

     • Points Accepted: Sum of story points for stories accepted in the PI.

   • Grouping: By PI, optionally by team.

   • Legend: “Points Planned” (blue), “Points Accepted” (green).

3. Filters:

   • Filter by team, PI, or other relevant fields.

Best Practices:

• Use consistent definitions for “planned” and “accepted” (see below).

• Validate your data model:

  • Points Planned: SUM(story points) for all stories assigned to the team and PI.

  • Points Accepted: SUM(story points) for all stories accepted and assigned to the PI.

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4. Definitions & Data Model Tips

• Points Planned:
  SUM(story points) for all stories assigned to the team and PI (not including stories outside the PI).

• Points Accepted:
  SUM(story points) for all stories accepted and assigned to the PI.

• Committed Stories: Stories planned for the iteration at the start.

• Accepted Stories: Stories with status “Accepted” or “Done” at the end of the iteration.

References:

• Dashboard templates for Jira Align Enterprise Insights | Atlassian Analytics | Atlassian Support

• Connect to Jira Align Enterprise Insights | Atlassian Analytics | Atlassian Support

• Customizing the Jira Align Enterprise Insights data source schema in Atlassian Analytics

I hope this information helps. 

Best regards,
Mohsin Shaikh
ATLASSIAN | Cloud Senior Support Engineer