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Delivery Predictability

The delivery predictability report shows iterations over time in which the team delivered within the guard bands, or between 80 and 120 percent of their iteration commitment. 

In the example to the right, this team's delivery is unpredictable. 

There are a number or possible explanations for variance in this chart. Some examples are;

• Priority injection/changes from stakeholders
• Insufficient or misunderstood requirements
• New team or project/product

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Historical Delivery By Work Type

This chart shows the type of work completed by percentage in the last 12 months

Time in Status

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Defect Management

The Defect Resolution Time Graph shows the average life of defects and bugs, number of defects and bugs created vs resolved, and how many defects and bugs are currently unresolved

Average time to Realized Value

This report shows the average time to deployment for all team level issue types.

• The report can be configured by Time Period, Issue Type, Priority, and Assignee
• This report represents the total cycle time of an issue, from the time of creation until the time of resolution
• Ideally the line on this chart remains as flat as possible. but a decreasing trend indicates improvements

Potential Explanations for upward slope:

• Unused backlog items not being removed or abandoned
• Team size is not adequate for workload

Cumulative Flow

Click here to see Anti-Patterns with Cumulative Flow

Planning Variance

This chart allows you too see how many of the points completed were part the commitment at the beginning of the sprint. In high performing teams this variance should be zero most of the time.

Potential reasons for seeing variance:

• Work injection from outside the team
• Work not well understood before commitment
• Adjusting story points during the iteration
• Splitting stories within the iteration

The purple bar showing velocity(The number of points completed during the sprint) should remain relatively steady, regardless of variance