ISG Playbook
APIsDelivery Predictability
The delivery predictability This 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
- Scarcity of of team resources
- No time for refinement
- Dependencies on other teams
- Under estimating the effort
- Over estimating available time
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Historical Delivery By Work Type
| This chart shows the different work item types by percentage in a team’s backlog. Similar to the program backlog, teams are responsible for applying capacity allocation to team backlog in order to determine how much of their total efforts can be used for each type of activity in a given iteration. The team works the highest priority items in the backlog, but includes work of different types to maintain a healthy backlog, and optimize the delivery of value. Benefits:
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Time in Status
| This chart shows the number of days that a work |
item spends in each status the team utilizes. |
Understanding the statuses used gives insight |
into how the team manages work, the flow and |
throughput of the team, the depth of the team |
backlog, and the batch size of the teams work |
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time in statuses before |
In Progress will be significantly higher than the rest of the |
statuses, with the exception of abandoned, which |
will increase until the team closes abandoned items. High times in specific statuses indicate potential |
bottlenecks and opportunities to improve flow. |
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Defect Management
The Defect Resolution Time Graph This chart 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.
This chart also shows the average resolutions days within a given time . This allows to see how many defects, bugs the team are rising each iteration to understand the number of defects/bugs arising each iteration, which helps with built-in quality by reducing technical debt each iteration. This is a number that should obviously be going down, ideally at or close to zero.
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Average
timeTime to Realized Value
This report shows displays 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 ; note that a decreasing trend indicates improvements
Potential Explanations explanations for upward slope:
- Unused backlog items not being removed or abandoned
- Team size is not adequate for workload
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Cumulative Flow Diagram (CFD)
This is an area chart that shows the various statuses of work items for an application, version, or iteration. The horizontal x-axis in a CFD indicates time, and the vertical y-axis indicates cards (issues). Each colored area of the chart equates to a workflow status (a column on your board).
The CFD can be useful for identifying bottlenecks. If your chart contains an area that is widening vertically over time, the column that equates to the widening area will generally be a bottleneck.
Cumulative flow diagram CFD shows the tasks at each stage of the project over time. For In the example on the left, the green area represents the tasks that are completed. In the chart example in the left. The , the blue area represents items in progress, while and the red area covers the backlog ready for development.
Cumulative Flow Diagram CFD may seem complicated at first , but at a upon closer look, it can easily show provide a number of useful insights. For example, the vertical axis of the chart shows how many the number of tasks are currently being worked on or completed. It allows understanding the optimal work in progress limits.
Click below to see Anti-Patterns with Cumulative Flow
Cumulative Flowhere to read more about anti-patterns with CFD
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Planning Variance
This chart allows you too to see how many the number of the points completed were part based on the commitment at the beginning of the sprintiteration. 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 the number of points completed during the sprintiteration) should remain relatively steady, regardless of variance.
