Due Date Performance Chart for Azure DevOps
Measure your delayed work. Evaluate the accuracy of your predictions. Calculate your on-time delivery ratio.
Measure your delayed work. Evaluate the accuracy of your predictions. Calculate your on-time delivery ratio.
The Due Date Performance Chart for Azure DevOps enables you to measure your due date performance by comparing the time between the start date and due date of a work item, with the actual time it took to deliver your work. Each dot on the graph represents a completed work item on your Azure board, with its cycle time plotted against the horizontal axis and its predicted time displayed on the vertical axis.
Your due-date performance is a measure of reliability. Furthermore, it determines the quality of your initial forecast. The accuracy of your forecasts strongly depends on the stability of your system - the more stable your system is, the more dependable your forecasts will be.
With the Due Date Performance chart for Azure DevOps, you can filter your completed work by ‘On-time work items’ and ‘Overdue work items’ in order to perform a root cause analysis of the reasons behind your delays.
Your predicted time is calculated as the difference between the moment a work item first entered your workflow and the due date of the work item, while your completion time is the difference between the same starting point and the work item’s actual completion date.
By clicking on each dot, you can access further details of the work item. This includes its total cycle time, its predicted time, a direct link to the card on your Azure board as well as the cycle times your work has spent in each process state.
Analyze your overdue work items individually and pay special attention to the states with the longest cycle times to locate the bottleneck impeding your system.
The line plotted across the chart is called a regression line. It flows roughly through the middle of all your completed work items. The slope of the regression line exposes the difference between your predicted time and the actual time needed to deliver your work.
The due date regression line helps you evaluate the accuracy of your predictions and gauge the efficiency of the system you are maintaining.
The ‘On-Time Delivery’ widget displays the percentage of times that you managed to deliver before your due date arrived. It also visualizes how your due date performance trends have moved over time.
The fundamental element of a due date performance analysis is assessing whether your work has been delivered on time. If the percentage is quite low, this denotes that your initial predictions are unrealistic. If that’s the case, consider forecasting your work items using your past performance data with the Cycle Time Scatterplot for Azure DevOps.