icon in this panel to launch the Predict Cycle Time Key Factors Analysis dashboard and analyze detailed information about the various Key Factors that have contributed to longer cycle times in completed Work Items.The Predict Cycle Time dashboard enables you to identify and mitigate risk factors contributing to unplanned delays that can affect scheduled releases. Delays can impact businesses by affecting the time-to-market and can result in lost market opportunities
The dashboard uses machine learning capabilities that predict the cycle time needed to complete Work Items, which can help you understand if your epics, features, or user stories are on track to complete in time to meet target dates, such as the end of an iteration.
As a Delivery Manager, you can find answers for some of the key business scenarios such as:
This dashboard is built using the Work Item Snapshot Daily, Work Item Key Factors and Work Item Recursive Hierarchy iCube and fetches data based on the filter specified for these iCubes.
Note: This dashboard supports Jira(Iteration end date only) and Digital.ai Agility source system.
The Predict Cycle Time dashboard consists of the following pages:
The Predict Cycle Time by Planned end date dashboard page enables you to analyze Work Items that are assigned to an Epic and are at risk of not completing before the planned end date, thereby affecting timely delivery of Projects. The valuable insights provided in this dashboard ensure that you identify schedule risks well in advance and be better prepared to reduce cycle times.
The Predict Cycle Time by Iteration end date dashboard page enables you to analyze Work Items that are assigned to an Iteration and are at risk of not completing before the Iteration end date, thereby affecting timely delivery of Projects. The valuable insights provided in this dashboard ensure that you identify schedule risks well in advance and be better prepared to reduce cycle times.
The Predict Cycle Time by Program Increment end date dashboard page enables you to analyze Work Items that are assigned to Program Increment and are at risk of not completing before the Program Increment end date, thereby affecting timely delivery of Projects. The valuable insights provided in this dashboard ensure that you identify schedule risks well in advance and be better prepared to reduce cycle times.
Note: 'Project' will mean 'Planning Level' for Agility customers and 'Jira Project' for Jira customers.
You can use the filters in the dashboard to analyze information related to projects associated with specific Engineering Managers, and the dashboard supports up to three levels of hierarchy in case of filtering results based on Managers.
The data displayed in this dashboard considers only primary Work Items that are in the In Progress or Resolved status and are by default configured to be an Epic or a Story, however, the primary Work Item type can be modified based on your organization needs.
Note: Use Filter Primary Work Items by predicted before-due or over-due completion dropdown to filter and analyze information related to Before due, Over due, End date not populated, or All primary work items.
This dashboard pages consists of the following sections:
Displays recommendations to prioritize the top 3 projects for Iteration end date page, and top 3 planning levels for Planned end date and Program increment end date page; that have the highest number of Primary Work Items and are predicted to end past their planned end date or iteration end date or program increment end date based on the page and at risk being delivered overdue.
The projects and planning levels are identified based on the Primary Work Items at Risk Opportunity Rank.
Displays bar charts that provide information about Enterprise, Portfolio, Product, Program Increment, Projects or Iterations that are at risk of not completing because of Work Items that are predicted to end past their end date. The bar charts are categorized based on the number of days by which the predicted end date of a Work Item is overdue as compared to its respective planned end date or iteration end date or program increment end date based on the page.
The predicted overdue days are grouped into three buckets that indicate if Work Items are overdue, before due, and planned work item or iteration or program increment end date is not populated based on the page and are denoted through orange, green, and blue colors respectively. Each section in the bar graph also displays the number of Work Items in each bucket.
You can click on a particular bucket group in the bar graph to view more details about the associated Primary Work Items in the subsequent sections.
The Project, Iteration and Program Increment Predicted Days Overdue bucket groups are based on the following preconfigured values and can be modified based on your requirements. Contact the Digital.ai support team to modify these configurations:
Note: Primary Work Items that are not associated with any Project or Iteration are considered as part of the UNSPECIFIED category.
Displays a donut pie chart with information about the number of days in which Primary Work Items are expected to complete. Each section of the pie chart categorizes Work Items based on the following preconfigured buckets that represent days needed to complete the task:
Note: These values are the default out-of-the-box values and can be configured based on your requirements. Contact the Digital.ai support team to modify these configurations.
The predicted overdue days are grouped into three buckets that indicate if Work Items are overdue, before due, and planned work item or iteration or program increment end date is not populated based on the page and are denoted through orange, green, and blue colors respectively.
You can hover over each section of the chart to view the number of Primary Work Items under each category along with the percentage contribution with respect to all Work Items.
You can also click a particular section of the chart to filter data and view more details about specific Work Items in the subsequent report.
This section is driven through selections made in the previous reports and displays more details about specific Primary Work Items, such as Work Item Number, end date of work item or end date of Iteration or end date of Program Increment to which the Work Item is assigned to, end date of the Work Item as predicted by the ML model, predicted days past due date, and number of Work Items that are currently blocked because of the primary Work Item.
The Predicted Days Past Due column indicates the number of predicted days by which the Primary Work Item is before due or overdue, and is calculated as the difference between Work Item predicted end date and Planned end date or Iteration end date or Program increment end date based on the page. Work Items that are predicted to complete before planned end date, iteration end date and program increment end date are denoted through green color and predicted overdue Work Items are depicted in red color.
You can also click the Source URL icon against a Work Item to launch the corresponding source system and view more details.
If you want to understand more about the prediction details of a specific Work Item, such as the key factors contributing to the delay or its dependencies, right-click a Primary Work Item and select the Go To Page: Prediction Detail option to open the Prediction Detail page specific to the selected Primary Work Item.
The Prediction Detail dashboard page is focused on the Primary Work Item that you selected previously and provides detailed insights about the Work Item with respect to key factors instrumental in determining the predicted end date, dependent Work Items, timeline illustrating the progress, and so on.
These insights enable you to perform detailed analysis and identify areas that you can focus on to improve the Work Item cycle time and ensure that the Work Item does not impede the project or iteration schedule.
Important: The data in this dashboard page provides information about the specific Primary Work Item that you selected in the previous dashboard page. Therefore, ensure that you do not modify the Engineering Manager filters at the dashboard level that you might have previously specified.
You can click Return in the page title to go back to the previous dashboard page.
The first section of this dashboard page provides information about the selected primary Work Item, its summary, type of work item like Story, Epic, or Feature, date when the Work Item first moved to an In Progress status, and date when the Work Item is predicted to end based on the ML model. You can click the Source URL icon against the Work Item to launch the corresponding source system and view more details.
You can also view detailed information about the selected primary Work Item through the following sections:
Displays detailed information about the Primary Work Item such as the Project and Iteration to which it is currently assigned. This section also provides the following details:
You can click on any of the above parameters to view related information in the subsequent sections.
Displays the top 8 key factors that are determined by the Cycle Time Prediction ML model. Key factors correspond to predictor variables used by the ML model to predict time to complete a Work Item. These factors help you in identifying areas associated with a Work Item that could potentially impact the schedule and enable you to take appropriate measures to reduce the cycle time.
For example, a high number of child Work Items could indicate additional time required to complete the Primary Work Item, a blocked flag could indicate blockers that could affect the schedule.
Note: The key factors are dynamically configured depending on the deployed Cycle Time Prediction ML model. The factors are based on the list of predictor variables that are provided out-of-the-box and can be configured to suit your business needs.
You can click the icon in this panel to launch the Predict Cycle Time Key Factors Analysis dashboard and analyze detailed information about the various Key Factors that have contributed to longer cycle times in completed Work Items.
Displays a timeline chart to indicate the progress of the primary Work Item's children as of the current date. The graph provides information about the number of completed child Work Items as compared to the created Work Items and indicates if completion rate is on track to meet the schedule. You can understand the amount of scope left to complete as of the current date and work with the team to mitigate any issues.
The earliest date in the graph corresponds to the date when the Primary Work Item first moved to an In Progress status and the latest date in the graph corresponds to the date when data was last extracted.
The portion of the graph covered in brown color represents the child, grandchild Work Items of the Primary Work Item and you can hover over each node to view the number of child Work Items created and the date when they were created. The line graph in red represents the completed child Work Items for a particular date.
Displays a visual representation of all the child Work Items associated with the Primary Work Item. The topmost node represents the Primary Work Item, and you can view its recursive hierarchy (child, grandchild, and so on). The child nodes also indicate the Work Item type of each child, and you can click a particular Work Item to view more details about it in the subsequent section.
Displays detailed information about Work Items driven through selections made in the Details for Primary Work Item, Road to Completion, or Work Item Hierarchy section. You can view details such as its parent Work Item, child Work Items, and the status of each child Work Item.
| Metric Name | Description |
|---|---|
| No of Projects at Risk (PlannedEndDate) | Count of projects with one or more primary Work Items predicted to end past their Planned end date. |
| No of Primary Work Items at Risk (PlannedEndDate) | Total number of primary Work Items that are predicted to end past their Planned end date. |
| No of Program Increments at Risk (PlannedEndDate) | Total number of Program Increments with one or more primary Work Items predicted to end past their Planned end date. |
| No. of Primary Work Items at Risk - Opp Rank (PlannedEndDate) |
Opportunity Rank indicating primary Work Items that are at risk of going past the Planned end date and is calculated by ranking these primary Work Items in descending order. For example, rank 1 indicates Work Item that is about to go past its Planned end date and requires immediate attention. |
| No of Projects at Risk | Count of projects with one or more primary Work Items predicted to end past their current iteration end date. |
| No of Primary Work Items at Risk | Total number of primary Work Items that are predicted to end after the iteration end date. |
| No of Program Increments at Risk | Total number of Program Increments with one or more primary Work Items predicted to end past their current iteration end date. |
| No of Primary Work Items at Risk - Opportunity Rank | Opportunity Rank indicating primary Work Items that are at risk of going past the iteration end date and is calculated by ranking these primary Work Items in descending order. For example, rank 1 indicates Work Item that is about to go past its iteration end date and requires immediate attention. |
| No of Projects at Risk (PIEndDate) | Count of projects with one or more primary Work Items predicted to end past their Program Increment end date. |
| No of Primary Work Items at Risk (PIEndDate) | Total number of primary Work Items that are predicted to end past their Program Increment end date. |
| No of Program Increments at Risk (PIEndDate) | Total number of Program Increments with one or more primary Work Items predicted to end past their Program Increment end date. |
| No. of Primary Work Items at Risk - Opp Rank (PIEndDate) | Opportunity Rank indicating primary Work Items that are at risk of going past the Program Increment end date and is calculated by ranking these primary Work Items in descending order. For example, rank 1 indicates Work Item that is about to go past its Program Increment end date and requires immediate attention. |
| No of Primary Work Items |
Total number of primary Work Items. Primary Work Item is an issue that represents work to be completed. Work Items can be of various types, such as task, enhancement, bug, feature, epic, and so on. By default, the primary Work Item is configured to represent Feature and can be modified to suit your business requirement. |
| Planned End Date Predicted Days Past Due | Total number of days past planned due date calculated as the difference between Work Item predicted end date and planned end date. |
| Iteration Predicted Days Past Due | Total number of days past Iteration due date calculated as the difference between Work Item predicted end date and Iteration end date. |
| PI End Date Predicted Days Past Due | Total number of days past Program Increment due date calculated as the difference between Work Item predicted end date and Program Increment end date. |
| Blocked Work Items | Total number of Work Items that are blocked because of the current Work Item. This is a level metric calculated only at the Work Item level and is based on the current date. |
| Predicted Remaining Days | Total number of days to complete the Work Item as predicted by the Cycle Time Prediction ML model and calculated as of the snapshot date. |
| Cycle Time To Date (Days) | Total duration between the first In Progress date of the Work Item and the last extraction date. For Completed records, it is the difference between first In Progress date and latest Completed Date of Work Item. |
| Idle Time To Date (Days) | Total number of days within a Cycle Time window when the Work Item was not in an 'In Progress' status. |
| Child Work Items/Created Work Items | Total number of child Work Items associated with the primary Work Item. |
| Blocked Work Items | Total number of Work Items that are Blocked because of the current Work Item. This is a level metric calculated only at the Work Item level. |
| Completed Work Items | Total number of completed child Work Items associated with the primary Work Item. |
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