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Improve Predictability dashboard

The Improve Predictability dashboard enables you to derive insights into your project or release commitments and understand if you are on track to meet the set expectations. The dashboard helps you identify areas of improvement with respect to delivering Work Items within due dates, ensuring teams are adhering to their estimated efforts, and prevent Work Items from spilling over to the upcoming sprints.

As a business stakeholder, you can find answers for some of the key business scenarios such as:

• Where are the biggest opportunities to reduce variances of actual effort vs estimated effort?
• Where are the biggest issues with work items spilling over from the sprint in which they were committed?
• In the last year, how have teams fared with respect to planned efforts? Has there been an improvement?
• Overall, what are the areas with predictability issues (effort variances, sprint spillover, past due delivery)?

This dashboard is built using the Work Item and Work Item Project Rollup iCube and fetches data based on the filter specified for these iCubes. Refer to the respective iCube topic for more details about the filter.

Note: This dashboard supports Jira, ADO and Digital.ai Agility.

The Improve Predictability dashboard consists of the following chapters:

• Past Due Delivery %
• Effort Variance %
• Iteration Spillover %

You can view data pertaining to the last 13 months (including current month) and can filter the dashboard to display data relevant to selected Engineering Managers (Level 1 through 3).

Past Due Delivery %

The Past Due Delivery chapter provides insights into Work Items that are past their planned end date. You can also view opportunities across projects that help you focus on improving estimation and manage schedule risks in these opportunity areas. You can also view the monthly trend of such Work Items that can help you understand if your estimation and Work Item execution is progressing as planned.

A Work Item in Completed state is said to be past due if the completed date is greater than the planned end date. For Work Items that are Active, past due is calculated if the last extraction date is greater than the planned end date.

The Past Due Delivery chapter displays the following sections:

• KPI: The KPI displayed on the Past Due Delivery tab indicates the percentage of Work Items that have gone beyond their planned end date, in the last 12 months.
• Recommendations: Displays recommendations to prioritize the top 3 projects that have the highest number of past due Work Items as determined by the Opportunity Rank.
• Past Due by: Displays a grid with information about projects or engineering managers associated with Active or Completed Work Items that have gone past their planned end date. You can view the overall past due delivery percentage of Work Items and the average number of days for which the Work Items have been past their due date.

  The grid also displays the Opportunity Rank that helps in prioritizing projects that have the most number of past due Work Items. The rank is calculated by summing up the ranks of individual metrics in this grid and then deriving the rank.

  You can click a particular project or manager in the grid to drill down and view only relevant data in all the subsequent sections.

• Trend by Month: Displays the monthly trend of Completed Work Items that are past their due date. You can hover over the nodes of the line graph to view the number of past due work items in each month. The report considers only those Work Items that are completed in the last 13 months (including current month).
• By Work Item Type: Displays the number of active or completed past due Work Items categorized by the Work Item type, such as Epic, Feature, and so on. You can click a specific Work Item type to view relevant Work Items in the Past Due Work Item Details section.
• Past Due Work Item Details: Displays detailed information about the past due Work Items, such as name of the person assigned to the Work Item, unique identifier for the Work Item, planned due date, and number of days for which the Work Item has been past its due date.

  You can click the Active and Completed tabs in this grid to choose to view only active or completed past due Work Items. You can also click on the source URL icon against a Work Item number to launch the corresponding source system and view more details.

  The data in this grid can be driven by the previous sections and will display data relevant to the selection.

Effort Variance %

The Effort Variance chapter provides insights into Work Items on which resources spent more time than what was estimated earlier. You can view opportunities across projects that help you focus on improving estimation and manage effort variance in these opportunity areas. You can also view the monthly trend of such Work Items, which can help you understand if there has been an improvement in reducing variance.

The Effort Variance chapter displays the following sections:

• KPI: The KPI displayed on the Effort Variance tab indicates the percentage of Work Items where actual time spent has been more than the estimated effort, in the last 12 months.
• Recommendations: Displays recommendations to prioritize the top 3 projects that have Work Items contributing to the highest amount of effort variance, as determined by the Opportunity Rank.

  Note: Only Completed Work Items whose effort variance is greater than or less than 10% and Active Work Items whose effort variance is greater than 10% are considered. The default threshold value of 10% is specified out-of-the-box and can be configured to suit your business requirements.

• Effort Variance by: Displays a grid with information about projects or engineering managers associated with Active or Completed Work Items that contribute to variance in effort estimates (effort variance = +/- 10%). You can view the percentage of effort variance for Completed Work Items calculated as the difference between actual time spent and current estimate as compared to the current estimate.

  The grid also displays the Opportunity Rank that helps in prioritizing the projects that have work items with large variances in efforts. The rank is calculated by summing up the ranks of individual metrics in this grid and then deriving the rank.

  You can click a particular project or manager in the grid to drill down and view only relevant data in all the subsequent sections.

• Trend by Month: Displays the monthly trend of Completed Work Items whose effort variances in greater than or less than 10%. You can hover over the nodes of the line graph to view the number of completed work items in each month. The report considers only those Work Items that are completed in the last 13 months (including current month).

  Note: The threshold value of +/- 10% is the default value and can be configured based on your business requirement.

• By Work Item Type: Displays the number of active (effort variance greater than 10%) or completed Work Items (effort variance greater than or less than 10%) categorized by the Work Item type, such as Epic, Feature, Bug, and so on. You can click a specific Work Item type to view relevant Work Items in the Work Item with Effort Variance section.
• Work Items with Effort Variance: Displays detailed information about active Work Items with effort variance greater than 10% and completed Work Items with effort variance greater than or less than 10%. You can view details such as name of the person assigned to the Work Item, unique identifier for the Work Item, current estimate, and percentage of effort variance.

  You can click the Active and Completed tabs in this grid to choose to view only active or completed past due Work Items. You can also click on the source URL icon against a Work Item number to launch the corresponding source system and view more details.

  The data in this grid can be driven by the previous sections and will display data relevant to the selection.

Iteration Spillover %

The Iteration Spillover chapter provides insights into Work Items that were not completed in the iteration or sprint they were committed in. The dashboard indicates opportunities across projects that you can focus on to improve predictability by managing spillover risks. You can also view the monthly trend of such to understand if there has been improvement and view more details about the work items that are causing delays.

The Iteration Spillover chapter displays the following sections:

• KPI: The KPI displayed on the Iteration Spillover tab indicates the percentage of Work Items that were committed in an iteration but were not resolved by the iteration end date.
• Recommendations: Displays recommendations to prioritize the top 3 projects that have the most number of committed Work Items that spilled over to later iterations, as determined by the Opportunity Rank.
• Iteration Spillover by: Displays a grid with information about projects or engineering managers associated with Work Items that were committed in an iteration but were not resolved by the iteration end date. You can view the percentage of Work Items that spilled over and understand the growth rate for Iteration spillover by comparing the spillover % of the 3 most recent iterations (iterations 1 through 3) with the 3 iterations prior to the last 3 (iterations 4 through 6).

  The grid also displays the Opportunity Rank that helps in prioritizing the projects that have a greater Work Item spillover. The rank is calculated by summing up the ranks of individual metrics in this grid and then deriving the rank.

  You can click a particular project or manager in the grid to drill down and view only relevant data in all the subsequent sections.

• Iteration Spillover Trend By Month: Displays the monthly trend (considers the month when the iteration ends) of Spillover Work Items as compared to the percentage of spillover in each iteration.

  The bars in the chart represent the total number of work items that spilled over and the line graph represents the percentage of spillover in each month.

• By Work Item Type: Displays the total number of spillover Work Items in the last 12 months categorized by the Work Item type, such as Epic, Feature, Bug, and so on. You can click a specific Work Item type to view relevant Work Items in the Iteration Spillover Work Item Details section.
• Iteration Spillover Work Item Details: Displays detailed information about committed Work Items in an iteration, such as Work Item number, iteration that the Work Item is committed to, status of the iteration as of the iteration end date, iteration to which the Work Item was most recently linked to, and current status of the Work Item.

  You can also click on the source URL icon against a Work Item number to launch the corresponding source system and view more details.

  The data in this grid can be driven by the previous sections and will display data relevant to the selection.

  Metrics used in this dashboard

  Metric Name	Description
  Past Due Delivery %	Past due Active and Completed Work Items as a percentage of all Work Items where status is not Canceled.
  Work Item Past Due Delivery Opportunity Rank	Consolidated rank where higher opportunity ranks (e.g. 1, 2, 3 etc) correspond to greater opportunities to reduce Work Item past due deliveries.
  Completed Work Items	Completed Work Items whose Completed Date is greater than the Planned End Date
  Active Work Items	Work Items where status is not in Completed or Canceled and whose Last Extracted Date is greater than the Planned End Date.
  Avg Past Due Duration (Days)	Average number of days for which Active and Completed Work Items are past their due date. For Completed Work Items , past due is calculated as the difference between Actual Completed Date and Planned End Date. For Active Work Items, past due is calculated as the difference between Last Extraction Date and Planned End Date.
  No of Past Due Delivery Work Items	Total number of Work Items that are past their due date and includes both Active (where Status is not in Completed or Canceled) and Completed Work Items
  Effort Variance % - Completed	Effort variance between Time Spent and Current Estimate compared to Current Estimate of Completed Work Items.
  Work Item Effort Variance % Opportunity Rank	Consolidated rank where higher Opportunity ranks (e.g. 1, 2, 3 etc) correspond to greater opportunities to improve predictability by reducing effort variances.
  Completed Work Items with Effort Variance Threshold	Total number of completed Work Items where Effort Variance percentage is greater than or less than the specified Threshold. The default threshold value is 10%.
  Active Work Items with Effort Variance Threshold	Total number of Work Items where status is not in Completed or Canceled and whose Effort Variance percentage is greater than the specified Threshold. The default Threshold value is 10%.
  No. of Work Items with Effort Variance Threshold	Total number of Completed and Active Work Items with Effort Variance Threshold. Completed Work Items whose effort variance % is greater than or less than Threshold or Active Work Items where status is not in Completed or Canceled and whose effort variance % is greater than the Threshold value. The default threshold value is 10%.
  Current Estimate (Hours)	Current Estimate (in hours) of Active and Completed Work Items
  Effort Variance %	Effort Variance calculated as the difference between Time Spent and Current Estimate of Active and Completed Work Items as compared to the Current Estimate of these Work Items.
  Iteration Spillover %	Percentage of Work Items that were committed to an iteration but were not resolved by iteration end date.
  Iteration Spillover Opportunity Rank	Consolidated Rank where higher Opportunity Ranks (e.g. 1, 2, 3 etc) correspond to greater opportunities to improve predictability by reducing sprint spillover.
  Spillover Work Items	Total number of Work Items that were committed into an iteration and were not Resolved as of the Iteration Actual End Date.
  Iteration Spillover Growth Rate	Percentage of growth rate calculated by comparing spillover Work Items of last 3 completed iterations to spillover Work Items of last to last 3 completed iterations.