Dataset: Issues & Pull Requests
Entity: Pull Requests, Issues
Field ID: time_estimate
Type: Integer
Description: The estimated effort (in seconds) to implement the issue or pull request, as entered in the source application.
Source: App
Transformation logic: N/A
From: |
|
Github (PRs, Issues) | N/A |
Gitlab (PRs, Issues) |
|
Bitbucket (PRs) | N/A |
Azure DevOps (PRs, Issues) | N/A |
JIRA (Issues) |
|
ClickUp (Issues) |
|
Trello (Issues) | N/A |
Reporting Use Cases
The Time Estimate field is a crucial element for agile planning, allowing teams to forecast workloads, manage sprint capacity, and improve their estimation accuracy over time. As a numeric value representing seconds, it is highly flexible for use in aggregations and calculations.
Filtering and Backlog Grooming: You can create actionable lists to ensure your backlog is ready for planning.
Find Unestimated Work: The most common use is to find issues that need to be estimated before a sprint planning session. A filter where
Time Estimate is null or Time Estimate = 0will create a "To Be Estimated" list.Identify Large Items: You can find work items that might be too large and need to be broken down into smaller tasks by using a filter like
Time Estimate > 8 * HOUR()to find anything estimated to take more than a standard workday.
Capacity and Workload Planning: You can aggregate this field to understand the total planned effort for a given period.
Sprint Workload: A KPI with the custom formula
SUM(time_estimate) / HOUR()can show you the total number of hours planned for the current sprint (when filtered by sprint). This is essential for ensuring the team has not been overcommitted.
Analyzing Estimation Accuracy: By comparing estimates to the actual time spent, you can measure and improve your team's forecasting ability.
Estimate vs. Actual Ratio: You can calculate your team's overall estimation accuracy with a formula like
SUM(time_spent) / SUM(IF_ZERO(time_estimate, 1)). A value greater than 1 indicates a tendency to underestimate, while a value less than 1 suggests overestimation.Deviation per Item: In a list report, you can add a custom dimension to see the variance for each individual item with the formula
(time_spent - time_estimate) / HOUR(), helping you identify which tasks were the most mis-estimated.