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Issues and PRs > Time spent

Tom Williams avatar
Written by Tom Williams
Updated this week

Dataset: Issues & Pull Requests

Entity: Pull Requests, Issues

Field ID: time_spent

Type: Integer

Description: The time spent (in seconds) on 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)

time_stats.total_time_spent

Bitbucket (PRs)

N/A

Azure DevOps (PRs, Issues)

N/A

JIRA (Issues)

timespent

ClickUp (Issues)

time_spent (requires the Time Tracking ClickApp)

Trello (Issues)

N/A

Reporting Use Cases

The Time Spent field is the counterpart to time_estimate, providing a record of the actual effort expended on a work item. It is a critical metric for conducting sprint retrospectives, improving future estimations, and understanding where your team's time is truly going.

  • Filtering for Process Compliance and Auditing: You can create reports to ensure that time is being logged consistently and to identify outliers.

    • Find Items Without Logged Time: To ensure your team is tracking their work, you can create a report of all completed items where Time Spent = 0.

    • Identify High-Effort Items: You can analyze which tasks consumed the most effort by creating a report and sorting by the time_spent value, or by filtering for items that took longer than a certain threshold, like Time Spent > 40 * HOUR().

  • Measuring and Analyzing Effort: You can aggregate this field to understand the total work delivered by your team.

    • Total Effort per Sprint: A KPI with the custom formula SUM(time_spent) / HOUR() will show the total number of hours your team logged in a given sprint or time period.

    • Effort per Work Type: By creating a bar chart with a dimension like Sub-Type and a metric of SUM(time_spent), you can see a breakdown of how many hours are being dedicated to "Bugs" versus "Stories."

  • Improving Estimation Accuracy: The most powerful use of this field is to compare it against the original estimate to 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 your team identify which types of tasks were the most mis-estimated during retrospectives.

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