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Issues and PRs > Resolved Issue first created at

Tom Williams avatar
Written by Tom Williams
Updated this week

Dataset: Issues & Pull Requests

Entity: Pull Requests

Field ID: resolved_issue_first_created_at

Type: Datetime

Description: The earliest creation date among all resolved issues (via auto-closing keywords).

It can be used to calculate specific stages of the cycle time. E.g. the time elapsed between the creation date of an issue and the actual end of the development.

Source: Calculated

Transformation logic:

  • Pull Requests: The earliest occurrence of all created_at fields from resolved issues. Resolved issues are issues that are referenced by a resolving pull request.

  • Issues: Not applicable. This field will always be null.

From:

Github (PRs, Issues)

Calculated

Gitlab (PRs, Issues)

Calculated

Bitbucket (PRs)

Calculated

Azure DevOps (PRs, Issues)

Calculated

JIRA (Issues)

N/A

ClickUp (Issues)

N/A

Trello (Issues)

N/A

Reporting Use Cases

The Resolved Issue First Created At field is a fundamental timestamp that marks the very beginning of a work item's lifecycle, starting from the moment the original idea or problem was first documented in an issue. This makes it the ultimate starting point for measuring the complete, end-to-end lead time for your projects.

  • Calculating "Idea-to-Production" Lead Time: This field's primary use is to calculate the total time elapsed from the moment an issue was first created until the code that resolves it is merged.

    • You can measure this holistic lead time with the custom formula (merged_at - resolved_issue_first_created_at) / DAY(). This metric provides a business-centric view of your delivery pipeline, showing how long it takes to turn an idea into a shipped feature.

  • Measuring Backlog and Triage Efficiency: By comparing this timestamp with when work was first assigned, you can measure how long issues sit in the backlog before being actioned.

    • The formula (resolved_issue_first_assigned_at - resolved_issue_first_created_at) / DAY() calculates the "Time in Backlog". A high average value can indicate a bottleneck in your planning or triage process.

  • Filtering for Historical Context: You can use this field to find pull requests that have resolved very old or long-running issues, which is useful for tracking technical debt cleanup.

    • To identify recently completed work that cleared out old feature requests, you could create a report filtered where Merged At in the previous 30 days and Resolved Issue First Created At before 1 year ago.

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