Measure
Measure overview
Use delivery, quality, and AI adoption signals without turning metrics into quotas.
- Audience
- engineering leaders, managers
- Required role
- Members can see their permitted views; managers and administrators can access organization-wide views when their capability allows it.
- Product access
- Measure
- Navigation path
- Measure > Overview
Outcome
Navigate Measure from an organization trend to the source evidence that explains it.
Before you begin
- At least one synchronized repository
- Completed metric processing for the selected period
Start with the overview
Choose a date range and confirm the active repository or team filters. Read delivery movement beside quality and AI attribution context. A single number without its period and scope is not a useful comparison.
Follow a change to evidence
Select a chart point, repository, or pull request to move from aggregate results to the underlying work. Confirm whether a change comes from volume, change size, quality, rework, deployments, or incomplete data.
Compare trends
Use consistent windows and comparable teams. Annotate changes in team shape, repository ownership, release process, or scoring configuration before drawing conclusions.
Use metrics responsibly
Use Measure to find system constraints and questions for investigation. Do not rank individual developers by output. Collaboration, mentoring, incident response, and design work are not fully represented by repository activity.
Related guides
Developer Velocity
Read durable throughput trends alongside quality and rework context.
AI Share
Compare AI-assisted contribution with quality, delivery, and attribution confidence.
People, teams, and Scorecard
Map contributors to teams and compare delivery systems with appropriate context.
Scoring methodology
See how velocity, effort, and quality scores are calculated and audited.