Lead & Cycle Time
Monitor how long issues take from start to finish and identify workflow delays.
The Lead & Cycle Time report helps you understand how long issues take to complete and identify bottlenecks in your development process. Whether your team uses estimation or not, this report provides valuable insights for predicting completion times and improving workflow efficiency.
Accessing the report
Navigate to Reports in the left sidebar and select Lead & Cycle Time. Use the date range selector to choose your analysis period. Available filters include start pipeline, completed pipeline, repository, a toggle for pull requests, labels, and a days/weeks scale selector.
TIP: The report works without story point estimates, making it valuable for all types of development workflows including Kanban teams.
Reading the visualization
Each dot on the chart represents a closed issue or pull request. The horizontal position shows when the issue was completed; the vertical position shows how many days it took. The blue average line shows the average completion time across the entire selected period. The green rolling average line displays a rolling average of recent completion times, helping you identify trends. The grey shaded area represents the normal range of variation — work within this area is predictable, while items outside indicate unusual completion times worth investigating.
Hover over any point to see the title and exact completion time. Scroll below the chart for a detailed table including start date, completion date, total time, and estimates.
NOTE: If issues move in and out of the selected pipeline range multiple times, the report calculates the total time spent within the selected pipelines.
Lead time versus cycle time
Lead time measures total time from issue creation to completion, including waiting periods. Set the start pipeline to your first pipeline (like New Issues) to measure this. It represents the complete stakeholder experience from request to delivery.
Cycle time measures only active work time, excluding waiting. Set the start pipeline to when active work begins (like In Progress) to measure this. Teams typically have more direct control over cycle time through process improvements.
Large differences between lead time and cycle time indicate work spends significant time waiting before active development begins, suggesting capacity or prioritization challenges.
Interpreting completion time patterns
When most points cluster near the average line within the grey shaded area, your completion times are predictable. Wide scatter, especially outside the grey area, suggests unpredictable completion times that make planning difficult.
When the green rolling average line trends upward, recent issues are taking longer than your historical average — this often indicates developing process issues. Downward trends show improving completion times. Gaps in chart points indicate periods when no issues were completed, possibly due to overcommitment or external dependencies.
Using the report for improvement
Use specific pipeline ranges to identify workflow stages with consistently long completion times. Work to reduce variability by addressing root causes of outlier completion times. Compare patterns before and after process changes to measure the effectiveness of workflow improvements. Use average completion times combined with throughput data to make realistic delivery timeline commitments to stakeholders.
FAQ
Q: What's the difference between lead time and cycle time?
A: Lead time measures total time from issue creation to completion including waiting time. Cycle time measures only active work time from when work begins to completion. Lead time shows stakeholder experience; cycle time shows internal process efficiency.
Q: Why are some completion times much longer than others?
A: High variability usually indicates differences in issue complexity, unexpected blockers, or inconsistent workflows. Issues outside the grey shaded area deserve investigation to understand what made them unusual.
Q: How do I know if my completion times are good?
A: Focus on predictability and trends rather than absolute numbers. Stable averages with minimal outliers indicate healthy processes, regardless of whether completion takes 3 days or 30 days.
Q: Can I use this report if my team doesn't estimate issues?
A: Yes. Lead & Cycle Time reports work entirely based on issue movement through pipelines and don't require story point estimates.
Q: What should I do about outlier issues that took much longer than normal?
A: Investigate outliers during retrospectives to understand what caused the delay. Common causes include unclear requirements, unexpected complexity, external dependencies, or workflow bottlenecks.