Glossary
Cycle time is the total elapsed time it takes to complete a single unit of work, from the moment active work begins until the work is ready for delivery.
Cycle time is the total elapsed time it takes to complete a single unit of work, from the moment active work begins until the work is ready for delivery.
In software development, cycle time specifically measures how long it takes to move a change from "actively being worked on" to "deployed to production." It's a measure of development velocity and process efficiency.
The key distinction: cycle time only counts active work time. It doesn't include time spent waiting in a queue, reviewing, or blocked on dependencies. That waiting time is part of lead time - a different metric entirely.
The most common way to calculate cycle time:
Cycle Time = End Date - Start Date
More specifically in software development:
Cycle Time = (Time PR Merged) - (Time Work Started)
Or in an Agile context:
Cycle Time = (Time Task Moved to Done) - (Time Task Started)
Some teams prefer:
Cycle Time = Total Time to Complete / Number of Units Completed
This gives you an average cycle time, which is more useful for tracking trends over time.
For example: If your team completed 40 tasks in a month (160 hours of work days), your average cycle time would be 4 hours per task. If a single feature takes three days from start to deployment, the cycle time for that feature is three days.
People ask this question constantly because the terms sound similar but measure very different things.
Cycle Time:
Lead Time:
Think of it this way: a task gets requested on Monday. It sits in the backlog for a week. On the second Monday, an engineer starts working. They finish on Wednesday. The feature ships on Thursday.
This is why cycle time is often much shorter than lead time. A task might have a cycle time of two days but a lead time of two weeks because it was waiting in the backlog for ten days.
For engineering leaders, this distinction matters enormously. A long lead time might indicate that your process is slow - but it might also just mean your backlog is large. A long cycle time indicates that the work itself is taking a long time, which usually means either the task is genuinely complex or your team is blocked by dependencies.
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