Cycle Time: How do you measure the lead time of work?

How long does it take for a task to go from start to delivery? Cycle Time answers this question. This is a crucial metric for Agile teams, as it provides insight into the efficiency of your workflow. But what does a short or long cycle time mean? How do you use this metric to improve your process? Let's delve deeper.

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What is Cycle Time?

Cycle Time is the time between when work actually starts and when it is completed.

Example:

• A developer starts a task on Monday.
• On Thursday, the task is completed and moved to ‘Done’.
• The cycle time is then 4 days.

Cycle Time is often confused with Lead Time, but there is an important difference:

• Cycle Time measures the time from the start of the work.
• Lead Time measures the time from when a task enters the backlog.

Cycle Time therefore provides insight into how efficiently work flows through the process.

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Why is Cycle Time important?

A short cycle time means work is processed and completed smoothly. A long cycle time can indicate obstacles such as:

• Overly large tasks that are difficult to complete.
• Too much Work In Progress (WIP) causing team members to spread their work across too many tasks.
• Dependencies on other teams or systems that cause delays.

Regularly measuring cycle time provides insight into where work gets stuck and how you can optimize your process.

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How do you measure cycle time?

Cycle time can be tracked manually, but it is often measured automatically in tools like Jira, Azure DevOps, or Trello.

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Visual analysis with a Cumulative Flow Diagram (CFD)

A Cumulative Flow Diagram (CFD) shows how much work is in each stage of the process. If the 'In Progress' column in a CFD continuously widens, it means that work is getting stuck for longer – and that cycle time is increasing.

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Calculating average cycle time

By looking at the cycle times of completed tasks over a certain period, you can calculate an average. For example:

• User Story 1: Start date April 1 → End date April 4 → Cycle time: 3 days
• User Story 2: Start date April 2 → End date April 6 → Cycle time: 4 days
• User Story 3: Start date April 3 → End date April 7 → Cycle time: 4 days

👉 Average cycle time: 3.67 days

With this information, you can better predict how long future tasks will take.

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How do you shorten cycle time?

Not all tasks can (or should) be completed super fast, but if cycle times are consistently too long, it can lead to problems.

1. Limit Work In Progress (WIP)
   • The more tasks are in progress simultaneously, the longer everything takes. Multitasking slows down work because team members constantly have to switch between tasks. Limit WIP to maintain focus.
2. Break down large tasks
   • If a task takes multiple Sprints, it's likely too large. Use Story Slicingto break down work into smaller, manageable pieces.
3. Automate repetitive work
   • Are there manual steps in your workflow that take a lot of time? Consider testing, code reviews, or approval processes. By implementing automation (e.g., automated testing), cycle time can be reduced.
4. Eliminate waiting times
   • A lot of time is wasted waiting for feedback or approval. Make these dependencies visible and look for ways to speed up this process.

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Common mistakes in cycle time analysis

1. Only measuring the average
   • The average doesn't tell the whole story. Also look at outliers: why do some tasks take much longer?
2. Using cycle time as a hard deadline
   • Cycle time is a tool, not an end in itself. It's about trends and improvements, not 'working faster' at the expense of quality.
3. Starting too many tasks at once
   • This unnecessarily extends cycle time. Use WIP limits to prevent too much work in progress.

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