Timing metrics explained: Lead time vs Cycle time
Timing metrics explained: Lead time vs Cycle time
Two essential time-based metrics that often get confused are lead time and cycle time. They are common KPIs domains such as manufacturing and agile software development. Though they may sound similar, they represent very different aspects of a process. This guide explains the difference between these two measures.
Two essential time-based metrics that often get confused are lead time and cycle time. They are common KPIs domains such as manufacturing and agile software development. Though they may sound similar, they represent very different aspects of a process. This guide explains the difference between these two measures.
Two essential time-based metrics that often get confused are lead time and cycle time. They are common KPIs domains such as manufacturing and agile software development. Though they may sound similar, they represent very different aspects of a process. This guide explains the difference between these two measures.
What is the difference between the lead and the cycle time?
Lead time refers to the total time it takes from the moment a customer places an order (or a work request is initiated) to the moment the finished product or service is delivered. It includes all steps in the process—waiting, processing, transportation, and any other delays.
Lead Time: The total time it takes from when a customer places an order (or a request is made) until the product is delivered.
Cycle time, on the other hand, measures the amount of time it takes to complete one unit of work once the actual work has started. It does not include the time spent waiting before the work begins.
Cycle Time: The time it takes to complete one unit of production from start to finish once the process has begun.
There’s no one-size-fits-all workflow as processes vary by team. What matters is defining cycle time so it matches how your team operates:
Engineering teams might track from “In Progress” to “Deployed.”
Marketing teams could measure from “Ready to work” to “Published.”
Customer support might track from “Request received” to “Resolved.”
Manufacturing may use steps like “Parts ordered” to “Shipped.”
There is also a third measure called Reaction time, which is the time before work is started. It is often used for tracking how quickly customer support messages are responded to, or whether SLAs are met.
Here's the illustration of the relationship between lead and cycle times:
What is the difference between the lead and the cycle time?
Lead time refers to the total time it takes from the moment a customer places an order (or a work request is initiated) to the moment the finished product or service is delivered. It includes all steps in the process—waiting, processing, transportation, and any other delays.
Lead Time: The total time it takes from when a customer places an order (or a request is made) until the product is delivered.
Cycle time, on the other hand, measures the amount of time it takes to complete one unit of work once the actual work has started. It does not include the time spent waiting before the work begins.
Cycle Time: The time it takes to complete one unit of production from start to finish once the process has begun.
There’s no one-size-fits-all workflow as processes vary by team. What matters is defining cycle time so it matches how your team operates:
Engineering teams might track from “In Progress” to “Deployed.”
Marketing teams could measure from “Ready to work” to “Published.”
Customer support might track from “Request received” to “Resolved.”
Manufacturing may use steps like “Parts ordered” to “Shipped.”
There is also a third measure called Reaction time, which is the time before work is started. It is often used for tracking how quickly customer support messages are responded to, or whether SLAs are met.
Here's the illustration of the relationship between lead and cycle times:
Lead and cycle time visualisations
Cycle time is usually reported as an average over a certain time period. A good visualisation is a rolling average, which allows you to see the trend of your average lead or cycle time.
In the above chart, each data point represents the average cycle time for the previous 30-day period. The descending trend tells that the average cycle time has decreased during this time period.
Another effective way to visualize cycle times is by using a scatter plot, which presents data points in a two-dimensional canvas according to any two variables in a dataset - in this case, the cycle time and the completion date.
In a scatter plot, each data point corresponds to an individual task, which allows you to spot outliers easily. In the chart above, the task completed on Wednesday has a much longer cycle time than the rest, and would therefore be a good candidate for a closer examination.
Lead and cycle time visualisations
Cycle time is usually reported as an average over a certain time period. A good visualisation is a rolling average, which allows you to see the trend of your average lead or cycle time.
In the above chart, each data point represents the average cycle time for the previous 30-day period. The descending trend tells that the average cycle time has decreased during this time period.
Another effective way to visualize cycle times is by using a scatter plot, which presents data points in a two-dimensional canvas according to any two variables in a dataset - in this case, the cycle time and the completion date.
In a scatter plot, each data point corresponds to an individual task, which allows you to spot outliers easily. In the chart above, the task completed on Wednesday has a much longer cycle time than the rest, and would therefore be a good candidate for a closer examination.
Why should you care about lead and cycle times?
What can you do with this data? Let's consider a situation where your team is being asked by business owners how long it takes to complete a certain task. Instead of just making a guess, the team can look at the data to see how long it has taken in the past to complete similar tasks and provide a data-driven estimate.
Knowing your cycle time is one thing, but many teams are also actively trying to drive down their lead and cycle times as part of their continuous improvement efforts. When doing so, understanding the difference between lead time and cycle time is crucial:
Reducing lead time improves customer satisfaction.
Shortening cycle time improves production efficiency.
Measuring both helps identify where delays occur—whether in waiting, working, or delivering. In a well-optimized system, both lead time and cycle time are minimized.
Why should you care about lead and cycle times?
What can you do with this data? Let's consider a situation where your team is being asked by business owners how long it takes to complete a certain task. Instead of just making a guess, the team can look at the data to see how long it has taken in the past to complete similar tasks and provide a data-driven estimate.
Knowing your cycle time is one thing, but many teams are also actively trying to drive down their lead and cycle times as part of their continuous improvement efforts. When doing so, understanding the difference between lead time and cycle time is crucial:
Reducing lead time improves customer satisfaction.
Shortening cycle time improves production efficiency.
Measuring both helps identify where delays occur—whether in waiting, working, or delivering. In a well-optimized system, both lead time and cycle time are minimized.
How to track lead and cycle times?
Tracking lead and cycle time is easy - you just need to record when the task was created, when work was started, and when it was completed.
Most electronic tools record this information automatically and provide it either through reports or via an API. As tasks move through the workflow, time spent on each step is stored, allowing information like cycle time to be calculated without the need for manual entry.
See also:
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Screenful is the most advanced analytics add-on for monday.com, Jira, Linear, Asana, Trello, GitHub, and GitLab. Read 100+ reviews.
How to track lead and cycle times?
Tracking lead and cycle time is easy - you just need to record when the task was created, when work was started, and when it was completed.
Most electronic tools record this information automatically and provide it either through reports or via an API. As tasks move through the workflow, time spent on each step is stored, allowing information like cycle time to be calculated without the need for manual entry.
See also:
—-
Screenful is the most advanced analytics add-on for monday.com, Jira, Linear, Asana, Trello, GitHub, and GitLab. Read 100+ reviews.