Lead Time for Changes Measure

A Lead Time for Changes Measure is a software product operations measure based on how long it takes a code commit to result in releasable code (or deployed code).

• Context:
  • It can (typically) be a Software Delivery Performance Measure.
  • It can be used to identify Software Development Process improvement areas.
  • …
• Example(s):
  • Mean lead time.
  • Median lead time.
  • Percentile lead time, e.g. the 95th percentile lead time would be the lead time that is exceeded by only 5% of changes.
  • Worst lead time.
  • Best lead time.
  • ...
• Counter-Example(s):
  • Deployment Frequency.
  • Time to Recover.
  • Change Failure Rate.
  • …
• See: DORA Metric.

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References

2023

• chat
  • Q: What is a Lead Time for Changes Measure, and give some examples.
  • A: Lead time for changes is a measure of the time it takes for code changes to be implemented and deployed in a software system, starting from the moment the change is requested or initiated, until the moment the change is live and in production. This measure can provide insight into how quickly changes are being delivered and can be used to identify bottlenecks in the development process and to track improvements over time.

    Examples of lead time for changes measures:

    • Mean lead time: The average time it takes for code changes to be implemented and deployed.
    • Median lead time: The middle value when all lead times are arranged in order of size.
    • Percentile lead time: the time it takes for a certain percentage of changes to be deployed. For example, the 95th percentile lead time would be the lead time that is exceeded by only 5% of changes.
    • Worst lead time: The longest time it takes for code changes to be implemented and deployed.
    • Best lead time: The shortest time it takes for code changes to be implemented and deployed.
  • These measures can be used to identify trends and patterns in the lead times of code changes, and can be used to identify areas of the development process that need improvement. They can also be compared with industry standards to see how your process compares with others.

    It's important to notice that lead time can be affected by many factors, not only within development, like testing, infrastructure availability, approvals and regulatory compliance but also external factors.

2022

• https://blog.codacy.com/how-to-measure-lead-time-for-changes/
  • QUOTE: ... There are four key Accelerate metrics that we will cover in detail:
    • Lead time for changes;
    • Deployment frequency;
    • Time to recover; and
    • Change failure rate.
  • … In a nutshell, Lead time for changes measures the time that a commit takes to reach production. This metric is correlated with both the speed and the quality of your engineering team. ...

2022

• https://www.blueoptima.com/blog/how-to-measure-devops-success-why-dora-metrics-are-important
  • QUOTE: ... 2) Mean Lead Time for Changes.
    • The lead time for changes is essentially how long it takes a team to go from code committed to code successfully running in production. Elite teams can complete this process in less than one day, while for low performers this process can take anywhere between one and six months.
    • Since change lead time also takes into account cycle times, this metric helps you understand if your cycle time is efficient enough to handle a high volume of requests and prevent your team from becoming snowed under by requests or delivering poor user experiences.
    • Companies often experience longer lead times due to cultural processes like separate test teams, projects running with different test phases, shared test environments, complicated routes to live, etc that have the potential to slow a team down.
    • The definition of lead time for change can also vary widely, which often creates confusion within the industry.

2022

• https://github.com/GoogleCloudPlatform/fourkeys
  • QUOTE: Lead Time for Changes: The median amount of time for a commit to be deployed into production.

2018

• (Humble et al., 2018) ⇒ Jez Humble, Gene Kim, and Nicole Forsgren. (2018). “Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations." IT Revolution Press. , 2018.
  • QUOTE: ... In our search for measures of delivery performance that meet these criteria, we settled on four: delivery lead time, deployment frequency, time to restore service, and change fail rate. ...

2017

• (Forsgren et al., 2017) ⇒ Nicole Forsgren, Monica Chiarini Tremblay, Debra VanderMeer, and Jez Humble. (2017). “DORA Platform: DevOps Assessment and Benchmarking.” In: International Conference on Design Science Research in Information System and Technology, Springer. doi:10.1007/978-3-319-59144-5_27
  • QUOTE: ... IT performance is comprised of four measurements: lead time for changes, deploy frequency, mean time to restore (MTTR), and change fail rate. Lead time is how long it takes an organization to go from code commit to code successfully running in production or in a releasable state.

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