BLOG

Change Lead Time vs. Cycle Time – Differences and importance in software development

Today, DORA metrics have become the de facto standard for measuring software development performance. The metrics provide a standard framework that helps teams measure their software delivery velocity and stability, compare their performance with peers and industry leaders, and take corrective actions. Mean lead time for changes (or change lead time) is one of these four key DORA metrics that help teams get a sense of their CI/CD efficiency.  

What is Mean Lead Time for Changes (Change Lead Time)?

The mean lead time for changes is the average time code changes take from the commit stage to reach production. The metric correlates directly with the speed and quality of development. A shorter lead time means that a team can implement feedback quickly to meet customer expectations. It also indicates that the team can resolve bugs and vulnerabilities faster. On the other hand, a higher lead time can indicate potential inefficiencies and bottlenecks in the process. Code complexity often affects lead times, making changes difficult while increasing the code maintenance costs and exposure to vulnerabilities.

The Importance of Measuring the Change Lead Time

On the surface, lead time appears to be straightforward; you only need to maintain a list of all deployments, keeping track of the timestamps on two occasions, viz., the time of a commit and the time of deployment. The metric is highly useful for change management as it gives you an idea about how much time you are going to need to implement changes. It is possible to measure the time across coding, code review, and deployment processes to get better visibility across different stages. Moreover, teams should be able to identify which tasks (stories, bugs, sub-tasks, etc.) are taking a long time and drill down to resolve bottlenecks.

Why is it Difficult to Track the Change Lead Time?

While it is simple to define the change lead time, challenges arise as soon as teams have to deal with different data sources. Teams need to track: 

  • Tickets – from project management tools like Jira  
  • Source code – from SCM tools like GitHub or GitLab  
  • Deployment data – from deployment tools like Jenkins, TeamCity, or CircleCI  

Though it is possible to manually collect, aggregate, and analyze data from all these sources, things can get out of hand when there are multiple ongoing projects and repositories. Gathr can help you solve this challenge with its out-of-the-box DORA metrics solution that automates data collection, saves time and effort in complex integrations, and simplifies analysis with interactive visual dashboards. 

Change Lead Time vs. Cycle Time vs. Lead Time

We have discussed the change lead time and its importance in software development. While the metric is a marker of pipeline efficiency, it doesn’t capture the entire value stream. To get visibility into how you deliver value to customers, you should consider measuring the lead time and cycle time metrics.  

Lead Time – The total time teams take to fulfill a customer request. Usually, it takes some time before a customer request is logged/documented and prioritized, and assigned to a team member. The lead time metric allows you to measure this duration, which can otherwise remain untracked. 

Cycle Time – The time teams take to complete work items (user stories, tasks, bugs). It is a useful metric to track and can help you ensure that the teams are making daily commits. 

While capturing the lead time (the point of customer request) can involve some approximations, engineering and business leaders get a much better picture of value streams by monitoring all three metrics. By integrating tools like Jira, GitHub, and Jenkins, it is possible to understand how much time teams spend on their planning, coding, and PR reviews. Moreover, teams sometimes have to wait for a standard release window, and in such cases, even these standard metrics may not capture the team’s efficiency and workloads. The teams can complete their work in a couple of days and remain idle for the entire week waiting for the business go-ahead and deployment. In such cases, the measurements will depend on the release management process used by your organization. If you are deploying a feature to the staging, pre-production, or test environments before rolling it out to production, you need to capture the time across all stages to get better visibility into the value stream.

Conclusion

It is evident that measuring the lead time, cycle time, and change lead time provides a better breakdown and understanding of your CI/CD workflows. The key to improving on all these metrics is ensuring that you get immediate, accurate information about the progress or flow of work with the ability to identify bottlenecks. Gathr can help you create visual dashboards with data from every stage in the pipeline to assess where teams spend most of their time. It can help you understand if the work involves new features or bugs. With these insights, you can make gradual and continuous improvements in your DevOps workflows to be an elite performer.

Recent Post

View More Post

Blog

50X faster time to value with Confluent and Gathr...

Blog

Data + AI Summit 2023: A must-attend for data scientists,...

Blog

Top 5 DevSecOps trends in 2022

Blog

SPACE Metrics – Why they matter & how to get started