Lead Time for Changes
Lead Time for Changes measures how long it takes for committed code to be successfully deployed to production. It reflects how efficiently a team delivers completed work and how responsive the delivery process is to product and business needs.
Calculation
A change is typically defined as a code commit or merged pull request that contributes to a deployable version of the software. Lead time measures the time from that change being made to when it is deployed to production.
Teams may choose to start the timer at the first commit, the PR creation, or the PR merge. What matters most is consistency in what is tracked.
This metric is calculated by measuring the time between when the code is committed and when it is successfully released:
lead time for changes = deployment timestamp – commit timestamp
Goals
Lead Time for Changes helps teams evaluate the speed of their development pipeline. It answers questions like:
- How quickly can we turn a developer’s work into a live feature?
- Where are delays occurring between coding, review, testing, and release?
- Are we moving fast enough to adapt to customer or stakeholder feedback?
Improving this metric leads to faster feedback loops and more adaptable development. For research-driven guidance, see DORA’s documentation on Lead Time for Changes.
Variations
Lead Time for Changes can be broken down in several useful ways:
- By service or repo, to compare delivery speed across technical domains
- By change type, such as features, fixes, or refactors
- By delivery stage, to isolate time spent in review, test, staging, and deployment
Some teams report median or 95th percentile lead time to reduce skew from outliers. Others segment lead time by team, ticket type, or deploy cadence.
A common variation is Cycle Time, which typically starts later than Lead Time, often from PR creation or ticket start, and ends earlier, such as when the PR is merged. While both measure flow efficiency, Lead Time includes more of the delivery process and better reflects time to customer impact. Cycle Time can be useful for internal workflow analysis, while Lead Time offers a more complete picture of time to value.
Limitations
Lead Time for Changes shows how fast code moves into production, but not whether that code is correct, valuable, or successful. A short lead time is not helpful if it produces poor quality or misses customer needs.
It also does not explain which part of the pipeline is causing delays. Bottlenecks could occur in review, testing, deployment, or cross-team dependencies.
To better understand where and why lead time varies, use it alongside:
| Complementary Metric | Why It’s Relevant |
|---|---|
| Cycle Time | Provides a narrower view of engineering workflow and where work gets stuck pre-merge. |
| Deployment Frequency | Reveals whether delays are due to infrequent releases rather than development speed. |
| Review Latency | Isolates how much time is lost waiting for code review, a common lead time bottleneck. |
Optimization
Improving Lead Time for Changes means accelerating the path from commit to production while preserving quality and safety.
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Break work into smaller changes. Small changes are easier to review, test, and ship. Teams that use Trunk-Based Development reduce the time spent merging large branches and improve flow.
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Speed up code reviews. Slow feedback loops are a major cause of long lead times. Apply clear Code Review Best Practices, limit PR size, and establish review SLAs to avoid unnecessary wait time.
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Automate and parallelize testing. Slow or flaky test pipelines often delay releases. Invest in [CI/CD] with reliable, fast-running test suites that catch defects without blocking progress.
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Reduce release coordination overhead. If lead time spikes due to infrequent or manual releases, shift toward on-demand deploys using Feature Flags and standard deployment tooling.
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Monitor each stage of the pipeline. Instrument your workflow to capture time spent in review, testing, and deployment separately. This provides actionable visibility into where changes are getting stuck.
Improving Lead Time for Changes enables teams to respond quickly to feedback, reduce risk through faster iteration, and continuously deliver customer value.
