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Change Failure Rate metrics and KPIs

What are Change Failure Rate metrics?

Developing an effective Change Failure Rate metrics can be intimidating, especially when your daily duties demand your attention. To assist you, we've curated a list of examples to inspire your planning process.

You can copy these examples into your preferred app, or alternatively, use Tability to stay accountable.

Find Change Failure Rate metrics with AI

While we have some examples available, it's likely that you'll have specific scenarios that aren't covered here. You can use our free AI metrics generator below to generate your own strategies.

Examples of Change Failure Rate metrics and KPIs

Metrics for Software Releases

  • 1. Release Frequency

    Measures the number of releases over a specific period. Indicates how quickly updates are being deployed.

    What good looks like for this metric: 1-2 releases per month

    Ideas to improve this metric
    • Automate deployment processes
    • Implement continuous integration/continuous deployment practices
    • Invest in developer training
    • Regularly review and optimise code
    • Deploy smaller, incremental updates

  • 2. Lead Time for Changes

    The average time it takes from code commitment to production release. Reflects the efficiency of the development pipeline.

    What good looks like for this metric: Less than one week

    Ideas to improve this metric
    • Streamline workflow processes
    • Use automated testing tools
    • Enhance code review efficiency
    • Implement Kanban or Agile methodologies
    • Identify and eliminate bottlenecks

  • 3. Change Failure Rate

    Percentage of releases that cause a failure in production. Indicates the reliability of releases.

    What good looks like for this metric: Less than 15%

    Ideas to improve this metric
    • Increase testing coverage
    • Conduct thorough code reviews
    • Implement feature flags
    • Improve rollback procedures
    • Provide better training for developers

  • 4. Mean Time to Recovery (MTTR)

    Average time taken to recover from a failure. Reflects the team's ability to handle incidents.

    What good looks like for this metric: Less than one hour

    Ideas to improve this metric
    • Establish clear incident response protocols
    • Automate recovery processes
    • Enhance monitoring and alerts
    • Regularly conduct disaster recovery drills
    • Analyse incidents post-mortem to prevent recurrence

  • 5. Number of Bugs Found Post-Release

    The count of bugs discovered by users post-release. Indicates the quality of software before deployment.

    What good looks like for this metric: Fewer than 5 bugs per release

    Ideas to improve this metric
    • Enhance pre-release testing
    • Implement user acceptance testing
    • Increase use of beta testing
    • Utilise static code analysis tools
    • Improve requirement gathering and planning
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Implement these metrics

Tracking your Change Failure Rate metrics

Having a plan is one thing, sticking to it is another.

Having a good strategy is only half the effort. You'll increase significantly your chances of success if you commit to a weekly check-in process.

A tool like Tability can also help you by combining AI and goal-setting to keep you on track.

Tability Insights DashboardTability's check-ins will save you hours and increase transparency

More metrics recently published

We have more examples to help you below.

Planning resources

OKRs are a great way to translate strategies into measurable goals. Here are a list of resources to help you adopt the OKR framework:

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