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2 examples of Qa Team metrics and KPIs

What are Qa Team metrics?

Finding the right Qa Team metrics can be daunting, especially when you're busy working on your day-to-day tasks. This is why we've curated a list of examples for your inspiration.

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

Find Qa Team 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 Qa Team metrics and KPIs

Metrics for Tracking Quality of Code

  • 1. Code Coverage

    Measures the percentage of your code that is covered by automated tests

    What good looks like for this metric: 70%-90%

    Ideas to improve this metric
    • Increase unit tests
    • Use code coverage tools
    • Refactor complex code
    • Implement test-driven development
    • Conduct code reviews frequently
  • 2. Code Complexity

    Assesses the complexity of the code using metrics like Cyclomatic Complexity

    What good looks like for this metric: 1-10 (Lower is better)

    Ideas to improve this metric
    • Simplify conditional statements
    • Refactor to smaller functions
    • Reduce nested loops
    • Use design patterns appropriately
    • Perform regular code reviews
  • 3. Technical Debt

    Measures the cost of additional work caused by choosing easy solutions now instead of better approaches

    What good looks like for this metric: Less than 5%

    Ideas to improve this metric
    • Refactor code regularly
    • Avoid quick fixes
    • Ensure high-quality code reviews
    • Update and follow coding standards
    • Use static code analysis tools
  • 4. Defect Density

    Calculates the number of defects per 1000 lines of code

    What good looks like for this metric: Less than 1 defect/KLOC

    Ideas to improve this metric
    • Implement thorough testing
    • Increase peer code reviews
    • Enhance developer training
    • Use static analysis tools
    • Adopt continuous integration
  • 5. Code Churn

    Measures the amount of code that is added, modified, or deleted over time

    What good looks like for this metric: 10-20%

    Ideas to improve this metric
    • Stabilise project requirements
    • Improve initial code quality
    • Adopt pair programming
    • Reduce unnecessary refactoring
    • Enhance documentation

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

Tracking your Qa Team metrics

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

Don't fall into the set-and-forget trap. It is important to adopt a weekly check-in process to keep your strategy agile – otherwise this is nothing more than a reporting exercise.

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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