QA performance metrics are required for eliminating ineffective strategies and improving internal processes. They also allow managers to track the progress of their QA team over time and produce data-driven decisions about future projects.
Your QA performance metrics process should recognize if goals are being met as and analyze resources to ensure they are producing to their maximum capacity. Performance measures and analysis should extend past the executive decision-makers with input from the complete team – that way, all QA engineers are motivated and can maximize their potency.
But where does your QA team start? Let’s first explore why quality assurance metrics are important, then discover required QA metrics examples for any performance review and the best methods to present performance KPIs.
Importance of QA Performance Metrics
Anyone can report vanity QA metrics. After all, who doesn’t want to promote their team with impressive numbers? While these statistics may glow on the paper, they often don’t drive revenue, product quality, or team productivity – in other terms, real results.
That’s why successful teams concentrate on tracking QA performance metrics. Instead of browsing for on-the-surface numbers, strategic QA teams dig deep into their quality control performance metrics to examine any inefficiencies within the product and their team’s process. Quality assurance metrics handle performance and testing challenges head-on, implementing tangible data towards a calculated solution intended to heighten productivity and product quality.
QA Performance Metrics Worth Measuring
QA teams can experience a variety of advantages when tracking performance metrics, from understanding the difficulties in their test cases and examining consumer expectations to improving current QA testing processes. But, the benefits will only be unlocked if your QA team evaluates the right numbers.
So, how can your team begin to assess quality assurance performance metrics? Below are five QA metrics examples that your team can start measuring today.
Number of Defects Detected in Any Given Build
The number of defects found should reduce from one build to the next over the course of the project. However, if a new feature is included, this may not be the case. In fact, additional features often improve the bug count, leading to longer testing cycles and weak product quality.
Choose to measure these quality assurance metrics in order to trace the stability of builds over time as well as examine various builds. Over the course of the project, the number of defects detected in each build should steadily reduce until the build becomes stable.
If you find that these QA performance metrics improve built after build, your team is possibly encountering one (or all) of the following:
- Multiple issues are tracked using one error or reported as new issues while regression testing the same defect
- Default spot checks are not performed before delivering testing environments to the QA team
- There are communication passages between your onsite team and your QA services partner
Need Help With QA Testing?
Time To Execute a Test Cycle
The first time your team performs a test or set of tests, the number should be higher than subsequent accomplishments. As the QA team becomes familiar with every test and learns to make them work smoother, test time should fall. In this case, set up and collecting the following results should take less time.
To track these QA performance metrics for performance, measure how long it takes to complete selected tests. Make these QA metrics even more useful to your QA team by recognizing which tests can be run concurrently or in parallel to gain time response.
If you find that testing time grows as the project progresses, your team is possibly encountering one (or all) of the following:
- Defect reports lack details
- Your QA team has inadequate understanding of the domain or product
- Your onsite and offsite teams do not interact well with each other
- Testing requirements continuously evolve during the project
- Software and/or hardware configuration modifications
Number of Automated Test Cases Accomplished
To deliver value without sacrificing effectiveness, monitor the percentage of total test cases that are automated through every test cycle. Measuring these QA performance metrics can point to a clearer path of action for incomplete test cases in modules with fewer automated test cases.
If your team sees that your automated test case count is low, your team is possibly encountering one (or all) of the following:
- Your module’s testing system is unstable
- The modified feature or module is out of date
- The affected module undergoes frequent changes, causing the creation of new automation scripts that stops testing until complete
The Severity of Bugs Found in Production
Ideally, no defects are disposed into production. Despite best intentions, bugs can get into the consumer experience. When defects so severe debilitate the ability of your consumers to use your product—then that’s a big difficulty.
Your team can trace these quality control performance metrics by first establishing checks and balances when analyzing the severity of the error. With that in place, measure how many defects at Urgent or Very High severity make it into production in every deployment.
If your team discovers a high count of bugs deployed, your team is possibly experiencing one (or all) of the following:
- Your QA team is not working thorough regression testing
- Not sufficient test cases are automated
- Your QA team does not have a post-deployment testing plan
Common Ways To Present Performance KPIs
Measuring the right QA performance metrics is just as crucial as how you show this data to your internal audience, be it c-suite managers or IT peers. These QA metrics examples can expedite your product quality and QA team’s productivity, so fix up your QA analysis process so that your team can receive the most perks from your data.
When presenting performance KPIs, ensure to:
- Invest in the appropriate tools to help you discover, measure, and track your performance numbers
- Eliminate all vanity metrics from your performance report
- Employ insight to the provided data, including causes for low performance and strategies to improve your testing method
Applying these QA performance metrics can help you handle your QA team more effectively and track your progress over time. Estimating the appropriate quality assurance performance metrics can quickly return impactful, measurable results upon implementation. Don’t hesitate to introduce additional metrics that measure performance ability so that you continue to maximize the productivity and deliverability of your QA team.
Need some guidance on how to measure the success of your QA testing process? Choose to partner with an experienced QA services provider like TestUnity. Our team of testing experts are skilled in QA analysis and can help your team identify the right quality assurance metrics for performance improvement with every testing cycle. Get a free quote today.
Testunity is a SaaS-based technology platform driven by a vast community of testers & QAs spread around the world, powered by technology & testing experts to create the dedicated testing hub. Which is capable of providing almost all kind of testing services for almost all the platforms exists in software word.