QA performance metrics are essential for eliminating inefficient strategies and improving internal processes. They also enable managers to track the progress of their QA team over time and make data driven decisions about future projects.
Your QA performance metrics process should identify if goals are being met as and analyze resources to make sure they are producing to their maximum capacity. Performance measures and analysis should extend beyond the executive decision makers with input from the entire team - that way, all QA engineers are motivated and can maximize their productivity.
But where does your QA team begin? Let’s first explore why quality assurance metrics are important, then discover essential QA metrics examples for any performance review and the best ways to present performance KPIs.
Importance of QA Performance Metrics
Anyone can report vanity QA metrics. After all, who doesn’t want to tout their team with impressive numbers? While these statistics may shine on paper, they often don’t drive revenue, product quality or team productivity - in other words, real results.
That’s why successful teams focus on tracking QA performance metrics. Instead of skimming for on-the-surface numbers, strategic QA teams dig deep into their quality control performance metrics to analyze any inefficiencies within the product and their team’s process. Quality assurance metrics tackles performance and testing challenges head-on, applying tangible data towards a calculated solution designed to heighten productivity and product quality.
QA Performance Metrics Worth Measuring
QA teams can experience a variety of benefits when tracking performance metrics, from understanding the problems in their test cases and analyzing consumer expectations to improving current QA testing processes. But, the advantages will only be unlocked if your QA team reviews the right numbers.
So, how can your team begin to evaluate quality assurance performance metrics? Below are five QA metrics examples that your team can begin measuring today.
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Number of Defects Found in Any Given Build
The number of defects found should decrease from one build to the next over the course of the project. However, if a new feature is introduced, this may not be the case. In fact, additional features often increase the bug count, leading to longer testing cycles and weakened product quality.
Choose to measure these quality assurance metrics in order to track the stability of builds over time as well as compare various builds. Over the course of the project, the number of defects found in each build should steadily decrease untill the build becomes stable.
If you discover that these QA performance metrics increase built after build, your team is possibly experiencing one (or all) of the following:
- Multiple issues are tracked using one defect or reported as new issues while regression testing the same defect
- Default spot checks are not executed before delivering testing environments to the QA team
- There are communication gaps between your onsite team and your QA services partner
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Time To Execute a Test Cycle
The first time your team executes a test or set of tests, the number should be higher than subsequent executions. As the QA team becomes familiar with each test and learns to make them run smoother, test time should fall. In this case, setup and collecting subsequent results should take less time.
To track these QA performance metrics for efficiency, measure how long it takes to perform selected tests. Make these QA metrics even more beneficial to your QA team by identifying which tests can be run concurrently or in parallel to gain time efficiency.
If you find that testing time increases as the project progresses, your team is possibly experiencing one (or all) of the following:
- Defect reports lack details
- Your QA team has insufficient understanding of the domain or product
- Your onsite and offsite teams do not communicate well with each other
- Testing requirements continuously change during the project
- Software and/or hardware configuration changes
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Number of Automated Test Cases Executed
To deliver value without sacrificing efficiency, monitor the percentage of total test cases that are automated during each test cycle. Measuring these QA performance metrics can lead to a clearer path of action for unresolved test cases in modules with fewer automated test cases.
If your team notices that your automated test case count is low, your team is possibly experiencing one (or all) of the following:
- Your module’s testing system is unstable
- The affected feature or module is out of date
- The affected module receives frequent changes, causing the creation of new automation scripts that halts testing until complete
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The Severity of Bugs Found in Production
Ideally, no defects are deployed into production. Despite best intentions, bugs can make it into the consumer experience. When bugs so severe debilitate the ability for your customers to use your product—then that’s a big problem.
Your team can track these quality control performance metrics by first establishing checks and balances when classifying the severity of the defect. With that in place, measure how many bugs at Urgent or Very High severity make it into production upon every deployment.
If your team detects a high count of defects deployed, your team is possibly experiencing one (or all) of the following:
- Your QA team is not performing thorough regression testing
- Not enough test cases are automated
- Your QA team does not have a post-deployment testing strategy
Common Ways To Present Performance KPIs
Measuring the right QA performance metrics is just as essential as how you present this data to your internal audience, be it c-suite executives or IT peers. These QA metrics examples can accelerate your product quality and QA team’s productivity, so set up your QA analysis process so that your team can receive the most benefits from your data.
When presenting performance KPIs, make sure to:
- Invest in the right tools to help you locate, measure and track your performance numbers
- Eliminate all vanity metrics from your performance report
- Apply insight to the provided data, including reasons for low performance and strategies to refine your testing process
Applying these QA performance metrics can help you manage your QA team more effectively and track your progress overtime. Measuring the right quality assurance performance metrics can rapidly return impactful, measurable results upon implementation. Don’t hesitate to include additional metrics that measure performance efficiency so that you continue to maximize 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 QASource. 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.
