QA test execution can only be as strong as the strategy you have in place. One of the best QA practices we’ve noticed across many software companies actually happens before any testing begins. By implementing a strong plan with thorough processes, every member on your QA team knows what to deliver, when to deliver it by and why it's important.
But how do you know if your strategy is sound?
A little insight can go a long way. Measuring performance metrics regularly is your team’s way of checking in on how well your testing processes are playing out. Are your current processes the best QA practices you can have in place? Is your software product continually advancing with frequent feature releases? Does your QA team regularly understand expectations from project to project? Where are the communication lapses occurring during the development cycle that can be improved upon?
Like your test processes, you want to concentrate your time evaluating performance metrics that deliver efficient results. We recommend that every QA team track these five performance metrics to reveal where problems lie within your processes, reinforce customer expectations and increase team productivity.
Reporting Defects
To adhere to best QA practices, it’s always recommended to measure the stability of builds over time. This performance metric reveals how many valid defects the QA team reports, including duplicate defects, invalid defects and defects that the Development team cannot reproduce.
The goal from one development cycle to the next is to decrease the number of defects found during the course of a project until the build becomes stable. Unfortunately, instances such as introducing a new feature can increase the number of defects. By reviewing reported defects from build to build, your team can recognize a pattern of encountered defects and stay on track to minimizing them.
If your team finds that the number of defects discovered increases built after build, you could be experiencing one (or all) of the following:
Time to Execute a Test Cycle
Since it’s a best QA practice for your testing process to maintain efficiency, your team should keep track of how much time it takes to execute a test. The purpose of this performance metric is to verify that the time it takes to run a test the first time should be significantly higher than subsequent executions.
As your team grows more familiar with the product and test cases, test time should decrease and run more smoothly during the project. Consider measuring this metric by identifying which tests can be run simultaneously to increase testing effectiveness.
If your team discovers that testing time increases as the project progresses, you could be experiencing one (or all) of the following:
Automation Velocity
Automation is considered to be one of the best QA practices because of its rapid turnaround time to develop and deploy your software to market. To ensure that your team is sustaining productivity levels, we recommend measuring the number of new automation test cases as well as the delivery of new automation scripts and resource allocation.
Teams find value in measuring this performance metric because it monitors the speed of test case delivery and identifies which programs need further examination. If your team uncovers a deviation in automation script delivery, you could be experiencing one (or all) of the following:
QA Regression Summary
Keeping track of which defects are revisited and reexamined from one development cycle to the next follows best QA practices. This performance metric shares the trends of verified, closed and reopened defects over time.
If your team finds that the number of reopened defects grows month after month, you could be experiencing one (or all) of the following:
Automation Coverage
Low automation coverage can impact the quality of your product as well as require unnecessary effort and time from your testers to manually test your product. To deliver value without sacrificing efficiency, we recommend examining your automation coverage by monitoring your total test cases to gain better insight on pending test cases for specific modules.
Measuring this performance metric follows QA best practices because this information can lead to a clearer path of action for unresolved test cases in modules with less automation coverage. If your team notices a deviation in the total automation test case count, you could be experiencing one (or all) of the following:
You’ll know that you are measuring the right performance metrics when the changes you implement to your QA testing process return impactful, measurable results. Still uncertain on how to measure the success of your QA testing process? Consider partnering with an experienced QA services provider like QASource. Our team of QA analysis experts are skilled in identifying the right performance metrics worth measuring so you release better quality software faster. Get a free quote today.
Want to learn how your peers measure their teams?
Download the report 20 Metrics VPs Use to Measure their QA Team below!