The Forgotten Cost of Skipping Regression Testing
The Forgotten Cost of Skipping Regression Testing
Author: Imtiaz Shaik, Senior QA Lead at ADP Canada
During sprints and under tight deadlines, it’s ever-tempting for QA teams to shave time off testing to get across the finish line. Skipping regression checks might look like a harmless time-saver in the short term but in reality it’s vice-versa: skipping regression testing doesn’t save time – it borrows it, with compound interest.
Regression testing is essential when running tests to make sure new changes have not broken the existing functionality, specifically if your software system deals with security vulnerabilities and compliance rules.According to the State of Quality Report, 55% of QA specialists report insufficient time to conduct comprehensive testing, but skipping a regression test in a sprint can bea fatal mistake, and it rarely produces the outcome you expect.
The only immediate “win” is time saved in that sprint. However, long-term costs of skipping it are much worse:
A few sprints back on a Human Capital Management product, my team and I skipped some regression checks to meet a hard deadline. Shortly after deployment, payroll calculations were wrong – employer and employee benefit contributions were miscalculated. As a result, an immediate fix had to be done delaying the release and even required a partial rollback. That day I learned that skipping regression testing, even under tight sprint deadlines, creates far greater risks and costs more than the short-term time saved.
But why do teams continue to skip regression testing
The common reasons I’ve seen so far:
How to protect essential regression checks under deadline pressure
It all depends on how often the product needs changes and maintenance. But, yes, you can keep quality without killing velocity. Firstly, I advise adopting a partial regression testing approach which targets only features impacted by the updated code changes and their dependencies. It reduces test execution while still preserving meaningful coverage.
This strategy is especially effective if you invest in automation: test automation is a very helpful tool which automatically executes test cases and verifies software functionality faster, repeatable, and reliable instead of manual tests which would be comparatively prolonged. If automation regression is integrated into CI/CD pipeline, it’s more reliable and runs immediately after code changes occur. Expertsemphasizethat automated regression suites make it realistic to protect core workflows without blocking sprints. Automation ensures critical workflows are tested every sprint with consistency, and test execution reports provide analysis on coverage and risk areas, enabling QA to prioritize high-impact regression checks and maintain overall product stability.
Finally, the good QA lead should lay down a test strategy to ensure essential regression coverage isn’t skipped in a sprint cycle depending on the new requirements. When identifying critical functionality, you must focus on the areas most affected by recent code changes. Integrate regression into the Sprint Definition of Done (DoD), prioritize risk-based regression tests and mark it out as mandatory.
After the catastrophe with a Human Capital Management product, we invested in automating core payroll validations and integrated them into our CI/CD pipeline, and adopted a risk-based approach for future releases to ensure that tax computations and benefit calculations are always included in regression tests. Since that, most defects were caught early, even before reaching production.
KPIs to monitor the impact of skipped regression testing
Personally, I focus mainly on three, the most effective, metrics to capture the impact of regression testing: defect leakage rate, rework effort and customer reported issues.
Defect Leakagerate shows what percentage of defects that escape into User Acceptance Testing (UAT). This way we can directly see how many issues have slipped through skipped regression tests.
Rework Effortshows how many hours was spent on fixing the defect, how many hotfixes or rollbacks were released. Using this metric we can see the time skipping regression testing costs.
The last most effective metric to use iscustomer reported issues. It measures how many payroll miscalculations or system errors are reported after product release. This metric shows the real life consequences of skipping tests. Together, these three key metrics show the quality gap, business cost and the user impact demonstrating a complete picture on why skipping regression testing is not efficient in the long run.