How Much is Manual Regression Costing You Each Quarter?

Manual regression feels simple on the surface. You run your tests again after a code change, check what still works, and you ship.

But beneath the surface, it eats time (since manually executing test steps take too much time). It also eats budget, and it quietly slows your release velocity.

If you’ve ever thought, “we just need a few days to finish regression,” you’ve likely already paid more than you think.

That’s why we created this guide. It shows you how to calculate your regression cost using a manual testing cost calculator. You’ll see where the hours go. You’ll understand what those hours cost. And you’ll walk away with a clear picture of what automation could return.

Here’s what we’ll cover:

• The hidden cost drivers behind manual regression
• A back-of-the-napkin formula to estimate your quarterly spend
• How manual vs automated testing cost trends shift over time
• Why every regression cycle is a release delay multiplier
• A case study of a QA team that slashed costs and saved time
• How automation tools like Katalon help you track ROI in real time

If you're planning your QA roadmap, this will help you budget smarter. Let’s get into it.

The real cost drivers of manual regression

Every manual regression cycle uses real time and real money. These costs often spread across teams and sprints, which makes them hard to track. But they show up in every cycle.

According to the World Quality Report 2024–25, “about 43 % of companies invest between 11 % and 20 % of effort relative to their development resources in testing, while a quarter dedicate between 21 % and 30 %” (p. 21). This highlights that testing can easily consume one-fifth to one-quarter of a development budget.

Let’s look at what actually drives the cost of regression testing.

• Tester hours per cycle: Higher code coverage gives the testing team more confidence that the code has been thoroughly tested. Code coverage and testing cost are closely related. Increasing coverage usually requires more tests, which leads to higher costs for the test suite.
• Number of cycles per quarter: If you run regression after every sprint, you’re doing it four to six times per quarter. That means the cost repeats often.
• Hourly rates: QA talent is valuable. Manual time is expensive. According to U.S. BLS data for May 2023, Software Quality Assurance Analysts and Testers earn on average $52.15/hr (≈ $108,460/year), with median wages around $48.94/hr and higher rates (75th-/90th percentile) exceeding $62–$79/hr. This means a single 30-hour regression cycle for a five-person QA team can cost well over $7,000 in wages alone. Every hour spent clicking through test cases has a real dollar value.
• Coordination and reporting: Manual testing takes prep time and status tracking. That effort is not always visible, but it always exists.
• Feedback loops: The longer it takes to validate features, the slower you can release. Teams wait, and ideas stall.

You can plug these inputs into a manual testing cost calculator to estimate quarterly spend. But here’s a high-level view to show how each cost driver connects to business outcomes:

Once you see how the pieces fit together, it becomes easier to model the cost of regression testing. That clarity helps you make stronger cases for automation and smarter QA decisions.

📚See our deeper guide on how manual regression cost grows and how automation flips the balance.

The back-of-the-napkin calculator

You don’t need a spreadsheet to start measuring the cost of regression testing. All you need is a simple formula and the numbers you already know.

Here’s the core formula:

Manual regression cost per quarter =
(Number of testers × Hours per cycle × Cycles per quarter × Hourly rate)

Let’s say your team has:

• 5 testers
• Each regression cycle takes 30 hours
• You run 4 cycles per quarter
• Each tester earns $50 per hour

Plug that into the formula:

5 testers × 30 hours × 4 cycles × $50/hour = $30,000 per quarter

Now look at the annual number. Multiply $30,000 by 4. You’re spending $120,000 per year just to rerun test cases manually.

That number comes from inputs you already track. When you use a manual testing cost calculator, you get a faster way to estimate and explain. You can show budget impact without the need for extra tools or meetings.

This kind of testing cost breakdown helps QA managers build a business case. It also helps product teams understand the trade-offs between testing coverage and delivery speed.

💡Try it yourself with Katalon’s interactive Test Automation ROI Calculator

Manual vs automated regression: cost comparison

Once you know your quarterly spend, it becomes easier to model the long-term cost of regression. Manual regression increases with team size and test volume. Automation, on the other hand, creates repeatable value every cycle.

A controlled case study confirms that “Automated graphical user interface (GUI) tests can reduce manual testing activities and increase test frequency,” demonstrating how automation scales more effectively than manual regression. 

Let’s compare the quarterly and annual cost between manual and automated regression for a growing QA team:

This projection shows how the return on automation grows over time. Manual regression grows with complexity. Automated testing stays stable once it’s set up. If you use a manual testing cost calculator, you can customize this projection to fit your team.

Pros of manual testing

• Requires little to no tool investment early on
• Fits teams that run short and simple test cycles

Cons of manual testing

• Consumes more time with each new test case
• Costs rise as your application and coverage grow

Pros of automated testing

• Test scripts can be reused across cycles and releases
• Regression runs faster and allows parallel execution

Cons of automated testing

• Setup requires time and planning in the first cycle
• Tools and frameworks need onboarding and support

Understanding the manual vs automated testing cost is key to budget planning. It helps teams decide when to invest and where automation creates the most value over time.

📚Explore our guide to calculating test automation ROI

The time factor: release velocity as a cost multiplier

Manual regression is not just a QA cost. It is also a product delay. Every extra testing day is a day your new features wait to reach users. Empirical evidence backs this up.

💡A study in Empirical Software Engineering on Mozilla Firefox found that “the rapid release model enables faster delivery of features and fixes without negatively affecting post-release defect density,” after moving to a six-week release cadence.

Take this example. A team spends three days per sprint on manual regression. Over twelve sprints, that adds up to thirty-six days. That is almost a full month where delivery slows down.

Now apply that across multiple teams. Across multiple products. That time becomes even more valuable when you look at what it could unlock with automation.

💡Faster feedback means faster releases. Teams can merge changes sooner. Product managers can deliver value earlier. Developers can iterate with less friction. The impact compounds over time.

Automated testing helps teams improve QA speed without sacrificing coverage. It supports continuous delivery and reduces release bottlenecks. That’s one reason more teams use it to achieve time saved with automation.

Speed is not just a nice-to-have. Industry data confirm how vital release speed has become.

The 17th State of Agile Report notes that 39 % of organizations rank time to delivery among their top priorities and 41 % adopt Agile specifically to accelerate time to market. When it aligns with testing accuracy, it becomes a growth lever. Automation makes that alignment possible.

Case example: Saga’s ROI from automation

UK-based insurer Saga faced a familiar bottleneck: every product release required extensive regression testing, but the manual process couldn’t keep up with the pace of Agile development.

To break this cycle, Saga adopted the Katalon Platform for automated regression testing. The shift transformed their QA operations:

• Testing scope tripled – from roughly 30 scenarios to at least 100 scenarios per product per development release
• Execution time collapsed – from two full days down to just two hours for each regression run

These gains directly improved release velocity and cost efficiency. More scenarios could be tested more frequently, and every development release reached production faster—with fewer overtime hours and less manual coordination.

Saga’s experience illustrates the business case your cost calculator highlights: automation converts regression testing from a multi-day, labor-intensive task into a repeatable two-hour process. The return on investment is not theoretical; it is demonstrated every sprint in faster releases, broader coverage, and lower per-cycle cost.

How Katalon delivers visible ROI

Katalon helps teams start fast.

• No need to build custom frameworks. You get a ready-to-use platform that supports UI, API, mobile, and desktop testing.
• Prebuilt integrations for CI/CD. You can connect tests to GitHub, Jenkins, or your pipeline of choice. That means every regression run happens when and where it should.
• Test results go to built-in dashboards. Managers can view pass rates, coverage, and execution trends. They can also track automation testing ROI over time. It becomes easier to show how automation reduces test effort and improves release confidence.
• Test data is reusable. Object repositories keep locators in one place. You can write tests once and use them across different devices. That helps teams scale without extra setup.
• Reporting is simple. You get HTML snapshots, email reports, and video logs. These reports make it easier to debug issues and share insights across teams.
• Katalon also supports test scheduling. You can run tests on a set time or in response to code changes. This keeps regression consistent, even when timelines shift.

When paired with a manual testing cost calculator, Katalon helps QA leaders model potential savings. They can plan for the future and measure impact from day one.

If you want results you can see, Katalon gives you the visibility and control to scale your test automation with confidence.

📚 See how to measure and prove your test automation ROI with Katalon

Conclusion

Manual regression comes with a clear cost. Every test cycle adds to your budget. Every hour spent on repetitive testing is an hour your team could use elsewhere. Each extra hour of manual regression represents a significant recurring cost.

Automation transforms that pattern. With the right tools in place, you turn regression into a process that scales with confidence and speed. You get faster feedback, higher coverage, and a consistent release rhythm.

The best way to start is with a manual testing cost calculator. Use it to model the cost of regression testing today. Then explore how much time is saved with automation once the process is in place.

That shift matters. You get earlier releases, faster cycles, and a testing model that supports growth without constant trade-offs.

Use the calculator. Share it with your team. Run the numbers together. You’ll get a clearer view of what you spend and what you could gain by automating now.

🚀 See Katalon in action — book a demo