Test Automation as Investment, Not Just Technical Choice

Vitaly Sharovatov -

Test automation is often treated as a checklist item: if you have it, great; if not, build it. But too many teams automate without knowing what value they expect, or how to measure whether the investment is paying off.

That’s a problem. Because automation is an investment. Like any investment, it has a cost, but it can also generate returns — if approached strategically.

In this post, we’ll reframe test automation as an economic decision, introduce the three types of value it can create, and explain why traditional cost estimation doesn’t work. If you’re a QA or product leader looking to make smarter decisions about test automation, this is the place to start.

The Three Types of Value in Test Automation

Before discussing ROI or cost, let’s talk about value. Automation isn’t about writing code for the sake of it — it’s about enabling outcomes that matter to the business. Here are three of the most common value drivers:

Reducing Repetitive, Time-Consuming Work

This is the most immediate benefit: automation replaces slow, manual tasks with fast, repeatable scripts. For most teams, the biggest time sink is manual regression testing — often taking days or even weeks per release.

To identify the best candidates for automation, you need to know where your testers are spending the most time. If you’re using a Test Management System like Qase, this kind of analysis is straightforward: you can track which test suites are executed most often and which take the longest.

Without a TMS, teams often rely on informal reporting or gut feeling, which makes it harder to spot automation opportunities with real business impact.

If your testers are repeating the same checks every sprint, you’re burning time (and salary) on work that could be offloaded to machines. Test automation here is not about elegance — it’s about economics. If you know how many hours are spent manually, you can estimate potential savings.

Think of it like this: if a bottleneck task takes 4 hours per week, and you automate it for a team of 5 engineers, that’s 20 engineer-hours saved every month. Multiply by your average hourly rate, and you’ve got a rough value figure.

Improving Release Speed

Speed matters. Faster releases mean faster feedback, faster feature delivery, and potentially faster revenue. That’s why Agile, CI/CD, and shift-left testing exist.

Test automation is critical here. If regression testing delays every release by 4 hours, and you release weekly, that’s 200+ hours of delay per year. What would your product managers say if you could give them 200 more engineering hours to release features earlier?

A useful question: If we made our release process 10% faster, how much more revenue could we generate this year?

Enabling New Types of Testing

Not all value is about saving time. Some of it is about enabling things that humans simply can’t do.

For example:

  • Simulating thousands of users with stress testing
  • Running security scans on every commit
  • Injecting failure scenarios in production-like environments with chaos testing

These forms of testing catch risks you weren’t even measuring before. In some cases, they can prevent outages or data breaches that cost millions.

If you’ve never run performance, security, or chaos tests — automation might be the only viable way to do it.

Why Estimating Automation Costs Doesn’t Work (Exactly)

If automation is clearly valuable, why doesn’t everyone do it?

Because estimating cost is hard. In software, effort estimations are notoriously unreliable — even for moderately complex projects. You may think a set of regression tests will take two weeks to automate, but scope creep, maintenance issues, or flaky tests often stretch that timeline.

This is why modern delivery frameworks like Kanban discourage up-front estimates and prefer incremental delivery with feedback loops. The same logic applies to automation.

Instead of asking “how much will it cost to automate everything?”, ask “What is one high-value area we can automate cheaply — and use as an experiment?”

Start small. Measure how much time it took to automate. Measure how much time it saved. Then expand. This is how rational investors behave under uncertainty.

A Smarter Approach to Test Automation

Here’s how to approach automation like an investor:

  1. Define the value you want: are you saving time? Speeding up releases? Reducing risk?
  2. Pick a small, high-impact target. For most teams, this is a subset of repetitive manual regression tests.
  3. Automate incrementally. Don’t build a full suite up front. Add automation in small, testable batches.
  4. Measure value. Track time saved, bugs caught, or release acceleration. Use real data.
  5. Scale only when ROI is proven. If the initial investment paid off, double down. If not, reassess.