Avoiding The Usual Mistakes In Test Automation

Building and shipping digital products is never easy. Teams are under pressure to release features fast, fix things even faster and still offer a smooth, reliable experience to users. That’s where test automation can really help, when it’s done well.

Get it right, and automation means fewer bugs, faster deployments and less time spent on repetitive manual testing. It can be a huge boost for continuous delivery. But too often, it doesn’t quite work out like that. Projects stall, tools get in the way or the plan was never quite right to begin with.

If your automation efforts haven’t delivered what you hoped, or if you're about to kick one off and want to get it right, then this post is for you.

‍Why automation often falls short

‍1. Chasing instant ROI
There’s often an assumption that automation will save time and money straight away. In reality, returns take time and depend on what you’re testing, how stable your product is and how mature your testing setup is.
The reality: ROI isn’t linear. Expect a slow burn before you see big gains.

‍2. Thinking automation replaces manual testing
Automation is great for speed and scale, but it’s not a silver bullet. It can’t spot design quirks, odd user flows or unexpected behaviour the way a human can.
The reality: Automation helps you move fast. Manual testing helps you go deep. You need both.

‍3. Automating the wrong things
If you're trying to automate fragile, constantly changing tests, especially around UI, you're setting yourself up for flakiness.
The reality: Focus on the repeatable, stable stuff. Leave dynamic or visual checks to manual testing or specialist tools.

‍4. Picking tools that don’t fit
No-code and low-code tools can look tempting, but if they don’t match your stack or scale with your needs, they’ll slow you down.
The reality: Choose tools that fit your tech, your team and your future plans.

‍5. Lacking the right skills
Automation isn’t just plug and play. You need people who understand testing, coding, frameworks and debugging.
The reality: Good tools still need good people.

‍6. A fragile framework
If your test framework isn’t modular, scalable or easy to maintain, you’ll spend more time fixing tests than writing them.
The reality: A solid framework today saves hours of rework tomorrow.

‍7. Running tests one by one
Without parallel execution, your tests become a bottleneck and the whole point of automation is lost.
The reality: Speed matters. Run tests in parallel to keep things moving.

‍8. Skipping the insights
Automation gives you data but only if you pay attention. Ignoring test reports means missing flaky patterns or repeated issues.
The reality: Reports are more than logs. Use them to improve your testing strategy.

‍9. Trying to do too much at once
Going all in from day one sounds ambitious, but often leads to messy, hard to maintain test suites.
The reality: Start small. Build something solid. Then scale.

‍10. Siloed efforts and lack of visibility
Automation doesn’t work in isolation. If devs don’t build testable products, or if testers and engineers aren’t working together, things will break. Add to that a lack of visibility across the team and trust in the test suite quickly disappears.
The reality: Automation works best when everyone’s involved. Build testability in, share progress widely and treat it like a team effort - not a side task.

‍How to make automation work

Automation fails when it’s rushed, siloed or treated like a one off task. But with the right approach, it can become a core part of your delivery pipeline. Here’s what helps:

‍Start with the right goals - Begin in areas where you’ll see clear impact, like regression or smoke tests. Track how much time and effort you’re saving and adjust expectations as you go. ROI takes time, but it should grow steadily.

‍Pick your battles - Not everything should be automated. Focus on stable, repeatable flows that really matter to the business. Leave the fiddly, fast changing stuff like UI visuals or exploratory testing to humans.

‍Prove it before you commit - Before choosing a tool, run a quick proof of concept using real scenarios. Can it handle dynamic locators? Integrate with your pipeline? Generate useful reports? If not, it’s not the right fit.

‍Build something you can grow with - Set up your framework properly from the start. Keep it modular, add meaningful logs and get it ready for parallel runs early. Design patterns like the Page Object Model can help keep things clean and scalable.

‍Treat it like production code - Automation is code. Put it in Git. Review it. Document it. Comment it. Keep it clean. The same engineering standards apply.

Bring in developers early - Work with your dev team to make the product easier to test - stable element IDs, reusable components, good structure. Make testability part of your Definition of Done.

‍Get the right people - Whether you're hiring or upskilling, make sure you have people who understand both testing and code. The best automation happens when testers and engineers work together, not in silos.

‍Don’t skip the maintenance - Old tests break. Flaky ones waste time. Make regular clean ups part of your process - triage failures, retire unused tests and keep the suite lean.

Good automation takes time, collaboration and clear thinking. It’s not all about tools or speed but about building something that supports your team and strengthens your delivery process.

Start small, build on solid foundations and keep things maintainable. Over time, the value becomes clear: faster feedback, fewer surprises and more time to focus on improving your product.