Why IT Teams Need to Think Like QA

July 23, 2025

Anna O.

Building Systems That Catch Failures Before Users Do

Let’s be honest - if you work in IT long enough, you’ve experienced this scenario:

Everything seems fine… until a user email says,

“Hey, this report didn’t generate.”

Or worse:

“Something’s broken and I didn’t know until our client told me.”

That moment when a user becomes your alert system? It's the worst.

And it’s also preventable — if your IT team starts thinking more like a QA team.

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QA Thinking Isn’t Just for Software Testing

Quality Assurance folks are trained to hunt for bugs before the software ever gets in a user’s hands. They think in terms of:

• What could go wrong?

• What should happen vs. what actually happened?

• How can we build confidence in this system?

They don’t just test what’s obvious. They test the edge cases. They test what happens when things go wrong — and then make sure those things are caught early.

Now imagine if we approached IT systems with the same mindset.

What It Looks Like to Think Like QA in IT

Let’s take a job scheduling environment as an example (like GECS or similar systems). You have hundreds of jobs running across multiple agents and servers. Everything depends on timing, data availability, and network stability.

QA-minded thinking in IT means:

✅ Verifying outputs. Did that job not only run but produce what we expected?

✅ Building alerts for the absence of success. Not hearing from a system doesn’t mean it’s healthy — maybe it silently failed.

✅ Adding sanity checks. Was the file updated? Was it over a certain size? Did a confirmation email go out?

✅ Logging more intelligently. Log the wins and the weird stuff. Missing log entries are often your first clue something’s off.

✅ Not trusting “green lights” alone. Just because something shows “Completed” doesn’t mean it did what it was supposed to.

A Real-World Example

We had a situation where one batch of jobs was checking a remote network folder that had over 5,000 files in it. The job didn’t crash — but performance tanked. Eventually, downstream jobs began timing out.

The root cause? That one overloaded network folder.

Once we applied some QA-style thinking, we added:

• A pre-check job to monitor file counts

• Thresholds to alert if volume was too high

• Smarter logs that highlighted slowdowns

Problem solved — and no more surprises.

QA Tools IT Can Use Right Now

You don’t need to overhaul your infrastructure to think like QA. Just borrow a few habits:

• Assertions in scripts (“If this file doesn’t exist, don’t continue”)

• Dry runs before real runs (staging/test modes)

• Mock data to test flow and output formats

• Job validations at each step (“Did Step 1 complete and produce the right data for Step 2?”)

• Version control for configuration files

• Error simulations — break it on purpose to see what happens

These aren’t just good ideas. They build trust in your systems — and help you sleep better.

It’s a Culture Shift, Not Just a To-Do List

You don’t need a separate QA team for IT (though if you have one, use them!). It’s more about changing your mindset.

Ask yourself and your team:

• “What would QA try to break here?”

• “What assumptions are we making that could bite us later?”

• “If this fails silently, who’s going to tell us — the system, or a user?”

The best systems don’t just run — they’re self-aware enough to know when something’s off and let you know first.

Final Thoughts

When IT teams think like QA, you're not just putting out fires — you're fireproofing your systems. You’ll reduce outages, eliminate mystery failures, and stop relying on your users to be your alert system.

Start small. Add a simple validation step to your next job. Set up one alert for an unexpected result.

You’ll be surprised how much smoother everything runs when your systems have a little more QA-style thinking baked in.

Want help coming up with test checks or validation logic for your own environment? Let’s talk. QA minds unite. 🛠️👀