As a data analyst, there’s one question I find myself coming back to again and again:

What’s the data actually telling us?

On the surface, that might sound straightforward, but in reality, it’s anything but. Our brains are built for shortcuts, we notice patterns, make assumptions and tend to look for evidence that backs up what we already believe it’s human nature.

But that’s exactly why critical thinking matters so much in data analysis.

The power of data isn’t in the obvious numbers sitting in a spreadsheet, it’s in what we’re willing to question, the patterns we don’t expect, the inconsistencies we might overlook and the stories that only come to light when we dig a little deeper.

A Quick Story from 1543 (Bear With Me)

Let’s rewind 500 years.

In 1543, a man called Andreas Vesalius published a book that changed the course of medical science for centuries, doctors had followed the teachings of Galen, a Roman physician whose understanding of human anatomy came from dissecting animals not people.

Everyone just assumed Galen was right and no one questioned it.

But Vesalius did, he dissected human bodies and realised there were big, glaring errors in Galen’s work. So he challenged it, and in doing so, he flipped the medical world on its head.

To me, Vesalius is the perfect example of what it means to think critically: not just taking things at face value, but asking “is this actually true?” and going out of your way to find out for yourself.

Fast forward to today our tools have changed, but the mindset should be the same, as analysts, we’ve got dashboards, KPIs, charts, AI tools, but none of that matters if we don’t question the assumptions behind the data.

Why Critical Thinking Isn’t Just ‘Nice to Have’

Without critical thinking, data analysis becomes guesswork with a nice graph.

I’ve worked with businesses who were convinced they knew what their problem was. One client had strong traffic to their online store, but hardly any conversions. They were tweaking product descriptions, adjusting prices, doing everything they could think of.

But when I looked at the data properly, it turned out the issue wasn’t the products at all, it was the checkout a clunky process was causing people to abandon their baskets at the last moment.

Fixing that one thing made all the difference, abandonment rates dropped by over 35% and revenue shot up.

That insight didn’t come from a tool or a trend, it came from not accepting the first answer and asking better questions.

How I Work: Curiosity First, Tools Second

When I’m analysing data, I don’t rush in looking for quick answers, I treat it more like a detective story.

First I start with the obvious stuff, what most people would check, but then I start digging:

• What feels off here?
• What are we assuming?
• Could there be something bigger going on behind the scenes?

I lean heavily on Socratic questioning, constantly challenging my own thinking and I flip between zooming in on the tiny details and zooming out to look at the wider system.

I’m also a big fan of Thinking, Fast and Slow by Daniel Kahneman. He explains how our brains are hardwired to go for quick answers, even when they’re wrong. So I’ve trained myself to pause, sit with the messy bits and keep asking until things make proper sense.

Metrics Are Not the Whole Story

One thing I see all the time is people treating metrics like they’re stand-alone facts: bounce rate, click-throughs, return on ad spend.

Yes they’re useful, but only in context, on their own they can be really misleading. Metrics are clues not conclusions, they’re just small parts of a much bigger system.

You can’t make good decisions by zooming in on one number and ignoring the rest, you’ve got to step back and ask:

• How does this fit into the bigger picture?
• What’s really going on across the whole customer journey?
• Are we solving the right problem?

Where AI Comes In and Where It Stops

I use AI tools all the time, they’re brilliant for speeding things up, spotting patterns and cutting down manual work.

But here’s the thing, AI doesn’t ask better questions that’s our job.

AI is great at showing you what’s happening, but not why. It won’t challenge your thinking or flag when your assumptions are off. That’s where human judgement comes in, where values, creativity and experience still matter.

I see AI as a tool not a decision-maker and I use it to support my process not replace it.

Stay Curious, Stay Uncomfortable, Keep Questioning

One of my favourite mantras is: “I know that I know nothing.”

It reminds me to stay humble to keep learning and to never assume the first answer is the right one.

Because when it comes to data, surface-level thinking just isn’t enough. The best insights come when you lean into the uncomfortable and things that don’t quite add up or the questions that don’t have easy answers.

If you want to get more out of your data, forget the fancy dashboards for a second, ask better questions, challenge your assumptions and be willing to be wrong.

That’s where the gold is.

Ready to Get More From Your Data?

If you’re a business owner, marketer or analyst and you’re done with surface-level reporting, I’d love to help.

Book a free 15-minute strategy session and let’s figure out what your data’s really saying.