The digital analytics industry stands at an inflection point. As generative AI and automation sweep through organizations, promising to handle everything from data collection to basic analysis, we face a fundamental question: What becomes of the digital analyst?

The answer isn't found in fighting the tide of automation or doubling down on technical skills. Instead, it requires us to acknowledge an uncomfortable truth that digital analytics, as we've known it, is already obsolete. Not because the work doesn't matter, but because the name itself has become too small for what we must now become.

What emerges from this disruption isn't the death of a profession but its radical evolution from mechanical data workers to what we call "organizational anthropologists," practitioners of Human-Centered Analytics who help businesses see the humans behind the data.

There’s a moment in every analyst’s career when they stop just reading data and start questioning it.

We’re not talking about being cynical or skeptical for the sake of it. We’re talking about curiosity-driven, clarity-seeking, insight-focused critical thinking.

Take U-Haul’s 2024 “Growth States Report.” It ranks U.S. states based on one-way U-Haul rentals, suggesting where people are moving to and from. At a glance, it’s a tidy list with intuitive appeal. But scratch the surface, and it becomes a perfect teaching tool, not because the data is “bad,” but because it invites better questions.

So let’s use this dataset not as something to critique but as something to practice on.

Ad agencies are buzzing about Meta’s new Incremental Attribution model with some calling it a breakthrough in “real” measurement and the end of vanity metrics.

But here’s what we’re not seeing: Critical discussion from a data perspective.

A friend once remarked to me that "unintentional evil is still evil," referencing how social media platforms might not have been designed with malicious intent, yet their engagement-obsessed algorithms often create harmful outcomes. Sometimes it's not evil but simply unethical, disrespecting humans, breaking trust, or manipulating behavior.

From an early age, children are naturally curious, asking questions, observing patterns, and trying to make sense of the world around them. In our modern, data-driven society, this innate curiosity can be nurtured through tools that teach them how to think critically, analyze information, and draw meaningful conclusions. This is why we created A is for Analytics—to make the world of data accessible to kids in a fun and engaging way.

Critical thinking and skepticism are not just optional tools for data analysts—they are essential. Without them, we risk allowing flawed, biased, or incomplete data to influence important decisions. In a world where data is used to shape narratives and drive opinions, our responsibility is to approach it with a healthy dose of doubt and a commitment to uncovering the full story.

Through almost 20 years of experience, one of the biggest problems we’ve observed, not just within companies but within schools, communities, and the world in general, is a frightening lack of data literacy. Not only has this lack of data literacy translated into missed business opportunities to create really positive experiences for customers, but in a more important and serious way, the lack of data literacy has allowed companies, journalists, and politicians to effectively distort data in order to create divisiveness and chaos.