The Dangerous Obsession with Measurement

Why the qualitative perspective might save your business in the AI era

I recently had a fascinating conversation with Dr. Katarina Graffman, a cultural anthropologist whose work stands in stark contrast to the data-obsessed business world we operate in. Our discussion challenged my ingrained patterns of thinking and left me questioning whether our collective worship of quantitative analysis might be our biggest blind spot.

What if, in our rush to measure everything, we're actually understanding less?

The measurement hysteria trap

"We're living in a measurement hysteria society," Katarina told me, and the observation hit home immediately. Think about the last important decision your company made. How many metrics, charts, and analyses informed it? How many people in the room asked, "but what does the data say?"

This isn't inherently bad – data provides immense value. But what struck me during our conversation was the connection Katarina made between our measurement obsession and rising leadership anxiety.

"The more you can measure, the faster you can make different types of investigations, the more anxious the decision-makers become," she explained.

I see this anxiety manifested in the shortening time horizons of business planning. Twenty years ago, it was normal to have corporate strategies with genuine 10-year visions. Now? Most companies struggle to look beyond the next quarter. Many leaders hesitate to make any significant decision without first "running it by the data" – not because they need more information, but because they're looking for permission to avoid accountability.

Wait, that can't be right... but actually, maybe it is? Maybe our quantitative addiction isn't about better decision-making at all, but about diffusing responsibility.

The limitations of quantitative thinking

Here's where things get interesting: when I challenged Katarina on this perspective, asking if there isn't real value in having more data rather than making purely gut-based decisions, her response was blunt: "I think that's bullshit."

Strong words, but she continued with an insight I've been wrestling with ever since: "There's a fear in this measurement-obsessed society that's somehow removing experienced people's ability to have intuition. It's gone to the other extreme."

The issue isn't data itself – it's our over-reliance on it at the expense of deep human insight. When we design surveys or analyze metrics, we often pre-determine the answers by how we frame the questions.

Katarina shared an example from her workplace design research, where she deliberately avoided using the term "stress" in her conversations, while other researchers specifically included stress-focused questions. Unsurprisingly, the stress-oriented questions yielded stress-focused answers, while her approach revealed entirely different patterns and priorities.

This isn't just academic methodology talk – it has profound implications for how we understand our customers, employees, and markets.

The qualitative insight revolution

So what's the alternative? Anthropology offers a radical approach to understanding human behavior through ethnography – the practice of deeply immersing in a culture or community to understand it from the inside out.

This qualitative approach doesn't replace quantitative analysis – it enhances it. But it requires something we're increasingly uncomfortable with: time.

An anthropologist might spend a year or more embedded with the people they're studying. They don't arrive with pre-determined survey questions or metrics. Instead, they observe, participate, and gradually identify patterns that might never have surfaced in a quantitative study.

"When you do a qualitative study, you might start with one idea about what you're studying, but then you arrive in the workplace and realize: that's completely uninteresting. These two or three other things are what really matter," Katarina explained.

The challenge is that most executives aren't trained to value this type of insight. They want immediate answers, preferably in dashboard format. But the most valuable insights – the ones that might fundamentally transform your business – often can't be reduced to a number or a bullet point.

The AI connection you're missing

One of the most compelling parts of our conversation centered on the role of qualitative insight in the age of AI. While most discussions about AI focus on automation and efficiency, Katarina highlighted a crucial perspective that's largely missing:

"I'm concerned about these people sitting and programming. Often they're very nerdy people sitting at home, never at workplaces, really immersed in their own world."

This leads to a problem we're only beginning to recognize: AI systems that miss crucial human details. Katarina shared an example from Swedish basic industry, where AI systems deployed on factory floors failed because they missed small but crucial behaviors of forklift operators – behaviors that would have been obvious to someone taking an anthropological approach.

"God, if there's anyone out there – include qualitative insights when you program AI," she implored. "It's so easy for things to go wrong when it's just these people sitting and programming."

This insight resonated deeply with Katarina's experience consulting with highly technical firms who are beginning to recognize this gap: "Super-engineers told me that the type of competence you represent will be so important for us when we work with these AI models and technology. We've already realized we miss so many details if we can't include how people do things and what's important."

The organizational structure problem

Another aspect of our conversation that struck me was how poorly most organizations are designed to incorporate qualitative insights. We've created rigid, hierarchical, silo-based structures where cross-functional understanding is nearly impossible.

"Do you have an organization built around consumer needs? That's a very fundamental question," Katarina noted. Many tech companies have moved toward organizing around life situations (family, work, leisure) rather than technologies or products, but this remains rare.

The deeper issue is that most organizational cultures actively discourage the kind of open-ended exploration that qualitative insight requires. When every initiative needs a clear ROI and a fixed timeline, how do you justify spending time simply observing how people work or use your products without a pre-determined hypothesis?

Authenticity in leadership

We also explored the concept of authenticity – a buzzword that Katarina finds problematic. "Every individual has their own definition of what's authentic, which makes it very difficult for a company," she explained.

This extends to leadership as well. Being an "authentic leader" isn't something you can learn through techniques or rules. "As humans, we detect whether a person is real or just playing by the rules," Katarina observed.

The popularity of authenticity as a concept may actually reflect how inauthentic our society has become. "We're living in such an inauthentic society – who can you trust? What is actually real? So it's not strange that we seek the authentic, from relationships to products to TV shows."

The lingering question

As our conversation concluded, I found myself wrestling with a challenging question: What if our greatest competitive advantage in the coming years isn't better measurement, but better understanding?

Companies that can combine rigorous quantitative analysis with deep qualitative insight may develop a kind of "peripheral vision" that purely data-driven organizations lack. They'll see opportunities and threats before they show up in the metrics.

This approach requires something countercultural in today's business environment: patience. The pressure for immediate results pushes us toward tools and methodologies that provide quick answers, even if those answers are incomplete or misleading.

"We live in a time where we would need to extend our perspectives when it comes to changing people and figuring out how to make this happen now," Katarina reflected. "But we've ended up in a situation where we're just putting out fires."

The companies that resist this short-term thinking – that make space for both measurement and meaning, for both data and deep human understanding – may gain an edge that no algorithm can replicate.

The question for you is: Are you brave enough to invest in understanding that can't be immediately quantified?