The air in the room has the texture of lukewarm coffee. Stale. On the giant screen, a presenter points a green laser at the top-right corner of a slide so dense it looks like a city grid seen from orbit. Seventeen charts, all aggressively colorful, fight for attention. ‘As you can see,’ he says, his voice hitting that practiced, confident cadence, ‘engagement is trending.’

And nobody moves. Nobody asks what ‘engagement’ means today, or why chart seven contradicts chart twelve, or what ‘trending’ signifies when the y-axis is logarithmic and the time scale is ‘since launch.’ The silence isn’t respectful. It’s a vacuum. It’s the sound of a dozen smart, well-paid people collectively agreeing not to admit they have no idea what they’re looking at. The presenter doesn’t know. The VP in the front row doesn’t know. I certainly don’t know.

We don’t ask because the chart isn’t for understanding. It’s for absolution. It’s a shimmering, data-driven security blanket that we can wrap around our decisions. If we fail, we can point to the dashboard and say, ‘But the data supported our strategy.’ The dashboard is a beautiful, expensive, and mathematically-sound way to defer accountability.

I say this, and I immediately feel like a hypocrite. For seven years of my career, I was the guy making the slides. I was the high priest of the dashboard cult. I loved the clean lines of a well-rendered chart, the satisfying click of a filter that made the numbers dance. I built a ‘mission control’ dashboard once that tracked 237 distinct user actions in real-time. It was my masterpiece. It was also completely useless. It told us everything and explained nothing. Worse, it led us to chase a meaningless metric for two quarters, a mistake that cost us a very specific $77,777 in wasted ad spend. We had more data than ever, and fewer insights.

It’s a strange thing, trying to go to bed early. You lie there and your brain, instead of shutting down, decides it’s the perfect time to replay your greatest hits of professional failure. Last night, that dashboard was the headline act. I wasn’t just thinking about the bad decision; I was feeling the phantom weight of the mouse in my hand as I arranged the charts, convinced that one more visualization would unlock the secret.

The Power of Observation

This obsession with comprehensive data reminds me of my friend Paul G. Paul’s job title is technically ‘Digital Experience Designer,’ but what he really does is design virtual backgrounds for video calls. He works for a huge company where you’d think they’d A/B test every pixel. But Paul’s greatest discovery came from simple observation. He noticed that executives who used backgrounds with a subtle, asymmetrical light source-like a window off to one side-were perceived as more trustworthy in meetings. It wasn’t a huge effect, but it was consistent. He started collecting anecdotal evidence. ‘How did that call go?’ he’d ask. The feedback was qualitative, human. People felt the calls were ‘better,’ the person ‘more engaging.’ He eventually ran a small, isolated test and found that these asymmetrical backgrounds received 47% more positive, unsolicited comments than the perfectly symmetrical, corporate-branded ones.

He found a truth.

No dashboard would have ever told him that. A dashboard would have tracked ‘background selection rates’ or ‘time spent with camera on.’ It would have given the company a number, but it would have completely missed the point. Paul found an insight by looking for a human reaction, not a data point. The company now ships 7 new asymmetrical backgrounds with their software.

Data as a Starting Point, Not an End

Of course, it’s foolish to abandon measurement. I’m not advocating for corporate anarchy where we all make decisions based on gut feelings and interesting anecdotes about lighting. That’s just another form of magical thinking. Data is a powerful tool. The problem is, we treat it like a destination. We present the numbers as the conclusion, when they should be the starting point of a difficult conversation.

We build dashboards to answer ‘What happened?’ but the only question that actually generates value is ‘Why?’. And a ‘why’ question can’t be answered by a chart. It requires context, conversation, and a willingness to be wrong. It requires us to turn away from the screen and talk to the people the data represents. It requires doing the hard, messy, unscalable work of thinking. Instead, we ask for another dashboard. Another filter. Another drill-down. We keep asking the machine for an answer it cannot possibly provide, because the answer isn’t in the data. It’s in us.

My mistake with that $77,777 dashboard wasn’t a technical one. The data was accurate. The queries were optimized. The failure was one of imagination. I fetishized the data, believing that if I could just show my manager everything, the right decision would become self-evident. But that’s not how insight works. Insight is subtractive. It’s about finding the one or two things that matter in a sea of noise.

It’s about what you choose to ignore. We don’t need more data. We need a better filter for reality.

The Question That Matters

So the next time you’re in that meeting, and the slide with seventeen charts comes up, and you feel that familiar wave of silent confusion wash over the room, resist the urge to nod along. Don’t ask for another metric. Ask a simple, human question. Ask what it means. Ask who it helps. Ask the one question the dashboard can’t answer: ‘Why should any of us care?’