Why Do We Say We’re Data-Driven When We’re Not?

Let’s get this out of the way first. I know the phrase “data-driven” is going to set some of you off. What does it even mean? Shouldn’t we say “data-informed” instead? Or maybe “evidence-based?” I get it. Please don’t let it be a distraction.  

I’ve chosen to use this phrase here because I see it as the common language. When companies say they’re data-driven, it tends to imply that they’ve invested in data capabilities and they expect that data will influence how decisions get made. It’s meant as a good thing. What I want to explore here is whether there’s any real action to back it up.

I’m an optimist, an idealist. I’ve read and believed various maturity models that describe how a data team can grow its influence within a company, increasing its impact as the partnership with business leaders strengthens. I’ve felt that I’ve experienced this in the places where I’ve worked, and I’ve helped shape its progression.

But I’ve come to realize that my beliefs are unusual. Over the years, as I’ve spoken and written about the connection between the data team and the rest of the business, I’ve noticed that very few other people share my optimism. Occasionally I’ll hear from folks who say, “I can’t use your advice. That’s not what my experience looks like at all. I doubt that my business leaders actually believe that data is important.”

I chalked it up to the fact that I work in big tech, where data does play a critical role. Even before I took a job in big tech, I worked in companies where I felt that I was experiencing forward momentum. The data/business connection seemed like it was improving. But lately I’ve been wondering what my peers see in their own organizations. Do they believe that their leaders truly value data? If not, what’s getting in the way?

So I ran a poll on LinkedIn to find out.

I asked, “If your company says it values data but doesn’t act like it, what’s the real reason?” The top response, by a long shot, was “There’s no urgency or accountability.” That response took 56% of the vote. “Leaders lack data fluency” came in a distant second at 22%. Almost no one blamed it on trust issues or said it was merely performative.

It is what it is, but it doesn’t sit well with me. It highlights a weird tension that could (to be a bit dramatic) undermine the entire profession of data work. Here’s how it goes: Companies fund data teams. Executives approve the hiring of analysts, engineers, scientists, and even Chief Data Officers. They allocate a substantial budget for infrastructure and tools to collect, manage, and explore data. These are signals of endorsement. This is real investment. And yet, despite all of it, people are telling me there’s no urgency or accountability when it comes to actually using data to make decisions. That seems broken.

The data team can only take our work so far. We define problems, collect data, develop insights, and deliver recommendations. But at some point, there’s a handoff to the business. I would say that’s often where the ball gets dropped. There’s no real action taken. What we provide is just “good to know.” When there’s inertia or lack of urgency, our deliverables often end up in the circular file.

Do our experiences vary by type of company? It’s possible. 

A reader of mine pointed out that companies with physical products and tight margins may have a stronger culture of accountability, where data has to play a central role in decision-making. He named Amazon and DoorDash as examples. But my poll told a more complicated story. Some of the respondents who chose “no urgency or accountability” work in big tech, too.

So maybe the problem isn’t confined to certain industries. Maybe it’s us.

Data folks have our share of imperfections. We’re rewarded for our attention to detail, and yet that same instinct can become a liability. If we fail to communicate our findings clearly, our message will fall flat. If we’re disconnected from business priorities, our insights might not actually address problems that matter. If we bury the lede, or over-index on insignificant details, or wallow in empty rabbit holes, we shouldn’t be surprised when our work gets ignored.

Nobody’s perfect. But if our leaders fail to treat data with any urgency, we can’t pretend we had nothing to do with it.

What can we do, then? Here are a few ideas to help close the gap.

1. Invest in communication skills. Often what holds data folks back is how we communicate. Clear writing, confident storytelling, and as much customer empathy as we can muster - these things matter just as much as our technical depth.
2. Advocate for quantitative business goals. When a company’s highest-level goals are set in measurable terms, it creates a natural incentive to define metrics, inspect progress, and use data. Even if you don’t set those goals yourself, it can be helpful to share your perspective.
3. Build a culture of experimentation. Experiments force specificity and structure. You’ve got to have a hypothesis, a success metric, and a decision. When more people are empowered to run tests, they will engage with data along the way.
4. Regularly inspect how data is being used. Ask what decisions were made, what actions were taken, and record the results somewhere visible. It’s totally possible. Here’s an article where I describe how to do it.

“Thanks for all the tips, June. I’m sure that will help (sarcasm).” So where is this all headed? An exercise in futility? Are you ready to tell me to stop looking directly into the sun?

I realize that not everyone has the power to change company culture or fix the things that are broken. But I do believe that small intentional changes will add up to something meaningful.

I remain optimistic. Getting clarity on the ironies and imperfections of our profession doesn’t make me want to give up. In fact it motivates me to keep learning and writing. The more we understand the gap, the better chance we have at closing it.

P.S. I’m also publishing on Substack: measurecraft.substack.com