You’ve seen the meme. It usually features a disappointed character or a snarky caption aimed at someone who just made a decision based on "vibes" rather than a spreadsheet. That wasn't very data-driven of you has become the go-to insult in corporate Slack channels and LinkedIn comment sections. It’s funny because it taps into our collective obsession with metrics. We live in an era where if you can’t graph it, it didn't happen.
But here’s the kicker. Some of the most successful people in the world are starting to push back. They’re realizing that hiding behind a dashboard is sometimes just a fancy way of being scared to make a call.
The phrase itself started as a bit of internet snark, a play on the "That wasn't very cash money of you" meme format. It quickly migrated from Reddit and Twitter into the actual lexicon of tech hubs like San Francisco and Austin. Now, it’s used to police behavior in meetings. If you suggest a creative direction that doesn't have an A/B test attached to it, someone inevitably chimes in with that tired line. It’s meant to be a joke, but it carries a heavy undercurrent of "don't trust yourself, trust the numbers."
The Tyranny of the Dashboard
We’ve reached a point of peak data. Companies are drowning in it.
Every click, hover, and scroll is tracked. We have Heatmaps. We have churn rates. We have "North Star" metrics that everyone is supposed to follow like a cult. But honestly? Most of this data is noise. According to a report by Seagate and IDC, about 68% of data available to enterprises goes completely unused. It just sits there. We’re collecting it because we think we’re supposed to, not because we know what to do with it.
When someone tells you that wasn't very data-driven of you, they are often clinging to the safety of a chart to avoid the risk of being wrong. If a data-driven decision fails, you can blame the data. If a gut-feeling decision fails, you have to blame yourself. That’s a scary prospect for a middle manager trying to survive a round of layoffs.
Take the world of streaming. Netflix is famously data-driven. They knew House of Cards would be a hit because they looked at the overlap of fans who liked the original British version, fans of David Fincher, and fans of Kevin Spacey. It was a mathematical certainty. But then you have a show like Squid Game. No algorithm on earth would have predicted that a violent, Korean-language social commentary about debt would become the biggest show in the history of the platform. That was a human bet. It was inherently "not data-driven" in its inception.
When the Numbers Lie
Data is only as good as the questions we ask. If you ask a biased question, you get a biased answer.
There’s this concept called "Survivorship Bias." During WWII, the military looked at planes returning from battle with bullet holes in the wings and tail. The "data-driven" move was to add armor to those spots. But Abraham Wald, a mathematician, pointed out that this was actually a terrible idea. The planes they were looking at were the ones that made it back. The armor needed to go where the holes weren't—the engines—because the planes hit there were the ones that crashed.
In modern business, we do the same thing. We look at our existing customers and optimize for them, completely ignoring the millions of people who aren't using our product because the "data" doesn't show them.
Relying solely on metrics can also lead to "Local Maxima." This is a fancy way of saying you’ve optimized a tiny part of your business so well that you’ve missed the fact that the whole mountain you’re standing on is actually a molehill. You can A/B test the color of a "Buy Now" button until it's the perfect shade of hex-code orange, but if the product itself is something nobody wants, you’re just rearranging deck chairs on the Titanic.
The Intuition Gap
Let's talk about Steve Jobs. People love to cite him as the ultimate anti-data guy. He famously said, "A lot of times, people don't know what they want until you show it to them."
He wasn't saying data is useless. He was saying that data is backward-looking. Data tells you what happened yesterday. It cannot tell you what will happen tomorrow in a world that doesn't exist yet. If Apple had been purely data-driven in 2006, the iPhone would have had a physical keyboard because that’s what the "data" from BlackBerry and Palm Treo users suggested they wanted.
Intuition isn't magic. It isn't some mystical force. It's actually a very high-level form of pattern recognition. When an expert makes a "gut" decision, their brain is processing thousands of previous experiences, subtle cues, and environmental factors that haven't been quantified yet.
Gary Klein, a psychologist who wrote Sources of Power, studied how fire chiefs and ICU nurses make split-second decisions. They don't sit down with a spreadsheet. They recognize a pattern—the way the smoke is curling, the specific shade of a patient's skin—and they act. If you told a fire chief "that wasn't very data-driven of you" while he was pulling his crew out of a building seconds before it collapsed, he’d think you were insane. His "gut" was just data that hadn't been written down yet.
The Social Cost of Being "Data-Driven"
There is a weird social pressure to perform "data-drivenness."
It’s a performance. We use terms like "KPIs," "OKRs," and "LTV to CAC ratios" to signal that we are serious, logical people. It’s a way of sounding smart without actually having to have an original thought.
This culture creates a "Permission to Act" barrier. In many companies, you aren't allowed to try something new unless you can prove it will work beforehand. But innovation is, by definition, the process of doing something that hasn't been proven yet. By demanding that every move be data-driven, we are effectively banning innovation.
We end up with "beige" products. Everything starts to look and feel the same because everyone is looking at the same data sets and reaching the same logical conclusions. Look at modern cars. They all look like slightly different versions of the same wind-tunnel-optimized egg. Look at movie posters. They’re all "Orange and Teal" because some data point somewhere said that’s what catches the eye.
When we mock people by saying that wasn't very data-driven of you, we are reinforcing a culture of mediocrity. We are telling people to stay in the lines.
How to Actually Use Data Without Losing Your Soul
So, should we throw away the spreadsheets? Of course not. That would be stupid.
The goal is "Data-Informed," not "Data-Driven."
Data should be a flashlight, not a leash. You use it to see where you are, but you still decide where you're going.
1. Identify the "Un-trackables"
Some things are vital but impossible to measure accurately. Brand sentiment, employee morale, and long-term trust are notoriously hard to put into a cell in Excel. If you only focus on what you can measure, you will eventually destroy the things you can't.
2. The "Smell Test"
If the data says one thing, but your common sense says another, don't automatically trust the data. Errors happen. Tracking scripts break. Bots inflate traffic. If a report says your new marketing campaign is a 1,000% success but the phones aren't ringing, the data is wrong. Period.
3. Build "Safe to Fail" Experiments
Instead of requiring months of data before starting a project, run small, cheap experiments where the cost of failure is low. This is how you generate new data. If you only look at existing data, you’re just recycling the past.
4. Qualitative over Quantitative
Talk to five real human beings. It’s amazing how many "data-driven" experts never actually speak to their customers. A 20-minute conversation will often reveal insights that a thousand survey responses will miss. You get the "why" behind the "what."
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The Pivot Back to Human Judgment
We are starting to see a shift. Venture capitalists are putting more weight on "founder-market fit"—essentially, does this person have the intuition and lived experience to win?—rather than just looking at their early traction numbers.
Designers are reclaiming their right to make things beautiful simply because beauty has value, even if it doesn't immediately increase the conversion rate by 0.2%.
The next time someone hits you with that wasn't very data-driven of you, don't get defensive. Smile. Tell them that you're operating on a different set of inputs. Tell them that you’re looking at the holes in the planes that didn't come back.
True leadership is about making decisions with incomplete information. If you have 100% of the data, the decision makes itself—and if the decision makes itself, why do they need you?
Practical Steps for the Recovering Data-Addict
If you’ve realized you’re a bit too obsessed with the numbers, here is how you start to rebalance:
- Set a "Gut Budget": Allow yourself or your team to spend 10% of your time or budget on projects that have zero data to back them up. Purely experimental, purely "I have a feeling about this."
- Challenge the Metric: Every time someone presents a "key metric," ask: "How could this number be true while the business is actually failing?" It forces people to look for the flaws in their own logic.
- Write it Down: When you make a gut decision, write down exactly why you’re doing it. What patterns are you seeing? What are you sensing? This turns "intuition" into a formal record you can learn from later.
- Kill the "Data-Driven" Catchphrase: Stop using it as a weapon. Start asking, "What is the data missing here?" instead of "What does the data say?"
The future belongs to the people who can read the map but aren't afraid to go off-road when they see a better path. Stop being a slave to the dashboard. Start being the person who decides where the dashboard should be pointing in the first place.
Real expertise is knowing when to follow the numbers and when to tell them to get out of the way. It’s okay to be "not data-driven" sometimes. In fact, it might be the only way to actually get ahead.