"Data-driven" is a buzzword
Some years personality tests are trending. Other years they’re considered unscientific. Right now “data-driven” is the thing.
Organizations follow fashion cycles. It applies to leadership theories, project methodologies and now to decision-making. Each cycle is presented as the definitive solution. The next cycle replaces it without anyone evaluating the previous one.
“Data-driven” sounds objective. It rarely is. Which data gets collected, how it’s interpreted and which decisions it justifies is just as subjective as the judgment it was supposed to replace.
Collecting data is not the same as deciding from data
A lot of what gets called “data-driven” is really data-collecting with a decision attached afterwards. The data is gathered because somebody asked for it (often the same person who already had a preferred answer). The metric is chosen because it’s measurable, not because it’s the right one. The dashboard is built because dashboards are what data-driven organizations have.
I’ve seen it from a few different angles. In one case a team spent four months building a BI-setup for warehouse operations. Beautiful charts, sensible KPIs, daily refresh. Nobody looked at it after week two. The operations manager kept making decisions based on what the supervisors told him in the morning meeting, which is probably what he should have done all along. The dashboard existed so that the project could be marked as complete.
In another case a leadership team had monthly KPIs they reviewed religiously. The numbers were correct. The interpretation was always: “we need more of what we already do.” If the KPI went up, current strategy was working. If it went down, current strategy needed more investment. The data was real, the framing was fixed, the conclusion was predetermined.
That is not data-driven decision-making. That is decision-justified data-collection. The difference is whether the data could, in principle, change the decision. If the answer is no, the data is decoration.
Why the buzzword keeps working
The reason “data-driven” works as a label is that it borrows credibility from something that does work: actual measurement, actual analysis, actual willingness to be wrong. Real data-driven work exists. It’s just rarer than the label suggests, and it tends to be quieter. The people who actually use data to change their minds don’t usually call themselves data-driven. They just say what they found and what they changed.
The label is most useful when it’s a flag. When an organization or a leader leans hard on the term, it’s worth checking what’s behind it: which decisions were actually changed by the data, which metrics were dropped because they turned out to mislead, which dashboards were retired because nobody used them. If the answer is “we have an analytics team and a quarterly KPI review,” that’s an org chart and a calendar, not a decision culture.
This is also why digitalization projects so often deliver dashboards that nobody opens. The project was framed as data infrastructure. Whether anyone would act on the data wasn’t part of the spec. The system gets built, the bonus gets paid, the link to the dashboard gets shared in a kickoff email, and after a few weeks the link stops working because nobody noticed.
In three years the backlash will come. “Qualitative decision-making” and “experience-based leadership” will be the new buzzwords, and the same dynamic will play out under a new label, with the same projects, the same dashboards, and the same morning meetings doing the actual work.