Data quality is everyone's responsibility? Then no one really cares.

If data quality is everyone's job, it's no one's priority.

When a business misses its revenue targets or botches a product launch, the root cause is often easy to spot: unclear goals, flawed strategy, or poor execution. But when data goes wrong—when reports are unreliable, customer insights are murky, or machine-learning models misfire—the culprit is usually harder to pin down. Everyone was supposed to care about data quality, but no one really did.

This is the hidden cost of "data quality is everyone's responsibility"—a mantra that sounds wise but often means data is no one's priority in day-to-day business. When employees are busy tackling urgent tasks—closing deals, shipping products, fixing bugs—they don't prioritize data quality. After all, data quality issues rarely explode in real time. Like technical debt, they erode progress slowly, invisibly, until major initiatives stall, and the company is left wondering why its data-driven transformation never took off.

Some businesses respond by pointing to their Chief Data Officer (CDO), expecting one powerful executive to fix the company's data problems. But this approach is only part of the solution. Data is created, used, and maintained everywhere across the business. A single executive, no matter how capable, can't overhaul a company's data culture from the top down. The real work of data integrity happens on the ground, within the teams that generate and use data daily.

The real solution is to treat data like other critical business assets—finances, customer relationships, or brand reputation—and make senior leaders directly accountable for the data produced in their domains. Just as the CFO ensures accurate financial reporting and the head of sales owns customer satisfaction, department heads must be responsible for the quality, accessibility, and usability of their data.

Their performance evaluations should reflect it. Data health metrics—like data accuracy, completeness, and cross-functional usability—should be tracked just as rigorously as sales targets or cost controls. When senior leaders know that part of their bonuses, promotions, and reputations hinge on clean, useful data, data responsibility moves from being a side project to core business work.

Real progress begins when we stop treating data quality as a collective aspiration and start treating it as what it truly is: a core business function that demands clear ownership. When leaders stake their reputations on it, clean and reliable data becomes not just a technical requirement, but a fundamental measure of business success.