The Organization Looked Different. It Operated Exactly the Same Way.

Most data problems I’ve seen weren’t really about data. They were about accountability: who owns it, who decides, who is responsible when things go wrong.

It doesn’t matter whether the company operates in one country or seventy, whether it has 500 employees or 50,000, or whether it sells cosmetics, chemicals, shoes or engineering services. After more than 25 years working across different industries, business models and geographies, I’ve noticed the same pattern over and over again.

When organizations struggle with reporting, data quality, analytics or AI, the conversation usually starts and ends with data. “We have data issues.” But the problem rarely does. More often than not, nobody has clearly defined who owns the process, nobody has agreed who makes the decision, and nobody has established the accountability required to make that decision stick.

One thing I’ve learned over the years is that many organizations confuse Operating Models with organizational charts. An organizational chart tells you who reports to whom. An Operating Model should tell you how decisions get made, who owns the process, who owns the data, who has decision rights, how conflicts are resolved and how accountability is maintained when priorities inevitably compete.

Those are very different things. Yet many transformation initiatives spend months redesigning reporting lines while leaving decision-making structures untouched. The result is usually predictable: the organization looks different, but it operates exactly the same way.

That’s why I’ve come to believe that many so-called data problems are actually operating model problems. The symptoms show up in reports, dashboards and systems. The root cause usually sits somewhere else: ownership, accountability and decision-making.

And until those things are addressed, no amount of technology, governance frameworks or AI initiatives will solve the problem for long.