The Organizational Dysfunction series.
A project needs product data from another part of the organization. The data exists, but the definitions don't match. So the project team fixes it: just enough, just for this use case. Each fix makes perfect sense in isolation. From an organizational perspective, it's penny-wise, pound-foolish.
Most organizations can't answer a simple question: what are you actually optimizing for? With agentic AI, leaving it unanswered has consequences that are faster, bigger, and harder to reverse than anyone anticipated.
The data professionals who consistently deliver outcomes aren't the ones with the strongest technical skills. They're the ones who understand how value moves through the organization. Most data problems are adaptive challenges that organizations keep treating with technical fixes.
Someone asks: 'What data do we already have?' Within minutes, the room is problem-solving. Everyone wants to deliver. So the team works with what's available. And from that moment, the most expensive decision in the project has already been made.