Using Data for Good

Data answers questions we didn’t know we had. Qualitative and anecdotal requirements gathering is essential, but it can’t tell the whole story.


On a project to replace a legacy system, I discovered that our requirements workshops had missed a crucial insight: no one had entered or updated data in that system for years.

That single insight completely reframed the work. The real MVP wasn’t about creating or editing data; it was about reading, organizing, and surfacing what already existed.

This is why analytics matter, whether you’re building internal tools, B2B products, or customer-facing systems. Data doesn’t replace user input, but it grounds decisions in reality and prevents teams from overbuilding solutions to problems that don’t actually exist.

In an AI-enhanced world, this matters even more. AI systems are only as good as the data (and assumptions) behind them. So the real question isn’t just what are your users saying, but what is their behavior quietly telling you?