Data Teams Are Not Service Teams

Over time, a lot of data teams drift into a pattern that’s hard to break out of. They become ticket takers, constantly responding to requests, pulling data for one-off questions, fixing dashboards, and explaining why numbers don’t match. It feels helpful at first. But eventually, the work starts to pile up, context starts to disappear, and the team is mostly reacting instead of building anything meaningful. The service model becomes the default, and that’s a …

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Structuring Data and Analytics Teams for Impact

As more companies invest heavily in data as they grow, the question of how to structure the data and analytics function becomes increasingly important. It is not just about reporting lines or team charters. Structure influences how effectively data is used, how talent is retained, and how aligned the team is to business priorities. In my experience, I have seen a range of models in action: centralized teams, embedded analysts, and hub-and-spoke hybrids. I have …

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