Building Trust in Data Teams

Great data science work is not only about models. It is also about trust.

When teams trust each other, discussions shift from defensiveness to problem solving. Over the years, I have seen three practices consistently improve trust:

1. Clarify assumptions before analysis starts.
2. Share interim findings early, not just polished final decks.
3. Tie recommendations to decisions, owners, and measurable outcomes.

These small habits reduce rework and improve the odds that insights are actually used.