They Requested It. I Built It. Nobody Ever Used It.

Data scientists often build models that never get adopted, and the reasons usually come down to three factors: lack of explainability, slow delivery, and poor integration into existing workflows. In healthcare especially, clinicians distrust black-box models they can't understand. The fix involves creating clear model briefs in business terms, shipping v1 fast rather than chasing perfection, and embedding predictions directly into tools stakeholders already use (like Epic EHR) rather than adding friction to their workflow.