What usually helps is shifting attention away from just offline scores to how the model behaves in slices and over time. Monitoring input distributions, confidence shifts, and business outcomes by segment made the degradation visible much earlier. Once we framed it as a data and system evolution problem—not a sudden model failure—it became easier to explain, fix, and prevent the same issue from repeating.