Data science tip: a drift alert needs an owner

Separate different kinds of change

Input distributions can change without an immediate performance loss, and performance can decline without an obvious shift in a simple summary. Monitor the data pipeline, prediction behaviour and outcomes where outcome labels become available. Account for the delay in observing those labels.

Write the response before the alert

Specify who investigates, what evidence they review and when the system should fall back to a safer process. Compare against a meaningful baseline, annotate known changes and test the alerting path. An unattended chart is not an operational control.

Sources & further reading

• NIST — AI Risk Management Framework

Sources checked 20 September 2026. Implementation commentary reflects a practical review perspective; source material may change.