Time-series cross-validation design

A technically strong model can still mislead if validation leaks future information. This brief explores time-series cross-validation design and the checks needed for credible comparison.

Practitioner lens

Operational monitoring for time-series cross-validation design should track residual patterns, input drift, interval coverage and performance by lifecycle state—not only a global score.

First experiment

Monitor feature drift, residual structure and changing error by segment after deployment.

This is an original educational brief. It is a starting point for discussion, not a claim that one technique fits every supply chain.