ARIMA identification and diagnostics

The central test for arima identification and diagnostics is whether it generalizes across time and operating conditions. Use rolling evaluation and compare against a simple, defensible baseline.

Practitioner lens

Operational monitoring for arima identification and diagnostics should track residual patterns, input drift, interval coverage and performance by lifecycle state—not only a global score.

First experiment

Propagate predictive distributions into the downstream inventory or capacity decision where possible.

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