POLARIS

Planning · Problem brief

Forecast Accuracy Is Low

DIRECT ANSWEREvaluate forecasts at the product, location and horizon where a decision is made. Compare against simple seasonal and naive baselines, separate systematic bias from random error, and inspect promotions, launches, stockouts and overrides. Validate one feature, hierarchy or override rule on a later untouched period before changing planning policy.

Updated September 28, 2026Diagnosis · Evidence · First proof

Start with these five checks.

Ask for only what can change the answer.

Test one reversible move.

Freeze an older training period and an untouched later evaluation period. Change one element—event feature, hierarchy rule or override policy—and compare error, bias and downstream inventory decisions by segment. Reject it if average accuracy rises while priority items, service or working capital worsen.

A decision your team can use.

Common questions.

Which forecast metric is best?

Use metrics suited to scale and intermittency, and always connect them to the operational decision.

Why compare with a naive baseline?

A complex method has not added value if it cannot beat a simple recent or seasonal forecast.

How do stockouts affect actual demand?

Observed sales are censored when inventory is unavailable; lost sales and substitutions need explicit treatment.

Authoritative references.

  1. ASCM, SCOR Digital Standard
  2. U.S. Census Bureau, Manufacturing and Trade Inventories and Sales

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