Does Better Forecast Accuracy Mean Better Business Performance?

Accuracy is an input to performance

A lower forecasting error is useful, but it does not tell the whole operating story. The business still needs to decide when to order, how much to buy and which service promise to support. Lead times, minimum quantities, capacity and allocation rules can prevent a better forecast from changing the outcome.

MIT’s Digital Supply Chain Transformation Lab highlights research distinguishing forecast accuracy from forecast value in inventory decisions. That overview supports asking a broader question; it does not supply a universal percentage improvement or prove the result for a different business. ^[2]

Compare forecasts fairly

Forecasting: Principles and Practice explains why model performance should be evaluated on genuinely unseen observations rather than fitted-data errors. The evaluation horizon should reflect the forecasting task. ^[1]

For an SCP assessment, retain the forecast that was available when the decision was made. Compare methods using the same products, horizons and information cut-off. A revised forecast created after demand becomes known is not a fair comparator. Separate regular sellers, intermittent items and new products where their decision needs differ.

Connect the forecast to the policy

Illustrative example, not a measured result: two forecasts produce different demand estimates, but both lead to the same order because the supplier only accepts full-pallet quantities. The accuracy ranking may change while the purchase decision does not. Elsewhere, a small bias on a critical item could repeatedly trigger shortages.

SCP would test each forecast through the same replenishment policy first, then assess whether the policy itself should change. Otherwise, an improvement attributed to the forecast may actually come from a different stock rule, lead-time assumption or service target.

Keep a balanced scorecard

Agree a small set of measures that connect prediction to operations.

• Forecast performance: relevant error measure, directional bias and decision horizon.
• Service: availability or fulfilment against an agreed, consistent definition.
• Stock: inventory, ageing and write-offs, with product-mix changes visible.
• Cost: carrying cost, lost-sales assumptions and premium freight, avoiding double counting.
• Usability: planner overrides, reasons, workload and action completion.

A practical next step

Choose a defined item group and compare the current approach with a simple baseline and a candidate method. Hold the operating assumptions constant, document uncertainties and assess results over a period that reflects lead times and demand patterns.

An Inventory and Service discovery workshop can agree the decision horizon, baseline and performance measures. The objective is a better operating decision, rather than an isolated improvement to an accuracy dashboard.

Explore the industries and services

• Retail and consumer goods priorities →
• Inventory modelling techniques →
• Existing insight: shortages and excess stock →