On the accuracy of judgmental interventions on forecasting support systems

All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission, provided that full acknowledgement is given. Abstract Forecasting at the Stock Keeping Unit (SKU) disaggregate level in order to support operations management has proved a very difficult task. The levels of accuracy achieved have major consequences for companies at all levels in the supply chain; errors at each stage are amplified resulting in poor service and overly high inventory levels. In most companies, the size and complexity of the forecasting task necessitates the use of Forecasting Support Systems (FSS). The present study examines monthly demand data and forecasts for 44 fast moving, A-class, durable SKUs, collected from a major U.K. supplier. The company relies upon a FSS to produce baseline forecasts per SKU for each period. Final forecasts are produced at a later stage through the superimposition of judgments based on marketing intelligence gathered by the company forecasters. The benefits of the intervention are evaluated by comparing the actual sales both to system and final forecasts. The findings support the case that adjustments do improve accuracy, particularly under the condition that the adjustment is conservative, in the right direction, but does not overshoot. The question is how best to meet these conditions.