Impact of Bias Magnification on Supply Chain Costs: The Mitigating Role of Forecast Sharing

The impact of forecast error magnification on supply chain cost has been well documented. Unlike past studies that measure forecast error in terms of forecast standard deviation, our study extends research to consider the impact of forecast bias, and the complex interaction between these variables. Simulating a two‐stage supply chain using realistic cost data we test the impact of bias magnification comparing two scenarios: one with forecast sharing between retailer and supplier, and one without. We then corroborate findings via survey data. Results show magnification of forecast bias to have a considerably greater impact on supply chain cost than magnification of forecast standard deviation. Particularly damaging is high bias in the presence of high forecast standard deviation. Forecast sharing is found to mitigate the impact of forecast error, however, primarily at higher levels of forecast standard deviation. At low levels of forecast standard deviation the benefits are not significant suggesting that engaging in such mitigation strategies may be less effective when there is little opportunity for improvement in accuracy. Furthermore, forecast sharing is found to be much less effective against high levels of bias. This is an important finding as managers often deliberately bias their forecasts and underscores the importance of exercising caution even with forecast sharing, particularly for forecasts that have inherently large errors. The findings provide a deeper understanding of the impact of forecast errors, suggest limitations of forecast sharing, and offer implications for research and practice alike.