Yes / Expert knowledge elicitation lies at the core of judgmental forecasting—a domain that relies fully on the power of such knowledge and its integration into forecasting. Using experts in a demand forecasting framework, this work aims to compare the accuracy improvements and forecasting performances of three judgmental integration methods. To do this, a field study was conducted with 31 experts from four companies. The methods compared were the judgmental adjustment, the 50–50 combination, and the divide-and-conquer. Forecaster expertise, the credibility of system forecasts and the need to rectify system forecasts were also assessed, and mechanisms for performing this assessment were considered. When (a) a forecaster’s relative expertise was high, (b) the relative credibility of the system forecasts was low, and (c) the system forecasts had a strong need of correction, judgmental adjustment improved the accuracy relative to both the other integration methods and the system forecasts. Experts with higher levels of expertise showed higher adjustment frequencies. Our results suggest that judgmental adjustment promises to be valuable in the long term if adequate conditions of forecaster expertise and the credibility of system forecasts are met.

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Yes / Demand forecasting is critical to sales and operations planning (S&OP) but the effects of sales promotions can be difficult to forecast. Typically, a baseline statistical forecast is judgmentally adjusted on receipt of information from different departments. However, much of this information has either no predictive value or its value is unknown. Research into base rate discounting suggests that such information may distract forecasters from the average uplift and reduce accuracy. This was investigated in situations where forecasters could adjust the statistical forecasts for promotions via a forecasting support system (FSS). In two ecologically valid experiments forecasters were provided with the mean level of promotion uplift, a baseline statistical forecast, and quantitative and qualitative information. The forecasters were distracted from the base rate and misinterpreted the information available to them. These findings have important implications for the design of organizational S&OP processes, and for the implementation of FSSs.