Event Details

Anna Sroginis (PhD student) will present a seminar to the Management Science Department

Abstract: Despite the continuous improvements in statistical forecasting, human judgment remains essential in business forecasting and demand planning. Typically, forecasters do not solely rely on statistical forecasts, which are obtained from various Forecasting Support Systems (FSS); they also adjust forecasts according to their knowledge, experience and information that is not available to the statistical models. However, we do not have an adequate understanding of the adjustment mechanisms, particularly how people use additional information (e.g. special events, promotions, strikes, holidays etc.) and under which conditions this is beneficial. To investigate this, we conduct experiments that simulate atypical supply chain forecasting process that additionally provides qualitative and model-based information about past and future promotional periods for retail products.

Using the laboratory experiment, we find that people (1) tend to focus on several anchors: a last promotional uplift, current statistical forecast and contextual statements for the forecasting period; (2) ignore given average promotional uplift and domain knowledge about the past promotions. These results highlight the need for a more fundamental understanding of processes behind human adjustments and the reasons for them in order to guide forecasters in their tasks and to increase forecast accuracy.