Abstract

http://ssrn.com/abstract=2130708
 
 

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The Sum and Its Parts: Judgmental Hierarchical Forecasting


Mirko Kremer


Pennsylvania State University

Enno Siemsen


University of Minnesota - Twin Cities - Carlson School of Management

Douglas J. Thomas


Pennsylvania State University - Department of Supply Chain & Information Systems

August 16, 2012


Abstract:     
Firms require demand forecasts at different levels of aggregation to support a variety of resource allocation decisions. For example, a retailer needs store-level forecasts for a particular item to manage inventory at the store but also requires a regionally-aggregated forecast for managing inventory at a distribution center. In generating an aggregate forecast, a firm can choose to make the forecast directly based on the aggregated data or indirectly by summing lower-level forecasts (i.e., bottom-up). Our study investigates the relative performance of such hierarchical forecasting processes through a behavioral lens. We identify two judgment biases that affect the relative performance of direct and indirect forecasting approaches: a propensity for random judgment errors, and a failure to benefit from the informational value that is embedded in the correlation structure between lower-level demands. Based on these biases we characterize demand environments where one hierarchical process results in more accurate forecasts than the other. Further, using field data, we demonstrate how to estimate the relevant correlation structure of lower-level demands.

Number of Pages in PDF File: 33

Keywords: forecasting process, exponential smoothing, covariation detection, behavioral operations, sales and operations planning


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Date posted: August 17, 2012 ; Last revised: March 24, 2015

Suggested Citation

Kremer, Mirko and Siemsen, Enno and Thomas, Douglas J., The Sum and Its Parts: Judgmental Hierarchical Forecasting (August 16, 2012). Available at SSRN: http://ssrn.com/abstract=2130708 or http://dx.doi.org/10.2139/ssrn.2130708

Contact Information

Mirko Kremer
Pennsylvania State University ( email )
University Park
State College, PA 16802
United States
Enno Siemsen (Contact Author)
University of Minnesota - Twin Cities - Carlson School of Management ( email )
321 19th Ave South
Minneapolis, MN 55455
United States
Douglas J. Thomas
Pennsylvania State University - Department of Supply Chain & Information Systems ( email )
Dept. of Supply Chain & Information Systems
University Park, PA 16802-3306
United States
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