The Sum and Its Parts: Judgmental Hierarchical Forecasting
| Autor: | Mirko Kremer, Enno Siemsen, Douglas J. Thomas |
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| Rok vydání: | 2016 |
| Předmět: |
Distribution center
Structure (mathematical logic) Computer science Process (engineering) Strategy and Management 05 social sciences Aggregate (data warehouse) Management Science and Operations Research Variety (cybernetics) ComputingMilieux_GENERAL 0502 economics and business Value (economics) Econometrics Resource allocation 050207 economics 050203 business & management |
| Zdroj: | Management Science. 62:2745-2764 |
| ISSN: | 1526-5501 0025-1909 |
| DOI: | 10.1287/mnsc.2015.2259 |
| Popis: | 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 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. This paper was accepted by Martin Lariviere, operations management. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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