On the performance of binomial and beta-binomial models of demand forecasting for multiple slow-moving inventory items

On the performance of binomial and beta-binomial models of demand forecasting for multiple slow-moving inventory items

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Article ID: iaor2009802
Country: United Kingdom
Volume: 35
Issue: 3
Start Page Number: 893
End Page Number: 905
Publication Date: Mar 2008
Journal: Computers and Operations Research
Authors: ,
Keywords: forecasting: applications
Abstract:

The paper deals with the lead-time demand forecasting for inventory management of multiple slow-moving items in the case when the available demand history is very short. Two stochastic models of demand are compared: (i) the first based on the ‘population-averaged’ binomial distribution of requests (the traditional approach); and (ii) the second based on the beta-binomial probability distribution that assumes that the demand probabilities for the inventory items follow the beta distribution, and employs the Bayesian framework to forecast the lead-time demand (longitudinal statistical approach). The conducted simulation study shows that using the latter model leads to the significant decrease of the holding cost and higher inventory system reliability. Besides, as follows from the simulation results, the beta-binomial demand model is especially useful when the demand probabilities are low and have the U-shaped distribution.

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