Int. J. Production Economics 108 (2007) 302–313 Global sensitivity analysis in inventory management E. Borgonovo à , L. Peccati IMQ, Bocconi University, Viale Isonzo 25, 20135 Milano, Italy Available online 18 January 2007 Abstract This paper deals with the sensitivity analysis (SA) of inventory management models when uncertainty in the input parameters is given full consideration. We make use of Sobol’ function and variance decomposition method for determining the most influential parameters on the model output. We first illustrate the method by means of an analytical example. We provide the expression of the global importance of demand, holding costs, order costs of the Harris economic order quantity (EOQ) formula. We then present the global SA of the inventory management model developed by Luciano and Peccati [1999. Capital structure and inventory management: the temporary sale problem. International Journal of Production Economics 59, 169–178] for the economic order quantity estimation in the context of the temporary sale problem. We show that by performing global SA in parallel to the modeling process an analyst derives insights not only on the EOQ structure when its expression is not analytically known, but also on the relevance of modeling choices, as the inclusion of financing policies and special orders. r 2007 Elsevier B.V. All rights reserved. Keywords: Inventory management; Parameter uncertainty; Global sensitivity analysis; EOQ 1. Introduction Uncertainty in inventory policy making stems from a variety of factors. Just as a simple example, consider a firm that uses the Harris economic order quantity (EOQ) formula as a support to its inventory policies (Erlenkotter, 1990; Harris, 1915; Piasecki, 2001). In order to come to a final decision on the EOQ, the firm must estimate demand, unit order costs and holding costs. Demand is seldom steady, and its value cannot be determined with certainty in most of the cases (Alstrom, 2001; Ray and Chaudhuri, 1997; Grubbstro˜m, 1996; Teng and Yang, 2004; Matheus and Gelders, 2000; Boylan and Johnston, 1996). Costs can be a further source of uncertainty (see Piasecki, 2001): on the one hand the criteria of cost classification are not always be sharply set and, on the other hand, even once the criteria are set, variability characterizes the costs themselves (Piasecki, 2001). Hence, rarely one can predict the behavior of an inventory system with the inputs fixed at a certain value; more likely, the decision-maker will be able to assign parameters within ranges determined by the analysis (Piasecki, 2001; Bogataj, 1998; Bogataj and Hvalica, 2003). To cope with the corresponding uncertainty in model predictions, usually a sensitivity analysis (SA) exercise is performed. The more direct SA scheme is the testing of the change in model output that follows a change in the parameters when they are ARTICLE IN PRESS www.elsevier.com/locate/ijpe 0925-5273/$ - see front matter r 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.ijpe.2006.12.027 à Corresponding author. E-mail address: emanuele.borgonovo@uni-bocconi.it (E. Borgonovo).