Abstract
Usually in stock control studies demand data are considered as an input to the model, without explicitly considering that they are the results of a demand forecasting system. Stock control system is examined independently of the demand forecasting system, and it is assumed that demand data (or forecast errors) have been properly modelled. However, the interactions that may exist between demand forecasting methods and stock control systems, in terms of their effects on global system performances, are not considered. In the paper an approach for evaluating these interactions, based on a comparative simulation test of global system costs using historical data, is presented. The approach is explained through a real case: the replenishment, from different suppliers, of a central depot of tinned food, which supplies more than 700 items to warehouses at the lower echelon. Results of the simulation study show that traditional measures of forecast errors cannot be taken as sole indicators for the choice among different demand forecasting methods. These methods, on the contrary, have to be evaluated on the basis of total costs and service level of the global inventory control system.
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