Simulation versus analytical modelling for supply chain dynamics analysis

Simulation has become an important information technology tool for analysis and improvement of entire supply chain operation. One of the most important supply chain operation stability measures is a bullwhip effect value. The bullwhip effect can lead to holding an excessive inventory, insufficient capacities and high transportation costs. It is important to investigate the magnitude of this effect by quantifying it. There are a variety of methods, which address bullwhip effect modelling. Nevertheless, there is a lack of methods for its numerical evaluation in a supply chain. This paper proposes statistics and probability theory based analytical methods which allow quantification of the bullwhip effect value in a supply chain that operates under uncertain market demand. Simulation technique is used to validate results obtained from the analytical model. Based on validation results, the logic of the analytical model is examined, and some specifications of the analytical model are analysed and described