Adjusting inventories based on demand prediction using dynamic inventory balancing model

This study examined inventory adjustment based on demand prediction in real case study environment. In this case study, action research method was applied on case, in which the manufacturer faced fluctuating demand, averaging to have four different phases in a year. Demand peaks follow the valleys in yearly basis, but the location of the peaks and valleys is not exactly known beforehand, which makes the demand and supply availability prediction and adjustment hard task to achieve in this manufacturing network. The research data has been collected from actual case, in which the case company applied the ideology of dynamic inventory management model on their purchasing operations. By using costs calculations, researcher has been able to show that the company saved in average of 20 000, in 9 moths time period, just in interests. This case is considered a good example of practicality of applying simple ideologies in practice on inventory management to achieve good impact with out applying too much resource on management level. Using demand prediction model presented in this paper the case company was able to synchronize inventories to the demand and also they were able to give their suppliers more time to prepare on future demand rises, which then cave them better service level in the situation of demand curve going up. The model is based on an idea of using both long and short time period history data to anticipate the future demand and its variations.