An integrated production and inventory model to dampen upstream demand variability in the supply chain
We consider a two-echelon supply chain: a single retailer holds a finished goods inventory to meet an i.i.d. customer demand, and a single manufacturer produces the retailers replenishment orders on a make-to-order basis. In this setting the retailers order decision has a direct impact on the manufacturers production. It is a well known phenomenon that inventory control policies at the retailer level often propagate customer demand variability towards the manufacturer, sometimes even in an amplified form (known as the bullwhip effect). The manufacturer, however, prefers to smooth production, and thus he prefers a smooth order pattern from the retailer. At first sight a decrease in order variability comes at the cost of an increased variance of the retailers inventory levels, inflating the retailers safety stock requirements. However, integrating the impact of the retailers order decision on the manufacturers production leads to new insights. A smooth order pattern generates shorter and less variable (production/replenishment) lead times, introducing a compensating effect on the retailers safety stock. We show that by including the impact of the order decision on lead times, the order pattern can be smoothed to a considerable extent without increasing stock levels. This leads to a situation where both parties are better off.
inventory control queueing markov processes supply chain management