Inventory control is crucial in supply chain management as it ensures customer satisfaction, efficient production planning, and reduced operational costs. However, inadequate budgeting of inventory expenses can have severe repercussions. The bullwhip effect, often observed in supply chain management, results in excessive inventory due to distorted information. This occurs when minor demand variations lead to exaggerated order amounts, causing a significant amplification of information as it moves upstream in the supply chain.
The paper focuses on the primary cause of the bullwhip effect, which is order batching. To illustrate this, a simplified two-echelon supply chain system is used, consisting of a single supplier and retailer with different replenishment policies. The study considers two types of inventory replenishment methods: the traditional methods (event-triggered and time-triggered ordering policies) and the statistical process control (SPC) based replenishment method.
The study demonstrates that the latter method is more effective than the traditional approach in terms of inventory variation and backlog count when the fill-rate of the previous model is set at 99%. This research offers an alternative strategy to reduce inventory costs, diverging from conventional methods such as information sharing, order batch cutting, and lead time reduction. By implementing an appropriate replenishment policy, both backorder quantity and inventory costs can be minimized.