This article focuses on improving supply chain management (SCM) at a poultry processing plant. The strategies applied in SCM are dependent on understanding customers’ demand, the ability to forecast accurately, and maintaining smart inventory management to achieve the full advantages of SCM. This study exploits the integration of SCM concepts with business simulation, along with exploring strategies to improve the whole operation of a chicken supply chain. Witness Horizon software is utilized to model the supply chain of Company X, and information gathered on the demand and sales of poultry (chicken) is applied and computed in the simulation. The study investigates several ordering strategies, which are based on the previous week’s demand (PWD), weighted (forward) 3-point average demand (WAFD), weighted (backward) 3-point average demand (WABD), and moving average demand (MAD). Each simulation result obtained from different ordering strategies indicates the effectiveness and potential of the proposed methodology. These strategies are successfully developed and simulated, in which the results obtained demonstrate a desirable level of inventory, and profitability can be achieved by implementing these strategies in real time. The study concludes with MAD as being a suitable forecasting method for the given scenario.

This article focuses on improving supply chain management (SCM) at a poultry processing plant. The strategies applied in SCM are dependent on understanding customers’ demand, the ability to forecast accurately, and maintaining smart inventory management to achieve the full advantages of SCM. This study exploits the integration of SCM concepts with business simulation, along with exploring strategies to improve the whole operation of a chicken supply chain. Witness Horizon software is utilized to model the supply chain of Company X, and information gathered on the demand and sales of poultry (chicken) is applied and computed in the simulation. The study investigates several ordering strategies, which are based on the previous week’s demand (PWD), weighted (forward) 3-point average demand (WAFD), weighted (backward) 3-point average demand (WABD), and moving average demand (MAD). Each simulation result obtained from different ordering strategies indicates the effectiveness and potential of the proposed methodology. These strategies are successfully developed and simulated, in which the results obtained demonstrate a desirable level of inventory, and profitability can be achieved by implementing these strategies in real time. The study concludes with MAD as being a suitable forecasting method for the given scenario.