The Consumer Product Goods (CPG) industry such as the bottled water business is subject to bottlenecks, due in part to both product characteristics, stochastic nature of the demand of products, and customer lead time volatility. Nevertheless, CPG companies are expected to be able to serve customers that rely on their products, even as demand can be unpredictable and erratic. In CPG companies, where the multi-stock keeping units (SKUs) and multi-period nature of manufacturing systems are taking place, finding the right balance between Make-To-Order (MTO) and Make-To-Stock (MTS) production strategy proves difficult. To ensure customers' demand is fulfilled, this capstone analyzes the current production strategy of the capstone sponsor, a bottled water company, and incorporates the dynamic market demand and customer lead time volatility to determine the best production strategy that will be capable to meet 90% fulfilment rate In this capstone, we developed a System Dynamics (SD) and Discrete Event Simulation (DES) to understand the overall drivers of supply chain and production strategy that minimizes the total relevant costs (inventory holding and change over costs) whilst producing the highest fulfilment rate. We analyzed live orders, forecast orders, economic production quantity (EPQ), safety stock (SS) of 10 key SKUs and ABC SKU segmentation of 1300 SKUs for one production plant over the last year. Scenarios of demand, forecast and lead time uncertainty were simulated to provide insights into key drivers of the model behavior and guide insights into useful production policies. Our findings demonstrate that in manufacturing systems characterized by stochastic demand and volatile lead times, understanding SKU characteristics (EPQ, SS, and Inventory levels) is critical to meet market demand with the optimal cost more so than the order patterns.