- Data Analytics
Companies in the Consumer-Packaged Goods Industry are faced with a chronic dilemma: efficiency vs. agility. Companies must find the balance between scale, which creates cost-saving opportunities, and flexibility, which often incurs incremental costs. The main questions addressed in this capstone pertain to manufacturing and logistics decisions. Simply put, how much should the company produce, when and how, and therefore how much inventory should they hold? Following extensive cost structure analysis and mapping of the company’s supply chain network, a comprehensive Mixed Integer Linear Programming model was created. The model’s objective function is cost minimization, which it must attempt considering “current-state” inputs as well as multiple operational constraints. The results suggest that a hybrid production planning strategy between “level-production” and “demand-chase” is preferred, and can generate significant cost savings across the supply chain. In summary, this strategy can help companies enhance their efficiency and reduce costs when attempting to optimize total end-to-end supply chain costs, instead of using department-based budget management.