Data-Driven Inventory Control for Reducing Waste and Promoting Environmental Innovation in Healthcare Logistics

Descripción

Pharmaceutical distribution networks face the dual challenge of maintaining service reliability while minimizing waste and costs. This study investigates the application of the Reorder Point (ROP) method to optimize inventory control across PT XYZ’s multi-branch distribution system. A quantitative approach was employed using two years of historical sales and lead time data to compute average monthly sales, safety stock, and reorder thresholds per SKU and branch. The ROP model embedded revised Days of Inventory (DOI) targets to enhance precision and responsiveness. Following implementation, excess inventory costs were eliminated (from IDR 7 billion to zero), and total inventory-related losses decreased by IDR 5 billion, despite a slight increase in lost sales due to demand volatility. These findings demonstrate the ROP model’s ability to improve inventory efficiency while contributing to Sustainable Development Goals (SDG 3 and SDG 12) by reducing pharmaceutical waste and enhancing access to medicine. The model represents a scalable eco-engineering solution aligned with environmental innovation and responsible consumption objectives.

Descripción de Zenodo, abreviada.

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