Supply Chain Transformation with Advanced Analytics

This document is a case study detailing the transformation of a global food and beverage leader's supply chain through advanced analytics. The objective was to establish a comprehensive data foundation to enhance operational visibility and intelligence, thereby optimizing warehousing, distribution, and demand forecasting while promoting sustainability. The client partnered with Tiger Analytics to implement various solutions, including machine learning for planogram compliance and crop monitoring, as well as computer vision for quality assurance. The study outlines the development of a unified data model and an Intelligent Warehouse Management System (IWMS) dashboard, which enabled real-time visibility and improved decision-making. The results included significant cost savings of approximately $17 million annually, enhanced inventory management, and improved customer satisfaction through predictive risk insights. The document emphasizes the importance of data-driven decision-making in achieving operational efficiency and sustainability goals.