A Vendor Managed Inventory Approach for Managing the Supply Network: the EssilorLuxottica Case

The thesis will give an overview of the integration of Supply Chain Manage- ment, predictive analytics, and retail, with the help of Oracle Retail Predictive Application Server (RPAS) technology. The dissertation reviews how this technology will influence demand forecasting, inventory management, and price optimization by showing how predictive tech- nologies enable retailers to make insightful decisions in increasingly volatile markets with fluctuating consumer behavior. It identifies the embedding of pre- dictive analytics within retail Supply Chain Management as a game-changer in improving supply chain operations, cost reduction, and increasing forecast accuracy while discussing a case study for EssilorLuxottica. The objective of the project, in fact, is to analyze and understand how the pro- gram utilized by the company’s VMI team operates and how it impacts decision- making in planning and forecasting with a specific testimony. The thesis concludes that, in the current global retailing environment, the con- vergence of Predictive Analytics with Supply Chain Management strategies can help retailers sustain their competitiveness. Based on this, the research focuses on fine-tuning tools such as RPAS and dynamic reports to identify future im- provements that will enable operational efficiency, customer experience, and long-term profitability.