Case Study
Monday, March 03
10:15 AM - 10:45 AM
Live in Amsterdam
Less Details
This presentation explores the transformative potential of machine learning (ML) in Supply Chain Management and Operations. By analyzing various real-world use cases, we will demonstrate how ML technologies can optimize inventory management, demand forecasting, and reliability, among others. Attendees will gain insights into practical applications of ML, its benefits, and lessons learned about broader implementation strategies.
In this session, you will learn:
Fabian Kneip is responsible for the Supply Chain Management of Evonik’s Care Solutions Business Unit which is supplying the world’s leading consumer brands with sustainable ingredients for personal care and cleaning applications. Fabian is motivated by his ambition to achieve high reliability and optimizing cash flows by managing the complexities of global value chains, making this role a highly integrative, customer-centric, and people-focused function with many opportunities for growth, change, and digitalization. Fabian’s career in the specialty chemicals industry includes leading Operations Excellence in the Americas and roles in in-house consulting in Germany. Prior to that, he served as an officer in the German Army with a focus on logistics. His roles have provided Fabian with the opportunity to work and live on four continents, allowing him to gain expertise in different markets and cultures, supply chain transformation, digitalization, and change management. His educational background is in economics, management, and industrial engineering from Munich, Shanghai, and Stuttgart universities.