How Michelin improves Aftermarket Sales and Customer Service with Apache Kafka

Aftermarket sales and customer service require the right information at the right time to make context-specific decisions. This post explains the modernization of supply chain business process choreography based on the real-life use case of Michelin, a tire manufacturer in France. Data Streaming with Apache Kafka enables true decoupling, domain-driven design, and data consistency across real-time and batch systems. Common business goals drove them: Increase customer retention, increase revenue, reduce costs, and improve time to market for innovation.

(Originally posted on Kai Waehner’s blog: “How Michelin improves Aftermarket Sales and Customer Service with Data Streaming”… Join the data streaming community and stay informed about new blog posts by subscribing to my newsletter)

The State of Data Streaming for Manufacturing in 2023

The evolution of industrial IoT, manufacturing 4.0, and digitalized B2B and customer relations require modern, open, and scalable information sharing. Data streaming allows integrating and correlating data in real-time at any scale. Trends like software-defined manufacturing and data streaming help modernize and innovate the entire engineering and sales lifecycle.