Leading mobility company, Michelin is using Confluent to power its global inventory management system. By leveraging Confluent Cloud, Michelin quickly scaled its real-time inventory system to meet demand while cutting operational costs by 35%.
“Confluent plays an integral role in accelerating our journey to becoming a data-first and digital business,” Michelin group chief digital and information officer, Yves Caseau said.
“Today’s customers demand rich, personalised experiences, and business operations must be optimised to stay ahead of the competition. We use Confluent Cloud as an essential piece of our data infrastructure to unlock data and stream it in real-time, with use cases like customer 360, e-commerce, microservices, and more.”
As one of the world’s largest tire manufacturers, Michelin’s teams require constant access to up-to-date information. For example, accurate status updates on raw and semi-finished materials. Michelin’s mobility solutions like predictive insights for tire replacements and route recommendations for fuel optimisation are dependent on frequent updates.
To power its business with real-time data, Michelin initially turned to Kafka’s open-source data streaming platform. Kafka provided Michelin with a real-time view and the ability to collect, store, and process data as continuous streams. This was a significant improvement from legacy applications that delivered daily or hourly updates using batch processing.
However, as they expanded Kafka’s footprint across the business, Michelin’s teams found Kafka increasingly difficult to scale and manage. The open-source technology did not provide a clear path to the cloud, which held Michelin back from a company mandate to transition off of monolithic, on-premises systems.
“Given today’s economic pressures, many businesses are faced with the challenge of cutting costs while also keeping ahead of the competition and customer expectations,” Confluent president of field operations, Erica Schultz said.
“We’re proud to help companies like Michelin achieve success on both fronts. With a truly cloud-native data streaming platform that goes above and beyond Apache Kafka, we help offload the costs and risks of self-managing Kafka while also helping drive real-time, data-driven decisions and operations.”
Michelin estimates cost savings of 35% with Confluent compared to on-premises operations, thanks to the cloud-native platform. Confluent also helped Michelin save an estimated eight to nine months of time to market. With Confluent’s 99.99% SLA, the Michelin team can offload operations and have peace of mind that mission-critical data streaming workloads in the cloud are resilient and highly available.