Normalized claim
Cost: 35% decrease
Reduced operations cost by 35%.
Michelin Transforms Manufacturing and Aftermarket Service Using Microsoft Azure and Apache Kafka
Use case typeSupply chain optimizationUpdated Jun 13, 2026
Michelin modernized their supply chain and aftermarket sales with a transition from a monolithic Business Process Management system to a microservices architecture using event-driven choreography powered by Apache Kafka, hosted on Microsoft Azure. They adopted cloud-native technologies like Kubernetes and Zeebe as part of the technical infrastructure and migrated operations to fully managed Confluent Cloud on Azure for real-time data streaming and integration. The new architecture enabled decoupled, real-time supply chain orchestration, predictive mobility services, and context-specific customer service, improving responsiveness and innovation speed across over 50 global manufacturing sites.
- Organization
- Michelin
- Industry
- Manufacturing
- Location
- France
- Published
- October 2023
Reported outcomes
−35%
costCost savings
Strategic outcomes
New product / capabilityEnabled real-time supply chain orchestrationCustomer experience & trustImproved context-specific customer serviceBetter decisions & insightEnhanced predictive insights for serviceMarket & geographic expansionImproved global manufacturing site operations
Catalog median for cost savings deployments: −40% across 177 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Michelin
- Provider
- Microsoft
- Maturity
- Unknown
- Linked source
- kai-waehner.de blog
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1Supply chain orchestration
- 2Aftermarket sales and service optimization
- Michelin faced maintenance difficulties and a single point of failure risk with their monolithic BPM system.
- There was a need for modernization to enable real-time data orchestration for better customer service, retention, and revenue while reducing costs.
- Migrated from a monolithic BPM to a microservices architecture with event-driven choreography powered by Apache Kafka.
- Moved operations from self-managed Kafka to Confluent Cloud on Microsoft Azure.
- Employed Kubernetes for cloud-native infrastructure and Zeebe workflow engine.
- Enabled real-time data streaming integration across logistics, inventory, and customer service systems.
- Reduced operations cost by 35%.
- Improved real-time inventory management across 50+ manufacturing sites globally.
- Enhanced aftermarket customer service with predictive insights.
- Increased supply chain management responsiveness and innovation speed.
Architecture
Microservices architecture with event-driven choreography using Apache Kafka, Kubernetes for cloud-native infrastructure, Zeebe workflow engine, and migration to Confluent Cloud on Azure.
Sources & evidence1
Evidence: Low35/100Evidence strength
- Customer explicitly identified
- Quantified outcome available
- Technical implementation details available
ExpandedExpanded
The same organization appears in newer AI deployment evidence.
- Same organization re-documented as recently as 2026.
Measures whether this deployment's public evidence persists — not whether the system is still in production.
Type: Blog PostPublished: Oct 2, 2023Publisher: kai-waehner.de blogEvidence: VendorConfidence: Medium
AI-generated summary. Verify important details with the linked sources before relying on this case.
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