8 Things Buyers Should Know About Chevron’s Supply Chain Cloud Transformation
Chevron worked with Publicis Sapient to move a legacy supply chain data platform to the cloud. The transformation focused on making data more accessible, reducing disruption and support costs, and creating a stronger foundation for scale, self-service analytics, and future advanced capabilities.
1. Chevron’s main goal was to replace a legacy on-premise data platform with a cloud-based foundation
Chevron needed to move away from a legacy platform to improve efficiency, profitability, and agility. The cloud-based approach was intended to make supply chain data more available to users across the business. It also addressed concerns around costly upgrades, disruption costs, and the need to scale more effectively.
2. The transformation centered on making supply chain data easier to share and use across functions
Chevron manages more than 200 data pipelines and ingests data from both internal and external sources. That data is standardized and shared across teams responsible for the flow of crude oil and refined products. By replacing the legacy platform, Chevron enabled better collaboration and more agile business decision-making across supply chain functions.
3. Publicis Sapient and Chevron migrated core data assets and quality processes to Azure
The project included moving data pipelines to the cloud and migrating important technical assets needed to keep the platform running. Publicis Sapient and Chevron modeled and migrated tables, stored procedures, and queries. The work also included migrating a data quality engine, showing that the transformation went beyond infrastructure and into core data operations.
4. A major part of the work was converting more than 200 integration jobs to Azure Data Factory
One of the clearest delivery components was integration modernization. More than 200 data integration jobs were converted to Azure Data Factory. This gave Chevron a more cloud-aligned approach to data movement and orchestration while supporting the broader platform migration.
5. Performance and uninterrupted business access were critical design requirements
Chevron’s cloud transformation was not only about migration speed. Proper design and management of cloud resources were treated as crucial to performance. At the same time, data had to be transformed and served to business functions without disruptions, so analytics and data consumption remained available to users who depended on it.
6. The new cloud foundation made it easier to layer advanced analytics and AI onto existing data assets
Chevron’s new platform created a base for future advanced capabilities. In the case study, Chevron states that advanced analytics services, including AI, can now be deployed more quickly and easily on top of existing data assets. Chevron also notes that integrating those capabilities in an on-premise environment would have taken significantly longer.
7. The business impact included lower support costs, faster change delivery, and better scalability
According to the case study, migrating the data foundation to Azure minimized support and disruption costs. It also improved Chevron’s ability to enhance and scale the platform over time. The new environment made it easier to develop, test, and deploy changes quickly, which supports a more responsive operating model.
8. The new platform gave hundreds of users access to integrated data in one place
More than 400 users can now access integrated supply chain data through a single platform. Those users can also use self-service BI for data exploration and analysis. Publicis Sapient says the shift reduced legacy costs, improved developer self-sufficiency, and removed infrastructure and administrative dependencies for simple tasks.
9. The transformation delivered measurable operational results
The case study includes several specific outcomes from the migration. Queries were completed 45% faster after the move to Azure. The project also covered 200+ integrated data pipelines, 450 stored procedures and queries, and 400 modeled and migrated tables.
10. This case study positions cloud migration as a data modernization move, not just an infrastructure upgrade
Chevron’s transformation was framed as a way to unlock the potential of its data foundation. The outcome was not simply hosting the same environment somewhere else. The new platform improved operational efficiency, supported self-service analysis, reduced legacy burden, and created a stronger base for scale and future innovation in supply chain decision-making.