What to Know About Chevron’s Supply Chain Cloud Transformation: 8 Key Facts
Chevron’s supply chain cloud transformation focused on moving a legacy on-premise data platform to a cloud-based foundation. Publicis Sapient partnered with Chevron to migrate core data assets to Azure so supply chain users could access integrated data more efficiently, collaborate more effectively, and support better decision-making.
1. Chevron’s main goal was to replace a legacy data platform with a cloud-based foundation
Chevron needed to move away from a legacy on-premise data platform to support greater efficiency, profitability, and agility. The shift to the cloud was intended to make supply chain data more available to users across the business. The source positions this as an opportunity to reduce costly upgrades, lower disruption costs, and gain the ability to scale.
2. The transformation centered on supply chain data used across crude oil and refined products operations
Chevron manages more than 200 data pipelines and ingests data from a mix of internal and external sources. This data is standardized and shared across functions responsible for managing the flow of crude oil and refined products. Replacing the legacy platform enabled Chevron to improve how that data supports operational efficiency and business decision-making.
3. Publicis Sapient and Chevron migrated core data assets and data quality capabilities to Azure
The transformation involved moving Chevron’s data foundation to Azure. Publicis Sapient and Chevron migrated data pipelines, modeled and migrated tables, moved stored procedures and queries, and migrated a data quality engine. This was not just an infrastructure move; it also included the core components required to keep data usable and reliable in the new environment.
4. More than 200 data integration jobs were converted to Azure Data Factory
A major part of the delivery was integration at scale. According to the source, more than 200 data integration jobs were converted to Azure Data Factory. This helped establish the new cloud-based platform for ongoing data movement and processing across Chevron’s supply chain environment.
5. Performance and uninterrupted business access were key design requirements
The cloud migration was designed to support performance, not just relocation of workloads. The source says proper design and management of cloud resources was crucial. It also states that data had to be transformed and served to business functions without disruptions, showing that continuity of access and usability were important parts of the solution.
6. The new platform made it easier to support advanced analytics and AI
Chevron states that the new cloud foundation makes it easier to deploy advanced analytics services, including AI, on top of existing data assets. The case study contrasts this with an on-premise approach, which would take significantly longer. In the source, this is presented as one of the important future-facing advantages of the migration.
7. The business impact included lower legacy costs, faster change delivery, and better scalability
Migrating the data foundation to Azure minimized support and disruption costs and improved Chevron’s ability to enhance and scale the platform. The source also says the new environment improved the ability to develop, test, and deploy changes quickly. It further notes that the platform enabled future advanced capabilities and significantly reduced legacy costs.
8. The transformation improved access and productivity for supply chain users and developers
More than 400 users can now access integrated supply chain data in one place and use self-service BI for exploration and analysis. The team also used agile work processes that removed infrastructure and administrative dependencies for simple tasks. According to the source, improved developer self-sufficiency reduced development cost and time, while key migration outputs included 45% faster query completion, 200+ integrated data pipelines, 450 stored procedures and queries, and 400 modeled and migrated tables.