Case Study: Shell achieves unified analytics and millions in savings with Databricks

Optimizing supply chain and inventory management

Shell, a century-old energy company accelerating its shift to cleaner energy, faced the challenge of mining and using massive, growing datasets across legacy infrastructure while scaling analytics and AI skills. Although a Data Science Centre of Excellence was identifying high‑value use cases, Shell needed a scalable, democratized platform to make data accessible to engineers, scientists and analysts worldwide.

By adopting Databricks as a core part of its Shell.ai platform, Shell unified its data analytics lifecycle into a self-service environment for modeling, BI and collaboration. The move enabled 160+ AI projects and hundreds of data practitioners to innovate — cutting inventory prediction runtimes from 48 hours to 45 minutes, delivering millions in annual savings, powering a 1.5M‑user loyalty recommendation engine, enabling real‑time lubricant diagnostics, and accelerating many workflows (label validation 9x faster).

Shell

Daniel Jeavons

General Manager Advanced Analytics CoE