Case Study: Steelcase achieves faster deal velocity and pricing automation with Databricks

Improving the speed and competitiveness of pricing to win more

Steelcase, a global leader in the world of work, needed a faster way to manage pricing across a large product portfolio. Its legacy approval process was slow and manual, making it harder for sales teams to respond quickly and competitively to high-stakes deals. Steelcase worked with Databricks and the Databricks Data Intelligence Platform to modernize this workflow.

Databricks helped Steelcase build an AI-powered pricing engine on Azure that unified data, automated feature engineering, and delivered instant discount recommendations directly into its pricing system. The results were significant: 20-minute pricing submissions were replaced with near real-time recommendations, auto-approvals rose from 35% to nearly 50%, and Steelcase improved deal velocity and responsiveness.

Steelcase

Ben Krill

Vice President of Pricing and Incentives