How HP Uses Databricks AI/BI Genie to Give Thousands of Employees Self-Serve Analytics

HP processes telemetry from hundreds of millions of printers and PCs, generating trillions of events annually. That data underpins decisions across the company — from inventory optimization and supply chain forecasting to product feature adoption and marketing attribution — but accessing it required technical expertise that most business stakeholders didn't have. Every question became a ticket, every insight a waiting game.

The problem surfaced most acutely at three points in HP's business. First, supply chain: a team managing thousands of SKUs across many countries needed to diagnose anomalies and run mix analysis quickly — but writing the exact SQL required was slow and error-prone. Second, product management: teams tracking battery life, feature usage, and customer interactions across millions of devices could only get answers by requesting reports from analysts, creating a dependency that slowed every decision. Third, digital commerce: during critical sales windows like Black Friday and Cyber Monday, marketing teams needed to know within half a day whether campaign adjustments were working — but by the time engineering teams surfaced the data, the opportunity had passed. 'When you're adjusting campaigns in a fast-moving market and need to know within half a day if it's working or not, you can't afford to wait for answers,' said Laurent Laguerre, HP's Global Head of Data Monetization.

HP deployed Databricks AI/BI Genie across these teams, allowing business users to ask data questions in plain English — no SQL, no Python, no dashboard request required. Product managers can now query feature adoption rates directly. Marketing teams can see campaign performance in near real time during peak periods. Supply chain analysts can run mix analysis conversationally during CEO meetings rather than submitting a ticket.

The efficiency gains are measured at 40-50% across product, sales, and customer pattern analysis. Billions of telemetry events from HP devices now flow into a single monitored platform. Thousands of users across the enterprise have been empowered with self-service access to data that previously required engineering involvement to retrieve.

HP plans to expand into AI-driven forecasting and strategic decision-making, building on the self-serve foundation that Genie established to move from reactive querying toward predictive analytics that nontechnical business users can drive independently.