Eric's first step was a deliberate departure from standard analytics project sequencing: instead of gathering data requirements, he interviewed every executive and operator to understand what decisions they actually needed to make. That conversation-first approach produced a KPI framework grounded in operational reality — production, write-offs, adjustments, appointments, and encounters — normalized across all 15 clinic groups and 50+ practices despite different system names, schemas, and data structures. The data integration layer connected all 50+ clinic systems into a centralized Azure and SQL Server infrastructure with nightly automated refresh. Every dashboard view was wireframed against how leaders actually read and acted on data — not against how BI tools default to displaying it. Once the reporting layer was stable and trusted, the platform moved into operations: front desk staff received daily patient lists flagging who needed specific imaging before their appointment, intake staff received eligibility status checks to prevent unrecoverable billing write-offs, and site managers received performance alerts. What began as a reporting problem became an early-warning system that prevented revenue from leaking before it was too late to act.