The Prescription 

Running a pharmacy benefit is a many-to-many job. A PBM has to coordinate health plans, employers, pharmacies, prescribers, manufacturers, claims, and contracts — just to name a few. This leading PBM manages millions of prescription claims, works with hundreds of pharmacy partners, and supports dozens of health plans and pharmaceutical manufacturers. Its business depends on turning complex data into practical decisions: which drugs are being used, where costs are moving, whether formularies are performing, and how members are getting the care they need. 

The Wrong Dose 

The company had plenty of data. What it needed was a better way to use it. 

Fragmented Data, Fragmented Truth. Data was scattered across internal databases, SaaS applications, spreadsheets, and reporting tools. Each business team had its own version of the truth. That made it difficult to reach a shared view of performance or compare metrics like formulary adherence and rebate yield. 

Costly to Extend. Thousands of mappings, along with a large collection of source-specific processes, made new integrations expensive to maintain. A new data source could take weeks to onboard, integrate, and troubleshoot. 

Manual Reconciliation. Manual data extracts and spreadsheet-driven reconciliation slowed analysis and led to inconsistent results. 

Weak Governance. Without stronger governance and lineage, every data request threatened to turn into a full-blown platform project. 

Anyone who’s ever worked in a pharmacy knows how busy it can get. What the PBM needed was a partner who could help it create a data environment that ingested information once, governed it properly, made it reusable, and supported today’s analytics and tomorrow’s machine learning.