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Home / Post-Acquisition Data Warehouse Alignment for a Research Innovator
A growing clinical trials company (under $100 million in revenue) had recently expanded through acquisition. While the business had previously worked with SolomonEdwards to implement a revenue cycle management data warehouse, the addition of a second entity introduced misaligned data models and fragmented reporting. The executive team lacked a unified view of key financial metrics across the combined organization, limiting their ability to assess performance, streamline operations and make informed decisions. Integrating data from multiple source systems in a secure and compliant way was essential to maintaining business continuity and supporting the company’s growth trajectory.
The client again sought our assistance to lead a data warehouse alignment initiative, ensuring consistent, enterprise-wide revenue cycle reporting. We extended the original warehouse to incorporate the newly acquired company’s data while standardizing underlying data models, metrics and definitions. This work enabled the creation of a consolidated “single pane of glass” for executive visibility, facilitating consistent insights across business units.
Our approach emphasized data governance and model alignment from the outset—defining authoritative data sources, setting validation protocols, and ensuring full documentation of all data transformations. We worked closely with stakeholders in finance and operations to confirm that the combined metrics were not only technically integrated but strategically aligned with leadership’s decision-making needs.
The result was a unified data warehouse environment that supports real-time, organization-wide insight into revenue cycle performance. Leadership now has access to consistent, trusted metrics across both legacy and newly acquired entities—enabling faster reporting cycles, better operational decisions and clearer accountability. Our work also positions the company to scale future acquisitions into the same platform with minimal friction, thanks to the foundational alignment and repeatable data integration model established during the project.