Our client, a claims consolidator and benefits manager for multiple BlueCross BlueShield companies, required the integration of 29 data sources into a single, streamlined data pipeline.
Transformation of Enterprise Data Strategy
Service Provided
Capabilities Utilized
Data Architecture & Engineering Data Governance
Client challenge
The client required a unified view of customers and members across the organization, encompassing medical, health, and pharmacy claims. An enterprise data warehouse (EDW) was considered as the solution, but it ultimately failed to meet expectations. The solution relied on outdated, non-scalable technology, overlooked critical data requirements, and contained logic errors in the implemented components.
Our solution
We created an interim solution by utilizing the existing infrastructure, which allowed the client to extract value from their data before the completion of the cloud-based data warehouse. This strategy enabled the client to access critical claims data while establishing a stable, scalable foundation for additional datasets and enhanced analysis, which was previously restricted by the on-premise system’s processing speed and capacity. The entire solution was deployed in three key phases:
Phase 1 – Transition: The first phase focused on aligning data requirements with business goals, as well as evaluating data quality to facilitate the development of the financial data mart and EDW claims processing mart. We outlined milestones, tasks, benefits, assumptions, and potential risks.
Phase II – Migration: Using an Agile methodology, we migrated to the recommended cloud-based CDS architecture over several iterations for all accounts, providing a roadmap for the acceleration plan in Phase III.
Phase III – Acceleration: In the final phase, we leveraged the newly established CDS architecture to enhance the client’s operational and developmental capabilities through stringent data governance and improved data management processes.
Results
Along with the enhanced efficiencies and resolution of challenges through standardized data and scalable infrastructure, this initiative also fostered skill development within SMEs during and after the implementation. We provided training on new technologies, cloud adoption, data consolidation, and data quality to ensure the project’s long-term success. These achievements allowed our client to phase out its costly and unreliable legacy system, expand the CDS to incorporate new business lines, and drive market growth. Additionally, this laid the foundation for leveraging artificial intelligence and machine learning to gain valuable insights and enhance outcomes, surpassing the client’s initial expectations.
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