This year, I had the privilege of collaborating with HealthEZ, a third-party administrator specializing in custom, self-funded benefit plans that reduce employer costs while enhancing member experiences. Our project focused on developing a data roadmap to support a new operational system, improve reporting, and establish a robust data infrastructure to fuel HealthEZ’s ambitious future plans.
From the start, the executive leadership team’s full commitment was instrumental. Their belief in leveraging data strategically drove the early success of the data roadmap, ensuring alignment with business goals and fostering a culture of data-driven decision-making.
The first phase centered on creating a modernized data and integration architecture. In just six months, our team of four full-time employees delivered a comprehensive data hub/data fabric, mastering:
This architecture laid a scalable foundation for HealthEZ’s data ecosystem, enabling seamless integration and efficient data management.
This pragmatic approach ensured early wins while maintaining long-term scalability.
A robust data catalog was another critical investment. It integrated:
Our rule: no development without prior definition, profiling, and mapping in the catalog. We meticulously mapped every data movement across the data hub’s layers, ensuring complete end-to-end lineage. This lineage, accessible via a web portal, empowers business users and IT developers to perform impact analyses and understand data flows comprehensively.
With over 240 business terms to define and limited availability from business stakeholders, we leveraged generative AI to create initial business definitions. Most were directly integrated into the catalog, with minimal tweaks for business-specific nuances. AI-generated definitions were flagged for future refinement, ensuring flexibility as business needs evolve.
An unexpected challenge was the need for a matching engine to align third-party data with internal systems. Two factors were critical to our success:
This approach achieved a 98%+ match rate quickly, addressing an unscoped issue. The validated rules were then integrated into the full data hub solution, ensuring reliability and scalability.
Mid-project, the business decided to pivot away from the planned transactional system due to its limited capabilities. This shift, while challenging, highlighted the data hub’s flexibility. By modifying only the access layer, the data hub seamlessly supported the business' new direction for their needs and expanded to accommodate additional data domains, aligning with the revised scope and supporting other projects.
With the data management foundation in place and initial data assets in production, the next phase focuses on leveraging these high-quality, reusable assets for enterprise analytics. This positions HealthEZ to unlock deeper insights and drive strategic growth.
Few organizations get a clean slate for data management. HealthEZ’s journey demonstrates that with strategic vision, executive support, and innovative approaches like the shortcut and AI-driven definitions, it’s possible to transform inherited systems and data into a powerful asset for the future.