Article
Building Trust: A Q&A on Community Health Choice’s Data Governance Journey
How Community Health Choice built trusted data as a foundation for AI and a strategic asset
October 07, 2026
Data governance can easily become an exercise in frameworks, policies, and technology. But its value is ultimately determined by something much more practical: whether the business trusts the data to make decisions.
For Community Health Choice, strengthening data governance meant creating clearer ownership, improving data quality, and embedding accountability into the way teams work. The effort has already produced measurable results, including improving member address accuracy from 75% to 98%, while creating a stronger foundation for analytics and AI.
We spoke with Head of IT Amit Anand about CHC’s data governance journey, what made the program work in practice, and what other organizations can learn from its experience. West Monroe experts also share their perspective on why these lessons matter for organizations looking to get more value from their data.
We also asked Managing Director Dan Campbell, who worked on the project with Amit and his team, to share West Monroe’s perspective on the broader lessons from CHC’s experience. His insights appear throughout the Q&A in callouts following Amit’s responses.
Explore CHC’s data governance journey
See how Community Health Choice improved member address accuracy, strengthened data ownership, and built a trusted foundation for analytics and AI.
Read the client result
Before this work, how were fragmented governance and inconsistent data quality affecting day-to-day operations and decision-making at CHC?
We also didn’t have clear ownership and accountability for some of our critical data domains. When an issue surfaced, it wasn’t always obvious who was responsible for addressing it. Ultimately, that made it more difficult for leadership to use data confidently and make critical decisions confidently in this competitive market.
West Monroe's Perspective
These challenges often show up as organizational friction rather than one highly visible data problem. Teams spend time reconciling reports, validating information, and resolving discrepancies instead of acting on insights.
When that happens repeatedly, confidence in the underlying data begins to decline. Defining ownership is particularly important because it gives organizations a clear path for resolving issues instead of allowing them to persist. It also creates the foundation needed to scale analytics and use data more consistently across business processes.
Why is it important for data governance to be business-led rather than IT-led, and how did that shift change engagement across CHC?
Our governance operating model established clearer ownership, stewardship, and accountability within the business. But defining those roles wasn’t enough. Change management was also critical. We focused on educating teams, communicating why governance mattered, and demonstrating the business value behind it. That helped us build shared ownership and participation across CHC.
West Monroe's Perspective
Because data is created and used within business processes, the business must help define what “good” looks like and remain accountable for outcomes. IT enables the platforms, integrations, access, and controls that support governance. Together, business and IT can address the definitions, processes, and accountability that shape data quality.
At CHC, that distinction helped shift the conversation from “Who owns the system?” to “Who owns the data and the business outcome?” That made governance more relevant to business teams and created shared accountability across business and IT.
What made your data governance program successful in practice, not just in design but in how teams actually adopted it across the business?
You also must be strategic to find the right business partner for the initial use cases, and your relationship in the organization plays a critical role to get the momentum and early wins. As teams began to see improvements in data quality and trust, interest grew. Governance became something the business wanted to participate in rather than something being imposed on it.
West Monroe's Perspective
We take a business-led, use-case-driven approach to data governance, connecting foundational capabilities to the business problems and outcomes that matter most. This helps organizations demonstrate value, build engagement, and create momentum for broader adoption.
CHC followed that approach by pairing roles, decision rights, standards, and processes with practical use cases that demonstrated business value. Change management—including active engagement, targeted education, and collaboration between business and IT—along with executive and board-level sponsorship helped embed governance into daily operations, sustain participation across domains, and build shared ownership.
What measurable business impact have you seen from improving data quality and trust?
We also established a formal process for identifying, tracking, and resolving data quality issues. Just as important, that success generated interest from other parts of the organization. We now have a growing pipeline of use cases coming from the business, which shows that teams increasingly see governance as a way to solve problems and improve performance.
West Monroe's Perspective
CHC’s improvement in address accuracy shows how governance can deliver a measurable operating result. It connects the work of defining, managing, and improving data to outcomes the business can see and track.
The effort also provides CHC with a repeatable model. By linking each issue to accountable business owners and the processes that create and use data, CHC can expand with greater consistency. The growing pipeline of business-led use cases suggests governance is becoming part of how the organization identifies opportunities to improve performance.
How has strengthening your data governance foundation improved your ability to scale analytics and AI, and what new capabilities does it unlock going forward?
It also means we can approach future AI investments with greater confidence with our strong data foundation. We now have stronger processes around data quality, ownership, and accountability, which will help us maximize the value of those investments while managing risk responsibly.
West Monroe's Perspective
Analytics and AI depend on reliable data, clear definitions, sound processes, and accountable owners. Strengthening governance gives CHC greater clarity around what its data means, who owns it, how quality is measured, and how problems are resolved.
With these fundamentals in place, CHC is approaching analytics and AI investments with greater confidence. Teams can focus on applying data to business opportunities and enabling more predictive, automated, and insight-driven ways of working.
What advice would you give to other organizations trying to improve data governance and unlock more value from their data?
Executive sponsorship and change management are also critical. People need to understand why governance matters and how it will improve the way they work. And choose partners who are invested in your business outcomes and shared success, rather than simply implementing a framework or technology.
West Monroe's Perspective
Start with a business problem and desired outcome. Choose a focused, high-value use case, establish the governance capabilities needed to support it, and use the lessons learned to expand deliberately. This approach helps organizations demonstrate value early while creating a practical foundation for broader adoption.
Governance also requires a change in how people work. Clear ownership, decision rights, communication, education, and stakeholder engagement support lasting adoption. Keep the model appropriately sized for the organization, and connect business strategy, technology, data, and change management to measurable outcomes.
