Modernizing Data and Governance Across Commercial and R&D: Lessons from a Top Pharma Company

Data has emerged as the foundation for competitive advantage and innovation in today's rapidly evolving healthcare ecosystem. For pharmaceutical companies, the modernization of data governance practices across commercial and R&D functions is no longer optional; it's essential.

At Axtria Ignite 2025, a panel of top global pharmaceutical company data leaders shared their experiences and insights on building an organization's unified, cross-functional data foundation. Their stories revealed the importance of using the right tools and platforms and the power of cultural change, collaboration, and strategic governance.

Moving from Reactive to Proactive Data Governance

The panelists discussed the story of one organization that transitioned from a siloed, affiliate-driven data model to an enterprise-wide foundation. The primary goal was to enable faster data onboarding, define data standards that promote data consistency, enable self-serve data service for better decision-making, accelerate time-to-insights, and establish the groundwork for advanced analytics and AI initiatives. This transformation demanded a comprehensive focus on global data standardization and fostering collaboration across regions and functions.

The Right Technology, People, and Process

Recognizing that a strong data foundation relies equally upon people, process, and technology, the organization took a structured approach to transformation. The team thoroughly evaluated the available tools, and because of its robust metadata management and governance capabilities, they selected Informatica for their data integration, quality, and governance needs. Databricks was chosen as the scalable cloud data platform to serve both Commercial and R&D needs.

While technology was central, the initiative's success hinged on clearly defined processes and shared accountability across teams. Standardized data management processes were established for data onboarding, quality management, and cataloging of data, as well as marketplace enablement. These processes were supported by clearly articulated roles and responsibilities and a decision-making matrix that ensured timely and consistent data lifecycle governance.

From Fragmentation to Agility in Commercial Operations

The commercial function initially lacked transparency into data assets, had limited documentation, and struggled with holding suppliers accountable for data quality. Implementing a comprehensive data quality framework allowed the company to gain real-time visibility into its data pipelines. Automated alerts, quality scorecards, and proactive monitoring significantly reduced the time analysts spent troubleshooting data issues. As a result, commercial teams could derive insights more efficiently, empowering field teams and supporting data-driven contract strategies and omnichannel execution.

Reimagining R&D with Insight-Driven Foundations

In R&D, the focus expanded beyond cataloging data collection to include cataloging insights, with democratization being the key to promoting the reuse of clinical data and insights. With an enterprise data catalog and marketplace, data users can explore da ta more effectively and independently, reinforcing a shift toward self-serve data.

Culture Change as a Catalyst

The organization understood that culture change would be a key element of this modernization effort and that effective change management was essential to a successful result. Leadership provided critical top-down sponsorship, allocating resources, budgets, and support to the data modernization agenda. At the same time, bottom-up engagement was cultivated through councils and working groups, where local affiliates and functional leaders contributed to shaping global standards. This federated approach fostered ownership and eased adoption across regions.

The organization developed a clear roadmap to enable change, highlighting each governance initiative's value, from cataloging and data quality to tool deployment and self-service. Business and IT stakeholders moved in sync, supported by transparent communication and measurable outcomes. This collaborative, value-driven approach created trust and reduced resistance.

The Power of the Enterprise Data Catalog

The enterprise data catalog emerged as a cornerstone of the company's governance framework, providing the organization with increased visibility into its enterprise data assets' lineage, ownership, and quality. It enabled data democratization via the marketplace, allowing more effective data vendor and data spend management and ensuring data is used effectively across functions.

"When you know your data, what you have, who owns it, how it's used, you unlock incredible value."
– Panelist, Ignite 2025 Session

The modernized process catalog is proactively updated by integrating data onboarding workflows that are tightly coupled with data quality instrumentation and monitoring. As a result, the company can measure how much of its data is accurate, timely, and compliant, and make procurement and governance decisions based on reliable metrics.

Looking Ahead: Master Data Management, Global Dashboards, and AI Readiness

With foundational elements in place, the organization is expanding its focus to include master data management, global brand analytics, key performance indicator frameworks, and readiness for advanced AI applications. Smaller country affiliates are being onboarded into the platform and supported by an offshore data management team that ensures consistent practices across markets. The company is also building global dashboards and reporting systems that leverage standardized, governed data products that improve decision-making across the enterprise.

Key Takeaways

The key takeaways from the panel discussion were:

• Federated Governance: Build global frameworks that support local autonomy through federated governance models.
• Strong foundation: Establish a strong foundation by aligning the right technology with standardized processes and clear accountability across teams, reinforcing that data modernization succeeds only when people, processes, and technology work in unison.
• Data Quality Builds Trust: Robust, proactive data quality embedded at every data layer ensures data is reliable, trusted, and analytics-ready, enabling better business decisions.
• Catalogs Enable Data Democratization: A living, searchable data catalog enables prompt data discovery, hence faster business decisions.
• Culture Drives Adoption: Top-down sponsorship and bottom-up engagement ensure sustainable change.

Conclusion

Data modernization is a continuous journey that requires the right combination of people, processes, technology, and culture. By building an integrated foundation and aligning governance to business value, this leading pharmaceutical company has transformed how it manages and uses data across US commercial and R&D, now scaling to other regions and functions. As the industry moves toward AI-enabled innovation, companies that treat data as a reusable, trusted product will be positioned to lead.

This success story demonstrates how investing in scalable platforms, federated governance, and proactive quality frameworks can unlock significant business value, accelerating insight generation, reducing risk, and enhancing collaboration across the enterprise.

FAQs