Standardize to Scale: Boehringer Ingelheim Data Harmonization in 100+ Markets

In the high-stakes world of life sciences, “good enough” data is no longer sufficient. As pharmaceutical leaders move toward advanced analytics and AI, they are hitting a common wall: geographical data fragmentation. When every market operates with a different data model, the dream of a seamless, global customer view and the AI insights that come with it, remains out of reach.

Leaders from Boehringer Ingelheim shared their journey of dismantling a fragmented legacy approach to build a unified foundation using Veeva OpenData and Veeva Network.

The hidden friction of legacy data

“Master data management (MDM) and reference data are usually invisible, so you are not winning a huge prize if you get it right, but you can lose a lot if you don’t do it right. People expect it to work,” explains Alexander Ullrich, head of platforms and data, medical affairs at Boehringer Ingelheim.

This inherent invisibility is exactly why reference data was dismissed for years as a back-office phonebook. But that perception is shifting, as reference data is increasingly understood as the essential foundational layer of a successful AI strategy.

Before this transition, Boehringer Ingelheim faced significant challenges that are common across large, global organizations:

• Local market silos: Different countries purchased their own customer reference data and MDM systems with varying scopes. This led to disconnected “islands” of data that made global analytics and scalability nearly impossible.
• Divided teams: Medical and commercial teams lived in separate worlds with disconnected insights, preventing a true 360-degree customer view.
• Costly customization: Highly customized solutions intended to address local needs actually created overwhelming operational complexity. In Germany, for example, managing five different data providers meant simple updates to healthcare professional (HCP) addresses could take multiple days.
• Operational burden of inconsistencies: Inconsistencies were so prevalent that auto-matching was unreliable. Manually matching HCPs in spreadsheets was often faster than trying to navigate the sluggish legacy systems.

These challenges are far from unique. Veeva research shows that the gap between current data health and AI aspirations is a systemic issue in the industry:

• 95% of companies are still forced to manually remap global to local specialties.
• 96% of pharma leaders admit their data is not yet ready for AI.

From complexity to connectivity

To break the cycle of fragmentation, Boehringer Ingelheim standardized its customer data strategy across more than 100 countries using Veeva OpenData and Veeva Network. By choosing a connected data and software approach, they established a “clean” data foundation that will seamlessly evolve into the next generation of data standards.

The connected approach provides the team with four primary strategic benefits:

• Global harmonization at scale: Boehringer Ingelheim moved from locally optimized data islands to a single, unified data acquisition strategy. This ensures a data analyst in Germany and field teams in France, Spain, and the UK are finally speaking the same “data language,” enabling the organization to scale analytics and AI across the entire globe.
• Operational simplicity: The new model dramatically simplifies the user experience and internal operations. Instead of juggling different data providers globally, Boehringer Ingelheim uses a highly commoditized, out-of-the-box solution that eliminates the need for heavy, expensive local customizations and integrations.
• A de-risked path to Vault CRM: Standardizing MDM is a critical prerequisite for Boehringer Ingelheim’s transition to Veeva Vault CRM. By harmonizing the data foundation first, the organization has significantly lowered migration risk, ensuring that the new platform launches with a comprehensive customer view.
• Lower total cost of ownership and project costs: By replacing a complex, highly customized MDM with a life sciences-specific solution like Veeva Network, the team ensures that data and software are natively connected. This shift away from heavy custom engineering is projected to reduce the total cost of ownership by 30% and project costs by approximately 70% over a five-year horizon.

Boehringer Ingelheim’s final decision was based on simplification, local data quality, user experience in priority markets, and cost. The leaders validated this direction through platform evaluations, rigorous data quality checks for focus markets, and process walkthroughs. Lastly, they developed cost scenarios accounting for implementation durations, platform combinations, and various transition approaches.

Lessons from the trenches

Leaders at Boehringer Ingelheim emphasize that this transition is a significant strategic undertaking that requires addressing cultural and operational gaps upfront:

1. Standardization requires compromise: The leaders defined early on what changes local markets would accept. Moving to a standard solution means explicitly accepting that certain custom local features will no longer be possible in exchange for global excellence.
2. IT and Market engagement is mandatory: The team prioritized early collaboration with both global IT functions and local market leads. This ensured the solution remained simple rather than becoming a complex, over-customized hybrid that would reproduce the very silos they aimed to eliminate.
3. Mapping MDM to strategic future: Shift the mindset around MDM from an invisible back-office asset to a non-negotiable prerequisite for future AI use cases and the impending organization-wide migration to Veeva Vault CRM. The mindset shift helped leadership see the tangible value in fixing the foundation to enable long-term commercial excellence.

Building the foundations

The team is currently executing an ambitious phased rollout, which started with its most complex market, the United States, followed by remaining global markets to prepare for the Vault CRM transition, and ending it with China and Japan, where specialized local data approaches are required.

By the time Boehringer Ingelheim finishes the implementation in 2027, the gap between data-ready leaders and the rest of the industry will be a chasm. If you don’t fix the foundation now, buying expensive AI tools later is like putting a fresh coat of paint on a house with no foundation, it won’t stop the walls from cracking. Leadership recognized that while this work is often invisible, it is the only way to stop “working around” data failures and finally stay ahead of the curve.

As Christian Gabriel, customer MDM manager at Boehringer Ingelheim, concluded when reflecting on the necessity of this global shift:

“Standardization will hurt on multiple levels since it necessarily breaks processes to some extent and will require some hard decisions. But not doing that is even more painful in the long run. You don’t want to be the person that always needs to explain why certain things don’t work.”

Watch the 3-minute video to learn more about Boehringer Ingelheim’s data transformation journey.