Unlocking AI innovation with a scalable, compliant Data Operating Model

A leading international healthcare group recognized that despite its scale and ambition, its ability to harness data was falling short.

Local data capabilities had developed unevenly; some markets had mature analytics and governance, while others were less mature. This fragmentation hindered compliant, cross-border use of sensitive healthcare data amid tightening regulations such as GDPR, the EU AI Act, and local laws.

Decentralization kept valuable innovations siloed; unlocking them would require a unified, scalable, and compliant data approach. This would give deliver smarter, faster decisions today and AI-driven innovation in the future.

Partnering to design a future-proof Data Operating Model

In partnership with the Group CIO, Chief Data Officer, and senior market leaders, we co-designed a Data Operating Model (DOM) that was ambitious yet practical – building on strengths, addressing capability gaps, and creating standardized, reusable data foundations to enable confident, insight-led decisions.

Our approach followed three structured phases:

• Step 1 – Establishing a clear baseline

We applied Wavestone’s Data Operating Model Maturity Framework to assess capabilities across strategy, governance, technology, processes, and people. This created a consistent, evidence-based baseline for every market, highlighting both pockets of advanced capability and priority areas for improvement.

• Step 2 – Selecting the right model for scale

Using the assessment insights, we evaluated three potential operating model archetypes; decentralized, centralized, and hub-and-spoke through Wavestone’s Data Operating Model Archetypes framework.
The chosen model was a federated hub-and-spoke approach:

• • Central hub: Defines standards, governs shared services, manages enterprise tooling, and drives innovation.
  • Local spokes: Apply central standards to local data, deliver market-specific priorities, and own execution within their region.
    This structure balances global consistency with local needs, closing key gaps and enabling scalable AI adoption.

This structure balances global consistency with local needs, closing key gaps and enabling scalable AI adoption.

• Step 3 – Building the roadmap for change

Recognizing the varying starting points across markets, we developed a pragmatic two-year roadmap with clear milestones.

Early phases focus on high-impact, cross-market use cases already underway – such as operational KPI dashboards, predictive maintenance for clinical assets, and AI-assisted diagnostics – to build momentum and demonstrate value quickly.

Subsequent phases progressively strengthen governance, technology, and people capabilities by:

• • Building a Data & AI Center of Excellence to speed up high-value use cases and scale best practices.
  • Strengthening local data teams in priority markets to deliver in-market priorities while aligning with central standards.
  • Rolling out enterprise-grade tooling such as data catalogs and governance platforms to en consistency and scalability.
  • Rolling out training to build a data-driven culture

Outcome: Turning design into tangible business value

The Data Operating Model (DOM) drives business impact from day one, going beyond regulatory compliance and AI-readiness to transform decisionaking, performance, and business growth.

• Regulatory readiness and risk mitigation – Ensures compliance with GDPR, the AI Act, and healthcare-specific requirements, while protecting patient trust through strong governance.
• Smarter, faster decision-making – Trusted data empowers leaders to optimize operations, improve patient outcomes, and shape commercial strategy.
• Unlocking future innovation – Solid governance, architecture, and skills create a safe path to scale AI when the time is right.
• Data-driven culture – Clear roles, career paths, and training programs build engagement and momentum across markets.
• Aligned execution – A shared roadmap keeps transformation strategically aligned and operationally actionable.

Laying the foundations for an AI-ready future

The partnership is moving the organization from fragmented, market-led data practices into a unified, insight-driven, and compliant enterprise. The new DOM delivers the foundations to make better decisions today – while creating the platform to unlock AI tomorrow.