Building a Measurement + Experimentation Engine for a Global Pharma Commercial Organization

Challenge

Leadership needed analytics they could trust and act on. Reporting cycles were slow, metrics were inconsistent, and there wasn't a finance-defensible way to attribute marketing and digital investments to outcomes. At the same time, customer and call-center signals needed to surface quickly to prevent costly operational issues.

What we did

• Established an analytics COE with governance, data quality standards, and a sustainable operating cadence.
• Rebuilt reporting standards and workflows to compress cycle time and improve consistency across teams and regions.
• Deployed AI-driven personalization supporting a commercial domain exceeding $800M in direct/eCommerce sales.
• Built call-center Voice-of-Customer (VOC) reporting for the C-suite to surface emerging issues and accelerate response.
• Implemented causal measurement: MMM plus $32M+ in geo-scale randomized trials for online/offline attribution.

Results

• Improved reporting timelines from monthly to weekly.
• Delivered personalization tied to $800M+ in direct/eCommerce sales.
• Detected and helped solve $80M+ in COVID-related vaccination issues via VOC reporting.
• Executed $32M+ geo-scale RCTs to strengthen attribution and investment decisions.

Strategic impact

The organization gained a durable measurement and experimentation engine—governed data, consistent reporting, and causal inference—so leaders could scale AI and marketing investments with confidence. The COE model reduced 'analysis churn' by turning analytics into an operating capability rather than ad-hoc projects.

Optics + governance

• Kept measurement CFO-defensible by combining models with experimental validation where feasible.
• Avoided vanity metrics—focused on decision velocity, revenue impact, and issue prevention.
• Implemented governance and change management so improvements survived leadership and vendor changes.