Redefining Commercial Insights with Data Products
For commercial pharma leaders, data’s true power is realized where decisions happen: at the edge.
Gilead built that connection, transforming global strategy into local execution.
Partnering with Axtria, Gilead restructured how commercial data is governed, delivered, and used, shifting from disconnected systems to reusable, insight-ready data assets that drive consistent decision-making across regions.
This transformation set a new standard for how life sciences organizations can accelerate insights, strengthen governance, and empower field teams with trusted, real-time intelligence.
Inside the White Paper
This paper, authored by Pranay Butala, Brad Sasaki, Anshul Mohan and Megha Kapadia explores:
- The Evolution of Data Management at Gilead
Gilead’s journey reflects the shift from siloed, manual data systems to a centralized, cloud-based foundation that enables cross-market accessibility, speed, and trust. With the introduction of its International Cloud Foundation (ICF), Gilead set the stage for a unified global platform to evolve alongside the business.
- From Data Lakes to Data Products
Traditional data systems store information, but data products deliver value. Designed for reuse and localization, they enabled Gilead’s affiliates to deploy global KPIs and logic while tailoring insights for each market, achieving “global consistency with local flexibility.”
- Building Last-Mile Connectivity
Axtria’s productized data architecture gave Gilead’s field teams near-real-time visibility into targeting, performance, and next-best actions, driving faster decision-making and building confidence across every level of the organization.
Results and Impact
- Deployed across more than eight regions with a unified data language.
- Significantly reduced data preparation time, accelerating analytics cycles.
- Increased trust and adoption among commercial teams through consistent KPIs.
- Established the foundation for AI-driven and next-best-action capabilities.
Gilead’s transformation shows how a productized data approach can bridge the gap between enterprise data platforms and on-the-ground commercial agility. With Axtria’s partnership, Gilead moved from managing data to mobilizing it, while creating the mindset for continuous innovation.
See what happens when data stops sitting in reports and starts driving every decision.
Get the full white paper to discover how data products help global teams act faster and win on the ground, where it counts.
FAQs
Data products are curated, reusable, and business-aligned data assets designed to serve specific functions such as sales performance, HCP engagement, or market access with built-in governance, business rules, and KPIs. Unlike static datasets or dashboards, data products are modular and insight-ready, enabling faster, more consistent decision-making across global and local teams.
Global pharmaceutical organizations operate across multiple markets with diverse data definitions, regulatory frameworks, and systems. Data products bridge this complexity by standardizing core data elements while allowing localization. This ensures a consistent “single source of truth” across affiliates improving transparency, compliance, and time-to-insight at scale.
Gilead partnered with Axtria to replace siloed systems with a unified, product-based data ecosystem. This enabled affiliates to access standardized KPIs and reusable data layers that could be tailored for local markets. As a result, decision-making became faster, data preparation time decreased, and front-line teams gained actionable insights directly aligned with their goals.
Organizations adopting data products realize measurable gains, including:
- Faster insight generation and analytics delivery
- Improved trust through governed, traceable data pipelines
- Reduced duplication and operational inefficiency
- Greater agility for AI, predictive modeling, and next-best-action use cases
Data products establish the structured, high-quality foundation AI models require. By embedding business context and rules within each product, organizations can deploy machine learning and agentic AI systems confidently, enabling automated insights, real-time decisioning, and scalable innovation across the commercialization lifecycle.
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