The Path to Enterprise-Wide Intelligence

By partnering with Sorcero, the company moved beyond fragmented, siloed data to implement an integrated AI strategy that positions the platform as the single enterprise-wide solution for evidence-based insights across the company. The core objective was to shift the focus from long-term, lagging indicators that take years to materialize to immediate, measurable links between Medical Affairs efforts and changes in stakeholder behavior. This transition empowers the company to tell a more compelling value story and make strategic decisions with agility.

 

 

The Medical Affairs team faced a fundamental "chicken or egg" scenario where its strategic goals required robust data, but the existing data was too fragmented and inaccessible to drive effective decisions. Crucial information—ranging from qualitative observations to field insights—was often trapped on individual laptops or within disparate SharePoint folders rather than being stored in a central, analyzable repository. This lack of centralized infrastructure hindered the organization's ability to gain a complete picture of its therapeutic landscape and left leadership relying on tedious, manual review processes.

 

Compounding these infrastructure issues was a significant AI readiness gap. Internal leadership explicitly recognized that the organization's processes were built around outdated surveys and dashboards that failed to provide the necessary depth of insight. Furthermore, the existing internal data ingestion process was a major threat to value realization, typically taking 4–5 weeks to set up secure exchanges, ingest data, and provision access. This lag time led to stakeholders becoming disconnected from their analytical systems, creating an urgent need to deliver immediate value.

 

Finally, the organization struggled with limitations of their existing agency partners. They were found to be either stretched too thin or reliant on manual processes that limited their ability to execute a robust Data, Analytics, and Insights Strategy. These factors left the team "having a hard time getting started," necessitating a new approach that prioritized speed, methodology, and expert guidance.

 

To overcome these obstacles, a data strategy was implemented that started with a focus on external data to deliver immediate value while internal data integration was managed in parallel. In addition, the limitation of agency partners was overcome with the shift to an AI-powered operational model.

• Accelerating Time-to-Value: The program initially prioritized external congress, social media, news, and publication data to deliver immediate insights and illustrate the "Art of the Possible" through out-of-the-box Key Information Topics (KIT) and Key Intelligence Questions (KIQ) reports.
• Advanced Infrastructure Integration: The solution leveraged the company’s existing Snowflake and Databricks data stores, working toward a future state where the company performs data joins in their transformation layers before pushing analytics-ready data to the platform.
• Data Engineering Support: To bridge the gap in resources, Sorcero provides data engineering support, preparing data into a form that lends itself to more impactful insights mining and maintaining technical momentum during critical launch phases.
• Legacy Agency Displacement: By absorbing complex report generation work formerly handled by partner-led manual processes, the company has created a direct path to displacement of legacy agency services while gaining a superior, AI-powered system of action.
• Strategic Advisory: Beyond just technology, Sorcero advised on the overarching Data, Analytics, and Insights Strategy to serve as a collaborative partner in the company's AI transformation.
  
  

 

The partnership has successfully transformed the organization's internal influence and financial outlook on AI and their insights program.

 

The evolution of the company from a "disconnected" state to AI readiness serves as a generalizable blueprint for medical strategy in the pharmaceutical industry.

By focusing on Data Coverage, Methodology, and Organizational Alignment, the company transitioned from a team struggling to find its footing to one that models the right behaviors and develops a laser focus on patient needs by efficiently translating complex scientific evidence from all relevant sources into clinical practice.