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Inform Online – Deploying Enterprise Search to a Large Scale Pharmaceutical Company (Pfizer)
Pfizer’s Enterprise Search Deployment: Tales from the Inside
How a Global Pharmaceutical Leader Transformed Information Access at Scale
Pfizer is one of the world’s most recognized biopharmaceutical companies — a global organization of more than 90,000 employees and contractors operating research, clinical, regulatory, manufacturing, and commercial functions across dozens of countries. The information management challenge at that scale is not theoretical: research scientists needing to surface prior findings across a vast internal knowledge base, regulatory teams navigating hundreds of thousands of documents across multiple submission systems, and knowledge workers throughout the organization losing hours every day to search experiences that were not built for the complexity of a global pharmaceutical data environment.
In this session, Bill, a key leader in Pfizer’s information management organization, walks through that journey from the inside — the problems that drove the search initiative, the evaluation and selection process, the deployment experience, and the lessons that Pfizer would carry forward from what worked and what required adjustment.
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Session from Inform Online 2020
What the Session Covers
The Case for Change: What Keyword Search Was Failing to Deliver at Pfizer
Pfizer’s information landscape includes scientific literature databases, regulatory submission repositories, clinical data systems, research knowledge bases, and the accumulated output of decades of pharmaceutical discovery programs, stored across systems that were built independently, indexed inconsistently, and accessible only to employees who knew exactly which system to search and exactly how to query it. The session begins with the honest articulation of what this fragmented search experience was costing: the time researchers spent navigating between systems, the findings that were missed because they existed in a system that did not surface in the search path a scientist followed, and the organizational awareness that the current state was meaningfully limiting knowledge worker productivity and research efficiency.
Selecting Sinequa: How Pfizer Evaluated Enterprise Search at Scale
The session provides a practitioner account of Pfizer’s vendor selection process, a rigorous evaluation that any organization of this scale must conduct before committing to a platform that will be deployed to tens of thousands of users and connected to the full breadth of sensitive research, regulatory, and operational data. The session covers the criteria that drove Pfizer’s evaluation: the business cases they needed the platform to address, the technical requirements around security and access control in a GxP-regulated environment, the scalability requirements for a global deployment, and what ultimately differentiated Sinequa in a field that included other enterprise search and insight engine vendors. This evaluation account is directly applicable to other pharmaceutical organizations currently navigating a similar selection process, the criteria Pfizer used are the criteria any large pharma organization should be asking.
Deploying at Scale: What the Implementation Actually Looked Like
The deployment account is the most distinctive part of this session and the primary reason it remains valuable years after recording. Enterprise search implementations at the scale of a global pharmaceutical company involve organizational challenges that vendor documentation does not cover: how to manage data onboarding across hundreds of source systems with varying data quality, access control architectures, and content governance maturity; how to drive adoption among research and knowledge worker populations with different search behaviors and information needs; how to sequence the deployment to maximize early value while managing the complexity of a full-scope rollout; and how to handle the inevitable moments when the production environment surfaces gaps that the pilot did not reveal. The session covers these deployment realities with the candor of a practitioner who lived them including what Pfizer would do differently and what they would do exactly the same.
Lessons Learned: What Pfizer Shares with Organizations on a Similar Journey
The session closes with the distilled lessons from Pfizer’s deployment experience, the insights that the team accumulated through the selection, implementation, and post-launch phases that they are willing to share with the broader enterprise search community. These practitioner lessons are not available in vendor case studies or analyst reports; they come from the people who made the decisions, managed the organizational change, and are accountable for whether the deployment delivers its intended value.
Frequently Asked Question
Pfizer’s selection process, as described in this session, illustrates the key criteria that any large pharmaceutical organization should apply. The primary technical criteria for pharma include: GxP compliance architecture — the platform must support the audit trail, validation, and access control requirements that regulated pharmaceutical workflows require; security and data governance — access controls must be enforced at the retrieval layer based on source system permissions, not as application-level filters; scalability — the platform must handle the data volumes of a global pharmaceutical organization without degrading retrieval quality as the connected data environment grows; and semantic search quality — the platform must understand pharmaceutical and scientific terminology with sufficient precision to surface relevant results for complex research queries that keyword search cannot handle. The organizational criteria are equally important: the platform must support the change management required to drive adoption among research and knowledge worker populations with different search behaviors, and it must provide the analytics and adoption metrics that allow the team to demonstrate ROI to leadership throughout the deployment.
GxP (Good Clinical Practice, Good Manufacturing Practice, Good Laboratory Practice) regulations impose specific requirements on information systems used in regulated pharmaceutical workflows that standard enterprise deployments do not face. In a GxP context, enterprise search must support: audit trail requirements that record who accessed what information when, and what searches they conducted; validation requirements that demonstrate the system functions as intended and changes are controlled; access control architecture that enforces need-to-know boundaries with the rigor that regulatory submissions and clinical data require; and data integrity standards that ensure the information the search system surfaces is accurate and from authorized sources. Sinequa’s platform is designed to meet these requirements through early-binding security enforcement, comprehensive audit trail capabilities, and deployment architecture options that support the validation workflows pharmaceutical IT and compliance teams require. The Pfizer deployment, conducted in a fully GxP-aware context, demonstrates these capabilities in one of the world’s largest and most compliance-scrutinized pharmaceutical environments.
The most transferable lessons from Pfizer’s deployment account fall into four categories. First, the importance of getting the selection criteria right before beginning an evaluation: Pfizer’s session demonstrates a rigorous evaluation process that identified the right platform for their specific environment — organizations that approach enterprise search selection as a commodity procurement tend to discover the gaps in the evaluation only after deployment. Second, the organizational change management requirements are as important as the technical implementation: driving adoption among research and knowledge worker populations in a global pharmaceutical organization requires deliberate investment in training, change management, and the feedback loops that identify where the deployment is not meeting user needs. Third, sequencing matters — the order in which data sources are connected and use cases are enabled affects how quickly the deployment delivers value and how easily organizational resistance is managed. Fourth, the investment in getting the data governance and access control architecture right before scale is not overhead — it is the foundation that determines whether the platform can be extended to AI capabilities without rebuilding from scratch.
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