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Unified Data Governance Unlocks Efficiencies & Insights for a Pharma Giant

Read | Nov 27, 2024

AUTHOR(s)

A WNS Perspective

Key Points

  • Fragmented data systems, redundancies and a lack of centralized governance limited a global pharma leader’s ability to extract actionable insights and optimize operational efficiency.
  • WNS Analytics undertook a strategic overhaul, introducing a unified data governance framework, integrating datasets, automating quality controls and standardizing data definitions to drive transparency and alignment.
  • The intervention delivered measurable improvements in operational efficiency and resource use, empowering smarter, cost-effective decision-making through high-quality, readily accessible data.

This is our story of transforming data governance for a global pharma leader, ensuring the on-demand availability of relevant and high-quality data for strategic decision-making.

As we know…

Data accessibility is a formidable challenge for businesses. While companies are amassing and generating more data than ever, only a few can harness its full potential. A notable dichotomy prevails as most data producers and technicians focus on metadata, data quality and tracing data lineage. Simultaneously, the demand from data consumers for readily accessible information to address pressing business issues and drive decision-making intensifies. Organizations equipped with high-quality data must have this valuable resource at their fingertips to react swiftly to market changes, capitalize on emerging trends and gain a competitive edge.

The challenge for our client was…

Extracting meaningful business insights from its datasets scattered across multiple platforms. The absence of a centralized data repository and glossary hindered the timely retrieval of relevant information. Redundancies and duplications proliferated, with identical data appearing in diverse formats. Moreover, the lack of a mechanism for purging non-relevant and obsolete data led to an increase in storage and management costs.

In response to these challenges, the firm sought to strengthen pharma data governance by implementing a searchable, centralized and cost-efficient knowledge base to improve transparency and facilitate the ready availability of organizational knowledge.

Stepping in as a consulting and end-to-end data, analytics and AI partner…

WNS Analytics (WNS' data, analytics and AI practice) mobilized a team of data engineering experts to drive a unique solution and service comprising Artificial Intelligence + Human Intelligence. The engagement focused on enabling a pharma data governance transformation by bringing together proprietary data engineering frameworks, best practices and assets from our utility library, while working closely with the client to comprehensively re-engineer its data ecosystem. The journey began with a structured foundation for pharmaceutical governance, which included:

Assessing legacy complexities

by performing a complete inventory count of data assets and processes across platforms

Developing a roadmap

To guide the pharma data governance initiative, ensuring alignment with the client’s business objectives, regulatory expectations and long-term digital strategy

Ensuring full stakeholder buy-in

for effective data stewardship. This embedded transparent processes in data governance, improved data confidence and enabled continuous system improvement

Leveraging our extensive network of technology partnerships, WNS Analytics' data engineering experts implemented a holistic solution designed to operationalize unified data governance in pharma through the following strategic measures:

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Data Integration Platform

Implemented a robust data integration platform, dismantling the barriers of scattered, siloed data. In the process, we introduced data quality checks and cleansing procedures and established standards for data entry and maintenance.

Data Glossary

Built a comprehensive data glossary to standardize terms and definitions across the organization. This, in conjunction with a secure, automated data de-duplication tool, eliminated redundancies across the system.
 

Information Review System

Deployed an information review system, with the agreement of data owners, to periodically identify and eliminate non-relevant and obsolete records. These steps ensured robust data control, instilling greater confidence in decision-making.

Finally, we successfully delivered a robust data governance and data management program to plan and implement operational models. The program defined data strategy, standards and tools for enhanced data quality, compliance and measurable outcomes.

Strategic data integration and governance…

The pharma data governance transformation augmented our client’s operations, ensuring timely availability of high-quality data while driving significant operational efficiencies and cost optimization.

By onboarding multiple datasets into a robust pharmaceutical governance model, we enhanced data asset optimization and decision-making. Automation of numerous data quality rules saved substantial man-hours annually, reducing errors and increasing the precision of our analytical models.

Furthermore, the use of a unified platform helped identify redundant and interconnected data elements, leading to the development of more efficient storage solutions and substantial cost savings. This showcases how unified data governance in pharma can unlock improved efficiency and productivity across processes and people respectively.

Key measurable outcomes included:

 percent increase in operational efficiency by integrating 15 datasets into a structured and comprehensive governance model

 man-hours saved annually across suppliers by automating 683 data quality rules

 

Explore how WNS enables enterprise-wide efficiency through augmented data management and governance solutions.

 

FAQs

1. What is unified data governance and why is it critical for pharmaceutical companies?

As a WNS customer, unified data governance enables us to establish consistent data definitions, ownership, quality standards, and compliance controls across the enterprise. For pharmaceutical companies operating in highly regulated environments, this framework is critical to ensure data accuracy, transparency, audit readiness, and reliable insights for clinical, commercial, and regulatory decision-making.

2. How does centralized data management improve operational efficiency and decision-making?

Centralized data management provides a single source of truth across functions such as R&D, supply chain, regulatory affairs, and commercial operations. With WNS’s structured governance framework, we eliminate data silos, reduce duplication, accelerate reporting cycles, and enable faster, evidence-based strategic decisions.

3. What role does AI and automation play in enhancing data quality and accessibility?

AI and automation help us identify data inconsistencies, flag anomalies, automate validation workflows, and maintain real-time data monitoring. WNS’s intelligent governance tools enhance data accuracy, streamline cleansing processes, and improve accessibility—ensuring stakeholders have timely, high-quality information for critical business decisions.

4. How can a data glossary and standardization reduce redundancies across datasets?

By implementing a centralized data glossary and standardized definitions, we reduce ambiguity and eliminate redundant or conflicting data entries across business units. WNS helped us harmonize terminology and metadata structures, improving cross-functional alignment, reporting consistency, and overall governance maturity.

5. What measurable benefits can pharma companies achieve from implementing unified data governance?

Through unified data governance, we achieved improved reporting accuracy, faster analytics turnaround times, reduced manual data reconciliation efforts, enhanced regulatory compliance, and better strategic insights. The result is greater operational efficiency, stronger risk management, and improved decision confidence across the enterprise.