Healthcare and life sciences organizations face a flood of data. The volume of information continues to grow exponentially from all sides – electronic health records, clinical trials, mobile health, and more. Implementing a comprehensive data governance strategy is not a “nice-to-have,” but an absolute necessity given pressing concerns around data quality, security, and compliance.

Unfortunately, many pharma, EBPs and MedTech companies are struggling to establish a formal data governance strategy. Without it, organizations are unable to manage the influx of information or gain optimum value from it.

When done effectively, however, data governance provides the foundation to harness data for competitive advantage and decreased risk. The key is starting early in a cross-functional effort guided by strong change management, so that everyone across the organization understand how good data management can benefit everyone.

The Glowing Opportunity

A data governance strategy establishes who is accountable for information across the enterprise. It covers policies, procedures, data quality standards, and everything else needed to manage data as a valued business asset. It is ideally the foundation, put in place before choosing technologies and operating models.

Unfortunately, research shows most life sciences companies have partial or no data governance in place. This prevents gaining a unified view of information, hampers data quality, and introduces security issues. A recent IQVIA survey found that only 31% of pharma companies have a fully implemented data governance strategy, leaving nearly 70% with either a partial strategy or none at all.

According to a recent Gartner^® report, “Data and analytics governance is essential in this data-driven business era. The Gartner Chief Data and Analytics Officer Agenda Survey for 2023 indicates that 35% of the respondents see data and analytics governance as the most important key for success — the top ranking. Without trusted data, even the best of models and algorithms will fail to deliver results.”¹

However, organizations that embrace modern data governance practices are poised to thrive with these distinct advantages:

• Consistent data across the board. Helps different groups avoid redundant, fragmented, or conflicting data sets. This makes getting a unified view of information easier across systems and business units. The less confusion, the better!
• Improved data quality. Data quality is maintained and consistently improved over time. Data is more accurate, complete, and up to date.
• Stronger security. Sensitive data like patient information is more secure with strong governance controls for security and access.
• Ready for analytics. High-quality data is better for performing analytics to drive actionable, trustworthy business insights.
• Error-proofing. Governance can prevent errors and inconsistencies in the first place, which can mean less time and money spent correcting data issues.

Understand Where Your Business Is Now and Where It Wants to Go

As we said, most organizations merely have informal data management practices in place with a focus on improving efficiency and adding value. Too often, data governance is seen as solely an IT function rather than a collaborative enterprise-wide effort.

A cross-functional approach – including data owners, data subject matter experts (SME’s), and data stewards across the enterprise – is the better way to go because it increases knowledge and builds engagement. When developing or updating your data governance strategy, pull together a multi-functional team to collaborate on answers to these questions:

• What is your business landscape? Understand your organization’s vision, goals, and where your strategic positioning is taking you. This is crucial to lay a strong data foundation to effectively explore technology trends like the GenAI wave.
• Who is taking care of what data and where are decisions made? Identify key data owners and stewards across business units. Who is generating, consuming, and making decisions with data?
• What data sources are important? Catalog core data assets. Prioritize sources like R&D data, manufacturing data, clinical trial data, patient data, commercial data and so forth.
• What are the critical needs of different business units? Ensure that data governance goes beyond the enterprise level to address unique local needs as well.

Build Excitement with Change Management

For data governance to work, it requires buy-in across the organization, including at the highest levels of leadership. There must be clear ownership, accountability, and stewardship of data across functions, not just in a siloed fashion.

Change management is critical because a data governance strategy will introduce new policies, procedures, tools, and culture changes. Organizations must ask key questions such as: How will we strategically implement these changes? How can we get buy-in across the organization? What training is needed for adoption? Some of the steps include:

• Starting with the status quo, holding value workshops, interviews, stakeholder mapping
• Understanding the change impact to different functions, accounting for global vs. local circumstances, and aligned to business strategy
• Determining the adoption strategy for building excitement to help employees understand why a good data strategy matters
• Get executive sign-off to make sure that the top leaders will be walking the talk

With the right foundation, everyone benefits from high-quality data.

The Payoff of Data Governance for Life Sciences Companies

• More trusted data for smarter decisions
• Regulatory compliance and decreased risk
• Increased access to high-quality data
• Foundation for data-driven innovations like AI/ML and GenAI
• More value from analytics investments

The healthcare data storm is intensifying. Organizations lacking data governance will struggle with quality and security while missing growth opportunities. Now is the time to take control and maximize your data advantage.

¹ Gartner, 2023 Data Science Must Rely on Data and Analytics Governance to Produce Trusted Results, 4 July 2023. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.