5 Key Benefits of Data Governance

Data Governance Is Essential for Driving Innovation and Impact

Effective data governance not only ensures data privacy and compliance with regulations, but also helps organizations generate revenue, achieve business goals, and gain a competitive edge.

What Is Data Governance?

DAMA International defines data governance as “the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.” According to Kelle O’Neal, founder and CEO of First San Francisco Partners (FSFP):

Data governance is the mechanism that creates trust in the data.

Good governance creates this source of truth by weaving existing business functions and formalizing them in a data governance framework. Through leadership support and buy-in across the company, organizations can align on governance roles, policies, and procedures and use them to achieve business outcomes.

While data management handles day-to-day operations, data governance transforms how organizations leverage their data assets over the long term. Read more about data governance vs. data management.

The Value of Data Governance

Proper data governance enables you to know your data, says O’Neal. According to recent research, 58% of organizations that invest in governance initiatives and mature their practices see measurable results, reporting improved data quality, reliable analytics, and more actionable insights.

Getting started with governance can nonetheless be a challenge. Robert S. Seiner, president and principal of KIK Consulting, notes that some organizations implement stand-alone governance programs, only to get slowed down by endless approval loops or people who don’t understand the crucial role of governance in business operations.

What’s more, a poor understanding of where innovation occurs in organizations can lead to poor data governance, says O’Neal. Business leaders may try to “boil the ocean” instead of implementing governance more gradually.

When governance is “applied intentionally and practically,” says Seiner, it consistently provides opportunities for valuable insights and business performance. Achieving these results demands skilled governance leaders and professionals who know how to implement data governance best practices effectively.

Reap the Benefits of Data Governance

Developing a successful data governance program offers multiple benefits, from improving data quality and establishing data ethics to enhancing strategic decisions and operational efficiency. Below are a few of the top benefits of data governance:

1. Data Quality

The primary benefit of data governance is better data quality, the degree to which information is accurate and fit for doing business. Governance frameworks achieve this by supporting metadata management, the policies and systems that standardize how data is described and understood. O’Neal explains that clarity about “what data exists, where it is, what it means, and how it can be used” enables organizations to discover and classify data quickly.

Seiner adds that formalizing a strong data governance framework leads to unlocking “visibility into data assets, with confidence in the data lineage and meaning of the data.” Moreover, leveraging this visibility and existing domain expertise “accelerates the ability to innovate faster–with less risk and fewer surprises.”

Real-world example: Feeding America created a transparent business glossary, standardizing definitions across thousands of programs and enabling legislators to better understand food insecurity data.

2. Data Ethics

Data governance processes establish data ethics, a code of behavior providing a trustworthy business climate and compliance with regulatory requirements. The IAPP calculates that 79% of the world’s population is now protected under privacy regulations such as the EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). This statistic highlights the importance of governance frameworks for risk management and customer trust.

Governance creates “repeatable standardized processes with clear accountability” across the data lifecycle, says O’Neal. This standardization ensures ethical data handling while enabling innovation. The resulting level of trust prevents what Seiner describes as “bias, inconsistency, and junk data” from compromising machine learning models and advanced analytics initiatives.

Real-world example: Delta Dental Michigan (DDMI) extended its governance structure to AI requests through standardized guardrails, effectively implementing valuable use cases while preventing problematic ones.

3. Better Communication

Without robust governance, business teams may struggle with miscommunication and data duplication. Seiner describes a client that had three departments produce different versions of the same customer report – with slightly different definitions. An effective governance program would avoid this issue by “improving communication between IT, compliance, legal, and business functions, reducing redundancy and helping people solve problems faster,” he says.

Data governance frameworks recognize data governance roles and responsibilities and streamline processes so that corporate-wide communications can improve. This systematic approach sets up businesses to be more agile, increasing the “freedom to innovate, invest, or hunker down and focus internally,” says O’Neal.

Real-world example: Freddie Mac developed a solid data strategy that streamlined data governance communications and later had the level of buy-in for the next iteration.

4. Data-Driven Decision-Making

Companies with a successful data governance plan benefit from comprehensive support that empowers confident decision-making. O’Neal stresses that “data governance is the best path to trusted analytics and AI,” enabling organizations to leverage data effectively across all levels.

With a complete picture of business activities, challenges, and opportunities, data governance creates the flexibility to respond quickly to changing needs. This allows for better self-service business intelligence, where business users can gather multi-structured data from various sources and convert it into actionable intelligence.

Non-invasive data governance frameworks, which organically integrate governance into existing workflows, can achieve even greater adaptability in their decision-making. As Seiner observes, this type of governance “improves outcomes and enables better business decisions.”

Real-world example: In 2022, the United States Transportation Command (USTRANSCOM) leveraged strong support for a data strategy and the resulting governance implementation, a business glossary, to advance its logistical decision-making.

5. Operational Efficiency

An effective governance program drives operational efficiencies that directly impact data activities and “indirectly [impact] how people leverage data in their work,” says O’Neal.

Moreover, O’Neal notes that governance allows companies to optimize what they already have rather than hiring new data scientists and investing in new applications. With the increased operational agility provided by a data governance framework, organizations find they can “reuse data assets confidently, share insights across teams, and pivot faster in response to market changes.”

Real-world example: Becks Hybrids educated business professionals about their data governance services, leading to quicker turnaround times for queries after their data architecture upgrade.

How Your Industry Can Benefit from Data Governance

From banking to retail to government, a wide range of industries can benefit from implementing elements of data governance.

Banking/Finance

Banking thrives on customer trust and data security. As Seiner points out, data governance in banks leads to streamlined communications, “reducing redundancy and helping people solve problems faster.” This reduces operational risks while enabling smarter business intelligence. American Express exemplified this approach by transparently demonstrating its data governance value to executives and stakeholders.

Energy

To overcome challenges with data silos, energy supplier E.ON implemented data governance as a service. The company created clear standards and roles that maintained compliance with industry regulations while supporting continued growth and innovation in renewables.

Insurance

As the insurance industry adopts AI and blockchain technologies, governance can help prevent fraud and support efficient claims processing. This enables both innovation and security, ensuring the right claims are processed at the right time. A top-50 property and casualty insurance carrier implemented data governance and accelerated revenue growth while strengthening regulatory compliance.

Utilities

Utilities face increasingly severe weather challenges that demand a proactive approach. Through governance-supported predictive maintenance and analytics, organizations can anticipate and address issues before they impact service. This results in efficient responses while maintaining business continuity. For example, one of the largest electrical providers in the world implemented a well-governed data program that empowered real-time insights and improved forecasting of energy needs.

Retail

Retailers leverage data governance to provide personalized customer experiences while protecting privacy and managing inventory. Abercrombie & Fitch, a clothing retailer, demonstrated this approach by increasing accountability and transparency, establishing an empowered governance practice.

Government

Government agencies use data governance to balance transparency with protection. This enables open data initiatives while ensuring sensitive information remains secure and citizens trust government services. Estonia exemplifies this transformation by setting up solid data governance foundations, roles, responsibilities, processes, and an X-Road service bus. This approach sped up business innovations.

Data Governance Advantages for Small, Mid-Sized, and Enterprise-Level Organizations

While businesses across all industries benefit from data governance programs, the size of an organization will determine specific needs and considerations.

Small Businesses

Smaller organizations may see governance as a resource drain, but customized governance models can enable them to accomplish more with less. By combining automated governance tools with non-invasive processes, these businesses can efficiently manage data quality and leverage generative AI. This will help unlock new revenue opportunities from existing data. Read more about data governance and generative AI.

Mid-Sized

Mid-sized companies face unique data governance challenges as they scale rapidly, with different teams developing their own data practices and definitions. This natural growth leads to communication silos between technical and business units, creating confusion over data meanings and anxiety about system changes.

By applying systematic governance and a data governance maturity model, mid-sized organizations can bridge communication gaps and align teams naturally. These governance efforts enable better stakeholder management and self-service capabilities through a shared data language, turning potential issues into opportunities for innovation.

Enterprise

Enterprise organizations require adaptive governance solutions to address complex integration across teams, processes, and technologies. Success comes from balancing top-down governance for compliance and unified data assets with bottom-up approaches for real-time decision-making.

This flexible framework reduces IT costs while empowering business teams through improved self-service. The resulting data quality management enables quick responses to opportunities, smarter privacy decisions, and greater agility during business changes.

How to Accelerate Your Data Governance Success

Successful data governance happens when employees across the organization lean into their governance responsibilities, understand the latest data governance policies and principles, and contribute to a smarter, more innovative culture. Accomplishing this objective requires continuous education – through data governance courses, certification, and conference attendance.

Empower Your Team with Data Governance Training

Whether you’ve just started exploring a data management career path or you are a seasoned data governance lead, DATAVERSITY offers on-demand courses to help you build your data management skills. Below are some of the most popular data governance training options:

• The Data Stewardship Learning Plan highlights how data stewards can embed existing governance practices into current projects.
• The Data Governance Learning Plan helps build fundamental knowledge of a data governance program.
• The Next-Generation Data Governance Learning Plan goes beyond the basics, guiding data governance professionals on the next stage of their journey.

Validate Your Experience with Industry-Recognized Certifications

Emerging technologies and changing regulations require a data-driven approach, gained through appropriate knowledge and skill sets. Training to become a certified data governance professional helps both individuals and entire organizations stay competitive.

Gain Real-World Insights at Data Governance Conferences

For organizations with limited resources, keeping up with the latest data governance tools and trends can be a challenge. DATAVERSITY’s data governance-focused conferences allow executives and practitioners to learn practical applications, collaborate with experts and peers, and stay up to date on the hottest topics – such as AI governance best practices and how to become a certified data management professional – in the ever-evolving data management field.