5 Critical Data Governance Truths Every Data Leader Should Be Aware Of

In today's digital age, data has become a valuable asset for businesses of all sizes. Companies are investing heavily in gathering, storing, and analyzing data to gain insights that can help them make informed decisions and improve their bottom line. However, despite the importance of data, many organizations struggle with its accuracy and consistency, which can significantly undermine their efforts.

According to a recent Experian survey, 69% of organizations reported that inaccurate data continues to be a major challenge for their business. The root cause of this problem is often the lack of a robust data management and governance strategy.

Data governance is a set of activities, processes, and policies designed to ensure that data is managed, stored, and used effectively and securely. It involves defining the roles and responsibilities of data stakeholders, establishing data quality standards, and implementing procedures for data access, use, and protection.

Data governance is vital for:

• Data ownership: Suppose you don't know who owns the data; you might be violating privacy laws or putting sensitive information at risk.
• Data quality: This refers to the accuracy, completeness, and consistency of your data. Poorly managed data can cause problems, from marketing campaigns to customer service interactions.
• Security: Data should only be accessed by authorized users. Thus, you protect it against hacks, cyberattacks, and leaks of information by employees.

The 5 Real Truths About Data Governance

Based on my experience, there are 5 truths about data governance:

1. Data governance is complex and cross-functional

Data governance is a multifaceted and cross-functional process that is challenging to explain. It requires deep know-how of the organization's data landscape and the roles played by business and technical stakeholders.

However, most organizations have low maturity for data literacy. Thus, it can further complicate the process.

The biggest challenge with data governance is the lack of clear ownership. Firms and technical stakeholders have joint responsibilities. However, sometimes it's unclear who is ultimately responsible for ensuring data accuracy and compliance.

It can lead to confusion and inefficiencies because different teams may have contrasting priorities and approaches to data governance.

2. Data governance is expensive but the risk of not doing (or half doing) it costs even more

Implementing a comprehensive data governance program comes with a significant price tag. As a result, firms can easily spend over US$1 million annually just on resources to maintain data integrity.

However, the risks associated with poor data governance are many, for instance, reputational damage, lost revenue, and more. Therefore, making decisions based on inaccurate data is costly, leading to poor business outcomes.

Suppose a company makes a strategic decision based on flawed data; it could result in wasted resources, lost revenue, or even a failed project. The cost of fixing the mistake and course-correcting can be much higher than the cost of implementing proper data governance.

3. Data governance is NOT just about data. It is about people, processes, and technology, too

Data governance is misunderstood to be solely about data. However, it's vital to understand data governance is about components, each playing a crucial role in ensuring data is managed effectively and efficiently.

• People: Suppose people don't care about or don’t understand their data. It means managers need to take ownership of their data governance efforts and inspire others to take pride in their work.
• Process: Processes need to be in place to ensure key items like data security and cleanliness are maintained. For instance, establishing policies and procedures for data management and implementing checks and balances for accurate and up-to-date data sets.
• Technologies: Technology is an enabler in scaling and automating repetitive tasks. Implementing software for data management and integrating data governance into existing systems and workflows is critical for success.

4. Your data governance program needs to have measurable and understandable KPIs

A good data governance program is one with KPIs. The KPIs should be specific, measurable, and understandable by everyone in the organization. By measuring these KPIs regularly and providing timely feedback, managers can determine whether their efforts are paying off or not. They can also communicate value metrics to key executives.

KPIs enable organizations to prioritize their resources on the most valuable data assets. Thus, firms can focus on improving the quality of their most critical systems and processes before focusing on less critical ones.

5. Proper data governance is the foundation and enables your organization to realize massive ROI from analytics investments

When a firm confides in its data, everything from business reporting and predictive analytics to artificial intelligence gains traction and adoption because people trust the output.

For instance, when data is properly governed, business leaders have greater confidence in the accuracy and reliability of the insights provided by analytics tools. Therefore, it leads to better decision-making, improved operational efficiency, and increased revenue.

We have seen organizations realizing massive ROI of up to US$ 240 million annually due to proper decisions. In addition, data governance helps identify and mitigate risks associated with data privacy, security, and compliance.

Conclusion

Investing in data governance is crucial for organizations to manage their data effectively and efficiently. It helps ensure compliance with regulatory requirements, maintain data quality, improve data security, and achieve ROI on analytics investments.

By providing accurate and reliable data, organizations make better-informed business decisions and facilitate collaboration among different departments and stakeholders. Therefore, investing in data governance is a smart move that can help organizations maximize the value of their data assets and achieve their business goals.

There is no better time to start than now!

About the Author

Gabriel Keeler is Managing Director at Evalueserve. He currently leads the commercial relationships for insights, advisory, and data analytics for the Industrial, Transportation, Consumer Goods, and Food verticals. He has been with the company for 10 years and has held client-facing roles for most of his tenure that support his client’s growth.

Keeler completed his studies in business, international relations, and Spanish at the University of Denver and currently resides in Raleigh, North Carolina with his wife and two daughters.