6 common data governance challenges and their solutions

Implementing data governance can be a complex and time-consuming process for organizations. Many struggle with resistance to change, lack of clarity on roles and responsibilities, and the delicate balance between data accessibility and security. Additionally, evolving regulatory requirements pose ongoing challenges for compliance.

Gartner’s research highlights common data governance challenges, including compliance audits (52%), warnings for non-compliance (40%), and data breaches (37%). When establishing data governance frameworks, organizations face hurdles such as talent management (62%), establishing data management best practices (58%), integrating data governance tools (43%), and lack of data leadership (21%).

As companies generate vast amounts of data, effective governance becomes crucial for extracting insights and gaining a competitive edge.

People-related challenges

Let’s dive into the key people-related challenges organizations face when implementing data governance and explore practical solutions to address them.

1. Cultivating better culture

Siloed departments and stakeholders pose obstacles to effective data governance collaboration and alignment, especially when coupled with employee resistance to adopting new data governance processes and technologies.

The solution: Cross-functional collaboration is essential for fostering an inclusive approach to data management. By encouraging teams to work together, organizations can break down silos and create a unified vision for data governance. They should also implement comprehensive change management strategies to manage cultural change and ensure employee engagement in new data governance initiatives and technologies.

2. Defining clear roles, responsibilities, and resource allocation

Various organizational departments have conflicting views on who is responsible for data governance. At the same time, limited funding and resources can hinder the implementation and maintenance of a robust data governance framework.

The solution: Establishing a dedicated data governance team or committee with clear roles and responsibilities is vital for success. This includes ensuring sufficient budget and resources to support this team, and providing it with an easy-to-use data catalog solution to lay the foundation for your efforts.

Process-related challenges

Now that we’ve addressed the people-related data governance problems let’s focus on the process-related hurdles that organizations often encounter in their data governance journey.

3. Ensuring data accuracy and uniformity

Data quality is fundamental to effective governance. However, inconsistencies in data can easily result in erroneous reporting and decision-making, leading to potential business losses and missed opportunities.

The solution: To solve this challenge, follow data quality methodologies, such as data profiling and cleansing, to guarantee precision and uniformity in data management. Implement foundational initiatives and capabilities, such as leveraging Master Data Management (MDM) in a single department or region, to establish a solid base for data quality improvement.

4. Sustaining monitoring and enhancement

As time progresses, neglecting routine assessment and improvement could lead to outdated and ineffective data governance processes, resulting in decreased data value and increased risks.

The solution: Implement ongoing monitoring and evaluation systems to track progress, assess achievements, and identify avenues for enhancing data governance best practices. The systems should be underpinned by clear key performance indicators (KPIs) for data governance that are regularly reviewed to ensure continuous improvement. It can also be helpful to encourage feedback from data users and stakeholders to identify pain points and further opportunities for enhancement.

Technology challenges

While people and processes are important to data governance, technology plays a vital role. Let’s examine the key technology-related data governance challenges and their solutions.

5. Ensuring security

Without the right data governance solutions, users will struggle to access required data securely, leading to potential data breaches or unauthorized access to sensitive information.

The solution: Implementing robust access controls and encryption technologies is crucial for maintaining data security while enabling necessary user access. Organizations must strike a balance between protecting sensitive data and ensuring authorized users can efficiently access the information they need.

6. Managing growth-related data governance scalability

When a business expands, its current data governance structure could come under pressure to accommodate increasing data volume and user base, leading to inefficiencies and potential compliance issues.

The solution: As organizations grow, their data governance methodologies and technologies must evolve to meet changing requirements. Scalability is essential to maintain an effective and efficient data governance framework in the face of mounting data volumes and user bases.

An ongoing journey

Addressing data governance issues is imperative for organizations to unleash their data potential and stay ahead in the data-driven landscape. By tackling issues related to roles, data quality, and security balance, you can lay a solid foundation for effective data governance.

Continuous monitoring, collaboration, and resource investment are vital for sustained data governance success. As industries evolve and new regulations emerge, adapting your data strategies is essential to ensuring ongoing compliance and integrity.

Remember that data governance is an ongoing journey that requires commitment from all levels of the organization. With the right approach and tools, you can transform data governance challenges into opportunities for enhanced data management and business success.