Data is likely your organization’s most valuable asset — or, at least, it could be. But chances are that it’s also one of your most underused and underappreciated assets.

    Every data source has the potential to yield a rich store of information that could advance your business goals and enhance performance across your company. A recent study by BCG and Google demonstrated how maximizing the value of your data can drive revenue growth, improve organizational resilience, and unlock new opportunities with AI.

    Yet, perhaps counterintuitively, the more data you have, the less value you’re likely to obtain from it.

    How can that be? The more data you have, the more you need to manage, and the more difficult that management becomes. It’s hard to keep track of where your data is and what it means. Some data sources may not be compatible with other platforms or formats. This can lead to conflicting interpretations or, worse, ignoring your data because it’s just too complicated and costly to untangle. Ultimately, the unmanaged pile of data impedes your organization’s ability to make decisions or pivot in response to new information, putting you ever further behind your competition. Instead of being an asset, ungoverned data is a burden.

    Data governance is the key to building a strong data foundation and unlocking the value of your data. Using the following best practices, you can build a robust data governance framework that will help your organization improve the quality of its data and, in turn, give you access to the insights buried within.

    10 data governance best practices

    Creating a strong data governance framework can help your organization improve its data quality, integrity, and security — and, in turn, simplify compliance and eDiscovery while also making it easier to extract business value from that data.

    Here are 10 data governance best practices to follow as you establish your organization’s data governance program.

    1. Set clear objectives for your data governance program

    What are you hoping to achieve with a data governance framework? Clearly articulating your program’s goals is a foundational step. For example, you might want to improve data accuracy and accessibility, train large language models (LLMs) on proprietary data, or mitigate risk with proactive data management initiatives. Consider the specific needs of your organization, your strategic priorities, and any relevant industry regulations when defining these objectives.

    Write your objectives so they are measurable and define the metrics you will use to assess your progress. Early clarity on what you want to achieve and how you measure success will guide subsequent decisions, ensuring that your data governance efforts align with your organization’s broader goals.

    2. Assign accountability

    Data governance isn’t just the mandate of the IT team, nor is it the sole responsibility of the legal department. Everyone must work together to make data governance an organizational priority.

    Creating a data governance council can ensure representation from all lines of business plus those stakeholders responsible for compliance, eDiscovery, and other data-related concerns. The council should be responsible for making key decisions, resolving conflicts, and updating the framework.

    3. Secure buy-in from company leadership

    Obtaining buy-in from executives is essential to the success of any initiative. Executive sponsorship not only ensures you have the resources necessary to support your program but also signals a commitment to prioritizing data governance throughout the organization. Establishing a direct line of communication can also help you overcome potential challenges during implementation.

    To boost executive buy-in, emphasize how effective data governance improves corporate decision-making, regulatory compliance, and operational efficiency.

    4. Create a data map

    You can’t optimize your data if you don’t know where it is. Create a comprehensive data map that outlines where your data is stored, how it flows through various systems, and how data sets are related to one another. This visual representation not only enhances transparency but also aids in identifying potential data risks and dependencies.

    A well-crafted data map enables better decision-making, risk management, and strategic planning. Regularly update the data map to reflect changes in data infrastructure.

    5. Monitor for compliance with applicable laws and regulations

    Your data governance policies must account for an evolving landscape of data protection laws and regulations, including the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), the California Privacy Rights Act (CPRA), the Health Information Portability and Accountability Act (HIPAA), and more, depending on your jurisdiction and industry. Determine what legal standards govern your business and keep tabs on new developments to ensure you maintain compliance.

    6. Set data quality standards

    Setting data quality standards is a cornerstone of effective data governance. High-quality data is crucial for making informed decisions, conducting accurate analyses, and supporting various business processes. Poor data quality can lead to errors, inefficiencies, and misguided decision-making.

    Generating and maintaining high-quality data is an ongoing process that involves multiple steps, including data profiling, cleansing, validation, and monitoring. It starts with clearly defining the acceptable levels of data accuracy, completeness, timeliness, and consistency, then taking measurements to verify that your data meets these standards — or correct it if it doesn’t.

    7. Establish a data classification system

    A data classification system is crucial for safeguarding sensitive information. From your data map, clearly define the data categories within each source based on sensitivity and criticality. Use these classifications to establish appropriate handling and protection for sensitive data. Implement tailored security protocols and access controls based on each classification to mitigate the risk of unauthorized access and potential data breaches and ensure compliance with legal requirements.

    8. Create and follow a records retention program

    Remember that more data is not better. Establish a records retention program to systematically dispose of data as it reaches the end of its useful life. Start by determining what you must keep and what you can dispose of according to applicable legal and regulatory requirements and industry standards. Once you understand what is required, you can develop comprehensive policies covering each type of data throughout its entire lifecycle, including creation, processing, storage, archiving, and disposal.

    9. Engage employees with ongoing training

    To be effective, data governance must be part of your organizational culture; all employees must understand their role in upholding data integrity and security. Regular training sessions enhance awareness and empower employees to contribute to your organization’s data governance efforts.

    Your training program should cover key aspects of data governance, including data security, privacy compliance, and best practices. Ongoing training will build a workforce that prioritizes responsible data management.

    10. Review and update all elements of your data governance framework

    Data governance is never finished. It is a dynamic process that requires regular attention and adaptation to changing circumstances. Don’t settle for a static approach; instead, aim for continuous improvement. Regularly assess the effectiveness of your policies, considering changes in laws, regulations, and available technology. Establish a feedback loop that incorporates lessons learned and evolving requirements to keep your data governance policies aligned with your organization’s evolving needs.

    Transform your data into a strategic asset

    A data governance framework balances business needs, legal compliance, and technological efficiency. IT, compliance, and legal professionals must collaborate to create policies that meet regulatory and legal requirements while building a culture that appreciates the value of enterprise data.

    Are your data governance practices up to the task? Take our data governance assessment to find out! If your score isn’t as high as you’d like, get in touch to learn how Onna can help your organization establish a strong data foundation, turning data from a burden into a strategic asset.

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