Do you know where to find specific data in your business or who to contact for that data?
Modern businesses know that making data-driven decisions is critical to improving their bottom line. A strong data governance strategy saves time and money by improving data quality and making it easy for teams to get the information they need. By following data governance best practices, you can reap the benefits of implementing the best data governance framework for your business.
What is data governance?
Data governance is the set of processes that make sure data meets business standards and rules as it’s entered into a system. It lets businesses control the management of data assets. Data governance involves three aspects that make sure data is usable, accessible, and fits its intended use:
A data governance plan is important for different types of organizations and industries. It’s especially important for those that have regulatory compliance, such as finance and insurance. To meet compliance regulations, organizations must have formal data management processes in place to govern their data throughout its lifecycle.
While data governance is a key focus for many organizations, not all strategies return the anticipated results.
Best practices for data governance
Following strong data governance practices means your business gets the most from a data governance strategy. We know what methods work best when building a data governance policy.
When developing your data strategy, one of the best data governance tips is to first focus on people, then refine processes, and finally integrate technology.
1. Get business stakeholders on board
To begin creating the best data governance strategies, you need executive buy-in, but getting a green light is just the start. You also want to inspire stakeholders to take action so your governance plan is adopted across your organization.
The best way to get executives excited about your plan is to build a business case for your data governance practices. By building a business case, you show leadership the specific benefits they can expect from a data governance strategy.
2. Data stewardship
Data governance practices are only successful when roles, responsibilities, and ownership structure are clearly defined. Defining the data governance roles of team members across your organization creates the framework on which a governance plan runs.
The goal of data governance is to improve data quality and collaboration between teams. It needs input and data ownership from all parts of your organization. While each organization’s data governance structure will look slightly different, there are a few key players to use in your framework:
Data governance council or board: This team oversees the entire governance strategy. They help guide the data governance plan through strategic suggestions, typically prioritize aspects of the strategy, and approve new policies.
Tactical team members: Members of the tactical data governance team develop data governance strategies based on the council’s suggestions. They create the data processes and policies that are then approved by the data governance council.
Owners: Data owners are the team members responsible for specific data. They are the person of contact when someone needs a certain type of data. For example, if you need last month’s sales information, you contact the sales data owner.
Data users: Team members actively inputting and using data as part of their regular work responsibilities.
Putting the right people in the right roles is one of the best practices for data management, especially when creating a data governance framework.
3. Data quality management
Your business needs data quality management to create the best data governance strategies. It enables you to harness the full potential of your data assets for informed decision-making, competitive positioning, and customer satisfaction. By guaranteeing consistent, secure, and credible data, your organization can unlock numerous benefits contributing to your success in today's dynamic marketplace.
Data governance is pivotal in unlocking better data quality by creating systems promoting actionable, accurate, and complete data. It empowers your business to adapt swiftly to evolving market trends and customer preferences. Your business can enhance the customer experience by delivering personalized communications, promotions, and customer service interactions.
High-quality data is needed for informed decision-making, and having it means you can confidently navigate any challenges your business faces and achieve your objectives.
4. Use metrics to measure progress
As with any change, it is critical to measure progress and display the success of your data governance program. Once you have executive sponsorship from your business case, you need data to support each step you take. Plan on defining your metrics before you start introducing data policies. This lets you set a starting point based on your current data management practices.
Track your progress using the original metrics regularly. Not only does this show how much progress has been made, but it serves as a checkpoint to make sure your data governance best practices are effective in practice and not just in theory. A plan that’s flawless on paper may not transfer to real life as well as you hoped. It is important to keep a close eye on your governance strategy and be flexible regarding adjustments and improvements.
5. Data security and privacy
When creating your data strategy, it is crucial to make sure your business’s data is safe and private. Data security practices protect data against unauthorized access, alteration, or destruction. Encryption techniques, access controls, and authentication mechanisms are commonly employed to mitigate risks associated with data breaches. Additionally, organizations often implement firewalls, intrusion detection systems, and data loss prevention solutions to bolster their defense mechanisms against external threats.
Data privacy concerns the ethical and legal obligations surrounding the collection, use, and disclosure of personal data. With more data-driven technologies available and the increasing volume of personal information collected by organizations, customer concern about privacy continues to grow. Organizations must adhere to established privacy regulations such as the GDPR (General Data Protection Regulation) in Europe or the CCPA (California Consumer Privacy Act) in the United States. Complying with these regulations means implementing privacy policies, data anonymization techniques, and consent management procedures to protect customer’s privacy.
The best data governance strategies establish clear guidelines for data usage and dissemination for accountability purposes and to foster responsible data stewardship. The best way to handle security and privacy in a data governance plan is through transparent communication regarding data practices, along with regular audits and assessments.
6. Encourage frequent communication
Whether you’re just starting a data governance program or have been practicing one for years, communicating early and often is essential. Consistent and effective communication helps show the impact of the strategy—from highlighting successes to reorganizing after a setback.
An executive team member, such as the Chief Information Officer (CIO) or Chief Data Officer (CDO), should become the communications leader of the data governance program. These leaders are the central contact for the current status of governance practices across the organization. Team leaders and data owners can give regular updates to the executive. The executive team member then brings the most important updates to the rest of the leadership team and the organization as a whole.
7. Data architecture and metadata management
Another one of the best practices for data management when creating your data strategy is using the right tools, data architecture, and processes. Data architects are critical in developing appropriate models and architectures to integrate and manage data across disparate systems. Central to a data governance framework are well-defined processes governing data storage, access, security, and management.
Metadata management processes allow your organization to maintain an inventory of data assets and verify their relevance and accuracy. Well-defined data governance processes govern data storage, access, security, and management, ensuring compliance with regulatory requirements and maintaining data integrity throughout its lifecycle.
All of these processes are tailored to your organization's objectives and structure, serving as guiding principles for data governance initiatives.
8. Data governance is a practice, not a project
Creating a data governance program often feels like tackling a new project. You might be tempted to assemble a team to take on the project while the rest of the organization waits for it to be done. This is where many businesses see their data governance strategies slow down.
A data governance strategy isn’t a one-time project. There is no set end date or conclusion. Instead, it’s an ongoing practice that’s introduced as a regular policy. Much like dress codes or policies for requesting time off, the best data governance strategies become part of everyday life at your organization.
Ready to put data governance practices to work?
Implementing the best data governance framework for your business helps it work more efficiently, but you’ll need to build a business case for stakeholders before getting started. Find out how to get the green light for your data governance strategy by connecting with our team today!
