5 Reasons to Invest in a Data Governance Framework

Data governance needs to be part of your overall data strategy. It can only can’t succeed with leadership support and cultural buy-in.

A robust, practical governance framework brings many benefits to your business. It starts with improved data quality, which leads to better decisions across all departments. This includes increased revenue, higher customer satisfaction, and better business performance.

Increased Revenue

A robust data governance framework will provide multiple financial benefits. For example, a manufacturing company may increase revenue by accurately forecasting demand and reducing inventory costs. This allows it to invest in more profitable product lines. Or, a legal firm can identify potential risks and reduce costs by structuring how insights are captured and used.

A well-rounded data governance team includes a mix of subject matter experts, data security professionals, and IT personnel. It also provides business line experts who can offer frontline experience and cross-functional perspectives. This helps to establish the ownership and authority necessary for successful program implementation.

Data governance programs should be designed based on the unique challenges and complexity of the organization. The most effective programs follow the tenets of change management by starting small and scaling as the participants gain confidence in the framework’s ability to address their needs. This approach will help ensure that the program is not seen as an unnecessary burden to participating resources. It will also maximize the return on investment and allow the company to meet its goals for revenue growth.

Increased Customer Satisfaction

A data governance framework gives employees a solid understanding of how their work contributes to the bigger picture. It also allows them to make informed decisions that lead to a better customer experience. For example, suppose a company consolidates login systems to enable customers to access their information from one location. In that case, it makes it easier for them to get help from customer support or marketing managers.

High-performing companies take data governance more seriously than others. To maximize value from their analytics and digital initiatives, they prioritize domains and the level of control necessary for each data element. Critical data elements (like a consumer’s name or address) require a more rigorous approach to data governance, including ongoing quality monitoring and precise flow tracking across systems.

These efforts are not always easy and can be challenging to scale. To avoid pitfalls, leaders need to engage stakeholders early in the process. Consistent communication helps to demonstrate progress, celebrate wins, and candidly acknowledge setbacks. Ultimately, it’s what makes these efforts successful.

Better Decision-Making

Data governance ensures that business leaders have access to high-quality data across the organization, creating insights and opportunities to propel growth.

Better decision-making also translates to more effective collaboration and innovation, enabling companies to differentiate themselves from competitors with data-driven initiatives. For example, a media publisher leveraged the Twilio Segment to consolidate customer data and streamline consent management, enabling marketing and sales teams to collaborate efficiently and save time and money.

A data governance framework promotes regulatory compliance, helping businesses safeguard their customers’ personal information against unauthorized access and cyberattacks. However, a data governance program requires more than just policy development. It also requires ongoing oversight, training, and communication to maintain buy-in and support.

Companies should prioritize domains and use cases to create lasting value, tailor governance to their needs, iterate quickly, and rely on data quality metrics to guide decisions. In addition, consistent communication with stakeholders is essential to show progress and celebrate wins while being honest about setbacks. Organizations can accelerate their journey to data governance success by focusing on these best practices.

Reduced Risk

Data governance provides visibility into the impact of a data breach, enabling organizations to identify affected customers and proactively contact them quickly. This reduces damage and risk while improving customer satisfaction and brand reputation.

Data quality metrics and centralized oversight are critical components of any data governance framework. These help ensure that all decision-makers understand the quality of the data they use, allowing them to consider that information as they make their choices.

It is also important to include considerations for data integrity in all procedures and a schedule of audits and checks by the data governance team. Adding these extra steps will likely add a bit of time to the processes, but they are an investment that can help you avoid costly errors. In addition, they can help you save money by eliminating redundant or inaccurate processes and reducing the need for manual corrections. The result is a lower operating cost and a more efficient data management process. This is especially true for high-value data assets used for business processes, such as customer records and supply chain optimization.

Improved Collaboration

A data governance framework enables better collaboration across teams, creating, analyzing, and using enterprise data. This is a huge benefit, especially when delivering quality data to customers.

The framework also sets transparent processes for collecting and storing information, which improves employee efficiency and results in more accurate data. This, in turn, leads to improved decision-making and higher performance.

With good data governance practices, businesses can identify and resolve problems with their data quickly and easily. This reduces the risk of costly errors and enables them to comply with regulatory requirements, such as GDPR.

The key to successful data governance is to tailor the framework to meet business needs. One way to do this is by prioritizing domains and applying need-based commands. Another is to use a data catalog, which acts as a centralized metadata repository to improve the discovery, management, and accessibility of enterprise data assets. This helps improve collaboration, reduce redundancy, and apply access controls consistently and efficiently. In addition, it allows users to search and find data faster and provides a clear understanding of the data available.

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