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16 November 2023

data governance business objectives

Aligning data governance to support business line objectives

Successful businesses recognize the strategic value of data. However, businesses are realizing that they must establish a strong data culture and increase data literacy across their business lines to capitalize on the immense value data can bring to their organization.

Establishing a robust and purposeful data governance framework is a good first step. But equally as important is the ability of organizations to align their data governance initiatives with business line objectives. Doing so fosters a culture of data-driven decision-making, enhances operational efficiency, and ultimately drives the overall success and competitiveness of the organization.

Understanding business line objectives

Business line objectives are specific goals tailored to the organization’s unique functions and responsibilities. They not only define how a particular business line contributes to the overall success of the organization, but they also guide how that part of the organization uses data to achieve its goals.

Because business lines have different responsibilities, their objectives are different, too. For example, sales and marketing will focus on expanding market share, driving leads, and increasing revenue, while finance will aim to control costs, improve cash flow, and achieve compliance.

Understanding the nuances between departments, as well as the internal and external factors that can impact a business line’s ability to meet its objectives, is critical. It’s also important that data teams understand where each business line obtains their data, and how they use it to drive business decisions.

Customizing data governance initiatives

Customizing your data governance initiatives requires tailoring your governance frameworks to a specific business line’s unique needs and objectives. Understanding their unique objectives is a good first step, but it’s also important that your data team complete an assessment of the business line’s structure and specific data requirements.

Begin by identifying key stakeholders and understanding their perspectives on data usage, privacy, and security. Ask them to share reports and dashboards that they rely on to gauge performance, make decisions, and report results. Find out where they struggle by asking questions such as:

  • Do you have access to the data you need?
  • Is the data easy to find and understand?
  • Do you know where the data comes from?
  • Do you trust the data?
  • Is the data protected and secure?

Answers to these questions will provide valuable information that will help you craft policies and procedures that align with the business line’s objectives while ensuring compliance with relevant regulations.

You’ll also need to establish clear roles and responsibilities for data stewards and custodians within each business line. Consider the technological landscape and customize data governance tools such as a data knowledge catalog to eliminate data silos and provide seamless integration with the business line’s existing systems. Doing so will help improve operational efficiency, increase data quality, and provide real-time value.

Because objectives and external factors constantly evolve and change, it’s important to dedicate time to regularly review and update your data governance framework so it remains in alignment with business line objectives.

Ultimately, a customized data governance initiative ensures regulatory compliance, enhances data quality, fosters a data-driven culture, and contributes to the organization’s overall success. However, it can only do so through regular monitoring, review, and adjustment.

Prioritizing data assets

Not all data is created equal. That’s why an important step when aligning data governance initiatives to business line goals is to prioritize the data assets that directly contribute to reaching (or exceeding!) business line goals.

By understanding and categorizing data based on each business line’s objectives, you can ensure that the highest-priority data is of high quality, security, and accessibility. Taking a strategic approach also helps to streamline data management, mitigate risk, and ensure your data governance initiative supports the goals of the business.

To identify high-priority data assets, meet with key stakeholders in each business line to understand what data, analytics, reports, and dashboards underpin key business line functions. You’ll need to understand key attributes, including where the data comes from, where it resides, and who has access to it.

You’ll also want to determine how frequently the business line uses the data, and its role in supporting key performance indicators, regulatory compliance, and customer experiences. Finally, remember to consider the potential impact of the data on the organization’s reputation in the event of a data loss or security breach.

Because data is changing all the time, you’ll want to keep an open dialogue with business line stakeholders so you can refine the list of high-priority data assets as sources change and organizational needs evolve. This kind of iterative and collaborative approach will help your team ensure that your data governance initiative can keep pace with changing business objectives and safeguard the most vital information resources.

Facilitating cross-functional collaboration

At its core, data governance involves change. It requires data teams and business teams alike to think differently about how they use and manage data in support of business line objectives. That’s why cross-functional collaboration between data teams and business line stakeholders is one of the most important elements of a successful data governance initiative. Without it, data governance initiatives will fail to deliver their promised value, leaving business line stakeholders loath to support future data-related projects.

Start by establishing clear lines of communication between data teams and business line stakeholders. Open dialogue helps to foster a mutual understanding of what’s working – and what’s not – when it comes to data and data-related initiatives. It’s also critical to ensure that communication is an ongoing effort.

Facilitating regular meetings, training sessions, and workshops helps you to bridge the gap between data professionals and business line stakeholders, helping to increase data literacy and promote a culture of collaboration and transparency. Some organizations take collaboration even further by embedding data experts within their business line to provide greater assurance that data insights align with business needs and objectives.

Implementing a data catalog to support data governance

The final piece of the puzzle when it comes to aligning data governance to business line objectives is technology. Without a data catalog, businesses will struggle to take control of their data and realize its true strategic value.

DataGalaxy’s Data Knowledge Catalog makes it easy for business line stakeholders to find the data they need to drive better decisions, identify opportunities for innovation, and uncover opportunities to grow the business. It fosters collaboration using centralized, homogeneous data sets, and saves both time and money by reducing redundancies and answering questions about commonly-used data sets.

By providing greater clarity into data definitions, data lineage, and critical business attributes, DataGalaxy makes it easy for business line stakeholders to better understand and use their data as a strategic asset. With user-friendly features, including a Business Glossary, intuitive visualization tools, detailed data lineage, and natural language search, users across business lines can access the trustworthy data needed to meet business line objectives.

To learn more about how DataGalaxy’s Data Knowledge Catalog can help your business align your data governance initiatives to business line objectives, please book a demo.

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