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Building a Business Case for Data Governance: Here’s How

Authors Photo Precisely Editor | July 19, 2023

Data governance is fast becoming a business imperative. Many top executives and line-of-business managers lack a clear understanding of the benefits of data governance. Data is a valuable organizational asset, yet if an organization isn’t capable of fully utilizing that asset, there can be a substantial opportunity cost.

Data governance plays a critical role in risk management and compliance as well. Giovanni Cervellati, Research Manager at IDC Europe, states that “Almost 70% of organizations view data privacy and security as key investment areas and 54% view data sovereignty, privacy, and governance as factors to be addressed.” Risk and compliance are a growing challenge for which data governance provides a clear solution.

How can you within your organization? Building a data governance business case is essential.

According to a recent report from the LeBow College of Business at Drexel University, 57% of companies that have a data governance program in place are seeing improvements in the quality of data analytics and insights, and 60% see improvements in the quality of the data itself. Yet these statistics only scratch the surface.  Every business is unique, so every organization requires a business case that speaks to its own goals and aspirations.

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The Foundational Case for Data Governance

While all businesses are eager to leverage data in a meaningful way, they first need a solid data governance foundation. As companies collect data from numerous sources, they must ensure it is accurate and reliable. They must also confirm business users understand where that data is located, where it originated, and how it applies to the business. Data governance is the strategy that organizes people, processes, and technology to establish trustworthy, easily understandable data.

Over the last decade, many organizations struggled with operationalizing data governance because of siloed approaches, competing priorities, and lack of resources. According to the Lebow study, poor data quality is the #1 challenge, with data integration and lack of contextual completeness being close runners-up.

Now, a major shift is underway. More and more organizations are increasing their investment in an enterprise-wide approach to data governance to ensure high-quality, well-managed information that is critical to decision-making, innovating, and modernizing.

How to Build a Successful Metadata Management Strategy within a Data Governance Framework

If you’re looking to build a business case for data governance in your organization, here’s how to get started:

  1. Articulate the Value of Data Governance

Bringing the value of data governance to the enterprise is imperative. Without an enterprise-wide data governance approach, organizations will fail to capitalize on countless business opportunities and suffer short- and long-term consequences.

One of the biggest roadblocks to data governance, however, is the need for buy-in among key stakeholders. This includes the executive team, of course, but it’s also important to garner support from functional team leaders across the organization.

Your business case should include input from diverging business lines about their data difficulties. Identifying the metrics around goals and objectives of all data users and how data governance will benefit them is critical to gain buy-in from your data team.

Until these key stakeholders can understand what data governance is, how it solves a host of problems, and how it generates competitive advantage, they will be reluctant to commit the time, effort, and organizational resources to help make it successful.

  1. Link Data Governance to Strategic Business Objectives

Many organizations set out to establish data governance frameworks without linking those programs to specific outcomes important to the organization. If the C-suite wants to improve customer satisfaction and reduce attrition, for example, then your business case should address that strategic objective. By addressing data quality, integration, and contextual completeness of customer data, the organization stands to gain a comprehensive 360-degree view of its clientele, enabling the improved service levels the executive suite is aiming for.

At Johnson & Johnson, the strategic goal was operational efficiency. Working with Precisely, J&J was able to bring all of its operating companies under a common supply chain solution, achieving substantial gains through effective data governance.

Strategic objectives bring clarity and focus. They also give your executive team and other stakeholders a clear reason for supporting your proposed initiative.

  1. Engage Your Stakeholders

Successful data governance requires participation from individuals across every department from sales and marketing to IT and operations. Everyone must contribute to make governance successful and maximize data value.

A compelling business case outlines why data governance is a top priority and addresses the organization’s challenges and solutions. While it’s important to tie your program to strategic business objectives, you will undoubtedly discover other existing challenges that can be addressed when your organization has an effective data governance framework in place.

For example, perhaps the organization is facing a slew of regulatory hurdles. The business case should outline how governance will streamline regulatory reporting for the compliance team and eliminate costly regulatory penalties.

Maybe the company is struggling to centralize data from disparate data systems. The business case would cover how governance helps ensure confidence in investment placed on consolidating systems or migrating to a cloud environment. Or, it could be that the IT team spends more time fixing data quality issues than running analytics. The business case would focus on how governance proactively solves data quality issues for the most impactful data, saving IT time and money.

  1. Assemble a Team of Data Governance Champions

Data governance is most successful when it’s built around an enterprise-wide strategy and a common set of processes that everyone can follow. To do this, organizations need a data governance team to create a program that accounts for everyone’s needs.

A successful data governance team starts with support from the leadership team. Typically, a chief data officer (CDO) leads governance efforts and works with a centralized or federated team, made up of leaders from various departments like marketing, HR, operations, and IT. Identifying data owners, stewards, and data users become a critical part of ongoing data governance management.

Together, the governance team creates and manages processes for resolving data quality issues, tracking compliance, documenting data lineage, ingesting metadata, building data catalogs, analytical reporting, and more. All procedures must be repeatable and easy to execute for both the IT and business teams.

  1. Define Your Expected Outcomes

Your data governance business case should outline the results you expect to achieve, the timeline for achieving them, and how they will be measured. Some examples of outcomes include:

  • Easily understandable data terms across the entire company
  • Improved data trust among business users
  • Enhanced end-to-end data quality
  • Clearly defined data lineage from both a business and technical standpoint
  • Increased data usage among business users, generating additional ROI
  • Verified data behind all business decisions
  • Fast and easy proof of regulatory compliance

In the end, outlining expected outcomes in the data governance business case demonstrates its value across the enterprise and boosts executive buy-in for the necessary funding and resources.

Once the data governance team selects the appropriate technologies to accompany their data governance strategy, it’s time to work on making data consistent, improving data quality, and impacting the bottom line.

Read our eBook Building a Data Governance Use Case to Get Budget and Buy-in and learn how you can generate support, secure budget, and gather momentum to build a data governance framework.