Crafting a successful data governance strategy can be more complicated and time-consuming than making it to the next level of your favorite arcade game. But there are similarities between the two quests: building effective data governance within your organization may require navigating uncertain terrain, jumping and climbing over obstacles (such as stakeholder misunderstandings), or powering up to defeat adversaries. Achieving success will go far in mitigating organizational compliance risks, protecting sensitive customer data, and keeping your business’s information assets safe, secure, and available to only those who need it, when they need it.
Data governance is a multi-player game. Creating a strategy that works for your organization will require input from multiple stakeholders, with everyone contributing to the cause. Without this kind of team effort, it’s going to be tough to make it to the final level.
We recommend that organizations looking to power up their data governance strategy follow a well-defined two-step process. First, they should build a winning team, and then that team will collaborate to identify their strategy. Only after the strategy has been decided upon will it be time to think about which technology tools to adopt.
Data governance is a key business process. Done well, it ensures that your organization’s most valuable data will remain trustworthy and consistent, and won’t be subject to misuse. To achieve this end, your organization will need to strategically manage the availability, usability, integrity, and security of the data it holds.
Effective data governance involves building standards and policies that control how data is used and protected. As regulatory oversight increases, consumer expectations climb, and businesses become more and more dependent upon using data analytics to guide decision-making, establishing robust data governance is growing in importance for organizations across industries. If yours is among them, it may be time to level up your data governance strategy.
What this means, in concrete terms, differs across verticals and for individual organizations. Which regulatory compliance standards apply to your company? This is the first question to ask when considering what an effective data governance strategy would look like for you.
Stakeholders in organizations in highly regulated industries are usually well aware of the relevant regimens (HIPAA in healthcare, Sarbanes-Oxley (SOX) and Gramm-Leach-Bliley (GLBA) in financial services, etc.), but businesses operating in verticals with less oversight may still need to demonstrate that they’re protecting customers’ financial data or adhering to data privacy requirements. Even those that aren’t explicitly mandated to implement data protection policies may be driven to do so in order to mitigate operational risks, satisfy third-party partners and vendors, or adhere to their legal team’s recommendations.
Building out effective data governance begins with understanding where your sensitive and protected data lives, and how it is used and accessed. If your organization experienced a significant breach in the past, which information assets were impacted? What data does your company hold that cybercriminals would be interested in exfiltrating—either because it would have value if sold (such as credit card numbers) or because it could be leveraged for purposes of extortion? Thinking about the biggest data-related risks that your organization faces can help you establish the priorities and parameters of your data governance strategy.
You’ll also want to consider your future plans. For instance, are you planning to roll out generative AI tools like Microsoft Copilot? It’s critical to have your data security and governance strategy in order before doing so, because giving the Copilot engine access to sensitive information could result in regulatory penalties or even consequences that are even more dire than that, like inadvertently turning your company’s most valuable intellectual property over to cybercriminals.
In order to successfully implement data governance, your organization must designate individual employees who will be responsible for the initiative. These roles can vary depending on the size and maturity of your organization, but it’s important that there’s an owner who is individually in charge of the efforts, as well as a team of contributors who participate in them. Team members usually hold positions in legal and risk management functions as well as in general corporate leadership.
Typically, the composition of data governance teams evolves as an organization’s maturity grows. Here’s what we usually see at the beginner, intermediate, and advanced levels.
Any organization looking to create a robust data governance strategy should encourage primary stakeholders and executive sponsors to collaborate in setting goals and objectives for the program. Once these have been established, it’s a good idea to bring in any secondary stakeholders who might need to understand and contribute to the strategy.
Organizations at the beginner and intermediate levels that don’t have the requisite resources in house may benefit from outsourced services (such as a vCISO). This can offset disadvantages like a lack of internal expertise, or not having anyone to take ownership of the data governance program, that would otherwise prevent them from following through effectively.
The most successful strategic initiatives begin with the ends in mind. This is certainly the case for data governance. You’ll want to start by identifying what you need to protect, which means inventorying your information assets, and understanding which of them are regulated and/or sensitive.
Key questions to ask include the following:
Initially, your team will attempt to answer these questions in general terms. As you progress through a data discovery process, your findings will become far more concrete and specific. This will make it possible for you to categorize your data. Such categorization entails placing all of your sensitive data into groups, defined by the type of data, as well as who should be able to access it, how, and under what conditions.
This process of categorization naturally lends itself to the creation of rules. Such rules establish which employees and technology systems can access data in particular categories, and when they can do so. These rules constitute your data governance policies.
Once you’ve written these policies, they need to become part of your organizational culture. You can make them known to stakeholders by communicating them to employees, but also explaining why data security is important. Training all employees is vital to the success of data governance initiatives because all end users are directly accountable for data security. If everyone understands the criticality of their role in protecting the company’s information assets—and their jobs—they’ll be better able to follow both the letter and spirit of your data protection policies.
Finally, you can deploy tools to help you manage your data governance strategy efficiently. These are technologies that help you maintain visibility, set rules, and enforce policies in ways that will make it easier to meet compliance requirements. Such tools help you put your data governance strategy into practice on a day-to-day basis.
When evaluating data governance tools and solutions, make sure your business needs come first. This means that technology choices should be made only after your goals and use cases are well understood. Never procure a solution just because you think you need it—instead, understand your goals first. That way, your team can have confidence that the technology will be implemented correctly, and in ways that meet well-established objectives.
Many of our clients choose Microsoft Purview to help them manage and govern their on-premises, multi-cloud, and Software-as-a-Service (SaaS) application data. Purview has many advantages, including the fact that it’s part of Microsoft’s holistic solution suite, and that its comprehensive capabilities make it easy to map and manage even the most complex data estates.
Want to learn more about building an effective data governance strategy? Listen in as we discuss the specifics on how to Build Your Data Governance Strategy to Win, or get in touch to hear about our hands-on strategy and planning workshops.
Mike’s experience covers all aspects of technology and security leadership. Since joining Netrix, Mike has been engaged as an outsourced CIO and CISO for companies in many different verticals. Responsibilities include working with businesses to align technology roadmaps, working with internal teams to leverage technology to improve business process, assisting with merger and acquisitions through developing playbooks and performing due diligence audits, performing technology and security assessments, designing and implementing information security programs and controls.
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