You’ve likely heard the term “data governance” used at your company in meetings, on underutilized roadmaps or in vendor proposals. But when it comes to a clear definition of a data governance program, the answers are inconsistent. Is it a set of policies? A technology solution? A checklist for compliance?
When it comes to defining what a data governance program is, the details can get murky. Organizations often struggle to pin down a clear, shared understanding of governance’s purpose and scope.
Some people in your organization may view governance purely as a set of rules or policies, while others see it as a broader framework for managing data as a business asset. This lack of clarity can make it hard to get started — or to make meaningful progress.
You don’t need a perfect solution to start a data governance program — only a clear goal, the potential for wins and an MVS that drives momentum.
Know Your "Why" Before You Begin
Every effective data governance program begins with a clear purpose. What problems are you trying to solve or prevent? What decision-making or reporting pain points keep resurfacing? How are industry regulations shaping demands for more effective data governance?
Before considering policies or data governance platforms, identify the outcomes that matter most to your company. Having clear objectives, such as building more trusted financial reporting, improving data quality for an ERP initiative, or prepping to roll out an internal AI tool lead to a more grounded backdrop on which you can begin to build your data governance program.
Clear goals help you get aligned, avoid scope creep and keep stakeholders engaged.
If you're unsure where to start, begin by defining a minimum viable state (MVS) that you want to achieve. That might mean documenting a set of critical data elements, creating a simple business glossary, or resolving a known data quality issue. It’s essential to keep your MVS concise yet meaningful. Easy, visible wins help drive broader organizational buy-in. Remember, you need early traction, not a perfect solution.
Here's the one thing about executive sponsorship of a data initiative.
Build a Team That Can Own the Work
Governance fails when ownership is unclear. That’s why a sustainable program depends on more than frameworks; it needs the right people, with proper accountability, from the beginning.
Here’s how you could structure your data governance team:
- Executive sponsor group to drive the cultural shift and provide top-level accountability. (For inspiration, read this brief executive sponsorship article).
- Data trustee council with partners from Privacy, Legal, Security, Risk and Compliance.
- Lead data steward forum to coordinate across domains and reduce silos.
- Domain working group(s) with stewards, custodians and SMEs advancing operational governance.
- Data stewards responsible for defining, managing and ensuring data quality and usage.
- Data custodians focused on system-level access, security and alignment with governance policies.
- Subject matter experts (SMEs) with specialized knowledge to support governance initiatives.
It’s also important to recognize that governance introduces new responsibilities, and with that comes the need for proper guidance. Ensure that you incorporate time for onboarding and channels for clear communication so that roles and expectations are easy for your team to follow.
Huck Sache-Hofheimer joined FSFP as an intern in the summer of 2022. Get to know Huck in his Meet the Team profile, and find out why he describes his FSFP role as being a librarian.
Assess Where You Are Before Getting Started
Before launching into implementation, take stock of what’s already happening. Even if your governance efforts so far have been informal or inconsistent, understanding what exists helps you avoid rework and uncover what’s already working.
You can start by identifying where the most common data problems occur, who is currently making data-related decisions, and what documentation or processes are already in place to facilitate decision-making. This current-state review forms the backbone of your data governance implementation plan. FSFP often helps clients with this foundational data governance work through discovery sessions and assessments.
Setting Up a Data Governance Framework That Fits
Establishing a data governance framework should reflect the way your organization operates. The structure needs to support the flow of decisions, not just mirror a textbook model.
Your framework should define how governance decisions are made and supported. This includes a clear operating model, standard processes for data requests and changes, and alignment with related areas such as data architecture, privacy, and compliance.
If you’re starting a governance program from scratch, focus on a few core workflows and build out from there. And what questions can be asked to determine what those workflows should be?
Consider these:
- How do we define enterprise business terms?
- What is our process for creating KPIs?
- Who is involved in identifying and communicating issues in our data pipeline?
A good framework makes it easier for people to collaborate and maintain consistency. It shouldn’t create unnecessary overhead; it should make governance work more focused and effective.
What data-related problems demand attention at your organization? Do you need to improve supplier data in procurement? Clean up customer data for more effective campaign targeting? Align financial reporting across departments?
Use Cases First: A Smart Approach to Starting a Data Governance Program
When you're figuring out how to start a data governance program, it’s tempting to try to solve everything at once. However, the most effective programs begin with a specific use case that matters to the business and works toward establishing the MVS for your data governance program.
Think about the problems your company knows about and wants to address. You may need to improve supplier data in procurement, clean up customer data for more effective campaign targeting, or align financial reporting across departments.
Choose a use case with visible impact and clear ownership. A focused effort builds credibility and provides a model you can scale across other areas in your company.
This approach is also helpful if you're looking for structured data governance implementation steps. A clear, targeted use case helps guide your efforts, makes it easier to show value early and paves the way for reimplementation in other areas of your organization.
Create Standards That Support Your Data Governance Framework
Once your framework and early use cases are in motion, you’ll need supporting policies and standards to ensure consistency. These might include data quality rules, naming conventions, access and classification standards or business glossary definitions. The key is to ensure policies and standards are defined, documented and used.
Too often, policies get created and then ignored. Ensure the standards are accessible, clear and directly tied to how people work. If possible, embed them into existing workflows or tools. The more you integrate these resources into everyday decisions, the more valuable they become.
Tools That Support (Not Lead) Your Data Governance Implementation Plan
If you’re just getting started with data governance, hold off on choosing software until your goals and processes are clear. Tools like Collibra, Alation or Informatica can support your governance program, but they won’t define your priorities for you.
When you’re ready, the right data platform can help manage metadata, workflows, stewardship activities and lineage tracking. But don’t let the tool lead your program. Let it reinforce the structure and practices you’ve already defined.
These tools should support your broader data governance framework implementation plan, not substitute for it.
Relevant and consistent messaging about data governance makes it easier for people to engage with your program.
Communicate Early and Often to Make Your Data Governance Program Stick
People don’t resist governance because they disagree with it; they resist it when they don’t see where they fit in — or when it seems like an administrative burden/roadblock to the work they do. Misconceptions around data governance can carry connotations of increased administrative burden and unwanted responsibility.
Enterprise-wide communication must be ongoing, role-specific and linked to value — and this is why every FSFP engagement includes an organizational change management (OCM) focus. OCM helps ensure our clients’ strategies, implementations and programs are integrated into their work and drive their success. (See our OCM articles.)
If you're just getting started with data governance, explaining the purpose and benefits early will help reduce resistance and build trust. Share what’s happening, why it matters and how it connects to broader goals. Highlight your use cases and how they drive progress toward your MVS.
Instead of relying on generic training, build targeted sessions that address each group’s specific role in governance. The more relevant and consistent your messaging, the easier it is for people to engage with the program.
Help your organization see that data governance isn't a project. It's a standard way of operating and it's scalable.
Track Results to Strengthen Your Data Governance Implementation Plan
A strong data governance program continues to evolve. Once your early initiatives are in place, start quantifying outcomes and identifying areas for improvement.
Measure what aligns with your goals, such as:
- Has data quality improved in key areas? If so, by what percentage?
- Has the time from report request to delivery decreased? If yes, by what percent?
- Are reports completed faster or with fewer revisions? How can this improvement be quantified?
- Are data roles being used consistently? If so, how has this consistency improved over time?
Use the quantifiable insights you gather to refine your processes and expand into new areas of the business. Over time, this turns governance into something durable. It becomes less of a project and more of a standard way of operating, proving that you’re not just starting a program but building one that can scale.
Ready to Develop or Improve Your Data Governance Program?
If you’re serious about starting a data governance program that drives value, begin with a clear goal. Assemble a team that can lead the work. Prioritize one or two areas where better data will make a visible impact. Laying this kind of groundwork is what enables you to start making focused and impactful governance changes that can be scaled to meet needs when they arise.
At FSFP, we help organizations move from planning to real, working governance programs. Whether you're setting up data governance framework foundations, enabling AI readiness or simply figuring out where to begin, we’re here to support you. Let’s talk about your goals and explore how we can help you move forward.
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