5 Steps for Implementing a Data Governance Program That Fits Your Company Culture

Authors:
James Kendrick, Principal Director, Professional Services, apiphani
Duane Tomlinson, Data Success Manager, Atlan

Data informs nearly all business decisions and is the main driver of company innovation. A 2025 Gartner poll found that 89% of CEO and senior business executives say effective data, analytics, and AI governance is essential for enabling business and technology innovation. Yet, many organizations have neither a data strategy nor a data governance program in place. 

Recipe for Data Success

Implementing a data strategy and governance program doesn’t happen overnight. Companies that rush into it often lack a clear vision and goals for their data. Without these, and without a plan for broadly communicating the strategic importance of your data program – and its critical success factors – you may be putting the program’s success at risk. 

In an informed organization, everyone understands why data strategy and governance are important. They also know their role in its implementation and have been educated on the end benefits. Conversely, poor communication creates confusion between the data strategy designers and those involved in its execution. This confusion wastes time, can be hard to recover from, and puts your whole data program at risk.

How to Implement a Data Strategy & Governance Program

Apiphani worked with Atlan, a leading active metadata platform and a modern data collaboration workspace, to create a combined human / technical environment for our client, a global manufacturer of innovative gas turbine components used by the clean energy industry.

Our objective was to instill data as a critical part of the client’s evolving digital culture. Together, we implemented a catalog and governance program for data product assets that were classified into 10 data domains. This gives our client the ability to sustain value at scale, as new and evolving data products are continually developed.

In this article, we share what we learned from our experience and explore a framework that includes the five steps necessary to achieve a data governance program, in motion, that fits your company’s culture.

Step 1: Set Context for Governance Over the Expansive Use of Data

The success of any initiative depends on how well it’s executed. A clear vision with well-defined goals and outcomes are a critical success factor. 

Successful organizations start by engaging a data champion who can advocate for expanding the role of data in driving successful business outcomes. Next they involve key business leaders who either have a need for specific data, or who have already requested specific data to drive better business outcomes. 

Engaging with these leaders uncovers opportunities to use data more expansively. Understanding their business challenges is also necessary. What’s preventing them from leveraging specific data for key business decisions? Difficulty extracting it from its current source? Lack of a “single source of truth”? Finding the answer begins to lay the foundation of the value of data governance. 

Once you involve the right business leaders, identify the following information:

1. Specific data opportunities, data challenges, data initiatives, or compelling events
2. Current state of data strategy and progress in advancing data usage
3. Current data and analytics environment, including its strengths and weaknesses
4. Data domains and data products around which to organize the future state 

Often, we see the initial data governance effort tied to retroactive governance. This means there has been an initial push on the existing data within the organization, and there has been some effort to enrich this data and then drive awareness of the enhanced discoverability of the data, considering “Enabling Self-Service” complete. 

What’s often forgotten are the future-state human behaviors that must be adopted to ensure the data enrichment is proactively embedded within the organization’s business processes. Ask these questions:

• What is the operating model? 
• What are the governance priorities for data domains and products? 
• What will the beneficiary’s workflow look like? 

These are all considerations to ensure retroactive work becomes proactive in the future.

Step 2: Formulate and Align Around a Governance Scope

Next, formulate a data governance program to match the current state. It may change or expand over time in accordance with data’s expanding role in driving successful business outcomes (see Step 1).

Start scoping by evaluating and understanding the current state and goals of the business in the context of the following five pillars of expansive use of data:

Get to know the true current state of data in the following areas: 

• Use of data to drive decisions
• Governance of data used to drive those decisions
• People involved in the end-to-end processes, from getting data to delivering it in the requested consumable format
• Technology used along the way, noted for each persona

A true reflection of the current state allows you to identify opportunities for removing, improving, or creating processes in the end-to-end flow. This will inevitably unify data and governance and will present an operating model for success. Success, meaning the organization addressed the defined outcomes and goals for their business.

Step 3: Determine the Best-Fit Governance Program

Ensure you have a clear vision and scope that is achievable, adds value, and clearly outlines the value of a sustainable, long-term governance program for your organization.  

Next, select the culture of the organization, as it is today, according to how business process changes are driven:

• Top down
• Function driven
• Hybrid     

With the details from Step 2, along with your culture selection (above), you’ll be better equipped to determine how the program should be introduced, communicated, spoken about, implemented, and what expectations to set when onboarding teams that are either part of the process and/or beneficiaries of the outcomes. 

This will clarify who within the organization should communicate the program so that there is an increased probability of success and decreased resistance to change.

This aligns perfectly with Prosci’s ADKAR Change Management framework. Use this framework to help ensure maximum impact in driving awareness, building desire, and determining how reinforcement communications should be delivered, and by whom.

Step 4: Expand Motivation and Create Momentum for the Governance Program

Awareness and reinforcement communications create momentum for the governance program by tying it to critical business needs in each data domain. Assimilating findings and drawing conclusions about the situation, opportunity, and how to proceed will expand motivation as the program takes shape. 

Consider using the following activities for awareness, desire, training, capability assessment, and reinforcement planning:

• Develop a read-out for working sessions
• Create a one-page executive summary for the C-suite
• Hold feedback sessions with key stakeholders
• Gain alignment and agreement on the business case
• Set clear expectations that align with the organization’s SMART goals
• Communicate how you will measure the organization’s involvement or the effectiveness and success of new behaviors

This approach enables the organization to reach a unified vision. Providing key stakeholders with an opportunity to ask questions and provide input drives an even greater sense of participation and unification around the identified goals.

Step 5: Proceed to Governance Program Implementation Tied to Goals from the Assessment

Typically, implementation falls into one of three patterns. These patterns are interdependent and can often evolve into other patterns. How a pattern gets defined depends on the operating model and the organization’s culture (top down, functional, or hybrid, as defined in Step 3). The patterns are as follows:

Success of each pattern hinges on your ability to execute according to fit with the organization’s culture and structure. Selecting the right pattern, along with the required attributes to support the ongoing program, is key.     

Reinforcement communications play a pivotal role here and are often forgotten. How well you communicate your expectations depends on your change management skills. There is a direct correlation between a clear data vision / goals (communicated methodically) and better business outcomes. If you follow Prosci’s ADKAR change management model, for example, you know that an organization is 7x more likely to achieve success with an initiative.

Data Governance – A Modern Approach 

Get started with your program today. Contact us to schedule an assessment /roadmap workshop that fits your organization and culture. We can help you find the right starting point and tailored steps to create a successful data foundation and data governance program using the framework we’ve described.

Read our case study to learn how apiphani helped Power Systems Manufacturing build a data pipeline.

About Apiphani

Apiphani is a managed services and IT services provider that believes in human exceptionalism in the time of AI. By integrating decades of industry experience with Deep Automation™ and machine learning we are able to drive extreme efficiency and reliability in support of our client’s mission critical workloads. To learn more about Apiphani, please visit our website and follow us on LinkedIn.

About Atlan

Atlan is the next-generation platform for data and AI governance. It is a control plane that stitches together a business’s disparate data infrastructure, cataloging data and enriching it with business context and security. With Atlan, data and business teams can easily find, trust, and govern AI-ready data. To learn more about Atlan, please visit our website and follow us on X (@AtlanHQ) and LinkedIn.