Implementing a Data Governance Program: Overcoming Reluctance to Change


“No thanks! We are too busy”, “Why do we need that?”, “Isn’t this just more corporate red tape?” – do these statements ring a bell? They represent the voice of resistance that echoes through many organizations when “Data Governance” is mentioned. While a topic that has steadily gained attention, these reactions remain prevalent, showcasing the disparity between understanding and acceptance.

At its core, Data Governance is crucial in ensuring the accuracy, availability, and reliability of data within an organization. Mike Ferguson from “Intelligent Business Strategies” describes it as a coordinated effort involving people, processes, and technology. This effort is made to manage and protect all types of data, ensuring that the entire organization can trust and securely use the data.

Yet, despite a clear understanding of its importance, the journey to implement a Data Governance program is often met with hesitation and opposition. This resistance emanates from misconceptions, a lack of understanding, and a fear of change.

In this insight, we explore the origins of this resistance and outline strategies to facilitate a successful adoption of a Data Governance Program, following the concepts from “Non-Invasive Data Governance” by Robert S. Seiner.

Understanding the Resistance

Many organizations mistakenly believe investing in a tool is a silver bullet for data-related challenges. However, as Mike Ferguson emphasizes, Data Governance relies on three main pillars: people, process, and technology. Relying solely on technology will not address all the company’s data challenges. People are key; building relationships, fostering ownership, and ensuring buy-in is crucial. Consider a company investing in a Data Catalog tool and expecting immediate transformation in their data practices. Neglecting the people and process aspects of Data Governance can lead employees to resist adopting the Data Catalog because they do not understand the benefits or do not know how to integrate this into their daily workflows.

Motivating employees for Data Governance can be a daunting task. However, it's crucial to ensure that everyone in your team understands the significance of Data Governance. There is a common misconception that it adds an extra layer of work and responsibility, which may not necessarily boost motivation for most individuals.

In 1969, Paul R. Lawrence wrote in an article from the Harvard Business Review: "One of the most baffling and recalcitrant of the problems which business executives face is employee resistance to change.". Though this concept was first introduced in the 1950s, resistance to change has a more extended history and is deeply rooted in human nature. People prefer the comfort and predictability of the status quo. Understanding this is key to managing change effectively.

As human beings, we tend to get to a comfort zone and stay in it. Change, more specifically rapid change, can push people out of their safe space too quickly, leading to anxiety, stress, and fear. It is hence crucial to ease people into change, to clarify what is coming, and to empower them to feel in control. Therefore, any change program should start by providing a good understanding of the notion of change.

Strategies for Overcoming Resistance – A Non-invasive Approach

Resistance to change often originates from a fear of the unknown and uncertainty about how changes affect responsibilities and personal work lives. Providing clarity and fostering a communicative environment where employees can express concerns, ask questions, and provide feedback is crucial. This approach builds trust and demystifies the entire Data Governance process.

According to Robert S. Seiner’s philosophy of Non-Invasive Data Governance, it is vital to recognize that Data Governance is already happening informally within organizations. For instance, an organization might have always followed certain undocumented practices when handling its data. Robert S. Seiner illustrates this in his book with scenarios like a data warehouse or master data management environment. In these settings, different individuals are tasked with defining what data goes into the data warehouse; others are responsible for producing data through ETL (extract, transform, and load) processes and others are responsible for using the warehouse data for reporting purposes. Though not labelled as ‘governance’, these practices serve the same purpose. Identifying and integrating these pre-existing practices is essential when transitioning to a formalized Data Governance approach.

Formally acknowledging people's roles in governing data and incorporating this recognition into an organization's strategy ensures it feels more like a natural progression than a disruptive change.

Aligning Data Governance with Existing Roles and Responsibilities

The program should integrate seamlessly with existing roles and responsibilities, maintaining a sense of familiarity and control. It should not feel like an external imposition that drastically alters current roles. Let's take the example of employees already responsible for managing a specific type of data, like ‘customer master data’. The Data Governance program should formalize and standardize these practices rather than introducing entirely new procedures. This helps counteract feelings of loss of control, which can arise when roles are perceived as being significantly altered. Embedding Data Governance practices within everyday business processes transform it from an additional task to a natural aspect of daily work, as advocated by Robert S. Seiner. This makes the program seem like business as usual, reducing resistance and fostering acceptance among employees.

Additionally, Robert S. Seiner highlights that it does not matter if the business or IT departments initiate the Data Governance initiative – ideally, it should reside in both. Nevertheless, the emphasis here is on the importance of individuals in charge, who should have a profound understanding of Data Governance and be highly motivated to drive the initiative forward.  For example, a Chief Data Officer might lead a successful Data Governance program with a strong business background or, conversely, with a strong penchant for IT and working closely with IT/business to ensure alignment.

A Stepwise Approach

Breaking down the Data Governance transition into manageable steps and involving employees ensures a smoother adoption. This involves explaining the ‘Why’ behind Data Governance, highlighting the benefits, avoiding jargon, and ensuring that concepts are introduced progressively and pragmatically. A first step, for instance, could involve training sessions for employees to explain the importance of accurate data in their respective functions. These sessions could be led by Data Governance champions, who would serve as program ambassadors, helping bridge the gap between theory and practice making the initiative more tangible for their colleagues.

Robert S. Seiner stresses the importance of educating people in business areas about Data Governance and the specific approach the organization takes to achieve its goals. He suggests asking detailed questions to prompt people to talk about their data-related challenges and daily issues (e.g., challenges associated with data accuracy or confusion coming from the various interpretations of business terminology, which can subsequently lead to miscommunications across different departments, etc.). Documenting these conversations demonstrates that the value of Data Governance is defined by the business rather than imposed by the Data Governance team.

Fostering Strong Leadership and Engaging Stakeholders

Strong leadership, clear identification of roles, and active stakeholder engagement are additional crucial factors for success. A company could appoint a Chief Data Officer to lead the program, providing the necessary leadership and strategic decisions. This engagement fosters a sense of ownership and accountability throughout the organization.

Data Stewards play a central role in this journey as guardians of data. They ensure data accuracy, privacy, security, and overall value, contributing significantly to the integrity and success of the Data Governance Program. Aligning their responsibilities with existing roles ensures they do not feel burdened with additional work, facilitating a smoother transition and stronger adoption of the Data Governance program. For instance, if a Data Steward is also a data analyst, its governance responsibilities include maintaining the quality of data used in its regular analysis tasks. This will ensure they will not feel burdened with additional work.

Committing to the Long-Term

Understanding that Data Governance is an ongoing commitment, not a one-time project, is crucial. Starting with the most critical data elements and adopting a proactive approach ensures that issues are addressed before they become problems. Take customer data as an example; prioritizing its accuracy and completeness directly enhances customer satisfaction and optimizes business operations, addressing “low-hanging fruits” immediately.

Furthermore, an incremental approach ensures the program is manageable and less overwhelming. A company could set short-term goals for improving the quality of customer data while also laying out a long-term plan for expanding Data Governance practices to other types of data. This proactivity helps prevent issues before they arise, rather than responding to them after the fact, which can be more time-consuming and costly.


As we have explored, implementing a robust Data Governance program is challenging, with human resistance to change standing out as a significant barrier. Addressing the human aspect, acknowledging the inherent resistance to change, and ensuring clear and transparent communication are critical steps in breaking down barriers to adoption.

Non-Invasive Data Governance fosters employee engagement, breaks the program into manageable steps, and ensures everyone understands their role in the process. Furthermore, integrating governance processes into daily workflows transforms Data Governance from a perceived additional burden to a natural and integral part of business operations.

While Data Governance is a long-term commitment, it is essential to manage company data, adapt to evolving needs, and proactively address challenges ahead. Embarking on this journey is crucial in today’s data-driven world.

We advise you to start today. Assess your organization’s readiness, initiate the conversation, and embrace the change. Are you ready to take the first step towards reliable and secure data usage within your organization? Don’t hesitate to reach out.


Robert S. Seiner, Non-invasive Data Governance: The Path of Least Resistance and Greatest Success (first edition, Technics Publications, LLC, 2014)