Making the Case for Data Enablement (Rather Than Data Governance)

There is a movement in the business and academic worlds to consider relabeling the name of the long-time data discipline of “Data Governance” to “Data Enablement”. Usually, when someone tells me something like this, my first response is to chuckle and nod my head. It takes a sizable formal movement to change the name of something that has become recognized around the world. Something that books have been written about. 🙂 Something that already aptly describes what the data discipline is all about.

That was, until I sat in on a conference a few weeks ago and heard several speakers refer to Data Governance and Data Enablement together, conjecturing out loud that the term “enablement” may replace “governance”. I was intrigued and dug deeper. If that many data leaders and practitioners are saying the same thing, perhaps I should investigate and educate myself and others on things to consider when selecting if you are going to call your DG program a DE program instead. You will be leading edge if you select the new name.

The question I raise in this article is: “Is there a reason to change the name of the discipline?” The truth is… maybe. There is certainly value in calling it data governance because the data will not govern itself and people must be held accountable for the data. The rules must be executed and enforced around your data.

And… the truth is that there is a lot of value calling it data enablement. Data Enablement is the happier and more positive term. The data must be enabled and furthermore, people, process and technology must be enabled to effectively define, produce and use the data as well.

For those of you who know about Non-Invasive Data Governance, you will probably guess that I would lean toward the less invasive term, which in this case is Data Enablement. I have not made that leap yet. But I do not believe that the label will make or break a program. Governance is the scarier term — but people understand what the term “government” means. Government for data (well, not exactly). If data governance is explained well… people recognize what governance means and what it takes to govern data and information (and metadata).

The next few sections of this article will share some basic insight into the use of the two terms including why you may want to consider making the change, reasons why that may not be a good idea, and things to consider when making the move. At the end of the article, you might make up your mind which term you will use (or you already have). You may decide to step toward the future of how the discipline potentially will be described, or you may decide to continue calling the discipline by the name you are presently using. Either way, this article focuses on things to consider when naming your discipline.

Why DG Should Be Called DE

Data Governance, traditionally understood as a set of policies and processes for managing and protecting data, and in the non-invasive approach understood as the execution and enforcement of authority and formalization of accountability, is essential for organizations to ensure data quality, security, and compliance. However, calling it “Data Enablement” instead of “Data Governance” can bring about a more positive and proactive perspective on the discipline. Here are several bullets that make a case for why some people believe that Data Governance should be called Data Enablement moving forward:

  • Emphasizes a positive approach – The term “Data Governance” can sometimes evoke a sense of command, control, and restriction, making it seem like a hindrance to data usage. By using the term “Data Enablement,” the focus shifts to empowering users and enabling them to make the most of the organization’s data assets.
  • Encourages collaboration – The term “Enablement” implies a cooperative and inclusive approach. It suggests that data management is a team effort that involves various stakeholders, including data analysts, IT professionals, business users, and management. This collaboration can foster a stronger data-driven culture within the organization.
  • Aligns with data-driven decision-making – Data Enablement highlights the role of data in facilitating informed decision-making. It encourages employees to access and utilize data effectively to support their business objectives, making data-driven decisions a natural part of their daily routines.
  • Enhances data accessibility and usability – The concept of Data Enablement promotes making data easily accessible and understandable to authorized users. It involves creating data catalogs, data dictionaries, and clear documentation, thereby making it easier for employees to find and utilize relevant data efficiently.
  • Integrates data security and compliance – Data Enablement doesn’t dismiss the importance of data security and compliance. Instead, it infuses these principles into the overall data enablement strategy, ensuring that data is used responsibly, ethically, and in accordance with relevant regulations.
  • Supports innovation and agility – The term “Enablement” is associated with empowerment and agility. By encouraging the efficient use of data, organizations can unlock innovative insights and respond swiftly to changing market dynamics and opportunities.
  • Engages stakeholders positively – Employees might feel more motivated and engaged when they perceive data management as a means of enabling their work, rather than something restrictive or bureaucratic.
  • Aligns with evolving data practices – In today’s data-driven world, the focus is on leveraging data for value creation and competitive advantage. By framing data management as “Data Enablement,” organizations acknowledge the transformative potential of data and how it can drive growth and success.
  • Enhances data literacy – The concept of Data Enablement encourages organizations to invest in data literacy programs and training initiatives. By equipping employees with the skills to work effectively with data, the organization can realize its data-driven potential to the fullest.

Renaming Data Governance to Data Enablement shifts the narrative from a restrictive approach to a more positive and collaborative one. This reframing can foster a culture where data is seen as an empowering asset that enables better decision-making, innovation, and business success.

Potential Breakdowns and Challenges

While renaming Data Governance to Data Enablement can bring positive connotations and emphasize a more proactive approach to data management, it’s essential to consider the potential downfalls and challenges that may arise from such a change:

  • Misinterpretation and confusion – The term “Data Enablement” might not clearly convey the underlying principles of data management, leading to misconceptions about its scope and purpose. This could result in misaligned expectations and confusion among stakeholders.
  • Dilution of regulatory and compliance focus – By emphasizing data enablement, there’s a risk of downplaying the importance of regulatory compliance, security, and privacy aspects associated with data governance. This could expose the organization to legal and reputational risks.
  • Insufficient attention to data quality – While data enablement encourages data accessibility, it might not emphasize the importance of data quality and accuracy. Poor data quality can lead to faulty insights and flawed decision-making.
  • Reduced accountability – The term “Enablement” might inadvertently reduce the sense of responsibility and accountability associated with data management. Data governance principles often involve clear roles, responsibilities, and oversight, which could be overshadowed by a more general enablement approach.
  • Lack of support for cultural change – Renaming data governance without adequately addressing cultural shifts and organizational buy-in can lead to resistance or lack of adoption. Employees might not fully grasp the significance of data enablement, impeding the successful implementation of data management practices.
  • Impact on data security – Emphasizing data enablement might inadvertently create an atmosphere where data access is prioritized over data security. Organizations must ensure that data protection measures are not compromised in the pursuit of data enablement.
  • Limited focus on data governance maturity – Data governance is often seen as a journey where organizations progress through different maturity levels. Renaming it to data enablement might obscure this growth-oriented perspective, resulting in an undervaluation of the need for continuous improvement in data management practices.
  • Resistance from stakeholders – Some stakeholders, especially those who have been accustomed to the term “Data Governance,” may resist the change, viewing it as merely a semantic shift rather than a meaningful transformation in data management practices.
  • Inconsistent application – Different teams or departments might interpret data enablement differently, leading to inconsistent application of data management practices across the organization. This lack of standardization could hinder collaboration and data sharing.
  • Difficulty in measuring success – With the term “Data Enablement,” it may become challenging to measure the effectiveness of data management practices, as the focus is more on enabling rather than governing. This can make it difficult to gauge the impact and ROI of data-related initiatives.

While renaming Data Governance to Data Enablement can introduce positive aspects, organizations should be mindful of the potential downfalls and ensure that the shift in terminology does not compromise the fundamental principles of data management, security, and compliance. Careful planning, clear communication, and a holistic approach to data management are essential for a successful transition.

Making the Move

Transitioning an organization’s culture from a focus on Data Governance to Data Enablement requires careful planning, effective communication, and a commitment to empowering employees with data. Here are steps your organization can consider taking to facilitate this transformation:

  • Define the vision – Clearly articulate the vision for Data Enablement within the organization. Highlight the benefits of enabling employees to access and utilize data effectively to make informed decisions, drive innovation, and enhance overall performance.
  • Educate and raise awareness – Conduct workshops, training sessions, and internal communication campaigns to educate employees about the concept of Data Enablement. Emphasize how it differs from traditional Data Governance and how it can empower them in their roles.
  • Involve leadership – Secure support from top-level executives to champion the shift towards Data Enablement. Leaders should actively promote the importance of data as a strategic asset and encourage a data-driven culture throughout the organization.
  • Develop a data strategy – Create a comprehensive data strategy that aligns with the vision of Data Enablement. Outline the steps, resources, and timeline required to enable data access, improve data quality, and enhance data literacy across the organization.
  • Foster collaboration – Promote cross-functional collaboration and communication to break down silos. Encourage departments to share data insights and best practices, facilitating a more holistic approach to data usage.
  • Empower data champions – Identify and empower data champions or data ambassadors within the organization. These individuals can act as advocates for Data Enablement, helping to drive adoption and facilitate knowledge sharing.
  • Establish clear guidelines – Develop clear guidelines and policies for data access, usage, and sharing. While enabling data access, ensure that data security and compliance are not compromised, and create protocols for data quality maintenance.
  • Implement data enablement tools – Invest in data analytics and visualization tools that are user-friendly and accessible to a wide range of employees. This can encourage self-service data exploration and analysis, promoting data-driven decision-making.
  • Measure and celebrate successes – Define key performance indicators (KPIs) to measure the effectiveness of Data Enablement initiatives. Celebrate successes and share positive outcomes to motivate employees and reinforce the importance of the transformation.
  • Provide ongoing support and training – Continuously support employees in their data enablement journey. Offer ongoing training, resources, and assistance to help them become more proficient in working with data.
  • Adapt and iterate – Be open to feedback and iterate on the Data Enablement approach based on lessons learned and changing organizational needs. Flexibility is key to a successful cultural transformation.
  • Share success stories – Highlight success stories and use cases where Data Enablement led to positive outcomes, improved decision-making, and enhanced business results. Encourage employees to share their experiences to inspire others.

Remember that transforming a culture takes time and perseverance. By taking these steps, an organization can gradually foster a data-driven culture that emphasizes the value of Data Enablement and empowers its workforce to leverage data effectively for business success.

Additional Considerations

While transitioning from a culture of Data Governance to one of Data Enablement, there are several other critical factors that an organization should consider:

Data Governance Integration

Ensure that the principles of data governance, such as data security, compliance, and data quality, are seamlessly integrated into the data enablement strategy. Data enablement should not compromise the organization’s ability to maintain control and accountability over its data assets.

Organizational Readiness

Assess the organization’s current data maturity level and readiness for the transition. Identify potential challenges and barriers to adoption and develop strategies to address them effectively.

Change Management

Implement a robust change management plan to guide employees through the cultural shift. Address resistance to change, provide support to employees, and communicate the benefits and long-term vision of Data Enablement.

Data Culture Ambassadors

Appoint data culture ambassadors or champions throughout the organization. These individuals can help advocate for Data Enablement, provide guidance, and act as liaisons between different departments.

Executive Sponsorship

Secure ongoing sponsorship and support from senior executives to sustain the Data Enablement initiative. Leaders’ commitment is crucial for driving the cultural change and overcoming potential roadblocks.

Data Literacy and Training

Invest in data literacy programs and training initiatives to enhance employees’ data skills and confidence. Ensure that employees understand how to work with data effectively and draw valuable insights.

Data Democratization

Promote a culture of data democratization, where data is accessible to all relevant stakeholders within the organization. Encourage data sharing, collaboration, and knowledge exchange.

Performance Incentives

Align performance incentives with data-driven behaviors and outcomes. Recognize and reward employees who actively embrace Data Enablement and demonstrate data-driven decision-making.

Communication and Transparency

Communicate openly about the goals, progress, and challenges of the Data Enablement initiative. Foster transparency to build trust among employees and stakeholders.

Data Ethics and Privacy

Educate employees about the ethical use of data and the importance of respecting data privacy and confidentiality. Embed ethical considerations into data enablement practices.

Data-Driven Decision-Making Culture

Cultivate a culture that values data-driven decision-making over intuition or anecdotal evidence. Encourage employees to base their decisions on data insights whenever possible.

Performance Measurement and Optimization

Continuously monitor and evaluate the impact of Data Enablement on the organization’s performance. Use feedback and data-driven insights to optimize and refine the approach over time.

Collaboration with IT

Work closely with the IT department to ensure that the necessary infrastructure, data systems, and security measures are in place to support Data Enablement effectively.

External Partnerships

Consider forming partnerships with external organizations, data experts, or consultants to gain insights and best practices on successful data enablement strategies.

Long-Term Commitment

Acknowledge that transitioning to a culture of Data Enablement is a continuous journey that requires ongoing commitment from all levels of the organization.

By carefully considering these factors, an organization can navigate the cultural transition from Data Governance to Data Enablement more effectively and foster a data-driven culture that propels the business forward.


The case for renaming or not renaming Data Governance to Data Enablement is primarily based on the following reasons:

  • Positive approach – Data Enablement emphasizes empowerment and collaboration, encouraging employees to make the most of data assets for better decision-making and innovation.
  • Data-driven culture – By framing it as Data Enablement, organizations can foster a culture where data is seen as an enabling asset rather than a restrictive element.
  • Enhanced data accessibility – Data Enablement promotes making data easily accessible and understandable to authorized users, leading to improved usability.
  • Integrating data security and compliance – Data Enablement incorporates data security and compliance principles, ensuring responsible and ethical data usage.
  • Support for agility and innovation – By enabling efficient data usage, organizations can unlock innovative insights and respond swiftly to market dynamics.

While there are potential challenges, such as confusion and reduced emphasis on compliance, I suggest that careful planning, communication, and a holistic approach to data management can facilitate a successful transition — if that is what you decide.

The article also offers steps organizations can take to facilitate the cultural transformation from Data Governance to Data Enablement. These steps include defining a vision, educating and raising awareness among employees, involving leadership, fostering collaboration, and measuring success. Additionally, the article advises considering data governance integration, organizational readiness, change management, data literacy, data democratization, executive sponsorship, and data ethics, among other factors, during the transition.

I hope that the article presented a comprehensive study of the considerations for shifting from Data Governance to Data Enablement and provided a level of guidance for you if you are going to embark on this transformational journey.

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Robert S. Seiner

Robert S. Seiner

Robert (Bob) S. Seiner is the President and Principal of KIK Consulting & Educational Services and the Publisher Emeritus of The Data Administration Newsletter. Seiner is a thought-leader in the fields of data governance and metadata management. KIK (which stands for “knowledge is king”) offers consulting, mentoring and educational services focused on Non-Invasive Data Governance, data stewardship, data management and metadata management solutions. Seiner is the author of the industry’s top selling book on data governance – Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success (Technics Publications 2014) and the followup book - Non-Invasive Data Governance Strikes Again: Gaining Experience and Perspective (Technics 2023), and has hosted the popular monthly webinar series on data governance called Real-World Data Governance (w Dataversity) since 2012. Seiner holds the position of Adjunct Faculty and Instructor for the Carnegie Mellon University Heinz College Chief Data Officer Executive Education program.

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