As a data governance expert at Keyrus UK, I regularly engage with data management and data governance leaders across various industries. Through these conversations, one challenge consistently emerges as the most pressing concern: “Who owns the data?"
This fundamental question lies at the heart of countless failed data initiatives. Most organisations struggle not just with defining data domains, but with establishing clear ownership of these domains. And for those who successfully navigate this initial hurdle, an even greater challenge awaits: identifying ownership for aggregated or cross-domain data.
The Data Ownership Dilemma: Why Most Organisations Struggle
In my experience working with enterprise clients, the data ownership problem stems from a common misconception. Many organisations believe they need to create entirely new structures and hire new personnel to solve their data governance challenges. This approach invariably leads to confusion, resistance, and ultimately, failure.
The reality is far simpler—and more complex—than most leaders realise.
Four Key Principles for Successful Data Domain Ownership
Through my work with clients who have successfully solved these data ownership challenges, I've identified four critical principles that separate successful initiatives from failed ones:
1. Drive Domain Definition and Ownership from the Top Down
Data governance is fundamentally about organisational alignment, not just technology. This alignment must be driven from the CXO level to be truly effective.
The enterprise data strategy should serve as the foundation for domain definition. Rather than allowing domains to emerge organically (which often leads to overlap and confusion), successful organisations embed domain definition within their overarching data strategy. This top-down approach ensures that domain-specific data strategies align with broader business objectives.
2. Recognise That Data Domains Already Exist Within Your Organisation
One of the most valuable insights I share with clients comes from Zhamak Dehghani's work on Data Mesh: "Your domains exist within the seams of your existing organisation structure."
Too often, organisations attempt to restructure their operations to accommodate new data domains completely. This approach is both unnecessary and counterproductive. Instead, successful data governance initiatives identify and formalise the domains that naturally exist within current organisational structures.
3. Establish Cross-Domain Accountability Through Value Chain Mapping
Cross-domain accountability represents perhaps the most challenging aspect of data ownership. However, it becomes manageable when you focus on understanding the data value chain and aligning it with existing organisational structures.
This approach enables organisations to identify cross-domain accountability and ownership patterns successfully. Building clean, consumer-ready, source-aligned data products also accelerates and supports the ownership definition process.
4. Identify Data Owners from Within Existing Resources
Similar to domains, data owners already exist within your organisation. They're rarely new hires who need extensive training on your data landscape. The most effective data owners are existing team members who possess two critical qualities:
Deep understanding of the data itself
Clear comprehension of the data's business purpose
These individuals are uniquely positioned to design, build, and manage data assets while ensuring proper governance and quality standards. The key is for business and organisational leaders to identify these natural data owners and provide them with clear role mandates and appropriate incentives.
Why Data Ownership is Critical
Solving the ownership problem serves as one of the key differentiators between successful and unsuccessful data management initiatives. Without clear ownership structures, even the most sophisticated technical implementations will struggle to deliver sustainable value. This connects directly to broader data governance challenges I've explored in previous work, particularly around building sustainable data governance frameworks and understanding why many initiatives fail.
Implementing Data Ownership Solutions: A Practical Approach
Based on my consulting experience, here's how I recommend organisations approach the data ownership challenge:
Start with Strategic Alignment
Begin by ensuring your C-suite understands that data ownership is a business problem requiring business solutions. Technical teams can support the implementation, but the fundamental decisions about ownership must come from business leadership.
Map Your Current State
Before attempting to create new structures, conduct a thorough assessment of your existing organisational domains. You'll likely discover that the foundation for your data domains already exists.
Define Clear Accountabilities
Establish explicit accountability frameworks that connect data ownership to business outcomes. This includes both single-domain and cross-domain scenarios.
Empower Your Natural Data Owners
Identify the individuals within your organisation who already understand both the technical and business aspects of your data. These are your future data owners—they just need formal recognition and support.
The Path Forward for Data Governance Excellence
The organisations that successfully solve data ownership challenges share a common approach: they recognise that data governance is fundamentally about people and processes, not just technology. By leveraging existing organisational strengths and establishing clear top-down direction, they create sustainable frameworks that deliver long-term value.
As data volumes continue to grow and regulatory requirements become more stringent, the importance of solving the data ownership challenge will only increase. Organisations that address this fundamental issue now will be best positioned to capitalise on their data assets in the future.
What's your experience with data ownership challenges? I'm always keen to hear from data management experts about the strategies and approaches that have worked in your organisations. Connect with me on LinkedIn to continue the conversation.
About the Author: Suyash Singh is a data and analytics expert at Keyrus UK, specialising in data governance, data management, and enterprise data strategy. He works with organisations across industries to solve complex data challenges and build sustainable data capabilities.
Further readings:
Blog: AI and Data Engineering: Enhancing Analytics & Data Governance