Welcome to an insightful conversation with Vernon Yai, a renowned data protection expert with deep expertise in privacy protection and data governance. With a career dedicated to pioneering risk management strategies and innovative techniques for safeguarding sensitive information, Vernon brings a unique perspective to the evolving landscape of records and data management. In this interview, we dive into the nuanced concepts of “record-ness” and “data-ness,” explore how these ideas impact organizational practices, and discuss the importance of collaboration between records and data managers. Join us as we unpack practical insights for navigating the complexities of information governance in today’s digital world.
Can you break down the concepts of “record-ness” and “data-ness” in a way that’s easy to grasp for someone new to these ideas?
Absolutely. Think of “record-ness” as the quality of something that captures a specific moment or action—like a contract or a birth certificate. It’s about documenting an event or decision so it can be understood or referenced later, even by someone who wasn’t there when it happened. “Data-ness,” on the other hand, is about the bigger picture. It’s the ability of information to be grouped together and analyzed to reveal patterns or trends, like using thousands of birth records to understand public health issues. So, record-ness is about the individual story, while data-ness is about what all those stories tell us when combined.
Why do you think it’s more helpful to focus on these characteristics rather than trying to label something strictly as a record or data?
The problem with strict labels is that they don’t always fit reality. In today’s digital environment, information often serves multiple purposes. A patient’s medical file, for instance, is a record of their specific care, but it can also be part of a larger dataset for studying treatment outcomes. By focusing on characteristics—what the information does rather than what it is—we can better understand its value and manage it more effectively. It’s a flexible mindset that avoids getting stuck in rigid categories that might not hold up as technology and needs change.
How did you first come to see records and data through the lens of what they do instead of what they are?
It started when I was working on a project involving digital archives. We kept running into debates about whether certain files were records or data, and it was holding up progress. I realized that the real question wasn’t about definitions but about purpose. What was this information being used for? Was it to preserve evidence of a decision, or to analyze trends over time? Shifting the focus to function rather than form made everything clearer. It was a lightbulb moment—understanding the “why” behind the information helped us make better decisions about how to handle it.
Can you share a real-world example of how something can embody both record-ness and data-ness at the same time?
Sure, let’s take a hospital’s patient records. Each record documents an individual’s treatment—dates, diagnoses, medications. That’s record-ness; it’s evidence of specific care provided at a specific time. But when you aggregate thousands of these records, you can analyze them to spot trends, like how often a certain condition appears or how effective a treatment is. That’s data-ness. So, the same information serves as a historical account for one patient and as a tool for improving healthcare on a broader scale.
What do you see as the core difference in purpose between records and data, based on this framework?
At their core, records are about preserving the past. Their purpose is to capture a specific act or decision—like signing a contract or recording a meeting—so that it can be referenced or proven later. Data, however, is more about informing the future. Its purpose lies in aggregation and analysis to uncover insights or predict outcomes, like using sales figures to forecast market trends. Records anchor us to a moment, while data helps us see where we’re headed.
How can this perspective of record-ness and data-ness improve the way organizations manage their information?
It shifts the focus from arguing over categories to understanding value and use. Organizations can stop worrying about whether something fits neatly into a “record” or “data” box and instead ask, “What purpose does this serve?” This helps in creating policies that are more adaptable. For instance, it can guide decisions on how long to keep information—does it need to be preserved as evidence of an action, or is it useful for ongoing analysis? It also encourages better systems design, ensuring information is structured for both documentation and insight.
What challenges do organizations run into when they try to draw a hard line between records and data?
One big challenge is that information often doesn’t stay in one category. Something might start as raw data, like customer feedback, and later become part of a formal record when it’s used in a report. Trying to force a permanent label can lead to confusion or mismanagement—like deleting something too soon because it was labeled “data” when it actually had long-term evidential value. Plus, digital tools blur these lines constantly, transforming information in ways that defy strict classification. It can create silos, too, where teams miss opportunities because they’re stuck in their own narrow definitions.
How do you see the roles of records managers and data managers overlapping in their work?
There’s a lot of common ground, especially when it comes to protecting and organizing information. Both roles are concerned with ensuring data or records are accessible to the right people and secure from risks like breaches or loss. They also both play a part in deciding what to keep and what to discard, even if their reasons might differ. In practice, whether it’s maintaining institutional memory or enabling smart decision-making, their goals often align—they’re just approaching it from slightly different angles.
Why is collaboration between records managers and data managers so important in today’s environment?
Collaboration is key because the lines between their responsibilities are increasingly blurred. In a digital world, information flows between systems and purposes so quickly that working in isolation can lead to gaps or inefficiencies. For example, a records manager might ensure a document is preserved for legal reasons, but a data manager might need that same document as part of a dataset for analytics. If they don’t communicate, one might delete something the other needs. Working together ensures a holistic approach, balancing compliance with innovation.
Looking ahead, what is your forecast for how the concepts of record-ness and data-ness will shape information governance in the coming years?
I think these concepts will become even more central as organizations grapple with growing volumes of digital information and new technologies like artificial intelligence. We’ll see a stronger push toward flexible governance models that prioritize purpose over strict labels, allowing for better adaptation to change. I also expect more integrated roles—where records and data management aren’t seen as separate but as complementary parts of a single strategy. Ultimately, this mindset will help organizations stay agile, ensuring they can both preserve critical evidence and leverage insights for decision-making in an increasingly complex landscape.
