Countless organizations invest hundreds of thousands of dollars into sophisticated data governance tools, only to see their records management programs collapse within months. The technology wasn’t the problem. In fact, the technology usually worked exactly as advertised. The real issue? They were trying to build a skyscraper on quicksand.
Here’s what typically happens: An organization realizes it has a records management problem. Maybe they failed an audit, or perhaps leadership just became aware of mounting compliance risks. The immediate reaction is to start shopping for solutions. They evaluate platforms, attend vendor demos, and eventually select what appears to be the perfect system. Everyone feels productive because they’re doing something. But they’re solving the wrong problem.
The question of who is responsible for records management programs never gets adequately answered. IT thinks Legal owns it, Legal assumes Compliance is handling it, and Compliance believes it’s an operational issue that belongs with department heads. Meanwhile, department heads are just trying to keep their teams productive and view records management programs as someone else’s problem entirely. This isn’t a technology gap, it’s a fundamental, organizational dysfunction that no data governance tools can fix.
Before you ever evaluate a single platform, someone needs to definitively answer who is responsible for records management across your organization. This doesn’t mean in theory or according to some dusty org chart. It means in practice, with actual authority, budget, and accountability. Without this clarity, even the most sophisticated system becomes just another expensive piece of shelfware.
The policy problem runs even deeper. Most organizations have a data governance policy that was written years ago, often copied from a template or borrowed from another company. Nobody’s looked at it recently. More importantly, nobody has tested whether it reflects how work gets done today. Your data governance policy might mandate retention schedules that made sense in 2015 but are completely impractical given how your teams collaborate now.
One data governance policy for a healthcare organization required all patient communications to be printed and filed within 24 hours. The company wrote the policy before implementing their patient portal, adopting Teams for clinical collaboration, and starting to use digital intake forms. No one updated the policy, so technically, every clinician was in violation every single day. That’s not a technology problem, that’s an organizational governance problem.
Then there’s the classification challenge that everyone underestimates. Organizations rush to implement data governance tools with elaborate taxonomies and metadata schemes without first asking whether anyone will actually use them. Classification systems often include 47 different document types and 23 retention categories. It might be theoretically perfect, but if your average employee needs a decoder ring and 15 minutes to figure out how to file a simple contract, they’ll dump everything in “Miscellaneous” or their personal drive.
Effective classification starts with understanding how people think about and use information, not how records managers wish they would. Effective classification requires involving actual workers in the design process – something that rarely happens before technology selection.
The executive alignment issue might be the most critical failure point. When asked who is responsible for records management at the executive level, most executives have no idea because they view records management as a “compliance checkbox” rather than a strategic business function. Without executive sponsorship, you’ll never get the cross-departmental cooperation necessary for success.
Your CFO cares about financial records, your General Counsel worries about litigation holds, your CISO focuses on data security, and your COO wants operational efficiency. Each has legitimate but different priorities for managing information. Someone at the leadership level needs to align these interests and establish clear data governance roles that cut across silos. This alignment must happen before technology deployment, not after.
The rush to technology is understandable. Platforms are tangible. You can demo them, test them, and deploy them. They create the appearance of progress. Organizational change is messy, political, and time-consuming. But here’s the reality: Data governance tools amplify whatever organizational capabilities you already have. If your governance is chaotic, technology will make it chaotic at scale (and at greater expense).
The most successful records management programs start with six months of foundational work before evaluating any technology. They clarify ownership, update policies to reflect reality, design practical classification schemes with user input, and secure executive alignment on data governance roles. Only then do they start looking at platforms.
Yes, this approach takes longer upfront. But it’s much faster than implementing a system, watching it fail, and starting over. Get the foundation right, and technology becomes an accelerator. Skip the foundation, and technology becomes just another failed initiative.
[Written by a human in collaboration with Claude.AI.]