As organisations grow, so does the volume of knowledge they rely on — policies, product documentation, support articles, internal guides and FAQs. What starts as a helpful knowledge base can quickly become a liability if information is outdated, inconsistent or incorrect. At scale, keeping knowledge articles accurate is no longer a matter of good intentions; it requires deliberate systems, ownership and technology.

So how can organisations maintain trustworthy knowledge content while continuing to grow?

Treat Knowledge as a Living Asset

The first mindset shift is to stop treating knowledge articles as static documents. Knowledge is a living asset that evolves alongside products, processes and regulations. Articles should be expected to change regularly, not written once and forgotten.

This mindset underpins all scalable approaches: updates are normal, reviews are planned, and improvement is continuous.

Establish Clear Ownership

Every knowledge article should have a clearly defined owner. This does not necessarily need to be an individual — ownership can be role-based or team-based — but accountability must be explicit.

Owners are responsible for:

• Ensuring accuracy and relevance

• Reviewing content on a defined cadence

• Responding to feedback or flagged issues

Without ownership, content becomes orphaned, and inaccuracies persist because no one feels responsible for fixing them.

Standardise Structure and Metadata

Consistency is critical when managing knowledge at scale. Standard templates make articles easier to read, review and update.

Effective standardisation includes:

• Common article structures (overview, steps, exceptions, references)

• Common styling to make knowledge consumption easier

• Consistent terminology and tagging

This reduces ambiguity and allows both humans and systems to work with the content more effectively.

Automate Reviews and Expiry

Manual review processes do not scale. Automation ensures that content hygiene does not depend on memory or goodwill.

Best practices include:

• Time-based review cycles (for example, every 90 or 180 days)

• Automatic reminders to owners

• Visual indicators for content that is overdue for review

• Temporary unpublishing or warning labels for stale articles

Use Real Usage Data to Prioritise Updates

Not all articles are equally important. Usage data helps teams focus their effort where it matters most.

Useful signals include:

• High traffic with low success or resolution rates

• Frequent searches that lead to no results

• High bounce or exit rates

• Repeated user feedback on the same content

By prioritising high-impact articles, organisations can improve overall knowledge quality without attempting to update everything at once. Universal Knowledge provides real time search analytics, multiple reports and dashboards which will reveal the most asked questions, unresolved queries, document usage and user adoption levels.

Build Strong Feedback Loops

The people using knowledge articles are often the first to notice when something is wrong. Feedback mechanisms should be simple, visible and encouraged.

Within Universal Knowledge by KPSOL, rework requests can be made by endusers – users who use articles to perform their role or resolve a customer query can be best placed to flag inaccuracies or unclear content.

At scale, distributed feedback becomes one of the most powerful quality controls.

Make Changes Transparent

Trust in knowledge content increases when users can see that it is actively maintained.

Good practices include:

• Visible “last updated” dates

• Brief summaries of recent changes

• Version history with the ability to roll back if needed

Transparency reassures users that the information is current and that errors are taken seriously.

Balance Governance With Speed

Excessive approval layers slow updates and discourage maintenance. Instead, organisations should adopt tiered governance with a KM solution which allows for different review and approval workflows:

• Low-risk edits (grammar, formatting, minor clarifications) can be published quickly

• High-risk content (legal, regulatory, safety-related) follows stricter review

• Periodic audits replace constant gatekeeping

The goal is to protect accuracy without creating bottlenecks.

Measure Knowledge Health, Not Just Volume

Finally, success should not be measured by how many articles exist, but by how healthy the knowledge base is.

Meaningful metrics include:

• Percentage of articles within review deadlines

• Number of ownerless or outdated articles

• Article success or resolution rates

These metrics provide early warning signs before knowledge quality deteriorates.

In Summary

Keeping knowledge articles accurate and up to date at scale is not a content problem — it is a systems problem. Organisations that succeed combine clear ownership, standardisation, automation, real-world feedback and intelligent use of technology.

When knowledge is treated as a living, governed asset rather than a static repository, accuracy becomes sustainable — even as scale increases.