Your Knowledge Base Is Failing. The Reason Is People (And the Fix Is, Too).
One of the biggest misconceptions I see in customer service is the belief that creating a successful knowledge base is a technology problem. The thinking goes: find the right software, populate it with a few documents, and you're set. In my experience, this approach is one of the single biggest predictors of failure for a knowledge base project.
If you don't put serious thought into the people who will create, maintain, and share knowledge, your project is doomed from the start.
The "Set It and Forget It" Graveyard
I once met with a client in 2024 to discuss their knowledge management ecosystem. They showed me their knowledge base, and as I scanned the list of articles, I noticed the "published" date for nearly every single one was from 2017. I told them, "Well, I know why nobody wants to use your knowledge base. Your content is ancient.".
This is a classic example of the "set it and forget it" mindset that plagues so many organizations. They focus on the system and the initial content load, but give little thought to how that content will be managed over time. This reluctance to invest in the people who maintain the content is a critical mistake.
The Old, Broken Model
The legacy approach to knowledge management often involved fairly heavy staffing. You'd have a knowledge manager and a team of technical writers responsible for managing all, or at least most, of the content. When a new support issue was identified, a tech writer would have to work with a subject matter expert (SME) to get a draft into shape, often leading to a long back-and-forth process. After all that, the article would still have to wait for a manager's review before it could be published.
This system extends the content publishing cycle from what could be hours or days into weeks or even months. By the time the information is available, it might already be obsolete.
A Better Way: Source Knowledge from the Front Line
The solution is to flip the model on its head. Empower the people on the front lines—your agents and SMEs within that population—to create and share knowledge directly.
This doesn't mean every agent needs to be a polished writer. But every single agent is skilled at recognizing knowledge gaps or incorrect information when a supposed solution fails with a customer. More tenured agents, in particular, are perfectly suited to share new knowledge and help review updates.
This is why I strongly advocate for creating two key roles within your organization: the
Knowledge Contributor and the Knowledge Curator.
Knowledge Contributors: These are not full-time positions. These are roles filled by your experienced Tier 2 or Tier 3 agents who have the tenure and deep knowledge of how things are supposed to work—and what to do when they break. With modern, AI-infused knowledge management systems, these contributors don't have to be expert writers. AI can help format their insights, which can then be passed to a curator for review.
Knowledge Curators: Like contributors, curators are not full-time staff dedicated solely to the knowledge base. Curation is simply a subset of their job. They review contributions for accuracy and also manage the feedback coming in from the wider agent population. It's crucial that when a frontline agent provides feedback on an article, it doesn't just go into a void. Curators ensure that feedback is reviewed and applied, closing the loop and continuously improving your content.
From Top-Down to Bottom-Up
By adopting this approach, you stop pushing knowledge from the top down and start sourcing it organically from the bottom up. This has massive benefits. Companies that adopt similar people-centric approaches like the Knowledge-Centered Service (KCS®) methodology have seen a 30–50% reduction in time to resolve issues, a 20% improvement in employee retention, and 70 percent faster time to proficiency for new agents.
This model engages your employees in a powerful new way. It allows them to share their hard-won expertise and develop new skills, helping them to further their careers. Even newer agents can be engaged by giving them easy-to-use tools to provide detailed written feedback on articles, knowing that a curator will see it and act on it.
Stop thinking about your knowledge base as a library and start thinking about it as a living, breathing part of your team. Invest in your people, and you’ll build a knowledge practice that actually works.
Transform Your Digital Landfill: The Essential Guide to Content Audits
If you’ve spent any amount of time in a customer service organization, you’re likely familiar with those sprawling knowledge repositories that feel less like a helpful resource and more like a "digital landfill." It's a dumping ground of unmanaged, uncategorized content where finding what you need is a struggle, and even if you do, you're left wondering if it's the right, authoritative version.
Getting a handle on all of it can be a challenge. The first step is to complete a comprehensive content audit; it's your treasure map to transform that landfill into a goldmine of useful information. Through an audit, you can identify valuable content, flag what desperately needs revision, uncover gaps, and truly understand what you’re working with. Ensuring the accuracy and relevance of your knowledge base has far-reaching effects – not just on agent performance but also on those tricky AI projects many customer service organizations are wrestling with today.
So, how do you conduct an effective content audit without getting completely overwhelmed? Let's break it down.
Step 1: Define Your Scope – Don't Try to Eat the Whole Elephant at Once!
The very first thing to do is decide which content sources you're going to audit. This could be your existing knowledge base in Salesforce or Zendesk, documents tucked away in SharePoint or Google Drive, or even content in Confluence or Microsoft OneNote.
The key here is to focus. Don't try to tackle everything at once. I highly recommend applying the Pareto Principle: aim to audit the 20% of content that solves 80% of your problems. In my experience, knowledge repositories often house hundreds or thousands of documents, and a microscopic look at each one is simply too time-consuming and resource-intensive. Narrowing your focus will get you a long way.
Step 2: Inventory Your Content – Get Organized!
Once you've identified your scope, it's time to create an inventory. A simple spreadsheet can work wonders here. You'll want to list each content item and include crucial details like:
Content title
Where it's located
Who authored it
When it was last updated
Any additional criteria relevant to your organization
Crucially, this tracker should also include a clear indication of the final action for that content. Are you going to archive it? Import it into your knowledge base? Or update it first, then import it? Tracking these decisions centrally is incredibly important.
Step 3: Systematically Audit Each Item – The Nitty-Gritty Evaluation
Now for the real detective work: evaluate every piece of content against specific criteria to ensure its quality and usefulness. Here’s what you should be looking for:
Accuracy and Relevance: Is the information correct, up-to-date, relevant to your audience, appropriate, and actionable?
Duplicates or Inconsistencies: Is the content unique? Does it conflict with other information? Is it internally and externally consistent?
Article Structure: Does it have a clear title? Does it flow logically? Is it scannable, concise, and searchable? Is the structure useful for both human agents and AI?
Language and Tone: Depending on your audience, the language will vary. For internal agents, it can be professional and a bit more technical. But if it's customer-facing or feeding AI chatbots, it needs to be friendlier and less technical.
Format and Accessibility: Is it in a knowledge-base-friendly format? Is it effectively formatted with consistent headers and clearly labeled sections that both humans and AI agents can easily understand?
Ownership and Review Dates: Who owns this content? Is that person identifiable? Does it have a clear review or expiration date to signal if it's outdated?
Step 4: Decide on Actions – What's Next for Each Piece?
After your thorough evaluation, you need to assign a clear action in your spreadsheet. These actions typically include:
Keep as is
Revise or update
Consolidate (merge with other content)
Archive or retire (remove it permanently)
This entire exercise is fantastic for getting a new knowledge base up and running, or even adding new material to an existing KB, especially when you're importing content from multiple repositories into a single source of truth.
Beyond the Initial Audit: Continuous Improvement is Key!
But the work doesn't stop once your knowledge base is live! You still need to conduct regular audits. Pay close attention to signals from your knowledge base metrics, such as:
Page views
User feedback
Article use
Failed search results
Expiration dates
Broken links
Content gaps
Redundant content
These are crucial indicators that an article needs attention or your knowledge base needs clarification to remain useful. If agents perceive it's not useful, they simply won't use it, and their work will suffer.
And here’s a pro-tip: involve Subject Matter Experts (SMEs) all along the way. They are absolutely indispensable for verifying the accuracy and relevance of your content. Often, these aren't just tech writers, but senior agents or managers who truly understand customer problems and what content is most useful for quick resolution.
Regular content audits are the key to continuous improvement for any knowledge base. By paying close attention to these signals and involving your SMEs, you ensure your knowledge base remains a valuable and trusted resource, both internally and externally. This helps you proactively avoid that dreaded "garbage in, garbage out" problem that a digital landfill will inevitably give you.
If you're looking to tackle your own content audit, Cognita Knowledge Management can help. Get in touch today or schedule a no-strings 15 minute consultation.
Welcome to the New and Improved Cognita Journal
Longtime subscribers already know that I’ve decided to make some changes to how I handle my newsletter. Basically, I’m simplifying my workflow and optimizing my content marketing strategy by going with a blog-first approach.
That means I’ll be publishing the newsletter at www.cognita-km.com/blog, then sending it out to subscribers. I’m also going to stop publishing the newsletter on LinkedIn, though I will still be quite active there as it’s my primary social media channel for Cognita.
Let me know if you have any suggestions for improvements!
Upcoming appearances
On September 18, I’ll be speaking at the Association for Talent Development Austin Chapter’s Quarterly Chapter Meeting. Topic: From “Just-In-Case” to “Just-In-Time” – Empowering Learning & Performance with MVP Knowledge Management. Learn more
I’m excited to announce that I’ve been invited to speak at the Contact Center AI Association’s quarterly meeting in New York City on September 25. The meeting will focus on Knowledge Base Management as well as Roles and People Driving AI Initiatives. Learn more
Don't Let Your AI Trip Over its Own Two Feet: Why Trusted Knowledge is the Real MVP!
I recently came across the State of AI 2025: Mid-Year Report from eGain and Unisphere Research, and found some insights that anyone who manages a knowledge base (or cares how they’re managed) should keep in mind.
The report says that 70% of the organizations they surveyed are already piloting or having deployed GenAI. From customer self-service (cited by 45% of respondents) to human-assisted contact centers (38%), AI is quickly becoming part of how we deliver support. Even knowledge workers, including authors and managers, are significant users of GenAI output, at 45% each.
But (and it's a big one) there's a crisis of trust, which probably comes as no surprise. In the survey, 61% of respondents said they’re concerned about the accuracy or consistency of AI answers, and 54% worry about non-compliance. “Garbage in, garbage out" has never been more relevant. If your AI is built on faulty data, you can't expect reliable results.
The report points directly to the Achilles' heel of many organizations: siloed knowledge bases and failing legacy systems. A majority of companies (55%) are wrestling with three or more knowledge silos, and 51% are juggling three or more different KM tools.
As the report puts it, "Simply slapping GenAI over these silos only takes chaos to the next level.” This is exactly why a badly managed KB is worse than no KB at all—you're paying to create problems, not solve them.
If I’ve said it once, I’ve said it a thousand times: knowledge management technology and processes are the key to successfully deploying customer service AI that works (and that people want to use). It looks like 83% of the survey respondents agree. Without a robust knowledge foundation, AI struggles to understand context and intent, leading to frustration for both customers and agents. This isn't just about efficiency; it's about making sure your AI isn't messing up your AI.
So, what's the solution? A robust, well-managed knowledge base that serves as your single point of truth. The approach outlined in my book, “MVP KB: A Practical Guide for Customer Service Knowledge Management" is one way to tackle this problem.
Here’s how a trusted MVP KB and AI can create a powerful duet:
Automation for Efficiency: AI can automate the discovery, creation, curation, publication, and optimization of knowledge, potentially leading to a ten-fold improvement in the speed of knowledge creation and findability of answers. This frees up your human experts to focus on complex issues.
Empowering Your People: Even with AI, human expert involvement is critical for assuring the quality of GenAI output. Your agents are the experts, and the MVP KB empowers them to contribute, share, and provide feedback, turning tacit knowledge into explicit, valuable assets. The knowledge manager acts as a change agent, not a gatekeeper.
Single Source of Truth: Unifying your knowledge into a single, trusted hub is essential. This means better, more consistent answers for customers and faster problem-solving for agents. Currently, close to two in three respondents (64%) in the survey I talked about earlier either have no plans for consolidating their knowledge silos or are unaware of such plans. This represents a key reason for the failure of KM initiatives.
Modern Capabilities: Many companies are still not actively using GenAI for content creation and curation. However, modern KM systems offer AI-powered features for drafting articles, summarizing information, and identifying knowledge gaps, making content creation faster and easier.
Don't Be Afraid to Start!
While 62% of companies are "not in 'love'" with their current KM technology, and many are missing opportunities to leverage GenAI for content creation, the good news is that it’s fixable. Get a jumpstart on building your MVP KB by reading MVP KB: A Practical Guide for Customer Service Knowledge Management, or schedule a free, no-strings consultation with yours truly.
Take the first step toward ensuring your AI systems truly work for your customers and agents, providing accurate, relevant, and accessible knowledge every single time. Make sure your AI plays a winning tune, not just noise.
KM News
This one has 4.5
Derek Smalls being one of the greatest bass players of all time means that I have to share this story about where AI consistently comes up short.
See Me, Feel Me
If you’re not following me on LinkedIn, you may not know that I recently was a guest on the Contact Center Gurus Podcast. I’ve been working with Fred, Darren and the team at Cloud Tech Gurus since late last year. They’ve recently restarted their podcast series, and invited me on to talk about the future of knowledge management. Check it out:
Take on me
I’m not much for hot takes, but I’m of the strong opinion that AI is the ultimate KM tool (if it’s used in the right way). A recent story from AI Invest supports my contention. The AI-driven KM market is on track to be about $9.6 billion by 2025, driven by the urgent need to automate data workflows and analyze unstructured information. By freeing employees from repetitive tasks, they can focus on high-value work, becoming much more efficient. But it can only happen with robust governance frameworks and a clear strategy, turning knowledge from a liability into a genuine competitive asset.
Song of the Week
“MRI” - Derek Smalls (feat. Dweezil Zappa)
Building a People-First Knowledge Base
It’s happened to me more than once: someone asks me to get a new knowledge base going, and during the initial assessment we find an old knowledge base just sitting around gathering dust.
At one company where I worked, I was hired specifically because the VP for Customer Care realized how important it was to have a solid, well-managed knowledge base.
When I got into the job and started digging, the first thing I found was a “sort-of” KB that some SMEs had put together in Microsoft One-Note. Yeah, there was a lot of info in there, but it was out of date, inconsistent and impossible to find. You had to know exactly what you were looking for to find anything – not a great experience, especially for new employees.
I dug a little deeper and discovered that some team managers had made a half-hearted attempt five years before to use Salesforce Knowledge. That was a whole lot better than One Note. But nobody was using it, and the people who had started it up had long since left for other jobs.
I’ve seen this pattern repeated in my consulting work time and again. Someone in the past thought it would be a good idea to have a KB, they tried to build something and then it just … went away.
In all of the cases, the failure boiled down to a simple reason: no one was thinking about the people it served. They were just putting together a system to hold some knowledge artifacts.
But the secret to a successful Knowledge Base (KB) isn't just about the system or even the knowledge it holds; it has put people first. When you empower your team to own the knowledge they use and create, you unlock the true potential of your knowledge assets.
Here’s how to foster a human-centered KB:
Empower Knowledge Users: Your frontline agents are the key to success. They should be using the KB daily to solve customer issues and are often the first to spot knowledge gaps or inaccuracies. When you give them the tools to highlight gaps or areas for improvement, that creates a sense of ownership – meaning they’re more likely to use it.
Leverage Knowledge Contributors (SMEs): In an ideal world, every single agent can share their know-how; that’s the promise of frameworks like Knowledge Centered Service (KCS). In my experience implementing KM programs, I’ve found that Subject Matter Experts (SMEs) are your go-to people for "know-how" and tribal knowledge. They are the ones that should create and update articles directly in the KB as they work. This captures their valuable insights and frees them from repeatedly answering the same questions.
Support Knowledge Curators: Even when you have a healthy number of expert contributors, you still need folks who can curate all the submissions, to make sure that they meet specifications, aren’t duplicates and so on. Knowledge Curators work right beside Contributors, reviewing submissions, ensuring consistency with style guides, and maintaining the KB's overall health and findability. In fact, it’s usually best if your Curators are drawn from the ranks of the Knowledge Contributors.
Define the Knowledge Coordinator/Manager Role: Many companies who don’t have a knowledge management function are adverse to creating management-heavy teams to do the work. Still, it’s crucial to have at least one person who "owns" the KB, overseeing daily operations, monitoring its health, planning improvements, and serving as the primary point of contact for leadership and cross-functional teams. They are a change agent, not a gatekeeper, facilitating knowledge sharing across the organization.
Cultivate a Culture of Sharing: Encourage open communication, collaboration, and reward employees for their valuable contributions. Implement forums like communities of practice (or "Knowledge Cafés" or use channels like Slack/Teams for informal sharing and new knowledge flagging.
At the end of the day, it’s important to remember: knowledge management is something that you do for (and with) people, not to them. Following a collaborative approach ensures your KB will be something people actually like to use because it’s continuously fresh, relevant, and truly valuable.
KM News Notes
Cresta Unveils New "Generative AI for CX" Features to Proactively Assist Agents
When most people think about KM for Customer Service Contact Centers, they think of customer self-help chat bots. But AI-based agent assist is a key tool for contact center leaders. Recently, Cresta announced a significant expansion of its generative AI capabilities that moves beyond reactive assistance to proactive knowledge delivery for customer support agents. The updated Cresta Agent Assist will now automatically surface knowledge base articles, step-by-step guides, and real-time coaching suggestions based on the live context of a customer conversation, without the agent needing to manually search. This addresses a key challenge in knowledge management: ensuring agents can find the right information precisely when they need it, reducing hold times and improving first-contact resolution.
Salesforce Study Reveals AI's Impact on Customer Service Knowledge Gaps
A recent report from Salesforce provides data-backed evidence that AI is crucial for knowledge management success in customer support. One key finding: 81% of service agents believe AI is most valuable for its ability to automatically surface knowledge from various sources. The study shows that companies using AI-powered knowledge management tools saw a significant decrease in agent onboarding time and more consistency in case resolution.
Glean Launches "Workplace Search" Assistant to Unify Enterprise Knowledge for Support Teams
A big challenge for customer support teams in virtually every organization is having to find knowledge that’s trapped in silos across the company. Tech startup Glean has officially launched its new workplace assistant designed to solve this problem. The Glean assistant connects to over 100 different applications – like Zendesk, Slack, Jira, and Confluence – to create a single, unified search experience. When a support agent has a complex customer query, they can ask the Glean assistant one question and get an answer from resolved tickets, internal wikis, team chats and more. This approach drastically cuts down on search time and improves the quality of agent responses.