How to Build a Business Case for Your KM Project
For as long as I’ve been working in contact centers, they’ve been stuck with the "cost center" label. It's the kind of thing that makes every single expenditure, especially for something as crucial as Knowledge Management (KM), feel like it's being scrutinized against razor-thin margins.
Last week, I talked about how to build a knowledge base that customer service contact center agents actually trust and want to use. But even if you're able to figure out why your agents are struggling with a clunky knowledge base and what needs fixing, getting the necessary buy-in – and by that, I mean money and resources – can feel like an uphill battle. The financial and political challenges of securing this kind of investment are pretty substantial?
What I’ve run up against time and again when I’ve tried justifying investing in KM is that it’s often viewed as intangible. And let’s be honest, sometimes attempts at proving ROI don’t exactly deliver on their estimates, which can make things even harder.
This is precisely why we need to reframe the entire conversation. It’s not just about improving your KB or implementing a shiny new knowledge management system. It's about investing in a strategic program designed to achieve specific, measurable business outcomes. Shifting the perspective is absolutely crucial, and it’s the first step in tackling that whole narrative of customer support as just a cost center.
To do this effectively, you've got to approach it from two key angles. The first, and most crucial, aspect of this reframing is strategic alignment. Your Knowledge Management program objectives must be explicitly linked to the overarching strategic goals of the organization.
I’ve seen it more than a few times: companies will spend a lot of time and effort developing an organizational or corporate-wide strategy, but they don't necessarily put a lot of thought into their knowledge management strategy.
If you don’t have a KM strategy that’s closely tied to your organizational strategy, then you’re setting yourself up for failure–or at the very least, holding your organization back from being as successful as it could be.
If your company is laser-focused on improving customer retention, then your KM strategy should directly support that. This could mean looking at key performance indicators (KPIs) like customer satisfaction (CSAT), Net Promoter Score (NPS), or even customer churn.
If the focus is on reducing operational costs, then KM's impact on metrics like Average Handle Time (AHT) or First Contact Resolution (FCR) becomes paramount. We can also look at how KM impacts agent attrition in this context.
When you align your KM initiative with these larger organizational priorities, it becomes part of the solution to a significant business problem, rather than just a standalone project. That’s how you get buy-in.
When you’re putting together your case for knowledge management, remember that a one-size-fits-all business case will fail. Your narrative needs to be specific to the concerns of each key stakeholder.
For example, the Head of Customer Support cares deeply about FCR and AHT. The Head of HR will be focused on agent attrition and engagement. And for the CFO? They're looking at cost savings, revenue impact, and a clear ROI calculation. Your business case must speak their language, presenting the metrics and financial projections that matter most to them.
To build a truly credible and compelling narrative, we need a holistic framework for measuring KM success that captures its full impact. This framework can be broken down into four distinct, yet interconnected, pillars:
Operational Efficiency: This is all about running leaner, cheaper, and faster. Think about how KM can directly reduce AHT and improve FCR. Crucially, a really good KM program can also shine by deflecting contacts through successful self-service, preventing them from even reaching the contact center. This ticket deflection is super powerful and a key area where KM can demonstrate significant savings.
Agent Enablement and Retention: This pillar focuses on creating a more effective and stable workforce. Can you reduce new agent training time or agent onboarding time? Can you lower agent attrition?
A better knowledge infrastructure is a direct answer to frustrated agents and burnout because it provides them with the support they need to do the jobs you're asking them to do. This translates into real money saved by reducing recruitment costs, retraining costs, advertising fees, and all the overhead administration of hiring and onboarding.
While sometimes considered "soft," agent satisfaction and engagement is a super powerful leading indicator for agent attrition. You can use internal surveys like eNPS to measure the impact of your improved KM system on agent morale, providing both qualitative and quantitative data to strengthen your business case.Customer Experience and Loyalty: The goal here is simple: create happier and more valuable customers. The metrics are clear and obvious: Customer Satisfaction (CSAT), Net Promoter Score (NPS), and Customer Effort Score (CES). CES, for instance, is a really good way to understand how hard your customers are working to get their problem solved. A really good Knowledge Management System, both for agents and for self-service, is going to make it a lot easier for customers to get their issues resolved.
When you lower that customer effort, that’s a really key driver for loyalty. When customers don't have to work hard, they're much more likely to stay.Direct Financial Impact: This is the bottom line, the total quantifiable sum of savings from all the other pillars we've talked about. This includes reduced labor costs from lower AHT, fewer repeat calls due to higher FCR, reduced recruitment and training costs from lower attrition, and significant savings from deflected self-service tickets.
Perhaps most strategically, you can connect improved customer service to tangible revenue outcomes. Research from Bain & Company suggests that a 5% improvement in customer retention can increase profitability by anywhere from 25% to 95%.
Your business case needs to model how the financial impact of reduced customer churn, resulting from higher CSAT and NPS scores due to a better KM system, is really going to impact that bottom line. When agents aren't struggling to retrieve basic information, they have a lot more capacity for higher-value activities like upselling or cross-selling, which can also be tracked and quantified.
Ultimately, a successful business case for KM isn't just a spreadsheet churning out a final ROI percentage. It's a compelling and defensible narrative that tells a powerful story of transformation. The most effective leaders understand they're not just presenting calculations; they're persuading skeptics and sharing a vision for a strategy that's going to drive success for the entire organization.
If you’re interested in making a stronger case for your KM program, let’s talk!
Why Your Agents Hate Your Knowledge Base (And How to Fix It)
One of the biggest problems I’ve faced as a knowledge manager in customer service contact centers falls under the umbrella of agent adoption. I’ve run projects where we replaced an old, clunky knowledge base—something built in SharePoint or OneNote (yikes)—with a brand-new system in Salesforce, complete with a much-improved search algorithm. And yet, even after the upgrade, I’d still hear the same complaint from agents:
“I can’t find anything.”
It’s a frustratingly common problem. Even if you have a good system, the KB often becomes a source of irritation rather than a tool for success. This isn’t just about one thing; it’s a failure on multiple fronts.
First, there’s the search itself. Even with powerful algorithms and suggested content, older keyword-based search is flawed. We used to spend so much effort maintaining lists of keywords for each article, but agents would still get a dozen results with the same tags. They’d have to click into each one, read a bit, and back out, all while a customer is waiting on the line. That wasted time is a direct hit to your metrics.
Second, the information itself isn’t reliable. Agents search and find multiple articles on the same topic with slightly different, contradictory takes. They use one, get burned in a QA evaluation or anger a customer, and immediately lose trust in the entire system. Content health is crucial; if agents can’t rely on what they find, the tool is useless.
Finally, the design and structure of the content is often a major pain point. Agents aren’t knowledge managers; they’re problem-solvers under immense pressure. They need information structured logically and intuitively.
I remember working at one company where we had a very detailed policy for handling certain issues. The subject matter experts were adamant that it needed to be one big document with everything included. I really had to fight the battle to break it up into digestible chunks. When we finally did, the adoption and user ratings for that content went way up. It became understandable.
These failures have real consequences. They create longer handle times, lead to inconsistent answers across channels, and erode customer confidence. Most importantly, they burn out your agents. When agents feel uncertain and get beat up every day because their tools are failing them, they’re not going to stick around. All the money you invested in training and retaining them is wasted.
So, how do we fix it?
Improving discoverability is paramount. Modern, AI-powered search helps a lot because it can better predict the agent’s intent. An agent co-pilot that listens to the conversation and suggests the right content in the moment is a game-changer.
But the most overlooked solution is to engage your agents in knowledge creation. They can’t just be consumers of knowledge. Methodologies like Knowledge-Centered Service (KCS), which the Consortium for Service Innovation has been developing for nearly 30 years, are built on this idea. In KCS, knowledge is created as a by-product of solving problems. Agents are actively involved in creating new articles and flagging what’s outdated or conflicting.
To make this work, you need to build great feedback mechanisms and incentivize their use. Maybe you create a program that rewards agents whose feedback results in a change to an article. Give them the tools to create and share knowledge when they come across something new. New AI tools can even help, taking case notes and conversations and drafting an article for an agent to validate.
The knowledge they’re sharing and updating must be structured correctly. This isn't just about making it look neat; it's about making it usable. Think like an agent and organize information in the natural order of a call: greeting, authentication, troubleshooting steps, and so on.
Use formatting that makes information scannable—bullet points, highlighted scripting, and clear headings instead of long, dense blocks of text. You also need different article formats for different needs. A brand-new employee needs a verbose, step-by-step guide, while a veteran agent just needs a bare-bones refresher. (Exposing content based on roles is a powerful way to help improve discoverability, too.)
These days, you also have to structure content for AI. This means using standardized templates, like the "Problem-Solution" format, and clearly labeling sections so that bots can digest the information correctly. A good practice is to include a detailed procedure for the main body of the article but also add a list of FAQs at the bottom. This gives both agents and AI the best of both worlds: a comprehensive guide and quick, specific answers.
The bad news? This sounds like a lot of work.
It is.
The good news: AI tools can help with all of it. It’s not here to replace your agents, it’s here to help them–and by extension, your customer service team–work smarter and faster. By engaging your users in the conversation, you amplify acceptance and adoption.
Ultimately, this is about more than just technology. It’s an organizational transformation. The Boston Consulting Group calls it the 10/20/70 rule: 10 percent of thought toward the algorithm, 30 percent toward technology and 70 percent on organizational transformation.
Starting with a holistic approach and focusing on the human element is the key.
KM for Contact Centers
Customer service contact centers face a unique set of knowledge management challenges, truly distinct from other parts of a business. Tackling these head-on isn't just a good idea; it's vital for keeping things running smoothly, making your agents shine, and, most importantly, keeping your customers happy.
The Onboarding Hustle and High Agent Turnover
One big headache in contact centers? High agent turnover. Often, it boils down to agents feeling unsupported or just plain unqualified to handle customer questions. This problem is deeply connected to agent onboarding, a process that can be a real marathon for your Learning and Development (L&D) teams. We're talking weeks of classroom training, online modules, videos, nesting programs, and mentoring – basically a "firehose of information" that new agents are expected to memorize. The big goal? Get agents proficient fast so they can solve problems without constantly escalating, bugging Subject Matter Experts (SMEs), or just giving up because they can't find the answers.
But here’s the rub: if all that crucial knowledge is stashed away almost exclusively within the L&D domain, or in docs that live on a shared drive, it becomes incredibly tough for agents to get their hands on it when they’re actually on a call. This directly hits their "speed to answer" a customer's problem, leading to longer handle times and potentially frustrating customers who experience delays in getting their issues resolved. Think of it: they're not taking calls or chats while they're learning. It's all about moving from "just in case" knowledge (like training for something that might come up months from now) to "just-in-time" knowledge – giving agents what they need, when they need it, right there in the moment.
Tackling Complex & Evolving Information
Contact centers are often drowning in complex product information. We're talking technical details, intricate policies, and tricky troubleshooting steps. This inherent complexity makes it a real challenge for agents, especially the new folks, to give quick and accurate answers. Take one solar panel installation company I worked with: they had some seriously robust and complex policies around roof leaks. Agents needed to grasp how to spot a leak, when to offer to pay for technician visits, and the different remedies – from fixing a single mount to replacing an entire roof and reinstalling panels. To navigate that maze, clearly outlined policies and step-by-step workflows were absolutely crucial for agents to make the right calls.
And it's not just static complexity; customer issues are constantly evolving. As products get new features or fresh bugs pop up, the knowledge needed to troubleshoot effectively becomes a moving target. This is where smart Knowledge Management (KM) can really shine! Why? Because your frontline agents are often the first to identify new issues and discover solutions as they troubleshoot. Capturing these insights, which is often tacit knowledge or tribal knowledge – the collective wisdom in people's heads – and turning it into explicit knowledge is absolutely critical.
The Perils of Suboptimal Knowledge Storage
Let's be honest, many contact centers don’t have a formal Knowledge Management System (KMS). Instead, all that valuable knowledge often lives within the heads of subject matter experts (your go-to gurus) or it's dumped into general content management systems like SharePoint or Google Docs. And a truly suboptimal approach, one you see far too often, involves documents being stuck in PDF format, which is just plain inefficient for knowledge workers (your agents!) who need to find answers super quickly. It's like trying to find a needle in a haystack when you're on the clock.
The core challenge? Quick information retrieval is paramount. Whether an agent is hunting for an answer or a customer is browsing an external help center, the solution needs to appear instantly. The painful process of digging through a content management system, then finding a PDF, and then searching inside that PDF for the right answer, can eat up a ridiculous amount of time. This often leads to a swivel chair experience, where agents are constantly flipping between disconnected systems, making their workflow slow and prone to errors. This inefficiency alone can increase the cost of doing business by millions of dollars per year.
In many organizations, knowledge management is just an afterthought, especially because customer support is seen as a cost center. This can lead to a digital landfill of unmanaged and uncategorized documents that users simply avoid because finding anything of value is such a headache. For example, one company I worked with tried to use Microsoft OneNote as a knowledge base, despite it not being designed for that purpose. This resulted in 700 articles being imported into Salesforce Knowledge, and it took about a year to break the habit of agents using the old OneNote notebooks. This illustrates how ingrained suboptimal practices can become.
The data further emphasizes this problem: a survey indicates that 70 percent of companies aren’t using purpose-built knowledge management systems. This is significant, especially when you consider that only 32 percent of companies using non-purpose-built KMS are satisfied with what they have, compared to 75 percent satisfaction for those using a purpose-built system. The implication? There’s a massive opportunity to improve both customer and agent knowledge experiences.
The Real Cost: Time, Money, and Upset Customers
In the contact center world, the old saying time is money couldn't be truer. The longer an agent spends on a call, the higher the cost of resolving that customer's problem. When agents can't quickly access the knowledge they need, forcing them to dig through old training decks or videos, it directly leads to longer handle times. That extended wait time can really tick off customers, leaving them frustrated and unhappy. So, it's not just about having content, it's about making sure it's easily digestible and findable, and organized in a way that allows agents to quickly determine the most directly relevant policy or solution. Remember, "garbage in, garbage out" – if your knowledge isn't top-notch, it'll mess up everything, even your shiny new AI tools.
The AI Challenge: Built on a Shaky Foundation?
Virtually every company is looking at how AI can help their business. But for customer service, AI's success hinges on good knowledge. Many customers aren't thrilled with AI systems, often because they don’t find them helpful. A Five9 survey reveals that 75 percent of customers still want to speak to a human being. While a PwC study found that 71% of consumers prefer human interaction, they are open to AI if it genuinely improves their experience.
The reality for AI projects can be grim: Gartner's 2023 report highlights that only 53% of AI projects make it from prototype to production, and even two years later this remains a challenge for many companies.
A big reason for this failure? Bad knowledge. While almost 80 percent of customers expect to encounter self-service options like AI chatbots, only about 30 percent of customers expect to be able to solve their problems using those tools. If a chatbot relies on an outdated or incomplete knowledge base, it will deliver wrong or incomplete answers, pushing customers to human agents who then still need a reliable KB. The bottom line: having a solid, quality KB is step one to building AI systems that actually work for customers and agents.
Leveraging Knowledge Management for Solutions
To overcome these unique and costly challenges, you need Knowledge Management expertise from someone who is well versed in the unique challenges faced by customer service contact centers. Such experts understand the specific roadblocks to improvement and can guide organizations in leveraging different Knowledge Management systems to effectively address these issues.
Even a basic KM strategy can reduce the time employees spend looking for information by as much as 35 percent, which directly impacts operational costs. For instance, a 10 percent reduction in Average Handle Time (AHT) for a company I worked with led to a savings of over $264,000 annually.
The right MVP KB helps your agents get up to speed faster, makes customers happier, and provides the solid foundation needed for future success, including effective AI tools.
Don't let your contact center be plagued by knowledge challenges any longer. Cognita Knowledge Management has over 20 years of experience in customer service, with a deep understanding of these specific issues and the proven paths to improvement. Get in touch with us today to discuss how we can help you build an MVP KB that transforms your customer service operation into a powerhouse of efficiency, agent proficiency, and customer satisfaction.
Bridging the Gap: Why Knowledge Retention is Essential for Organizational Success
After a recent show with my band, I was talking to a band member’s wife who will soon be eligible to retire and claim a pension (a rare thing in this day and age). She has worn many hats in her organization, and lately she has been working to document the knowledge she has accumulated over the years. But it’s been slow going, mostly because there’s been no formal program to plan for succession; she’s doing what she can, but knows that so much of what she has learned will walk out the door with her.
In today's fast-paced, competitive business landscape, knowledge is power. But what happens when that power walks out the door? The departure of experienced employees, whether through retirement, career advancement, or changing circumstances, can create a significant knowledge gap, impacting productivity, innovation, and overall organizational success. This is why knowledge retention is critically important.
The Silent Drain: How Knowledge Loss Impacts Organizations
When experienced employees leave, they take critical things with them:
Tacit Knowledge: This is the "know-how" you can’t easily write down – the nuances, problem-solving approaches, and internal relationships. It’s the kind of knowledge that can't be found in manuals.4
Institutional Memory: The collective understanding of your company’s history, processes, and culture.5 Losing this can lead to repeated mistakes, wasted resources, and a decline in efficiency.6
Project-Specific Expertise: Insights gained from past projects, including lessons learned and best practices.
The consequences of this loss can be huge. A study by the Society for Human Resource Management (SHRM) found that the cost of replacing an employee can range from one-half to two times the employee's annual salary. This cost includes recruiting, onboarding, and training, but it doesn't fully account for the lost productivity and expertise. According to a report by Panopto, employees spend 5.3 hours per week searching for information. When critical knowledge walks out the door, searching gets even harder.
Building a Knowledge Fortress: Strategies for Effective Retention
So how do you keep knowledge from walking out the door? Here are a few MVP strategies:
Formal knowledge transfer programs
Mentorship programs: Pair newer folks up with more experienced employees.
Documentation: Created detailed documentation of processes, procedures, and best practices – starting now, not just as someone is about to leave.
Knowledge management systems (KMS): Use systems to make it easier for employees to capture, share and access knowledge.
Leverage Technology:
Video recording: Capture presentations, training sessions, and expert demonstrations.
Communities of practice: Implement collaborative platforms facilitate knowledge sharing.
AI tools: Use AI-powered tools to analyze data and identify key knowledge areas.
Create a Culture of Knowledge Sharing:
Open Communication: Encourage employees to talk and collaborate.
Recognition: Reward employees for sharing what they know.
Learning Environment: Make it okay to ask questions and seek help.
Knowledge-Focused Exit Interviews: Focus on capturing knowledge, not just reasons for leaving
Succession Planning:
Identify Key Positions: Plan for smooth transitions when people leave.
Cross-Training: Broaden employee skills.
Document Tacit Knowledge: Identify employees with key tacit knowledge and transfer it to others.
Data-Driven Approach:
Track Metrics: Measure time spent searching for information, onboarding time, and project completion times.
Use Analytics: Identify knowledge gaps and areas for improvement.
The Long-Term Investment
Knowledge retention isn’t a one-time effort. It’s an ongoing process that requires commitment and investment. By making it a priority, you can:
Reduce the impact of employee turnover.
Improve productivity and efficiency.
Foster innovation and creativity.
Enhance organizational resilience.
Preserve your company's culture and legacy.
Knowledge retention is a must for any organization that wants to succeed in today's world. Take action to capture, share, and preserve knowledge, and you'll build a sustainable and profitable future for organization.