Powering Knowledge-Centered Service with Atlassian, Confluence, and Gliffy

With growing pressure on support teams to embrace AI and resolve issues faster, it’s easy for a “traditional” documentation practice to fall by the wayside.  

However, teams who fail to prioritize documentation eventually lose out on the long-term benefits of having a central source of truth.  

This is where the Knowledge-Centered Service methodology plays a unique role: including documentation in the workflow creates a flywheel effect that allows teams to find answers and resolutions faster than ever.  

In this blog, we’ll explore what the Knowledge-Centered Service methodology means and how you can help your own team take advantage of it using Atlassian, Confluence, and Gliffy together. 

What Is Knowledge-Centered Service (KCS)?  

Knowledge-Centered Service is a method of including documentation as a step in your workflow. 

Its core idea is that knowledge should be created as a byproduct of solving customer issues. It’s iterative, meaning articles continue to evolve as they’re used; every member of the team is engaged and considered an “owner” of the collected knowledge.  

For teams who already embrace agile workflows, KCS is a great culture fit because it reflects a similar philosophy of work.  

Benefits of KCS for Support and Service Teams  

The iterative, collaborative documentation created by following the KCS method is a valuable tool for improving team productivity. Overall wins against key metrics include:  

• Faster issue resolution as previous answers are better documented 
• Reduced ticket volume over time as documentation allows customers to self-serve 
• Consistent, high-quality responses available across teams and regardless of employee tenure 

Along with these performance benefits, KCS also improves the service agents’ experience through: 

• Faster, easier onboarding 
• Establishing a clear path to expertise as teams can identify who can contribute to an article and reach them directly for support or clarity 
• Less rework as articles are less likely to become outdated  

Finally, KCS benefits the customer as all the advantages listed above lead to better experiences and interactions with the support or service org! 

The KCS Process: Step by Step 

1. Search Knowledge  

The KCS process always starts with a problem. When a service agent begins investigating a ticket, they start with a search of the existing knowledge base to see if the same question has been addressed before.  

2. Leverage, Create, or Update Knowledge 

If the relevant knowledge already exists, it can be used to resolve the ticket. 

However, if the knowledge around a particular issue is incomplete, outdated, or unavailable, it is the agent’s responsibility to capture the new knowledge that they gain while they work through the problem.  

3. Resolve a Ticket, Publish an Update 

In the KCS framework, the customer’s problem is not considered resolved until the solution is documented and available for the entire team to reference, giving every team member access to the latest and greatest ways to solve a problem.  

Ongoing Optimization  

When handling common requests, agents will often not need to make major changes. Updates may be as simple as updating a screenshot to reflect a new user interface or adding a link to a related article. But over time, the emphasis on iteration means the most important articles will always continue to improve in quality and performance. 

Why the Atlassian Platform Is Ideal for KCS 

Atlassian’s ecosystem is a great fit for knowledge-centered workflows, primarily because of the integrations between Atlassian products that allow documentation to live and function alongside customer service systems. 

With Jira Service Management, knowledge is surfaced directly in the ticketing experience. Since customers can access this knowledge before submitting their requests, more tickets will be deflected, allowing service agents to prioritize more complex work.  

The documentation available to service agents and customers lives in Confluence, a centralized knowledge base with versioning and collaboration that allows anyone, not just service agents, to contribute to the collective knowledge.  

To further enhance the value of your documentation, Rovo, Atlassian’s AI functionality, can query the knowledge contained in your Confluence space, helping users quickly find answers to their questions.  

Ensuring Knowledge-Centered Service Works: Diagramming as a KCS Best Practice 

A well-structured KCS platform is a strong start, but its effectiveness is limited when knowledge is presented exclusively through text. Teams often encounter persistent challenges that undermine the core principles of KCS, even with excellent written content. 

• Articles are text-heavy and difficult to scan: Support agents and customers are typically under pressure to find answers quickly. Faced with a wall of text, they must invest significant time and mental energy to locate the exact piece of information they need, slowing down the resolution process and leading to frustration.  
• Complex processes are difficult to describe with words: Certain types of information are not easily conveyed through language alone. Trying to describe a multi-step workflow, a complex system architecture, or a conditional troubleshooting path with only text can result in convoluted and confusing documentation, and the risk of misinterpretation is high. 
• Knowledge is technically correct, but not easily understood: An article can be 100% accurate and still fail to be useful if the audience cannot easily comprehend it—a common problem in technical support, where subject matter experts create knowledge that makes sense to them but is impenetrable to a junior agent or an end-user.  

Including diagrams as part of your KCS workflow leads to better outcomes: 

• Faster comprehension for agents and customers: A well-designed workflow diagram or decision tree can convey in seconds what might take several minutes to read and digest. This accelerated comprehension leads directly to faster ticket resolution times and a more efficient support operation. 
• Reduced ambiguity in processes: Written instructions are susceptible to misinterpretation, but a visual workflow leaves no room for doubt about the sequence of steps, ensuring that every agent follows the same correct procedure every time. 
• Better knowledge reuse across teams: A clear diagram transcends differences in role, language, or tenure. A new hire can understand a process flowchart as easily as a senior engineer, and visual elements are often less dependent on language fluency. This makes your knowledge base more valuable to a wider audience, maximizing the return on your content investment. 

Use Cases Where Visuals Drive Clarity 

Diagrams are particularly effective for conveying complex information in an intuitive format. In a KCS context, their value is most apparent in the following scenarios: 

• Workflows: Visualizing a business or technical process from start to finish allows agents to understand the entire sequence of events at a glance. 
• System Integrations: A diagram illustrating how different systems connect and share data is far more effective than a lengthy written explanation of APIs and data flows. 
• Decision Trees: When a troubleshooting process involves multiple "if-then" scenarios, a decision tree provides a clear, step-by-step guide to help agents navigate the possibilities and arrive at the correct solution. 
• Escalation Paths: A visual chart of the escalation process ensures that issues are routed to the correct team or individual quickly, defining roles and responsibilities without ambiguity. 

Use Gliffy to Elevate Your Knowledge Base in Atlassian 

The KCS methodology is built on a loop of capturing, structuring, and reusing knowledge. Gliffy supports this cycle by integrating seamlessly into your existing workflows and making visual knowledge adaptable. 

Based on feedback from support interactions, agents can quickly refine a workflow, adjust a decision tree, or update a system diagram, all without ever leaving the Atlassian environment. 

The Benefits of Using Gliffy for KCS 

Diagrams Live Alongside Written Knowledge 

With Gliffy, diagrams are created and stored directly within your Confluence pages or Jira issues. This eliminates the need for context switching or managing files in separate systems. The visual explanation is embedded exactly where it is needed, right next to the corresponding text. 

Easy Updating for Evolving Processes  

KCS emphasizes that knowledge is never final; it must be continuously improved. Gliffy makes this easy. Diagrams can be updated in seconds, and since they are embedded in the page, every update is immediately reflected. There are no broken image links or outdated attachments to worry about. 

Fast Creation with AI-Powered Functionality 

Gliffy’s "Create with AI" feature allows you to generate diagrams from simple text prompts. This empowers any team member, regardless of design skill, to create clear and effective visuals and accelerate the knowledge creation process. 

Consistent Visuals Across Articles and Teams 

Gliffy’s templates and shape libraries enable your organization to standardize the look and feel of its diagrams. This creates a consistent visual language across your entire knowledge base, making it even easier for users to understand and navigate content. 

Get Started with Visual KCS in Atlassian 

While Atlassian products like Confluence and Jira provide the platform for your knowledge, KCS is the strategy that makes that platform powerful, and Gliffy adds the essential layer of visual clarity that enables your team to fully realize the benefits of KCS. 

With these elements together, you equip your organization to create a more effective and efficient knowledge base and drive faster resolutions. 

Ready to see the difference for yourself? Start building a more effective, visual knowledge base today. 

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