Knowledge is power. This statement is as true in life as it is in IT Service Management (ITSM) and Enterprise Service Management (ESM).

Delivering great service experiences is becoming more challenging, with customer and end-user expectations increasingly steadily, and many organisations investing heavily to deliver outstanding service as a differentiating factor for their business.

For enterprises looking to meet or exceed these expectations, Knowledge-Centred Service (KCS) stands as a strategy applicable in service management to transform the service experience. By intertwining knowledge management and knowledge creation with everyday service delivery, KCS not only boosts operational efficiency but also empowers both agents and customers to resolve incidents and problems faster.

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What is Knowledge-Centred Service?

Knowledge-Centred Service (KCS) is an approach to service delivery that incorporates the creation and maintenance of knowledge and documentation into regular day-to-day service delivery. This sees support teams not only providing service to end-users or customers, but also creating and maintaining knowledge.

The KCS methodology revolves around four key principles:

• Knowledge Creation: Documenting knowledge as a natural byproduct of resolving issues.
• Knowledge Evolution: Content that adapts based on real-time demand and usage.
• Knowledge Base Development: Developing a centralised repository that captures collective organisational experience.
• Continuous Learning: Fostering collaboration to refine and improve knowledge continuously.

This approach ensures each interaction, whether with a customer or internal stakeholder, becomes an opportunity to capture valuable insights.

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How Knowledge-Centred Service Benefits Service Management

Implementing Knowledge-Centred Service can be transformational for how businesses deliver service, by addressing customer experience preferences and tightening internal operations.

1. Give customers and end-users the knowledge to enable self-service

67% of customers prefer to resolve their own issues via self-service instead of speaking to a support agent (Zendesk 2013). With many people finding it more inconvenient to speak to a human or wait for a response, they often turn to forums, blogs, Reddit and other sources of information to resolve their own issues. A robust knowledge base built through a KCS approach can give customers and end-users access to a comprehensive self-service portal, and get service the way they want it.

2. Faster ticket resolution

When a customer can’t resolve their problem themselves, a well-maintained knowledge base will ensure that your service agents can quickly access the information they need to deploy remediations quickly, without having to do research or escalate an issue. End-users will experience less downtime or waiting for a fix, and your service agents can increase their overall productivity.

3. Reduce double-handling and increase agent productivity

KCS continues to improve the overall productivity of your service agents as more and more problems and their resolutions are captured in your knowledge base. Instead of agents having to research, ask their colleagues or escalate tickets when they come across a problem unfamiliar to them, they can refer to the knowledge base to quickly access the required information.

4. Continuous organisational learning and reduced onboarding friction

Through ongoing, systematic knowledge capture and retention, KCS helps preserve expertise when employees leave the organisation and fosters a culture of continuous improvement and innovation. This knowledge also reduces the time it takes to onboard and train new service agents, with a wealth of knowledge they can draw upon to get up to speed quicker.

5. Reduced Service Costs

By shifting customers and end-users towards self-service resolution, speeding up ticket resolution with knowledge to aid your service agents and reducing the time it takes to train new service agents, KCS can drastically reduce your service operational costs.

6. Enable the use of AI in your service management processes

AI loves data. In fact, AI needs data to power its understanding when it comes to your service management processes. While past tickets, incident summaries and problem records will give it a wealth of data, what your AI will be able to do with a healthy knowledge base is incredible. By employing a KCS approach, your knowledge articles will power an AI embedded into your service management platform and give it the ability to resolve incidents, fulfil requests, answer specific questions, and act as a copilot to your agents.

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How to Implement Knowledge-Centred Service

Transitioning to a KCS-driven approach requires careful planning and alignment across people, processes, and technology. Here’s a step-by-step guide to implementing KCS effectively:

1. Get organisational buy-in

Change management is critical for KCS adoption. Start by educating stakeholders about the benefits of KCS and securing leadership support. Highlight how it aligns with organisational goals like improving customer satisfaction or reducing operational costs.

In many cases, the main push back will be from your service agents, who see this as additional workload that you’re trying to squeeze into their day-to-day activities. It’s important that you convey the outcomes that KCS will have on their work in the long-term, including the ability to resolve tickets faster, cutting down the time they need to sped researching resolutions, enabling self-service, and the ability to switch on AI tools to take over manual, low-level tasks so that they can focus on higher-value, more fulfilling work.

2. Design your KCS processes

KCS relies on two core loops:

• The Solve Loop: where agents document solutions during issue resolution.
• The Evolve Loop: which focuses on refining and improving the knowledge base over time.

It’s important to map out these processes and ensure that they can be performed efficiently and sustainably by your service agents. You’ll also need to consider the process for approvals and whether you allocate subject matter experts to certain areas of your knowledge base.

3. Choose the right knowledge base technology

A centralised knowledge management platform is essential for KCS success. We recommend looking for a knowledge management platform that is integrated into a broader, AI-native Service Management platform, like Servicely. Tools like Servicely will make it easier to capture, organise and retrieve knowledge seamlessly, as a part of your service delivery workflows. Additionally, built-in Generative AI functionality will be able to assist your service agents in identifying knowledge gaps and creating new articles.

4. Train your service agents and create a culture of knowledge

Equip your agents with the skills they need to contribute effectively to the knowledge base. Provide training on writing clear and concise articles, using templates consistently, and updating content based on feedback.

As your team start building your knowledge base, foster the KCS culture within the team by sharing the impact of the knowledge with them, including changes in self-service resolution, the journey towards AI-powered service delivery, and changes in incident resolution times.

5. Establish governance

To prevent knowledge base bloat or inconsistencies, implement governance policies for content review and approval. Assign roles for content curators who ensure that articles remain accurate and relevant over time. Create a version tracking system so that your team can audit updates to knowledge articles.

6. Monitor performance, identify knowledge gaps and provide feedback

Track key performance indicators (KPIs) like resolution times, self-service success rates, and article reuse rates to measure the impact of your KCS implementation. Use knowledge gap analysis capabilities within your service management platform to identify topics not covered by knowledge articles. And provide insights and feedback to your team on how they can improve their knowledge creation and maintenance.

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How KCS Powers AI in your Service Management

The link between AI and knowledge is symbiotic, with each enhancing the capability of the other in transformative ways. At its core, AI draws its strength from data, which can come in the form of knowledge articles, previously resolved issues, conversations with end-users, and more. With a KCS approach in place, organisations can accelerate the creation of the data needed to power AI.

A well-organised knowledge base becomes an invaluable asset to train AI systems, providing the high-quality data required to allow AI models to learn and adapt to your service delivery processes. This knowledge serves as the foundation for AI algorithms to develop more accurate models, allowing them to predict and respond to user needs more effectively. The richer the knowledge base, the better AI can mimic human-like reasoning, making service delivery not just more efficient but also more intuitive and personalised.

In return for this knowledge, AI embedded into your service management platform can deliver context-aware, personalised experiences and enable you to use AI in a few transformative ways:

• Resolve incidents autonomously via 24/7 AI virtual agents‍
• Answer very specific queries with Retrieval Augmented Generation (RAG)
• Instantly classify and route tickets
• Recommend and carry out remediations for service agents via an AI copilot

In true symbiosis, AI can also bolster your KCS efforts by being utilised to both spot knowledge gaps and create knowledge articles for your service agents to review before publishing. AI virtual agents, like Servicely’s, have the ability to keep track of questions or problems that they haven’t been able to answer or resolve, giving service teams guidance on where knowledge is missing. You can then draw on Generative AI capabilities to draft those knowledge articles, speeding up the pace of knowledge creation.

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Start your Knowledge-Centred Service journey

Knowledge-Centred Service can be transformative for enterprise service delivery teams. By embedding knowledge creation and maintenance into daily workflows, your service teams will be able to deliver faster resolutions, enable self-service, and accelerate your service delivery with AI.

If you’re looking for a service management platform with feature-rich knowledge management and native AI built in, Servicely helps ambitious enterprises accelerate their service delivery and make work flow. Get in touch with us here to learn more about how Servicely can power your KCS journey.

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