Knowledge management in IT service for more efficiency

In almost all corporate areas, knowledge management is the basis for efficient processes as well as satisfied customers and employees. Can a good knowledge base also improve IT service? And what influence does artificial intelligence (AI) have?

Table of contents

Why knowledge management in IT service?

Disruptions in IT or inadequately answered service requests affect work processes and frustrate both employees and customers. Suddenly, travel expenses cannot be submitted promptly, an important online meeting with a customer is interrupted, or a new function after a team update remains unused because nobody is informed about it.

In addition, service inquiries are often answered several times from scratch – depending on the processor with different solutions. That takes time, leads to inconsistencies and is inefficient. But does that have to be like that?

According to the Federal Ministry of Labor and Social Affairs (BMAS, December 2024), the shortage of skilled workers in IT professions will also remain a persistent problem by 2028. For companies, this means a growing challenge to reliably fill their service desk and to work efficiently.

How can knowledge management in IT service contribute to this To increase productivity and to improve user satisfaction sustainably? Let us take a look at it.

Advantages of a knowledge database

The establishment of a knowledge database offers companies a wealth of advantages for their service management:

Faster support and higher customer satisfaction: Support employees can access solutions faster, which significantly shortens the response time and increases the satisfaction of the end users. In the event of recurring problems, IT support can react automatically through prefabricated solution items.

Knowledge transfer and continuous improvement: A well-structured knowledge database promotes cooperation and the exchange of knowledge within the IT support. New solutions can be included in the database and made available to other employees.

Proactive problem solving: A knowledge database not only contributes to troubleshooting, but can also be used preventively. The collection of more often problems and solutions can identify potential disorders and address it early.

Efficiency and cost reduction: By automating routine inquiries, IT teams can use their resources more specifically, which leads to cost savings in the long term. Less time for the solution of already known problems means more capacity for more complex tasks.

Knowledge management in ITIL as a framework for IT service management is a central process and thus a fundamental part of successful IT service management. If you want to achieve efficiency and thus a cost reduction, the use of a knowledge database must also be considered.

There are big differences in design, technical and editorial options:

• Use of simple text fieldsthrough which the support notes noted the solution in the ticket after a problem.
• Presence of small knowledge banksthat enable it with a simple editorial process to document solutions and offer a search.
• Use of an extensive Knowledge Center With editorial and release processes, update routines and feedback function. Formats for knowledge content can be defined and automatic connections with support inquiries can be made.
• Use of a AI-based search or a chatbot For user -centered placement of information. The basis here is also an extensive basis of knowledge that contains company -specific information.

Factors for a good knowledge database

So that a knowledge database can also meet its purpose, it should meet the following requirements:

Using friendliness: The knowledge database must be intuitive to use. Handling must be self -explanatory both in the editorial process and in the search. In the best case, relevant content is provided proactively.

Integration into an existing ITSM system: Integration of the knowledge database into the corporate ITSM tool is crucial. This is the only way to work efficiently and use the knowledge directly in the workflow.

Automation options: The proposal of solution items based on the information entered can be made automatically. This reduces the need for manual search and ensures quick processing. An editorial process or the maintenance of content can also be automated in parts.

Scalability and flexibility: A company continues to develop, so the knowledge database should be scalable. With the requirements of her organization, it must offer with the requirements of growing up and enough flexibility to record different types of content – from technical instructions to FAQs.

Security and access control: The knowledge database should be able to define different access levels. At the same time, general articles should be available for a broad target group.

Futability: The use of AI should already be considered when choosing an ITSM tool and the knowledge database. In the future should support from a AI in the future? For example, editorial processes, the care of the data, search optimization or the use of a chatbot are conceivable here.

Does artificial intelligence abolish the knowledge databases?

The use of artificial intelligence has a major impact on knowledge management. Above all, the search and evaluation of information and the establishment of connections between information is optimized by using AI.

A AI can only generate knowledge in a company if the underlying information is actually also in electronic form. In addition, decisions on relevance and topicality must be made in the company. For example, a DIHK guideline also refers to the need for human review of AI generated content using the example of Chatgpt.

In order to be able to make reliable service offers via an ITSM tool with AI, the following things are still required, especially in the corporate environment:

• A sustainable knowledge processWhich ensures that knowledge is recorded, prepared, saved, updated and made available (SU component model of the knowledge management of Probst).
• Certified and structured knowledge pools

Building stone model of knowledge management according to Probst, Raub, Romhardt 1999, p. 58

If these foundations and thus a secure knowledge stock are missing, even a AI-supported ITSM tool cannot provide good results and the hoped-for improvement in the processes and the increasing satisfaction of customers and employees will be missing.

Conclusion

The integration of a knowledge database into an ITSM system is an investment that pays off in the long term. It not only improves the efficiency of IT support and increases the employee and customer satisfaction, but also helps to use the IT resources in a targeted manner and reduce costs. In addition, companies set the course for future-oriented offers such as chatbots and other AI assistants.

Was this article helpful for you? Or do you have any further questions about ITSM tools or knowledge management? Write us a comment or please call us.

Astrid Blume is a senior consultant in the subject area “Business Applications”. She has many years of experience in advice, conception and structure of knowledge management, as well as in the implementation and administration of knowledge databases and processes based on different platforms.