Knowledge Management System for an SME, Optimizing the knowledge management system for an SME in a highly regulated social security environment
Today, the insurance sector is increasingly operating in a dynamic environment and is facing rising customer expectations. Faster service provision, reliable and comprehensible decision making, and increasing customer expectations require a high degree of adaptability.
Koller Leeroy, 2020
Bachelor Thesis, Beratungsgesellschaft für die zweite Säule AG
Betreuende Dozierende: Hans Friedrich Witschel
Keywords: knowledge, knowledge management, decision support system
Insurance companies differ only marginally from each other. Prices and services are gradually identical. One of the few distinguishing features is the quality of service and its satisfactory support and processing speed. Insurance companies face considerable challenges in this regard. Unclear laws can lead to differences and delays in the granting of benefits. Permanent changes in the legal basis make it difficult to implement and apply them promptly and with legal compliance. Even the most experienced insurance companies face the problem of keeping their knowledge up to date.
This study proposes a suitable solution for these challenges and aims to improve the knowledge management process of an SME in the social security sector. The analysis includes the examination of a key process, the analysis and revision of the knowledge management process, the classification of knowledge repositories and workers through interviews, an assessment of similar, external companies through interviews, and the specification of requirements. Resulting in a recommended solution.
By connecting the knowledge producer and the knowledge consumer, the knowledge contained in the mind of one worker is conveyed to the mind of someone who seeks that knowledge. Thus, new situations can be managed, and decisions can be made.
The analysis concluded in key requirements that guided the proposed solution. The initial system utilized the documentation of question-answer pairs and their corresponding contexts to solve problems. The recommended solution describes an approach where specific data from the cases are parameterized to query suitable questions based on their contexts automatically. Through systematic and central management of the expert knowledge, the accessibility of the knowledge is improved.
Explicit knowledge flows into the case management software and suggests relevant internal directives to the user, depending on the status of the case data at hand. Knowledge is applied as a control element in a process-supported system. Furthermore, users could be made aware of dangers and tendencies during case processing in future.
Studiengang: Business Information Technology (Bachelor)
Fachbereich der Arbeit: Wirtschaftsinformatik & IT-Management