Vorteile von Process Mining im Unternehmen

Abstract

The work emphasizes the importance of Process Mining as a key technology for optimizing business processes. It is stresses that traditional methods of process analysis reach their limits due to their subjectivity and time intensity, and Process Mining offers an objective, data-based approach to analyze actual process flows and uncover optimization potentials. The practical relevance of Process Mining is underscored by its ability to understand and improve complex business processes. The diverse areas of application, from production to healthcare, demonstrate the broad spectrum of application of this technology. To answer the research questions “How are internal processes optimized with the help of process mining?” and “What requirements are placed on data quality in this context?”, the methodology of a literature review is chosen for this work, which is based on three existing case studies. Even though no new substantial knowledge gain can be achieved through this approach, the advantage of being able to view the topic from different perspectives within the framework of this work outweighs this point. This should put the answer to the research question on a broader basis. The case studies have shown that Process Mining is a powerful tool for improving process efficiency and supporting digital transformation in companies. It enables data-based decisions for process improvement and the establishment of a continuous improvement process. The quality of the data plays a crucial role. Faulty data can significantly affect the process flow, leading to higher process costs. Companies that have recognized the importance of data quality are trying to make clear guidelines for data maintenance in the company by introducing Data Governance policies. In summary, Process Mining offers a data-driven approach to process optimization and improvement that is based on real, objective data and not on subjective estimates or assumptions. It enables companies to continuously improve and optimize their processes to increase their performance and efficiency. Future research could focus on further improving data quality and developing methods for more effective uses of Process Mining.

Date of Award	2024
Original language	German (Austria)
Supervisor	Harald Dobernig (Supervisor)