PROCESS MINING: PRINCIPLES, CHARACTERISTICS AND IMPLEMENTATION POTENTIAL

Abstract

Digital transformation is forcing companies to rethink their processes to meet current customer needs. Business Process Management (BPM) can provide a means to structure and address this change. However, most BPM approaches face limitations on the number of processes they can optimize at the same time, due to complexity and resource constraints. The article is devoted to data mining as a tool for modeling and improving the company's business processes. Process Mining is a collection of data-driven diagnostic and business process improvement methods that combine machine learning and BPM. Among the advantages of Process Mining is more efficient management decision making. The possibility of introducing Process Mining methods into the work of a telecommunications company for the automatic collection of information about business processes and building a map of business processes is analyzed. The use of Process Mining methods will allow a telecommunications company to optimize the work of its departments and increase customer satisfaction. In addition, the implementation of this system contributes to a better analysis of the results of the execution of business processes for providing access to the Internet. This will improve the regulations for these processes, control of their compliance and the procedure for making managerial decisions at a higher quality level.