State-of-the-art and trends in process mining

Abstract

Business process management is an established methodology the main purpose of which is to effectively improve organizational processes by applying a variety of techniques and technologies that are largely based on process models. A prerequisite for the successful management is the provisioning of valid models, which is often difficult to achieve in practice as commonly, due to human factors, process models tend to be incomplete, inaccurate, or outdated.
An alternative or complementary approach, which has been established in recent years in the field of business process management, considers empirical process-related data, which especially in the form of event logs, are generated by business applications. Process mining is a synonym for a multitude of techniques and technologies that enable automatic event log-based generation and visualization of process models that make possible the detection and analysis of processes, checking the compliance of implemented processes and detection of potential deviations.
In this paper, we will present and position process mining in the business process management lifecycle. Process mining will be demonstrated with the steps of a common process mining algorithm – Alpha. The central part of the paper is aimed at presenting the capabilities of modern tools for process mining, which are becoming an indispensable part of business analytics in modern business environments. With their help, it is possible to make precise process or business decisions based on real operational data.