Process Mining Software

Abstract

The successful application of process mining relies on good tool support. Traditional Business Intelligence (BI) tools are data-centric and focus on rather simplistic forms of analysis. Mainstream data mining and machine learning tools provide more sophisticated forms of analysis, but are also not tailored towards the analysis and improvement of processes. Fortunately, there are dedicated process mining tools able to transform event data into actionable process-related insights. For example, ProM is an open-source process mining tool supporting all of the techniques mentioned in this book. Process discovery, conformance checking, social network analysis, organizational mining, clustering, decision mining, prediction, and recommendation are all supported by ProM plug-ins. However, the usability of the hundreds of available plug-ins varies and the complexity of the tool may be overwhelming for end-users. In recent years, several vendors released dedicated process mining tools (e.g., Celonis, Disco, EDS, Fujitsu, Minit, myInvenio, Perceptive, PPM, QPR, Rialto, and SNP). These tools typically provide less functionality than ProM, but are easier to use while focusing on data extraction, performance analysis and scalability. This chapter provides an overview of available tools and trends.