Spreadsheets for business process management: Using process mining to deal with "events" rather than "numbers"?

Purpose Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a metaphor to introduce process mining as an essential tool for data scientists and business analysts. The goal is to illustrate that process mining can do with events what spreadsheets can do with numbers. Design/methodology/approach The paper discusses the main concepts in both spreadsheets and process mining. Using a concrete data set as a running example the different types of process mining are explained. Where spreadsheets work with numbers, process mining starts from event data with the aim to analyze processes. Findings Differences and commonalities between spreadsheets and process mining are described. Unlike process mining tools like ProM, spreadsheets programs cannot be used to discover processes, check compliance, analyze bottlenecks, animate event data, and provide operational process support. Pointers to existing process mining tools and their functionality are given. Practical implications Event logs and operational processes can be found everywhere and process mining techniques are not limited to specific application domains. Comparable to spreadsheet software widely used in finance, Wil M.P. van der Aalst Process and Data Science (PADS), Department of Computer Science, RWTH Aachen University, 52056 Aachen, Germany. E-mail: [email protected] 2 Wil M.P. van der Aalst production, sales, education, and sports, process mining software can be used in a broad range of organizations. Originality/value The paper provides an original view on process mining by relating it to spreadsheets. The value of spreadsheet-like technology tailored towards the analysis of behavior rather than numbers is illustrated by the over 20 commercial process mining tools available today and the growing adoption in a variety of application domains.