A Practitioner’s View on Process Mining Adoption, Event Log Engineering and Data Challenges

other

Author(s): Rafael Accorsi , Julian Lebherz

Publication date (Online): June 27 2022

Publisher: Springer International Publishing

Read this book at

Publisher

Buy book

Bookmark

There is no author summary for this book yet. Authors can add summaries to their books on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Process mining is, today, an essential analytical instrument for data-driven process improvement and steering. While practical literature on how to derive value from process mining exists, less attention haas been paid to how it is being used in different industries, the effort involved in creating an event log and what are the best practices in doing so. Taking a practitioner’s view on process mining, we report on process mining adoption and illustrate the challenges of log contruction by means of the order to cash (i.e. sales) process in an SAP system. By doing so, we collect a set of best practices regarding the data selection, extraction, transformation and data model engineering, which proved themselves handy in large-scale process mining projects.

Related collections

Most cited references 17

Record: found
Abstract: found
Article: not found

Process mining in healthcare: A literature review.

Eric Rojas, Jorge Munoz-Gama, Marcos Sepúlveda … (2016)

Process Mining focuses on extracting knowledge from data generated and stored in corporate information systems in order to analyze executed processes. In the healthcare domain, process mining has been used in different case studies, with promising results. Accordingly, we have conducted a literature review of the usage of process mining in healthcare. The scope of this review covers 74 papers with associated case studies, all of which were analyzed according to eleven main aspects, including: process and data types; frequently posed questions; process mining techniques, perspectives and tools; methodologies; implementation and analysis strategies; geographical analysis; and medical fields. The most commonly used categories and emerging topics have been identified, as well as future trends, such as enhancing Hospital Information Systems to become process-aware. This review can: (i) provide a useful overview of the current work being undertaken in this field; (ii) help researchers to choose process mining algorithms, techniques, tools, methodologies and approaches for their own applications; and (iii) highlight the use of process mining to improve healthcare processes.