This chapter provides a 360 \(^\circ \) overview of process mining, introducing basic concepts and positioning process mining with respect to other technologies.
These can be found in all organizations and industries, including production, logistics, finance, sales, procurement, education, consulting, healthcare, maintenance, and government. The focus of process mining is on operational processes, i.e., processes requiring the repeated execution of activities to deliver products or services. Both backward-looking and forward-looking analyses can trigger actions (e.g., countermeasures to address a performance or compliance problem). Process mining techniques can be backward-looking (e.g., finding the root causes of a bottleneck in a production process) or forward-looking (e.g., predicting the remaining processing time of a running case or providing recommendations to lower the failure rate). By using a combination of event data and process models, process mining techniques provide insights, identify bottlenecks and deviations, anticipate and diagnose performance and compliance problems, and support the automation or removal of repetitive work. Process mining can be defined as follows: process mining aims to improve operational processes through the systematic use of event data.
