Although the popularity and adoption of process mining techniques grew rapidly in recent years, a large portion of effort invested in process mining initiatives is still consumed by event data extraction and transformation rather than process analysis. The IEEE Task Force on Process Mining conducted a study focused on the challenges faced during event data preparation (from source data to event log). This paper presents findings from the online survey with 289 participants spanning the roles of practitioners, researchers, software vendors, and end-users. These findings were presented at the XES 2.0 workshop co-located with the 3rd International Conference on Process Mining. The workshop also hosted presentations from various stakeholder groups and a discussion panel on the future of XES and the input needed for process mining. This paper summarises the main findings of both the survey and the workshop. These outcomes help us to accelerate and improve the standardisation process, hopefully leading to a new standard widely adopted by both academia and industry.

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.