Process Mining

Process mining is a process analysis technique which makes it possible to reconstruct and evaluate business processes based on digital traces within IT systems. With process mining methods, business processes can be visualized, helping to examine and improve actual processes. The fundamental goal is to uncover the process-diversity in systems which allows the identification of questionable procedures first. As a next step, process mining can then help to initiate necessary optimizations of process flows.

In practice, process mining offers enormous savings potential. With the gained knowledge about real processes, erroneous processes can be eliminated, or others can be converted to fit mandatory guidelines or legal requirements. Possible deviations or variations of the processes allow the finding of conclusions about which factors influence a process in a positive or negative sense. The idea of Process Mining is not new, but the increase of Big Data technology is a game-changer. With the help of Big Data, information systems are now available to collect and evaluate process relevant information, e.g., information about individual activities, their sequence, and their duration, in the context of the overall process. The collected mass of data is the basis for the so-called Process Discovery, which is the basic functionality of every Process Mining tool. Within the Process Discovery, the log data from the ERP systems form the basis for the graphical, user-friendly presentation of the process model.

Modern tools such as “Celonis Process Mining” do not only use their cloud platform as an analysis tool, but they also support the connection to a diverse set of legacy systems. This support is technically provided via specific data extractors for diverse process types. With their conformance checking method, a chosen process sequence can be compared to a previously designed ideal process. The actual comparisons can not only be considered as snapshots but can also be tracked over a more extended period. That means that e.g., the process could be tracked, even after re-engineering based on the original findings that took place. If, in addition, process-relevant information about suppliers, customers, delivery quantities, and values is stored, conclusions can be drawn as to how much savings potential exists at which point of each process. Dashboards allow the linking of process variants or process sections and the collected data.

Another feature is the root cause analyses which enable the user to recognize outliers in the process flow.  Thus, outliers for disproportionate slowdowns within the process can be identified fastly. To allow quick insights into the operation and the associated Key Performance Indicators (KPIs) Celonis Process Mining offers support via pre-defined analyses from its App Store. If you are interested to learn more about the Celonis Process Mining tool, please contact us for more information or even an introductory webinar.

Process Mining technology is a real improvement for business operations. With Data Mining Technology, companies can use the daily data in a meaningful way and thus create added value for their organization. The use of PM tools can, therefore, lead to a considerable increase in the performance of operational processes.

For questions about the topic of data mining, please contact the authors Dirk Meise and Roland Wenner.