Process Mining & Intelligence


Process Mining is a process management technique that reconstructs and analyzes business processes from datasets and maps the implicit process knowledge into model form. Process mining can be used anywhere where individual process steps have been recorded in comprehensible chronology and togetherness, such as workflow management data, ERP transactions or processes in ticket systems.

Key application areas of process mining are process harmonization across various organizational units and subsidiaries, process optimization in terms of throughput times, process costs, process stability, ensuring compliance requirements, assistance systems and knowledge management.

Process Mining bridges the gap between traditional, model-based process analysis and data-driven analytic techniques, combining data analysis with modeling, control, and business process improvement.

Process mining does not consider the target, but the actual data acquisition.

Process Mining shows how results were actually achieved.

Process mining does not look for patterns in databases, but for causalities in process flows. Exceptions that are not considered in other procedures are a key indicator of potential for improvement.

Process mining techniques enable the dynamic optimization and even generation of processes based on current data.