Process Mining is based on the approach of reconstructing each process instance from transaction data, which is extracted from IT systems. These processes can be visualized as individual instances, and process executions can be aggregated and filtered according to any criteria. Of course, all metrics relevant to process performance in terms of time, cost and quality are measured.

What are the success factors that have recently helped this technology to achieve a breakthrough? The success is primarily based on the ten following aspects.

1. The methodology enables the analysis of processes across system boundaries, for example, with interrelated process sections that are executed in different IT systems, reconstructed and visualized as end-to-end processes.

2. As a result of increasing automation, significantly more analyzable data is available than was the case in the past. In particular, online sales processes now provide data on all relevant customer touchpoints.

3. The generation and visualization of actual processes and the analyses based on them are automated without manual effort through automated process discovery.

4. In contrast to classic business intelligence systems, the analysis goes far beyond the calculation of metrics, with key figures indicating problems as the “tip of the iceberg” and the root cause analysis performed by looking at the structure of processes. The greatest optimization potential usually lies in the elimination of unnecessary loops, complicated special cases and overabundance of process variants.

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(originally published  09/15/2021, Why process mining has reached the ‘must-have’ tipping point (processexcellencenetwork.com)