Business process discovery

The discovery algorithms should solely depend on a small percentage of data provided by the event logs to develop the closest possible model to the actual behaviour.

Automated Business Process Discovery tools capture the required data, and transform it into a structured dataset for the actual diagnosis; A major challenge is the grouping of repetitive actions from the users into meaningful events.

A deeper analysis of the "as-is" process data may reveal which are the faulty parts that are responsible for the overall behavior in this example.

It may lead to the discovery of subgroups of repairs that actually need management focus for improvement.

The representation and accuracy of the discovered model depend both on the technique used for the discovery and the type of visualization that is chosen.