What Is Process Mining?
In simple terms, process mining is the extraction of knowledge from the event commits and application logs to gain insight into business processes. It gives an enterprise insight into its business processes so it can enhance productivity, profits, and customer satisfaction.
Process mining use cases include:
- Discovery: The ideal process model is created after analyzing the event logs and there was no previous process model
- Conformance: Also called deviation analysis, in this use case, you already have a process model, which acts as a benchmark to compare the collected event logs
- Performance: You already have a process model with performance indicators in this use case, which helps improve the process’s outcome
What Is Process Discovery?
Process discovery is the actual discovery of how any process in your enterprise is executed. Using newer technologies such as computer vision, machine intelligence, and deep learning. The AI-based approach of process discovery takes a more fluid, continuous, and near-real-time approach to unveil all ad hoc human-digital interactions.
Unlike process mining, process discovery does not require any logs, databases, or API access, and there is no integration to your system required. It disregards any noise from the interaction and presents the process as it is working. In addition:
- It does not need any integration to your system application.
- It incorporates computer vision and machine intelligence to reveal the dark and invisible processes powering your digital enterprise
- It continuously monitors the processes to ensure real-time analysis and rapid retraining ideas in case of changes in the process
- Instead of a process model, it creates a metamodel for the future of work to enable a smooth digital transformation