Process mining

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Process mining is a process management technique that enables business processes to be reconstructed and evaluated on the basis of digital traces in IT systems.

background

Process mining is a business data analysis discipline that aims to improve processes in the operational area of ​​a company. The individual steps of the process stored in the systems are combined and the process is visualized in its entirety. Process mining enables the implicit and otherwise hidden process knowledge contained in data to be modeled and thus made tangible and transportable. The technique is often used when other approaches do not allow a formal description of the processes or when the quality of existing process records is questionable. Contemporary management trends such as B. BAM ( Business Activity Monitoring ), BOM (Business Operations Management), BPI (Business Process Intelligence) show the great interest in further developing the analysis options in this area.

Areas of application

In principle, process mining can be used wherever individual steps of a process are stored in an IT system in such a way that the togetherness and chronology of the steps can be traced. This traceability is ensured by a process or sequence log. This particularly applies to workflows that are stored and managed in workflow management systems . A workflow is a formally described business process that can be coordinated and controlled by a workflow management system. User interfaces allow users to interact with the system and save and edit individual steps in a workflow. The totality of the stored steps ultimately results in a process that can be extracted and reconstructed with process mining. So z. B. the transactions from ERP systems , the history of tickets in a ticket system or clinical treatment paths of patients in a hospital can be displayed. The main areas of application of process mining are process harmonization across different organizational units and companies, process optimization with regard to throughput times, process costs, process stability and ensuring compliance requirements. Further possible uses for process mining can be found, for example, in knowledge management or in assistance systems .

A use case of process mining would also be, for example, ordering processes in purchasing that are too long due to long approval times by the specialist departments.

technology

Process mining can be seen as the link between data mining and business process management . In contrast to data mining, however, process mining concentrates on enhancing the implicit process knowledge already contained in the data.

The starting point for process mining is a collection of data in which individual process steps are stored. The quality of this data is very important for process mining. A number of statistical models are then applied to this data, with the help of which the standard course of the process (core process) is determined. This core process then serves as the basis for the other process flows and enables deviations from the standard process to be determined.

Process mining types

The Task Force on Process Mining of the Institute of Electrical and Electronic Engineers IEEE , headquartered in New York, defines three different types of process mining:

Discovery

The processes contained therein are reconstructed from the existing process logs of the data available without having any information or models of existing processes beforehand. Process mining is used here to simply elevate existing processes. This type of application of process mining is currently the best known.

Conformance

With this type of process mining, a model for a process flow already exists. The existing data is now checked on the basis of the model and the existing process logs with process mining for conformity to the existing model.

Enhancement

Here too, the process logs and a model of the existing process are already available. In contrast to the conformance type, not only should theory and practice be checked for conformity, but the existing model should be adapted and expanded if necessary. Ideally, this approach leads to a new, better model of the desired process.

Related techniques and management approaches

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Individual evidence

  1. ↑ How to avoid the most common mistakes: Use process mining correctly. Retrieved June 4, 2019 .
  2. ↑ Data makes processes more efficient: process mining turns the classic BI world on its head. Retrieved June 4, 2019 .
  3. ↑ Process Mining: Examples and Use Cases. Accessed June 4, 2019 (German).
  4. ^ Gesellschaft für Informatik (GI): Process Mining. May 31, 2019, accessed June 4, 2019 (German).
  5. ↑ Process Mining Manifesto (PDF; 806 kB), IEEE Task Force on Process Mining
  6. ↑ IEEE Contact & Support. Retrieved June 4, 2019 .