The landscape picture of Process Mining
"Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. However, it is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis"
Wil. van der Aalst, Professor at RWTH Aachen University - Godfather of Process Mining
The high-level view
Information system Event data Process model Conformance Performance Diagnostics ML Predictions Improvements Success "World" Extract Explore Discovery Align Replay Enrich Apply Compare Act Select, filter, clean Show Show Transform Model adapt Interpret, drill down
ML Information system Event data Process model Conformance Performance Diagnostics Predictions Improvements Success "World" Extract Explore Discovery Align Replay Enrich Apply Compare Act Select, filter, clean Show Show Transform Model adapt Interpret, drill down
Why Process Mining?
Process discovery

Process discovery techniques use event data to create process models describing the operational processes in terms of their key activities. These process models reveal the actual processes and can be extended to show bottlenecks and outlier behavior.

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Conformance checking

Conformance checking techniques compare observed behavior (i.e., event data) with modeled behavior (i.e., process models). These techniques can be used to show deviations, i.e., behaviors different from what is expected or desired.

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Performance analysis

Once the process model is revealed, using performance analysis techniques, people can detect the bottlenecks in the organization.

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Extracting, Filtering, and Cleaning Event Data

After extracting event data from one or more information systems, one can explore, preprocess these data to feed process mining so that it can produce the desired result.

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Comparative Process Mining

Besides the techniques that discover and analyze a single process, process mining can break down the differences between various processes, for example, the process of students that passed the course versus the process of students that failed.

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Predictive Process Mining

Predictive process monitoring is a process mining technique concerned with predicting how running (uncompleted) cases will unfold up to their completion.

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Action-Oriented Process Mining

Having insightful diagnostics from discovery and analysis techniques, it is important that the process owner can convert that into actual actions to improve the process.

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Robotic Process Automation

Robotic Process Automation (RPA) aims to replace people with automation in repetitive, simple works so that the business can be more efficient, agile, and profitable.

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Automation

Automation describes a wide range of technologies that reduce human intervention in processes. The amount of work done by a human is reduced by predetermining decision criteria and triggering corrective actions and workflows. These actions and workflows may be executed by humans, software robots, or existing software.

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Machine Learning

The integration of machine learning and process mining can help businesses to automatically identify weaknesses in processes together with their root causes and prescriptive recommendations for how to improve efficiency even faster.

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