Organizations these days have a lot of data stored in the form of big data. One of the main problems organizations face is extracting knowledgeable information from such large amounts of data. Using the latest technologies such as machine learning, artificial intelligence and complex mathematical models they are able to glean information which can help to improve services, product quality and also efficiency.
Process mining is one of the approaches which allows organizations to make use of the data stored in their systems to identify trends, patterns, bottlenecks contained in event logs.
Uses cases for process mining
Discovery: in this use case it is possible to determine the structure of a process, the path taken by the process and determining what are the frequent and infrequent paths
Conformance Checking: In this use case, deviations from standard processes are detected. Anomalies or outliers can be determined by conformance checking
Enhancement: enhancement can be time perspective or organizational perspective. When time perspective, it is possible to determine cases which are the most time consuming, future problems which may make the process more time consuming and the time taken for completion of a process. When organizational perspective, it is mainly resource oriented which includes how resources are allocated and what processes require similar resources.
Conclusion: Process mining is going to be increasingly used by organizations in future because it opens up new ways of analyzing cases and event logs. With the advent of IoT, there is a definite need for mining IoT devices and process mining can help achieve it. Also, with machine learning and AI which can predict future performance, process mining tools are going to be widespread.
References:
http://wwwis.win.tue.nl/~wvdaalst/publications/p660.pdf
http://www.fit.vutbr.cz/study/courses/TJD/public/1415TJD-Rudnickaia.pdf