Research project Organizational Digital Twin using Process Mining

Business Process Mining is a rapidly growing research area, enabling organizations to analyze their business processes based on recorded data. It can help businesses to discover their process models, check the conformance of their processes to rules and regulations, predict the performance of their process and running cases, and more.

A wide spectrum of use cases is enabled, not only by advances in this area but also by using process mining methods in combination with different artificial intelligence (AI) techniques, including machine learning, deep learning and natural language processing.

Such a combination opens up new possibilities for simulating business process models providing unique opportunity to optimize business operations. The ultimate goal of using process mining is to analyze and understand organizational processes to reveal how they are running, as well as how changing them can affect future business outcomes. The changes also need to be applied in a timely manner so that organizations can benefit from such analysis.

Digital Twin is a recently emerging trend that aims to empower organizations with important insights into their processes, enabling them to investigate outcomes of different changes through predictions, supporting data-driven decisions, optimizing operations, ensuring compliance, and driving continuous improvement.

The main goal of this PhD project is to move forward the current edge of knowledge in the process mining discipline by developing new theories, methods, algorithms, and techniques, to support the development of digital twins of organizations’ processes.

This is Najmeh Miri’s PhD thesis project. Main supervisor is Amin Jalali, supervisor is Jelena Zdravkovic.