[AISWorld] CFP: 2nd International Workshop on Data-Driven Business Process Optimization

[Kumar, Akhil]

The 2nd International Workshop on Data-Driven Business Process Optimization will be held on 11 September 2023 in the beautiful city of Utrecht, The Netherlands.  BPO 2023 will be held in conjunction with the 21st Conference on Business Process Management (BPM 202<https://www.google.com/url?q=https%3A%2F%2Fbpm2023.sites.uu.nl%2F&sa=D&sntz=1&usg=AOvVaw0cGOxA4J7oTfexqXn5tuyy>3<https://www.google.com/url?q=https%3A%2F%2Fbpm2023.sites.uu.nl%2F&sa=D&sntz=1&usg=AOvVaw0cGOxA4J7oTfexqXn5tuyy>)<https://www.google.com/url?q=https%3A%2F%2Fbpm2023.sites.uu.nl%2F&sa=D&sntz=1&usg=AOvVaw0cGOxA4J7oTfexqXn5tuyy>.



Business process management is a very promising paradigm for optimizing the way in which work is performed in an organization. Decisions that are always implicit in business processes, if they are described using traditional business process modelling techniques, include: assigning resources to the tasks for which they are most suited, deciding on the execution order of tasks to meet customer deadlines, and deciding on the overall design of the process to minimize the overall processing time of customer cases. While such questions are important in administrative processes, they are even more important in processes that have a physical component, such as transport processes, production processes, and clinical pathways, in which assigning tasks to the wrong resource, or performing them in the wrong order immediately leads to higher costs, dissatisfied customers or even health risks. Traditionally, the research area of operations research has studied techniques for modeling and solving optimization problems in much detail. At the same time, the research area of business process management has studied techniques for aggregating the data that is needed for modeling, analyzing, and in the end optimizing business processes. Combining techniques from both areas makes it possible to solve optimization problems from practice, using models that are based on real-world data, with fewer assumptions. In particular, it allows us to create clear and realistic data-driven models of the way in which customer orders pass through the organization and of the behavior and performance of resources. While this provides clear benefits in terms of more realistic models and analysis, it also brings challenges in terms of the computational complexity of the used analysis and optimization techniques.



The workshop’s primary aim is to address solutions to business process optimization problems, by combining data-driven techniques, such as data mining or process mining, with optimization techniques, such as job-shop scheduling or supply chain optimization.  Examples of such combinations could include (but are not limited to):



-    using process mining to predict the future states of a process, then using job-shop scheduling to assign tasks to resources for those future states



-    mining nurse and doctor schedules in such a way that they can be used effectively in hospital ward optimization



-    creating specialized mining techniques for supply chain processes that can demonstrably be used in supply chain optimization algorithms.



For more information about the BPO workshop, please check https://sites.google.com/view/bpo2023/. Important dates:

Workshop paper submission: 30 May 2023
Workshop paper notification: 30 June 2023
Workshop camera-ready paper submission: 14 July 2023
Workshop: 11 September 2023



For questions or thoughts on work you may wish to discuss, please feel free to contact Prof. Dr. Remco Dijkman (r.m.dijkman at tue.nl).

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Akhil Kumar

Professor of Information Systems

Penn State University

University Park, PA 16803.