Bottlenecks arise in many processes, often negatively impacting performance. Process mining can facilitate bottleneck analysis, but research has primarily focused on bottleneck detection and resolution, with limited attention given to the prediction of bottlenecks and recommendations for improving process performance. As a result, operational support for bottleneck resolution is often partially or not realized. The aim of this paper is to propose a method for Bottleneck Detection, Prediction, and Recommendation (BDPR) using process mining techniques to achieve operational support. A design science research methodology is adopted to design, develop, and demonstrate the BDPR method. A systematic literature review and a developed classification model provide theoretical support for the BDPR method and offer scholarly in the field of process mining a starting point for research. The BDPR method extends the utility of the classification model and aims to provide guidance to scholars and practitioners for assessing, selecting, evaluating, and implementing process mining techniques to realize operational support. A case study at a logistics service provider demonstrates the use of the proposed BDPR method.
Bottlenecks arise in many processes, often negatively impacting performance. Process mining can facilitate bottleneck analysis, but research has primarily focused on bottleneck detection and resolution, with limited attention given to the prediction of bottlenecks and recommendations for improving process performance. As a result, operational support for bottleneck resolution is often partially or not realized. The aim of this paper is to propose a method for Bottleneck Detection, Prediction, and Recommendation (BDPR) using process mining techniques to achieve operational support. A design science research methodology is adopted to design, develop, and demonstrate the BDPR method. A systematic literature review and a developed classification model provide theoretical support for the BDPR method and offer scholarly in the field of process mining a starting point for research. The BDPR method extends the utility of the classification model and aims to provide guidance to scholars and practitioners for assessing, selecting, evaluating, and implementing process mining techniques to realize operational support. A case study at a logistics service provider demonstrates the use of the proposed BDPR method.
Currently, Omnichannel distribution services are experiencing very rapid development around the world. In the Omnichannel distribution services, each existing sales channel will be connected to each other through integration capabilities so that no channels are left neglected. This is able to provide the best experience for consumers when shopping both online through mobile devices, laptops, and in physical stores. But on the other hand, this creates problems for business people who develop Omnichannel services. On the one hand, it facilitates the marketing process, but on the other hand, business people have difficulty reading the behavior of consumers who use Omnichannel distribution services. One way to analyze consumer behavior is to use the Process Discovery approach to obtain a process model. There are several Process Discovery Algorithms capable of describing and analyzing process models. In this paper, an experiment was carried out using the sales event log dataset generated from the Omnichannel distribution service system.
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