Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes
Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for business process management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM.
Abstract. The quality of a business process model is presumably highly dependent upon the modeling process that was followed to create it. Still, there is a lack of concepts to investigate this connection empirically. This paper introduces the formal concept of a phase diagram through which the modeling process can be analyzed, and a corresponding implementation to study a modeler's sequence of actions. In an experiment building on these assets, we observed a group of modelers engaging in the act of modeling. The collected data is used to demonstrate our approach for analyzing the process of process modeling. Additionally, we are presenting first insights and sketch requirements for future experiments.
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