Jana-Rebecca RehseUniversität Mannheim · Management Analytics Center
Jana-Rebecca Rehse
Doctor of Business Administration
About
33
Publications
7,645
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
667
Citations
Citations since 2017
Introduction
Jana Rehse currently works as an assistant professor of management analytics at the University of Mannheim. Her research is focused on artificial intelligence in business process management, more specifically process mining, process prediction, and process assistance systems. She is interested in finding data-driven solutions to practical problems.
Publications
Publications (33)
AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for...
Conformance checking is a major function of process mining, which allows organizations to identify and alleviate potential deviations from the intended process behavior. To fully leverage its benefits, it is important that conformance checking results are visualized in a way that is approachable and understandable for non-expert users. However, the...
Robotic Process Automation (RPA) is an emerging automation technology that creates software (SW) robots to partially or fully automate rule-based and repetitive tasks (aka routines) previously performed by human users in their applications’ user interfaces (UIs). Successful usage of RPA requires strong support by skilled human experts, from the det...
User interaction (UI) logs are high-resolution event logs that record low-level activities performed by a user during the execution of a task in an information system. Each event in a UI log corresponds to a single interaction between the user and the interface, such as clicking a button or entering a string into a text field. UI logs are used for...
Object-centric event logs have recently been introduced as a means to capture event data of processes that handle multiple concurrent object types, with potentially complex interrelations. Such logs allow process mining techniques to handle multi-object processes in an appropriate manner. However, event data is often not yet available in this new f...
In this paper, we introduce the SAP Signavio Academic Models (SAP-SAM) dataset, a collection of hundreds of thousands of business models, mainly process models in BPMN notation. The model collection is a subset of the models that were created over the course of roughly a decade on academic.signavio.com, a free-of-charge software-as-a-service platfo...
User interaction (UI) logs are high-resolution event logs that record low-level activities performed by a user during the execution of a task in an information system. Each event in a UI log corresponds to a single interaction between the user and the interface, such as clicking a button or entering a string into a text field. UI logs are used for...
Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems that draws upon trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for...
A major dimension for assessing organizational performance is efficiency, i.e., the amount of output obtained from a given input. Organizational efficiency is closely connected to business process efficiency. Inefficiently executed processes may consume a lot of resources and still not achieve their internal goals. Because “you cannot improve what...
Complaints about finished products are a major challenge for companies in the medical technology industry, where product quality is directly related to public health and therefore strictly regulated. In this paper, we examine how available data can be used to provide automated support to the complaint handling processes in the medical technology co...
The goal of process discovery is to visualize event log data as a process model. In reality, however, these models are often highly complex. Process trace clustering is a well-studied and powerful technique to address this. It groups an event log into more cohesive sub logs, such that the discovered process models become less complex and easier to...
Mobile robots like drones or ground vehicles can be a valuable addition to emergency response teams, because they reduce the risk and the burden for human team members. However, the need to manage and coordinate human-robot team operations during ongoing missions adds an additional dimension to an already complex and stressful situation. BPM approa...
Der Einsatz von Rettungsrobotern kann die Arbeit von Einsatzkräften der Feuerwehr erheblich erleichtern. Allerdings müssen die Einsatzkräfte dafür entsprechend geschult werden. Im vorliegenden Beitrag wird ein Softwareprototyp vorgestellt, der vorhandene Daten zum Ablauf von Feuerwehreinsätzen für eine prozessorientierte Schulung der Einsatzkräfte...
Complaints about finished products are a major challenge for companies. Particularly for manufacturers of medical technology, where product quality is directly related to public health, defective products can have a significant impact. As part of the increasing digitalization of manufacturing companies ("In-dustry 4.0"), more process-related data i...
With the advent of digitization on the shopfloor and the developments of Industry 4.0, companies are faced with opportunities and challenges alike. This can be illustrated by the example of AI-based process predictions, which can be valuable for real-time process management in a smart factory. However, to constructively collaborate with such a pred...
Reference models are special conceptual models that are reused for the design of other conceptual models. They confront stakeholders with the dilemma of balancing the size of a model against its reuse frequency. The larger a reference model is, the better it applies to a specific situation, but the less often these situations occur. This is particu...
Complaints about finished products are a major challenge for companies. Particularly for manufacturers of medical technology, where product quality is directly related to public health, defective products can have a significant impact. As part of the increasing digitalization of manufacturing companies (“Industry 4.0”), more process-related data is...
The advent of Industry 4.0 is expected to dramatically change the manufacturing industry as we know it today. Highly standardized, rigid manufacturing processes need to become self-organizing and decentralized. This flexibility leads to new challenges to the management of smart factories in general and production planning and control in particular....
Predicting the final state of a running process, the remaining time to completion or the next activity of a running process are important aspects of runtime process management. Runtime management requires the ability to identify processes that are at risk of not meeting certain criteria in order to offer case managers decision information for timel...
Reference models provide generic blueprints of process models that are common in a certain industry. When designing a reference model, stakeholders have to cope with the so-called ‘dilemma of reference modeling’, viz., balancing generality against market specificity. In principle, the more details a reference model contains, the fewer situations it...
Predicting the next activity of a running process is an important aspect of process management. Recently, artificial neural networks, so called deep-learning approaches, have been proposed to address this challenge. This demo paper describes a software application that applies the Tensorflow deep-learning framework to process prediction. The softwa...
Predicting business process behaviour, such as the final state of a running process, the remaining time to completion or the next activity of a running process, is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural netwo...
Reference models are a cost-and time-saving approach for the development of new models. As induc-tive strategies are capable of automatically deriving a potential reference process model from a collection of existing process models, they have gained attention in current research. A number of promising approaches can be found in recent publications....
![Fig. 1: Stages of Inductive Reference Modeling [Fe14]](profile/Peter-Fettke/publication/314116399/figure/fig1/AS:614126598512667@1523430599934/Stages-of-Inductive-Reference-Modeling-Fe14_Q320.jpg)
Reference modeling offers attractive bene®ts for both research and practice. The induc-tive strategy for reference model development derivesreference models by generalizing individual enterprise models. It has recently gained attention in research, however, its practical application still faces numerous challenges. The objective of the article at h...
Business process management is one of the most widely discussed topics in information systems research. As process models advance in both complexity and maturity, reference models, serving as reusable blueprints for the development of individual models, gain more and more importance. Only a few business domains have access to commonly accepted refe...
Projects
Projects (2)
The competition is aimed in particular at students and doctoral candidates in the field of business informatics, information systems and related fields. The participants shall analyze a set of business travel management process data provided on the workshop website (https://bpm.dfki.de/mobis-challenge/) with IT tools of their choice (e.g. existing process mining tools, BPM solutions, but also self-developed programs) to identify compliance violations and problematic incidents and to provide solutions for securing the compliance of a future as-is-process. In addition, they are welcome to identify weaknesses in the process or the organization beyond conformance issues and make suggestion for their improvement. The exact task definition and some guiding questions can be found on the above website. The challenge submissions will be examined and compared regarding their results and selected method for addressing the task on hand. The best solutions will be presented during the workshop.
