title: Business Process Management in the Digital Age: Advancements in Data, Networks, and Opportunities
Creators: name: Seyfried, Johannes
Publisher: name: University of Bayreuth
Year: 2019
Subjects: subject: Business Process Management
subject: Digitalization
subject: Data
subject: Networks
subject: Opportunities
subject: 650

description: Business Process Management (BPM) is the art and science of managing distributed work, involving various activities, resources, and actors. The increasing prevalence of digital tech-nologies, known as digitalization, affects individuals, organizations, and society as a whole. Business processes themselves, as well as BPM as a management discipline, are also heavily affected by digitalization, specifically in six overarching topics, namely data, networks, oppor-tunities, humans, context, and change. In order to shed light on the ways in which digitalization affects the BPM domain, this doctoral thesis contributes to the latter three overarching topics: data, networks, and opportunities. The overarching topic of data refers to attempts to capitalize on the increasing availability of data, leading to evidence-driven analytical methods and data-intensive business processes. In the context of digitalization, significant advancements in the field of machine learning led to promising new approaches for analysing structured and unstructured data. However, these advancements remain largely unexploited in the BPM domain. Therefore, research paper #1 focuses on the potential impact of deep learning on process outcome prediction. The paper reports on a structured comparison of a deep learning classifier and a classical machine learning classifier, based on five different event logs. The results show substantial potential for deep learning in process outcome prediction. Research papers #2 and #3 focus on the analysis of unstructured data, exploring the potential for cognitive computing in BPM. In doing so, re-search paper #2 develops a framework for structuring Cognitive BPM use cases. Based on these results, research paper #3 proposes a Cognitive BPM reference architecture. The overarching topic of networks refers to a view of processes as parts of interconnected net-works instead of single units of analysis. Research papers #4 and #5 highlight the need to take the interconnectedness of processes into account when prioritizing processes for improvement. Building on literature related to process improvement, process performance measurement, and network analysis, the research papers propose an approach for ranking processes according to their network-adjusted need for improvement, taking process interconnectedness into ac-count. The overarching topic of opportunities highlights the need for an opportunity-centric mindset in the context of BPM. This is necessary in order to identify the potential of emerging digital tech-nologies, new regulations, and demographic shifts for the BPM domain. Fostering the fusion of the digital and the physical worlds, the Internet of Things (IoT) is regarded as one of the most disruptive emerging digital technologies, yet offers great potential to the BPM domain, e.g., for higher automation, more accurate data collection, reduced errors, and overall efficiency gains. To enable the tapping of this potential, research paper #6 develops design principles which foster the success of IoT ecosystems. Research paper #7 takes an economic view, shedding light on the assessment of the customer value of IoT-solutions from an industrial company’s perspective.