Improving Business Processes with the Internet of Things - A Taxonomy of IIoT Applications

The Industrial Internet of Things (IIoT) paradigm constitutes the connection of uniquely identifiable things to the internet in an industrial context. It provides disruptive capabilities and value propositions, especially for the management and improvement of business processes. To exploit these, many companies have already implemented manifold IIoT applications along their value chain activities aiming at beneficial Business Process Improvements (BPI). However, research on IIoT-based BPI is low on theoretical insights. To add to the descriptive knowledge of the IIoT, a structured synoptic view and classification scheme are required. The work at hand addresses this need by providing a taxonomy of IIoT-based BPI applications. Based on the combination of an inductive and deductive research methodology, the created taxonomy consists of six dimensions, seven subdimensions, and 40 characteristics. The taxonomy is evaluated on a sample of 30 IIoT applications from the literature and 10 real-life applications from a market-leading company

Digital Transformation and Improvement of Business Processes with Internet of Things: A Maturity Model for Assessing Readiness

Companies of all industrial sectors are increasingly integrating Internet of Things (IoT) technology into their processes to realize a data-driven transformation of their businesses. The generation and use of comprehensive process data in real-time and the connection of process entities enables an improvement and beneficial redesign of business processes of all kinds. However, a goal-oriented exploitation of IoT technology for digital transformation and Business Process Improvements (BPI) is challenging due to the complexity of integrating IoT into existing processes. Companies require appropriate guidance to evaluate and scope their initiatives regarding IoT-based BPI. We therefore propose a holistic IoT-based BPI Maturity Model that assists organizations to determine their current state and get assistance to optimize or develop specific capabilities. This paper provides an overview about the structured development process of the maturity model comprising an extensive literature review and a six-round Delphi study

A framework for efficiently mining the organisational perspective of business processes

Process mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions, which is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they do not aim at providing efficient solutions; or (iii) the discovered process models are difficult to read due to the number of assignment conditions included. In this paper we address these problems and develop an efficient and effective process mining framework that provides extensive support for the discovery of patterns related to resource assignment. The framework is validated in terms of performance and applicability