Abstract
There is a broad consensus that the transformative power of the Internet of Things (IoT) will affect all kinds of industries; or, to put it in a more optimistic light, that almost no domain is excluded from the opportunities to leverage the IoT. But, what does this mean for the future of industrial processes? This article introduces the concept of high-resolution management (HRM). IoT enables the collection of high-resolution data for the physical world where, as in the digital world, every aspect of business operations can be measured in real-time. This capability facilitates high-resolution management, such as short optimization cycles in industrial production, logistics and equipment efficiency, comparable to methods like A/B-Testing or Search Engine Optimization, which are state of the art in digital business. We take the following two perspectives on leveraging high-resolution management. First, through greater insights into their industrial processes, companies that apply HRM in their operations are able to achieve higher efficiency, quality and flexibility. The example of vehicle fleet management illustrates this effect. Second, we build upon the St. Gallen Business Model Navigator in order to look in greater detail on how the IoT affects industrial processes. Gassmann et al.[1] introduce 55 generic business model patterns, of which our extended research identified 20 that could profit significantly from the IoT[2]. Analyzing these 20 patterns allowed for the identification of six key components: Remote Usageand Condition Monitoring, Object Self Service, Digital Add-on, Digital Lock-in, Product as a Point of Sales and Physical Freemium. These building blocks help companies to supply HRM-supported offerings. Finally, the example of remote monitoring of process parameters shows that these business model components can also be deployed to create offerings that enable others to apply HRM.
Zusammenfassung
Dieser Artikel befasst sich mit dem Konzept des ,,High Resolution Managements“ (HRM). Das ,,Internet der Dinge“ (IoT), die Vision einer zunehmenden Verschmelzung der physischen mit der digitalen Welt, spielt dabei eine entscheidende Rolle. Neue Sensor- und Aktuator-Technologien ermöglichen Unternehmen Daten in unbekannter Detailschärfe auszuwerten. Die vorliegende Arbeit betrachtet das Konzept des ,,High Resolution Managements“ aus zwei unterschiedlichen Perspektiven: Einerseits wird die Hypothese ausgearbeitet, dass die neu gewonnene Fülle an Daten Unternehmen erlauben wird, ihre Prozesse effizienter, flexibler und qualitativ hochwertiger zu gestalten. Andererseits stellt sich die Frage, wie das Internet der Dinge Geschäftsmodelle im Industriekontext beeinflussen wird. Aufbauend auf den 55 Geschäftsmodellmustern von Gassmann et al., werden aus fortführender Forschung sechs Kernkomponenten von IoT Geschäftsmodellen präsentiert: Remote Usage and Condition Monitoring, Object Self Service, Digital Add-on, Digital Lock-in, Product as a Point of Sales und PhysicalFreemium.
About the authors
Markus Weinberger is Director of the Bosch IoT Lab at the University of St. Gallen. His work is focused on IoT applications in the domains of “Smart Home” and “Connected Mobility”, as well as on IoT business models. Markus holds a PhD from TU Munich.
Bosch Software Innovation GmbH, Bosch IoT Lab, Dufourstrasse 40a, 9000 St. Gallen, Switzerland
Dominik Bilgeri is a PhD candidate at the Bosch IoT Lab of the Swiss Federal Institute of Technology in Zurich where he investigates the phenomenon of digital business models in the IoT context. Dominik holds an MSc from Erasmus University Rotterdam.
ETH Zurich, 8092 Zurich, Switzerland
Elgar Fleisch has a double appointment at ETH Zürich and University St. Gallen (HSG). At ETH, he is a full professor of information management, at HSG of technology management. In his research, Elgar Fleisch and his team aim at understanding and designing the ongoing merge between the physical and digital world. Elgar Fleisch is a co-founder of several university spin-offs and he serves as a member of multiple management boards and academic steering committees.
University of St. Gallen, Dufourstrasse 40a, 9000 St. Gallen, Switzerland; and ETH Zurich, 8092 Zurich, Switzerland
©2016 Walter de Gruyter Berlin/Boston