The role of digital technologies for the service transformation of industrial companies

Abstract

The role of digital technologies in service business transformation is under-investigated. This paper contributes to filling\ud this gap by addressing how the Internet of things (IoT), cloud computing (CC) and predictive analytics (PA) facilitate\ud service transformation in industrial companies. Through the Data–Information–Knowledge–Wisdom (DIKW) model, we\ud discuss how the abovementioned technologies transform low-level entities such as data into information and knowledge\ud to support the service transformation of manufacturers. We propose a set of digital capabilities, based on the extant\ud literature and the findings from four case studies. Then, we discuss how these capabilities support the service transformation\ud trajectories of manufacturers. We find that IoT is foundational to any service transformation, although it is mostly\ud needed to become an availability provider. PA is essential for moving to the performance provider profile. Besides\ud providing scalability in all profiles, CC is specifically used to implement an industrialiser strategy, therefore leading to\ud standardised, repeatable and productised offering

Exploring How Usage-Focused Business Models Enable Circular Economy through Digital Technologies

“…Moreover, among the several digital technologies highlighted by the fourth industrial revolution, only IoT, Big Data, and analytics have been considered, in accordance with recent works in this field [5,52,53]. Thus, the study in particular focuses on how IoT, Big Data, and analytics act in the deployment of usage-focused Business Models to increase resource efficiency, extend product lifespan, and close the loop, i.e., to attain the fundamental circular economy value drivers.…”

“…Despite the drawbacks of usage-oriented BMs towards CE, with respect to result-oriented BMs, we decided to focus on usage-oriented BMs, since they are nowadays reaching an ever-increasing diffusion in both the business-to-business (B2B) and business-to-consumer (B2C) sectors, also thanks to the growing popularity of the "sharing" paradigm [3]. Moreover, among the several digital technologies highlighted by the fourth industrial revolution, only IoT, Big Data, and analytics have been considered, in accordance with recent works in this field [5,52,53].…”

“…While the enabling role of digital technologies for the servitization of companies has been investigated by previous studies (see, for instance, the work of Ardolino et al [53]), their specific role as enabler for CE has been quite under-investigated to date [5,23].…”

“…In fact, analytics leverages software and data mining techniques to extract useful information from data, by developing business intelligence and decision support systems to identify patterns in the data and make predictions [23,53]. To find the proper application, analytics need to work with large amounts of data [53]. In this case, analytics allow companies to transform data into insights, which provides the basis for a better decision making [52,58].…”

“…Big Data are usually seen in literature as a valid approach to enable a better decision making, if combined with appropriate analytics techniques [23]. In fact, analytics leverages software and data mining techniques to extract useful information from data, by developing business intelligence and decision support systems to identify patterns in the data and make predictions [23,53]. To find the proper application, analytics need to work with large amounts of data [53].…”