Digitalization as a Paradigm Changer in Machine-Building Industry
Research output: Book/Report › Doctoral thesis › Monograph
|Publisher||Tampere University of Technology|
|Number of pages||232|
|Publication status||Published - 9 Dec 2016|
|Publication type||G4 Doctoral dissertation (monograph)|
|Name||Tampere University of Technology. Publication|
This dissertation examines the digitalization impact on the machine-building industry that serves global container handling customers - ports and terminals. It is a traditional capital intensive business-to-business industry that has a relatively small number of global players. The investigation adopted a value chain view in which machine builders are actors, actors apply digital technologies provided by enablers. The end customers, ports and terminals are referred as users. The objective of the research was to increase understanding of digitalization’s potential for disruption or paradigm change as well as to identify the most important concepts that drive and inhibit this change. As the change brought about by digitalization is underway, it is necessary to understand whether the views regarding its impact differ between enablers, actors, and users. Mixed methods were applied that partly overlapped for triangulation purposes. The primary methodology included two rounds of Delphi interviews that were complemented by a survey and three case descriptions.
Big Data/Artificial Intelligence emerged as the most prominent digital technology that can enable disruption in machine-building. Empirical results have shown that Big Data/Artificial Intelligence challenges the ways knowledge is created; it is more effective when machines and their components are connected to data networks, and the technology is both rapidly advancing and becoming more affordable. The cost, speed, availability, and features of Big Data/Artificial Intelligence development are driven by multiple industries where machine builders can have a relatively small impact.
Empirical results have also shown that discipline and industry-based platforms are the most powerful economic drivers. The current management of the incumbents has little experience with these new elements, which have a major influence on industry dynamics. The platforms are especially powerful for change, as they enable a global network economy in which entrepreneurial knowledge workers can contribute to value creation in collaboration with startups and multinational corporations. Platform development cannot be stopped or delayed by incumbents in machine-building. They can ignore the development, adapt to it, or pursue a platform strategy of their own if the opportunities match the companies’ capabilities.
Examples of the sub-drivers pushing the digital concepts forward are classical and rational productivity, lead times, features, quality, and cost. In addition, some of the inhibitive sub-drivers are relatively easy to identify, such as 3D printing speed or users providing access to their data. Concerns regarding data security delay investment, and changing legacy processes and systems requires time; however, empirical results have indicated that the strongest inertia is related directly to people and decision making. Three of the strongest people-related inhibitive sub-drivers are lack of systemic understanding, management beliefs, and lack of capabilities. The practical contribution for management is twofold. First, it must be believed that digitalization will somehow disrupt the current business, and second that the transformation is too complex to be only planned, but instead requires also experimental learning. A successful combination that has been suggested by books and articles as well as the results and comments from the Delphi interviews is developing an entrepreneurial mindset, conducting multiple small experiments, and applying the knowledge of external networks. This enables strategy formation through learning, which simultaneously develops the capabilities that are needed in data and user-centric business environments.
- Digitalization, Industrial Internet, Big Data, Artificial Intelligence, platforms, open innovation, industry disruption, strategic management, Delphi, container handling industry