Managing change in industrial organizations : the role of emerging technologies in driving innovation in manufacturing

Abstract

The rapid evolution of Industry 4.0 technology has brought considerable possibilities for the use of innovation in the industry. However, an ongoing issue called the "Implementation gap" hinders the scaling of technologies in practice. The current research focuses on the analysis of both organizational and psychological barriers standing against the success of AI and IoT adoption. This thesis aims at discovering the management practices needed to address the problem under discussion. The study relies on the narrative literature review methodology and analyzes the most recent publications, studies, and management theories on the matter. The findings suggest that inefficiencies related to digitalizing processes that have not been standardized have become the major cause for staying in pilot purgatory. Moreover, narrative tensions areas of supply chains where technological transformation undermines stable operation can be discovered within the context of the research. Finally, technological resistance from employees along with stress resulting from digital transformation has become another factor affecting the implementation process negatively. Accordingly, the research examines the utility of well-structured change management frameworks. Furthermore, a combination of Kotter’s eight-step approach to creating momentum in strategic initiatives and the ADKAR model for managing individual psychological change serves as an effective vehicle for aligning organizations. Additionally, the investigation highlights digital leadership as the key enabler in bridging the implementation gap. Effective transformation is contingent upon evidence-based managerial decisions and organizational flexibility. The findings of the research are summarized in a strategic action plan, stressing the necessity of an equilibrium between technology adoption, process improvement, and empathy in smart manufacturing.