Analytics-enabled escalation management: System development and business value assessment

Abstract Industry 4.0 initiatives can help traditional manufacturing industry cope with increasing global competition. Such solutions facilitate transparency, automation as well as business process transformation. This paper elaborates on a collaboration with a medium-sized manufacturing company. We highlight the design, evaluation and roll-out of an escalation management system with integrated data-driven decision support. We do so by applying an action design research process. Thereby, our study focuses on the system design concerning the creation of business value. The system leverages state-of-the-art machine learning algorithms for disruption type classification and escalation handling duration prediction. These predictions can be embedded in an integrated planning procedure leveraging diverse organizational data sources (e.g., personnel availability, production plans) to instantiate a prescriptive analytics solution. Combined with informative analytics insights, this allows the proposed system to generate significant business value by reducing escalation durations. In the long run, the transformational business value enabled by the system is likely to exceed the automational business value. This highlights the special importance of tight integration of industrial analytics applications within business processes.