Michael Vössing

Towards Managing Complexity and Uncertainty in Field Service Technician Planning

With increasing servitization efficient delivery of maintenance, repair and overhaul services has become a top priority for many manufacturing companies. But, even though a variety of exact and approximate solution methods have been developed for vehicle routing problems, many manufacturing companies still heavily rely on manual dispatchers with little to no technical support. This paper outlines why the complex, dynamic and deterministic nature of real-world scheduling and routing problems limits the applicability of published vehicle routing solutions to real-world vehicle routing problems. A research agenda is proposed that illustrates how simulation modeling, novel heuristics, and predictive analytics can bridge the identified research gaps.

Employee-Centric Service Innovation: A Viable Proxy for Customer-Intimacy for Product-Focused Enterprises

Servitization has received significant attention from scholars and practitioners over the last decade. However, despite substantial research contributions in the fields of new service development and service innovation, product-focused small and medium-sized enterprises struggle to develop sophisticated service offerings. This paper attempts to better understand this discrepancy and suggests ways to overcome it. We have conducted a case study with a medium-sized manufacturing company that currently undertakes first steps in the development of advanced services. In terms of a theoretical contribution, our study indicates a limited understanding of the perceived value of services during the fuzzy front end of service innovation. Therefore, companies need to adopt new ways to understand their customers (i.e. increase customer intimacy). However, they often struggle to directly involve customers in the co-development of advanced services. In terms of a practical contribution, our research suggests that employee-centric service innovation—the idea of utilizing front line employees as proxies of customers—is a viable strategy to mitigate the identified challenges.

Digitalization of Field Service Planning: The Role of Organizational Knowledge and Decision Support Systems.

Increasing competition and decreasing margins force manufacturers of industrial machinery to augment their products with complementary services—several dependent on field service planning. Hence, the efficient delivery of field services has become a main competitive differentiator and is driving companies to digitalize their processes and utilize decision support systems. Based on a qualitative interview study of maintenance providers, the paper provides empirical insight on the role of organizational knowledge and decision support systems in this digital transformation. The study shows that while maintenance providers have digitized their field service processes, many are only beginning the process of digitalization. Today, employees heavily rely on tacit and embedded knowledge in their decision-making. Therefore, knowledge-driven decision support systems—which have not yet been adopted in the industry—have been identified as an important cornerstone of the coming digitalization of field service planning.

Field Service Technician Management 4.0

Models for workforce planning and scheduling have been studied in operations research for decades. Driven by the Industrial Internet of Things new data sources have become available that have not yet been used to improve field service management. This paper proposes a research agenda towards leveraging this potential in the context of industrial maintenance. By combining predictive analytics (e.g. forecasting demand) with prescriptive analytics (e.g. determining optimal maintenance schedules) companies can decrease uncertainties in their maintenance planning, increase the availability of machines, decrease overall maintenance costs, and ultimately develop new business models.