Analyzing resource behavior to aid task assignment in service systems
RIS ID
104654
Abstract
Service organizations increasingly depend on the operational efficiency of human resources for effective service delivery. Hence, designing work assignment policies that improve efficiency of resources is important. This paper explores the role that data (specifically service execution histories) can play in identifying optimal policies for allocating service tasks to service workers. Using data from the telecommunications domain, we investigate the impact of assigning similar and distinct tasks within the temporal frames of a day, across days and a week. We find that similar work, when done within a day, significantly improves the efficiency of workers. However, workers working on distinct tasks across days also have higher efficiency. We build a simulation model of the service system under study, to gain insights into the dispatch policy considering similarity and variety of tasks assigned. Our work demonstrates use of data to generate critical insights on resource behavior and efficiencies, that can further aid in improving task assignment to resources.
Publication Details
Sindhgatta, R., Ghose, A. & Dasgupta, G. Banerjee. (2015). Analyzing resource behavior to aid task assignment in service systems. In A. Barros, D. Grigori, N. C. Narendra & H. Khanh. Dam (Eds.), Service-Oriented Computing: Proceedings of the 13th International Conference, ICSOC 2015 (pp. 412-426). Heidelberg, Germany: Springer.