Asymmetries of Service: Interdependence and Synchronicity

What Makes Service Different from Computation? Often, service systems are modeled through the same queueing theoretic frameworks that would be used in computational settings: a queue can be both a line of customers for an agent and a schedule of jobs for a machine. However, at the within-service level, queueing models are quite coarse: the duration of service is simply represented as some random variable. In “Asymmetries of Service: Interdependence and Synchronicity,” Daw and Yom-Tov analyze a model of service that is more micro than macro. This history-driven interaction model illuminates the (a)symmetries in the speed and volume of work that the customer and agent each contribute to the service. Moreover, this model offers new insight into how real-world services can differ from queueing theoretic models. For instance, multitasked services have widely exhibited “inverted U-shaped” throughput as a function of the number of simultaneous customers, yet the corresponding processor-sharing queues only take on such shapes via explicit assumption. By contrast, the interaction-level model establishes conditions under which an inverted U arises; in fact, it also shows that the optimized throughput will be U-shaped as a function of the customer’s relative volume of contributions. In both cases, these insights are consequences of asymmetry between the customer and agent, demonstrating how micro-level details matter for services.