It is well known that resource pooling (or, equivalently, the use of flexible resources that can serve multiple types of requests) significantly improves the performance of service systems. On the other hand, complete resource pooling often results in higher infrastructure (communication and coordination) costs. This leads us to explore the benefits that can be derived by a limited amount of resource pooling, and the question whether a limited amount of pooled resources can deliver most of the benefits of complete resource pooling. Applications in skill-based call centers, healthcare, and flexible supply chains are among our main motivations.
We demonstrate, in the context of some concrete models, that a very small amount of flexibility can be surprisingly powerful in improving performance, both in terms of queueing delay and system capacity. However, to harness the benefits of flexibility, one should carefully architect network topologies, scheduling policies, and how to properly leverage (predictive) information in making dynamic resource allocation decisions. In this talk, I will discuss stochastic models and analytical results that provide interesting insights on these challenges, as well as an application in the context of congestion control for emergency departments.