Call centers usually handle several types of calls, but it usually is not possible or cost-effective to have every agent be able to handle every type of call. Thus, the agents tend to have different skills, in different combinations. In such an environment, it is challenging to route calls effectively and determine the staff requirements. This paper addresses both these routing and staffing problems by exploiting limited cross-training. Consistent with the literature on flexible manufacturing, we find that minimal flexibility can provide great benefits: Simulation experiments show that when (i) the service-time distribution does not depend on the call type or the agent and (ii) each agent has only two skills, in appropriate combinations, the performance is almost as good as when each agent has all skills. We apply this flexibility property to develop an algorithm for both routing and staffing, aiming to minimize the total staff subject to per-class performance constraints. With appropriate flexibility, it suffices to use a suboptimal routing algorithm. Simulation experiments show that the overall procedure can be remarkably effective: The required staff with limited cross training can be nearly the same as if all agents had all skills. Hence the overall algorithm is nearly optimal for that scenario. Subject classifications: Queues, applications: call centers with skill-based routing. Queues, algorithms: staffing and routing in call centers with skill-based routing. Queues, networks: call centers with skill-based routing.
Simulations in REF show empirically that limited cross-training can be highly effective in a large call center under a skill-based routing algorithm.
A staffing algorithm for call centers with skill-based routing
Manufacturing and Service Operations Management
Computer Science