A Simple Staffing Method for Multiskill Call Centers (original) (raw)
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Staffing Multiskill Call Centers via Linear Programming and Simulation
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We study an iterative cutting-plane algorithm on an integer program, for minimizing the staffing costs of a multiskill call center subject to service-level requirements which are estimated by simulation. We solve a sample average version of the problem, where the service-levels are expressed as functions of the staffing for a fixed sequence of random numbers driving the simulation.
Optimizing Call Center Staffing Using Simulation and Analytic Center Cutting-Plane Methods
Management Science - Management, 2008
We consider the problem of minimizing staffing costs in an inbound call center, while maintaining an acceptable level of service in multiple time periods. The problem is complicated by the fact that staffing level in one time period can affect the service levels in subsequent periods. Moreover, staff schedules typically take the form of shifts covering several periods. Interactions between staffing levels in different time periods, as well as the impact of shift requirements on the staffing levels and cost, should be considered in the planning. Traditional staffing methods based on stationary queueing formulas do not take this into account. We present a simulation-based analytic center cutting-plane method to solve a sample average approximation of the problem. We establish convergence of the method when the service-level functions are discrete pseudoconcave. An extensive numerical study of a moderately large call center shows that the method is robust and, in most of the test cases...
Call Center Staffing with Simulation and Cutting Plane Methods
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We present an iterative cutting plane method for minimizing staffing costs in a service system subject to satisfying acceptable service level requirements over multiple time periods. We assume that the service level cannot be easily computed, and instead is evaluated using simulation. The simulation uses the method of common random numbers, so that the same sequence of random phenomena is
Optimizing the Staffing and Routing of Small-Size Hierarchical Call Centers
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M ultiple-skill call centers propagate rapidly with the development of telecommunications. An abundance of literature has already been published on call centers. Here, we want to focus on centers that would typically occur in business-to-business environments; these are call centers that handle many types of calls but where the arrival rate for each type is low. To find an optimal configuration, the integrality of the decision variables is a much more important issue than for larger call centers. The present paper proposes an approach that uses elements of combinatorial optimization to find optimal configurations. We develop an approximation method for the evaluation of the service performance. Next, we search for the minimum-cost configuration subject to service-level constraints using a branch-and-bound algorithm. What is at stake is to find the right balance between gains resulting from the economies of scale of pooling and the higher cost or cross-trained agents. The article shows that in most cases this method significantly decreases the staffing cost compared with configurations with only cross-trained or dedicated operators.
Management Science, 2008
Call center managers are facing increasing pressure to reduce costs while maintaining acceptable service quality. Consequently, they often face constrained stochastic optimization problems, minimizing cost subject to service-level constraints. Complicating this problem is the fact that customer-arrival rates to call centers are often time varying. Thus, to satisfy their service goals in a cost-effective manner, call centers may employ permanent operators who always provide service, and temporary operators who provide service only when the call center is busy, i.e., when the number of customers in system increases beyond a threshold level. This provides flexibility to dynamically adjust the number of operators providing service in response to the time-varying arrival rate. The constrained dynamic operator staffing (CDOS) problem involves determining the number of permanent and temporary operators, and the threshold value(s) that minimize time-average hiring and opportunity costs subj...
Innovation and Supply Chain Management, 2013
In this paper, we consider the customer call center operation which is one of the personal computer enduser services. We deal with the problem as a case study where the optimal allocation of the call center staff which is called agents is determined. This previous proposed model was to provide the optimal agents' allocation for the call center service based on queuing (Erlang loss formula) [18, 19] and linear programming theory [20]. Here, besides it, we're going to address or examine the mode, considering the queuing space of not-using phones or the phones that no agents are using and the repeated calls that the customers would call when they couldn't reach any agents directly or immediately, and they couldn't even get into the queuing space of not-using phones. Then we show the effectiveness or the extent of the effectiveness of the model.
Simulation-based optimization of agent scheduling in multiskill call centers
2008
We examine and compare simulation-based algorithms for solving the agent scheduling problem in a multiskill call center. This problem consists in minimizing the total costs of agents under constraints on the expected service level per call type, per period, and aggregated. We propose a solution approach that combines simulation with integer or linear programming, with cut generation. In our numerical experiments with realistic problem instances, this approach performs better than all other methods proposed previously for this problem. We also show that the two-step approach, which is the standard method for solving this problem, sometimes yield solutions that are highly suboptimal and inferior to those obtained by our proposed method.
Modelling and simulation of a telephone call center
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2003
We consider a system with two types of traffic and two types of agents. Outbound calls are served only by blend agents, whereas inbound calls can be served by either inboundonly or blend agents. Our objective is to allocate a number of agents such that some service requirement is satisfied. We have taken two approaches in analyzing this staffing problem: We developed a simulation model of the call center, which allows us to do a what-if analysis, as well as continuous-time Markov chain (CTMC) queueing models, which provide approximations of system performance measures. We describe the simulation model in this paper.
Optimization of Multi-skill Call Centers Contracts and Work-shifts
Service Science, 2011
all centers are complex systems in which it is essential to optimize the trade-off between the service level provided to the customers and the cost for the personnel. In this paper we describe a quantitative approach to choose the most suitable contracts to hire the call center operators. The aim is to organize their work-shifts and their rest periods, including lunch-breaks, in such a way that the mix of skills obtained in each time slot is as close as possible to a desired level, estimated according to demand forecasts. The approach here proposed is based on a heuristic method which exploits a general purpose linear programming solver.