Scheduling of agents in inbound multilingual call centers (original) (raw)

Managing trade-offs in call center agent scheduling: methodology and case study

Summer Computer Simulation Conference, 2007

This paper develops a flexible and tractable scheduling methodology that produces near-optimal call center agent schedules while taking into account the costs associated with customer waiting time, customer abandonment, and call center agents. Our methodology combines integer programming (to find a desirable staffing plan for a given total number of agents) and simulation modeling (to evaluate the weekly costs of a given staffing plan). We describe the advantages of this approach over the traditional scheduling method, and test both methods by building schedules based on actual demand and shift data from an actual call center operated by Expedia.com under a variety of cost scenarios. The new scheduling approach not only out-performs the traditional staffing approach in all scenarios examined, it reduces total weekly costs of the call center's existing agent schedule by 8-25%, depending on the scenario.

Staffing Multiskill Call Centers via Linear Programming and Simulation

Management Science, 2008

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 daily agent scheduling in a multiskill call center

European Journal of Operational Research, 2010

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.

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.

Staff Scheduling for Inbound Call Centers and Customer Contact Centers

The staff scheduling problem is a critical problem in the call center (or more generally, customer contact center) industry. This paper describes Director, a staff scheduling system for contact centers, Director is a constraint-based system that uses AI search techniques to generate schedules that satisfy and optimize a wide range of constraints and service quality metrics. Director has been successfully deployed at over 800 contact centers, with significant measurable benefits, some of which are documented in case studies included 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.

Staff scheduling for inbound call and customer contact centers

2002

The staff scheduling problem is a critical problem in the call center (or more generally, customer contact center) industry. This paper describes Director, a staff scheduling system for contact centers. Director is a constraint-based system that uses AI search techniques to generate schedules that satisfy and optimize a wide range of constraints and service quality metrics. Director has been successfully deployed at over 800 contact centers, with significant measurable benefits, some of which are documented in case studies included in this paper.

Optimizing the Staffing and Routing of Small-Size Hierarchical Call Centers

Production and Operations Management, 2008

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.

Intelligent Procedures for Intra‐Day Updating of Call Center Agent Schedules

2010

For nearly all call centers, agent schedules are typically created several days or weeks prior to the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra-day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade-off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.