Does the Erlang C model fit in real call centers?

We consider the Erlang C model, a queuing model commonly used to analyze call center performance. Erlang C is a simple model that ignores caller abandonment and is the model most commonly used by practitioners and researchers. We compare the theoretical performance predictions of the Erlang C model to a call center simulation model where many of the Erlang C assumptions are relaxed. Our findings indicate that the Erlang C model is subject to significant error in predicting system performance, but that these errors are heavily biased and most likely to be pessimistic, i.e. the system tends to perform better than predicted. It may be the case that the model's tendency to provide pessimistic (i.e. conservative) estimates helps explain its continued popularity. Prediction error is strongly correlated with the abandonment rate so the model works best in call centers with large numbers of agents and relatively low utilization rates.

[1]  Averill Law,et al.  Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management) , 2006 .

[2]  Ward Whitt,et al.  Heavy-Traffic Limits for Queues with Many Exponential Servers , 1981, Oper. Res..

[3]  Thomas R. Robbins,et al.  Managing service capacity under uncertainty , 2007 .

[4]  Thomas R. Robbins,et al.  Evaluating Arrival Rate Uncertainty in Call Centers , 2006, Proceedings of the 2006 Winter Simulation Conference.

[5]  Sonja Kuhnt,et al.  Design and analysis of computer experiments , 2010 .

[6]  J. Michael Harrison,et al.  Design and Control of a Large Call Center: Asymptotic Analysis of an LP-Based Method , 2006, Oper. Res..

[7]  Shane G. Henderson,et al.  FORECAST ERRORS IN SERVICE SYSTEMS , 2009, Probability in the Engineering and Informational Sciences.

[8]  Terry P. Harrison,et al.  A stochastic programming model for scheduling call centers with global Service Level Agreements , 2010, Eur. J. Oper. Res..

[9]  Peter J. Kolesar,et al.  Improving the Sipp Approach for Staffing Service Systems That Have Cyclic Demands , 2001, Oper. Res..

[10]  Pierre L'Ecuyer,et al.  Good Parameters and Implementations for Combined Multiple Recursive Random Number Generators , 1999, Oper. Res..

[11]  Avishai Mandelbaum,et al.  Empirical analysis of a call center , 2000 .

[12]  Amy R. Ward,et al.  Fair Dynamic Routing in Large-Scale Heterogeneous-Server Systems , 2010, Oper. Res..

[13]  Ward Whitt,et al.  A Staffing Algorithm for Call Centers with Skill-Based Routing , 2005, Manuf. Serv. Oper. Manag..

[14]  Avishai Mandelbaum,et al.  Telephone Call Centers: Tutorial, Review, and Research Prospects , 2003, Manuf. Serv. Oper. Manag..

[15]  Ward Whitt,et al.  Staffing a Call Center with Uncertain Arrival Rate and Absenteeism , 2006 .

[16]  Avishai Mandelbaum,et al.  Statistical Analysis of a Telephone Call Center , 2005 .

[17]  Ward Whitt,et al.  Server Staffing to Meet Time-Varying Demand , 1996 .

[18]  Zeynep Akşin,et al.  The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research , 2007 .

[19]  Shane G. Henderson,et al.  Service system planning in the presence of a random arrival rate , 2004 .

[20]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[21]  Linda V. Green,et al.  AN IMPROVED HEURISTIC FOR STAFFING TELEPHONE CALL CENTERS WITH LIMITED OPERATING HOURS , 2003 .

[22]  J. Michael Harrison,et al.  A Method for Staffing Large Call Centers Based on Stochastic Fluid Models , 2005, Manuf. Serv. Oper. Manag..

[23]  Noah Gans,et al.  Call-Routing Schemes for Call-Center Outsourcing , 2007, Manuf. Serv. Oper. Manag..

[24]  Sem C. Borst,et al.  Dimensioning Large Call Centers , 2000, Oper. Res..

[25]  Shane G. Henderson,et al.  Two Issues in Setting Call Centre Staffing Levels , 2001, Ann. Oper. Res..