Arbeitspapier

Statistical and Economic Evaluation of Time Series Models for Forecasting Arrivals at Call Centers

Call centers' managers are interested in obtaining accurate forecasts of call arrivals because these are a key input in staffing and scheduling decisions. Therefore their ability to achieve an optimal balance between service quality and operating costs ultimately hinges on forecast accuracy. We present a strategy to model selection in call centers which is based on three pillars: (i) a flexible loss function; (ii) statistical evaluation of forecast accuracy; (iii) economic evaluation of forecast performance using money metrics. We implement fourteen time series models and seven forecast combination schemes on three series of call arrivals. We show that second moment modeling is important when forecasting call arrivals. From the point of view of a call center manager, our results indicate that outsourcing the development of a forecasting model is worth its cost, since the simple Seasonal Random Walk model is always outperformed by other, relatively more sophisticated, specifications.

Language
Englisch

Bibliographic citation
Series: Nota di Lavoro ; No. 6.2017

Classification
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
Forecasting Models; Simulation Methods
Criteria for Decision-Making under Risk and Uncertainty
IT Management
Subject
ARIMA
Call Center Arrivals
Loss Function
Seasonality
Telecommunications Forecasting

Event
Geistige Schöpfung
(who)
Bastianin, Andrea
Galeotti, Marzio
Manera, Matteo
Event
Veröffentlichung
(who)
Fondazione Eni Enrico Mattei (FEEM)
(where)
Milano
(when)
2017

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Bastianin, Andrea
  • Galeotti, Marzio
  • Manera, Matteo
  • Fondazione Eni Enrico Mattei (FEEM)

Time of origin

  • 2017

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