Forecasting Daily Call Arrivals Within an Inbound Call Center - Centre Génie Industriel
Conference Papers Year : 2023

Forecasting Daily Call Arrivals Within an Inbound Call Center

Prévision des arrivées quotidiennes d'appels dans un centre d'appels entrants

Samer Alsamadi
  • Function : Correspondent author
  • PersonId : 1134705

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Clea Martinez
Canan Pehlivan
Nicolas Cellier
Franck Fontanili

Abstract

When it comes to managing inbound call centers throughout the days of the week, we are met with a challenge concerning the incertitude revolved around the volume of incoming calls. By training either statistical or neural network forecasting models, we are able to anticipate the number of incoming calls within a certain degree of error. Of crucial importance is determining what type of model to train and how to configure this model’s hyperparameters in an optimized manner. By benchmarking different optimized forecasting models, we were able to generate daily call volume forecasts for an inbound call center.
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Dates and versions

hal-04742044 , version 1 (17-10-2024)

Identifiers

  • HAL Id : hal-04742044 , version 1

Cite

Samer Alsamadi, Clea Martinez, Canan Pehlivan, Nicolas Cellier, Franck Fontanili. Forecasting Daily Call Arrivals Within an Inbound Call Center. SAGIP 2023 - 1er congrès de la Société d'Automatique, de Genie industriel & de Productique, Société d'Automatique, de Génie Industriel & de Productique, Jun 2023, Marseille, France. ⟨hal-04742044⟩
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