DocumentCode :
633973
Title :
Forecasting in Multi-skill Call Centers: A Multi-agent Multi-service (MAMS) Approach: Research in Progress
Author :
Motta, Gianmario ; Barroero, T. ; Sacco, Daniele ; Linlin You
Author_Institution :
Dept. of Ind. & Inf. Eng., Univ. of Pavia, Pavia, Italy
fYear :
2013
fDate :
29-31 May 2013
Firstpage :
223
Lastpage :
229
Abstract :
Workforce management is critical in call center business. Human resources are the highest cost, and therefore efficiency is a key success factor. On the other side relevant peaks of incoming calls have to be served. We here consider a complex case, with a many-to-many relationship between agents and services, i.e. the same agent serves many customers and the same customer may be served by many agents. In this perspective, we propose a model to forecast calls in long- and mid-term by ARIMA (Auto-Regressive Integrated Moving Average), and to size workforce in mid-term by integrating an Erlang model. Finally, we have developed a tool to forecast calls in a multi-agent multi-service call center. Field tests are running and first results validate our model.
Keywords :
autoregressive moving average processes; call centres; customer services; forecasting theory; human resource management; multi-agent systems; ARIMA; Erlang model; MAMS approach; auto-regressive integrated moving average; call center business; human resources; incoming calls; many-to-many relationship; multiagent multiservice approach; multiagent multiservice call center; multiskill call center forecasting; workforce management; workforce size; Analytical models; Autoregressive processes; Computational modeling; Forecasting; Mathematical model; Predictive models; Time series analysis; ARIMA; Box and Jenkins; Call center; Forecasting; Regression analysis; Service level agreement; Service level management; Time Series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Science and Innovation (ICSSI), 2013 Fifth International Conference on
Conference_Location :
Kaohsiung
Type :
conf
DOI :
10.1109/ICSSI.2013.47
Filename :
6599389
Link To Document :
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