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ABSTRACT
Using stochastic models to plan call center operations, schedule call center staff efficiently, and analyze projected performance is not a new phenomenon, dating back to Erlang's work in the early twentieth century. However, several factors have recently conspired to increase demand for call center simulation analysis. • Increasing complexity in call traffic, coupled with the almost ubiquitous use of Skill-Based Routing. • Rapid change in operations due to increased merger and acquisition activity, business volatility, outsourcing options, and multiple customer channels (inbound phone, outbound phone, email, web, chat) to support. • Cheaper, faster desktop computing, combined with specialized call center simulation applications that are now commercially available. In this tutorial, we will provide an overview of call center simulation models, highlighting typical inputs and data sources, modeling challenges, and key model outputs. In the process, we will also present an interesting "real-world" example of effective use of call center simulation. REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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