CALL CENTERS (CENTRES) - Faculty of Industrial Engineering and ...

computer-based simulator by running an experiment using data obtained from our observations
of the real world setting.
Keywords: Computer simulation, Emergency call centre, Cooperative systems, Bottom-up approach,
Environmental factors, Noise, Cognitive factors, Object-oriented approach, Experiment,
Ergonomics, Multi-agent systems
(Appears also in Section IV.)
19. Ridley, A. Performance optimization of a telecommunication call center. Proceedings of the
Applied Telecommunication Symposium (ATS’00). SCS, San Diego, CA, USA, 2000, 163–167.
Abstract. Telecommunication call centers have become the primary channel of customer interaction
service for many businesses. The level of professionalism and efficiency that call center
agents deliver to customers provides a significant advantage over traditional customer service
practices. The growth of call centers has been substantial over the last two decades. This growth
is driven by a company’s desire to lower operating costs and to increase revenues (Kim 1997).
The author investigates analytical and simulation-based models for the design and management
of a call center. Given three classes of traffic (voice, E-mail, and facsimile) with different
target waiting-times in queue and target service levels, the goal is to optimize the call center
performance. The system performance can be measured with quantities such as the expected
waiting-time in queue, the expected time in system, the percentage of calls answered within a
given time, and the expected waiting-time probability distribution. The system performance of
the call center is measured using analytical and simulation-based queuing models. For analytical
models, the traffic classes will have exponential inter-arrival and service time distributions where
the arrival and service rates will differ among classes. Also, each customer call will be assigned
a queue priority based on its traffic class. The call agents will be able to handle calls from any
class. For the simulation-based models, the inter-arrival and service time distributions will not
be exponential, the agents will have different skill-levels, and the queue length will be finite.
Keywords: Performance optimization, Telecommunication call center, Simulation-based models,
Management, Voice traffic, E-mail, Facsimile, Service levels, Expected waiting time, Probability
distribution, Queuing models, Exponential inter-arrival distributions, Service-time distributions
(Appears also in Section I.)
20. Gulati, Sandeep and Scott A. Malcolm. Call center scheduling technology evaluation using simulation.
Proceedings of the 2001 Winter Simulation Conference, Arlington, VA, USA, 2, 2001,
1438–1442.
Abstract. Telemarketers, direct marketing agencies, collection agencies and others whose primary
means of customer contact is via the telephone invest considerable sums of money to make
the calling operation efficient and productive. Investments are required in human resources,
infrastructure and technology. Having invested the dollars, businesses want to ensure that value
is maximized. Call scheduling algorithms provide an efficient method to maximize customer
contact. However, management at a large, national credit-card bank was not convinced that the
software used to schedule calls was providing an adequate level of service. Simulation studies
showed that management was justified in this assumption. The study also revealed that process
improvement opportunities exist, which if implemented would likely produce the desired perfor-
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