Blended call center performance analysis

Bernett, H.G.; Fischer, Martin J.; Masi, D.M. Bevilacqua

doi:10.1109/mitp.2002.1000458

Cited by 15 publications

(7 citation statements)

References 4 publications

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“…The key distinction of problems with blending comes from the fact that e-mail calls or callbacks have less urgency and can be inventoried to some extent, relative to phone calls. The call blending problem has led to research on performance evaluation (Bernett, Fischer, and Masi 2002;Pichitlamken et al 2003;Deslauriers et al 2007) and analysis of blending policies (Gans and Zhou 2003;Bhulai and Koole 2003;Armony and Maglaras 2004a,b). Keblis and Chen (2006) consider a staffing problem in a setting with blending as well as "cosourcing," which is defined in the next section.…”

Section: Pooling and Design Of Multi-skill Andmentioning

confidence: 99%

The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research

Akşin

Armony

Mehrotra

2007

Production and Operations Management

614

515

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C all centers are an increasingly important part of today's business world, employing millions of agents across the globe and serving as a primary customer-facing channel for firms in many different industries. Call centers have been a fertile area for operations management researchers in several domains, including forecasting, capacity planning, queueing, and personnel scheduling. In addition, as telecommunications and information technology have advanced over the past several years, the operational challenges faced by call center managers have become more complicated. Issues associated with human resources management, sales, and marketing have also become increasingly relevant to call center operations and associated academic research.In this paper, we provide a survey of the recent literature on call center operations management. Along with traditional research areas, we pay special attention to new management challenges that have been caused by emerging technologies, to behavioral issues associated with both call center agents and customers, and to the interface between call center operations and sales and marketing. We identify a handful of broad themes for future investigation while also pointing out several very specific research opportunities.

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Section: Pooling and Design Of Multi-skill Andmentioning

confidence: 99%

The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research

Akşin

Armony

Mehrotra

2007

Production and Operations Management

614

515

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“…The key distinction of call center problems with blending comes from the fact that outbound tasks have less urgency relative to inbound calls. Blended operations problems have led to research on performance evaluation (Bernett et al, 2002;Pichitlamken et al, 2003;Deslauriers et al, 2007), staffing (Pang and Perry, 2014) and analysis of blending policies Bhulai and Koole, 2003;Armony and Maglaras, 2004a;Armony and Ward, 2010;Legros et al, 2013Legros et al, , 2015b. Because of the lack of service level requirement on outbounds, it is best to give higher priority to inbounds.…”

Section: Introductionmentioning

confidence: 99%

Optimal scheduling in call centers with a callback option

Legros

Jouini

Koole

2016

Performance Evaluation

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International audienceWe consider a call center model with a callback option, which allows to transform an inbound call into an outbound one. A delayed call, with a long anticipated waiting time, receives the option to be called back. We assume a probabilistic customer reaction to the callback offer (option). The objective of the system manager is to characterize the optimal call scheduling that minimizes the expected waiting and abandonment costs. For the single-server case, we prove that non-idling is optimal. Using a Markov decision process approach, we prove for the two-server case that a threshold policy on the number of queued outbound calls is optimal. For the multi-server case, we numerically characterize a switching curve of the number of agents reserved for inbound calls. It is a function of the number of queued outbound calls, the number of busy agents and the identity of jobs in service. We also develop a Markov chain method to evaluate the system performance measures under the optimal policy. We next conduct a numerical study to examine the impact of the policy parameters on the system performance. We observe that the value of the callback offer is especially important for congested situations. It also appears that the benefits of a reservation policy are more apparent in large call centers, while they almost disappear in the extreme situations of light or heavy workloads. We moreover observe in most cases that the callback offer should be given upon arrival to any delayed call. However, if balking and abandonment are very high (which helps to reduce the workload) or if the overall treatment time spent to serve an outbound call is too large compared to that of an inbound one, there is a value in delaying the proposition of the callback offer

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“…Further, note that many types of call blending can be identified; Koole and Mandelbaum [4] provide an excellent overview. A high-level discussion and basic performance analysis is provided in [7]. The paper [8] presents a collection of Markov chain models for call centers, including a discussion of model fidelity and efficacy, in a simulation context.…”

Section: Introductionmentioning

confidence: 99%

Two Way Communication Retrial Queues with Balanced Call Blending

Phung-Duc

Rogiest

2012

Analytical and Stochastic Modeling Techniques and Applications

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Abstract. In call centers, call blending consists in the mixing of incoming and outgoing call activity. Artalejo and Phung-Duc recently provided an apt model for such a setting, with a two way communication retrial queue. However, by assuming a classical (proportional) retrial rate for the incoming calls, the outgoing call activity is largely blocked when many incoming calls are in orbit, which may be unwanted, especially when outgoing calls are vital to the service offered.In this paper, we assume a balanced way of call blending, through a retrial queue with constant retrial rate for incoming calls. For the single server case (one operator), a generating functions approach enables deriving explicit formulas for the joint stationary distribution of the number of incoming calls and the system state, and also for the factorial moments. This is complemented with a stability analysis, expressions for performance measures, and also recursive formulas, allowing reliable numerical calculation. For the multiserver case (multiple operators), we provide a quasi-birth-and-death process formulation, enabling deriving a sufficient and necessary condition for stability in this case, as well as a numerical recipe to obtain the stationary distribution.

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Blended call center performance analysis

Cited by 15 publications

References 4 publications

The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research

The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research

Optimal scheduling in call centers with a callback option

Two Way Communication Retrial Queues with Balanced Call Blending

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