Discrete Event Simulation Model Performed with Data Analytics for a Call Center Optimization (original) (raw)
Related papers
A Tutorial On Modelling Call Centres Using Discrete Event Simulation
ECMS 2013 Proceedings edited by: Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang, 2013
Arriving at an optimal schedule for the staff and determining their required skills in a call centre is imperative to balance the conflicting requirements of delightful customer experience, high employee satisfaction and low cost. Due to the complex nature of modern call centres, simulation modelling is increasingly being used to predict their performance. We have modelled a call centre using our in-house discrete event simulation tool called DESiDE. This paper describes how every component of call centres were modelled as simulation resources. This paper also describes the changes that had to be made to DESiDE in order to handle the special requirements of call centre modelling and also the metrics used by call centres.
Ditila Ekmekçiu: Optimizing a call center performance using queueing models– an Albanian case
The world of call centers is an important reality nowadays and helping the decision making of the operations management is fundamental for this industry. A call center generally represents the first contact of a customer with a specific company. As a result, the quality of the service offered is of fundamental importance. The objective of this paper is to see how to apply the queueing models in order to optimize the call centers’ performance. A crucial factor of the call centers’ optimization is determining the proper number of agents, during a working day, considering the chosen performance measure. The experiment is done in one of the Albanian outsourcing call centers. The literature related to the application of such models at call centers is reviewed. A suitable number of agents was determined for different peak periods of the working day, considering the most important performance measures. The obtained results prove how useful and applicable are the stochastic queueing models as a tool for a call centers’ performance, in terms of the expected waiting time, number of customers waiting for service and of call centers service levels optimization. Practically, all the data needed for this mathematical/analytical approach is provided. This paper has the purpose to illustrate how such data can be efficiently used to advantage the operations management. Keywords: Call center, Service Levels, Optimization, Queueing Models
Optimization of a Call Centre Performance Using the Stochastic Queueing Models
Business Systems Research Journal, 2014
Background: A call centre usually represents the first contact of a customer with a given company. Therefore, the quality of its service is of key importance. An essential factor of the call centre optimization is the determination of the proper number of operators considering the selected performance measure. Results of previous research show that this can be done using the queueing theory approach. Objectives: The paper presents the practical application of the stochastic queueing models aimed at optimizing a Slovenian telecommunication provider's call centre. Methods/Approach: The arrival and the service patterns were analysed, and it was concluded that the call centre under consideration can be described using the M/M/r {infinity/infinity/FIFO} queueing model. Results: An appropriate number of operators were determined for different peak periods of the working day, taking into consideration the following four performance measures: the expected waiting time, the expected number of waiting customers, the probability that a calling customer will have to wait, and the call centre service level. Conclusions: The obtained results prove the usefulness and applicability of the queueing models as a tool for a call centre performance optimization. In practice, all the data needed for such a mathematical analysis are usually provided. This paper is aimed at illustrating how such data can be efficiently exploited.
Modeling and Simulation of Call Centers
Proceedings of the Winter Simulation Conference, 2005., 2005
In this review, we introduce key notions and describe the decision problems commonly encountered in call center management. Main themes are the central role of uncertainty throughout the decision hierarchy and the many operational complexities and relationships between decisions. We make connections to analytical models in the literature, emphasizing insights gained and model limitations. The high operational complexity and the prevalent uncertainty suggest that simulation modeling and simulation-based decision-making could have a central role in the management of call centers. We formulate some common decision problems and point to recently developed simulation-based solution techniques. We review recent work that supports modeling the primitive inputs to a call center and highlight call center modeling difficulties.
Call Center Scheduling Technology Evaluation Using Simulation
Proceedings of the 33nd conference on …, 2001
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 produc-tive. Investments are required in human resources, infra- ...
2012
The ability to profitably manage the level of resources in a service system can be considered a strategic skill in all those organizations, including no-profit ones and Public Administrations, that aim at providing an added value service to customers as well as balancing the level of service (in terms of quality) with costs. In this paper we will focus on a typical service system inside of which, in every moment, management struggles in order to reach that balance, because of the extremely dynamic behavior of the entire system: a Call Center. Our aim is to show that an efficient management of the customers abandonment and the quality of service offered to customers, can positively impact on a correct resource leveling in the system, which may otherwise be found by means of typical Operations Research or Queuing Theory methods. In particular, we want to show that this can be more easily inferred and understood by resorting to simulation. After introducing some preliminary aspects by means of Queuing Theory (Erlang's formula), we'll first study the problem of customer abandonment (balking and reneging) by simulating a Call Center simple model by means of a process-oriented discrete-time simulation tool (Arena), and then explore a more complex model taking into 2 account customer satisfaction an the quality of the service offered, approaching the modelling process of the system by means of System Dynamics. Results show that the level of resources can be further reduced, and that the customer (often thought as an entity external to the system) plays instead an important role on the performance of the whole system, both operationally and economically.
A simulation-based decision support system for workforce management in call centers
SIMULATION, 2013
Workforce management is critical in call centers, where thousands of calls are handled by hundreds of agents every day. In a call center, where the call arrival rates tend to fluctuate during the day, the agent allocation plans are required to be planned flexibly and the number of operating call center agents ought to be updated whenever needed, in order to keep the customer satisfaction level over a predefined level. Workforce plans are usually generated by the use of queuing models that are based on Erlang C calculations. However, they have assumptions that oversimplify the real system and jeopardize the validation of the model. At this point, the simulation models, which do not have such restrictive assumptions, are effective in calculating the required number of agents for each time period and measuring the performance of a given shift schedule. In this study, a simulation-based decision support system (DSS) is developed that runs on real-time data for one of the largest call centers in Turkey. The graphical user interfaces (GUIs) are designed in accordance with the man-machine interaction consideration to increase the usability, functionality and effectiveness of the DSS. It is shown that the combination of the advantages of simulation with a flexible and user-friendly DSS environment provides more effective and efficient workforce planning and performance reporting in call centers.
Managing trade-offs in call center agent scheduling: methodology and case study
Summer Computer Simulation Conference, 2007
This paper develops a flexible and tractable scheduling methodology that produces near-optimal call center agent schedules while taking into account the costs associated with customer waiting time, customer abandonment, and call center agents. Our methodology combines integer programming (to find a desirable staffing plan for a given total number of agents) and simulation modeling (to evaluate the weekly costs of a given staffing plan). We describe the advantages of this approach over the traditional scheduling method, and test both methods by building schedules based on actual demand and shift data from an actual call center operated by Expedia.com under a variety of cost scenarios. The new scheduling approach not only out-performs the traditional staffing approach in all scenarios examined, it reduces total weekly costs of the call center's existing agent schedule by 8-25%, depending on the scenario.
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/simulation-of-service-industry-an-effective-approach-to-improve-service-quality-under-dynamic-demand-scenario https://www.ijert.org/research/simulation-of-service-industry-an-effective-approach-to-improve-service-quality-under-dynamic-demand-scenario-IJERTV2IS80430.pdf In today's world of global competition, customer satisfaction has become a major concern in service industry settings like banks, hospitals, call centers, etc. Service organizations, in general, are characterized by high variability in demand. Under changing demand scenario, if the workforce is constant, customer's waiting time may increase drastically which may result in heavy loss to business. Customer's efficient staff scheduling which takes into account varying demand levels. This paper investigates the various processes of bank at a branch of a nationalized bank in India. It also suggests a methodological framework that can be implemented in this service industry. This investigation reduces waiting time, processing time and finds a way for proper utilization of resources.
Performance Indicators Analysis inside a Call Center Using a Simulation Program
International Journal of Business & Technology, 2016
This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as a key case at the time where the events analyses could be executed. This article comes to the conclusion that Simulation is a completely suitable instrument to accomplish its purpose since it could be adequate to demonstrate, for the call center taken into consideration principally that: (a) it is feasible to reduce the agent contingent; (b) reasonable variatio...