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Reseach Article

A Performance Evaluation of Call Resolution Oriented Routing Rules to Enhance Resolution Rates

by Mughele Ese Sophia, Stella C. Chiemeke
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 143 - Number 8
Year of Publication: 2016
Authors: Mughele Ese Sophia, Stella C. Chiemeke
10.5120/ijca2016910328

Mughele Ese Sophia, Stella C. Chiemeke . A Performance Evaluation of Call Resolution Oriented Routing Rules to Enhance Resolution Rates. International Journal of Computer Applications. 143, 8 ( Jun 2016), 32-38. DOI=10.5120/ijca2016910328

@article{ 10.5120/ijca2016910328,
author = { Mughele Ese Sophia, Stella C. Chiemeke },
title = { A Performance Evaluation of Call Resolution Oriented Routing Rules to Enhance Resolution Rates },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 143 },
number = { 8 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 32-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume143/number8/25100-2016910328/ },
doi = { 10.5120/ijca2016910328 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:45:50.515984+05:30
%A Mughele Ese Sophia
%A Stella C. Chiemeke
%T A Performance Evaluation of Call Resolution Oriented Routing Rules to Enhance Resolution Rates
%J International Journal of Computer Applications
%@ 0975-8887
%V 143
%N 8
%P 32-38
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In contemporary society, satisfying customer’s needs has become a phenomenon seen to be highly inevitable for business that wants to survive in this era of high competition amidst the global financial crisis. A customer’s experience during a service encounter consist of two parts namely: the time spent waiting for the service and the service itself. The nature of the service, which is the resolution status, is a major key performance indicator (KPI) to measure the success of a call center. The challenge in the traditional call centres in Nigeria, is the ineffective resolution of calls which causes customers to call back immediately after an interaction with a call center agent. This is because the issue was not resolved in the previous encounter. The purpose of this research is to evaluate the performance results of three Call Resolution (CR) routing rules, using data collected from the call center of a telecommunication organisation Nigeria. The evaluation was conducted using simulation techniques. A sample of 2,000 calls was used for the simulation. Java programs were developed for each of the routing rules because they vary from one approach to another in operation. Results from the simulation gave the performance of all routing rules for CR, non CR, percentages of resolved call and call backs. From the result, we observed that the higher the resolved calls the lower the rate of call backs and vice versa. We also observed that out of the proportion of unresolved calls, a particular number of customers did not call back. The result from the study gave the optimal routing rule to be the Shortest Queue Routing (SQR), which proffered an enhanced call resolution rate and a very low call back rate. The implementation of the SQR as the optimal routing rule, will improve performance of call center management with respect to enhanced CR and reduced call backs.

References
  1. Aksin, Z. Armony, M. and Mehrotra. V. (2007) The modern call-centre: A multi-disciplinary perspective on operations management research. Production and Operations Management, 16(6):665–688, November–December Available at http://www.stern.nyu.edu/om/ faculty/armony/research/CallCentreSurvey.pdf.
  2. Armony .M (2005), Dynamic routing in large-scale service systems with heterogeneous servers. Queueing Systems, 51(3-4):287–329, December 2005.
  3. Brizola, N, Costa .S, Pazeto .T, and Freitas P. (2001). Planejamento de Capacidade de Call Center. In : ICIE, Flo-rianópolis
  4. Dabrowski .M. (2013), Business Intelligence In Call Centers. International Journal of Issue Computer and Information Technology (ISSN: 2279 – 0764) Volume 02–02, March 2013. www.ijcit.com
  5. Gans .N, and Zhou .Y. (2002), Managing Learning and Turnover in Employee Staffing.Operations Research, 50(6), Nov-Dec
  6. Gans, N., N. Liu, A. Mandelbaum, H. Shen, H. Ye. (2010). Service times in call centers: Agent heterogeneity and learning with Powering Applications—A Festschrift for Lawrence D. Brown, IMS Collections, Vol. 6. Institute of Mathematical Statistics, Beachwood, OH, 99–123. some operational consequences. Borrowing Strength: Theory Powering Applications—A Festschrift for Lawrence D. Brown, IMS Collections, Vol. 6. Institute of Mathematical Statistics, Beachwood, OH, 99–123.
  7. Garcia. D, Archer .T, Moradi .S, and Ghiabi .B (2012), Waiting in Vain: Managing Time and Customer Satisfaction at Call Centers. Science Research, http://dx.doi.org/10.4236/psych.2012.32030. Psychology 2012. Vol.3, No.2, 213-216 Published Online February 2012 in SciRes http://www.SciRP.org/journal/psych)
  8. Klenkei .M. (2006) Call center staffing : the complete, practical guide to workforce management. Nashville, Tenn.: Call Center School, 3. Print, 197 S. graph. Darst. 23 cm, ISBN: 0974417904, 978-0-9744179-0-5
  9. L’Ecuyer. P. (2006), Modelling and optimization problems in contact centres. Proceedings of the Third International Conference on the Quantitative Evaluation of Systems - (QEST’06), pages 145–154, 2006.
  10. Mehrotra .V, Ross .K, Ryder .G and Zhou .Y (2012), Routing to Manage Resolution and Waiting Time in Call Centers with Heterogeneous Servers. MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Vol. 14, No. 1, Winter 2012, pp. 66–81 ISSN 1523-4614 (print) . ISSN 1526-5498 (online) http://dx.doi.org/10.1287/msom.1110.0349 ©2012 INFORMS
  11. Zeithaml .Z, Parasuraman .A and Berry .L (1993) The nature and determinants of customer expectations of service. Acad. Marketing Sci., 21(1),
Index Terms

Computer Science
Information Sciences

Keywords

Call Center Call Resolution Call Backs Routing Rules Simulation