QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER

Hakan Öztürk; Naci Murat; Sermin Elevli

QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER

Abstract

As a first contact point of a company with customers, call centers are important to keep customers happy and satisfied. There are key performance metrics and other minimum requirements that a Call Center has to meet. In order to improve service quality, performance metrics are monitored by routine daily calls. In this study, the performance metrics of an inbound hospital call center located in Samsun were studied to measure and understand the variability in performance metrics. The control charts were used to detect assignable causes of variability in average speed of answer, abandonment rate and service level so that necessary precautions can be taken to improve process. Since autocorrelation was recognized in data, Autoregressive Integrated Moving Average (ARIMA) model was used to model correlative structure and then control chart were applied to the independent and identically distributed stream of residuals. ARIMA (6,1,1) for all performance metrics was determined as the best time series model to eliminate autocorrelation. The results showed that the call center process was not under statistical control and sources of variability should be investigated and eliminated.

Keywords

References

[1] Koole, G. and A. Mandelbaum, Queueing models of call centers: An introduction. Annals of Operations Research, 2002. 113(1-4): p. 41-59.
[2] Lin, Y.-H., et al., Perceived job stress and health complaints at a bank call center: comparison between inbound and outbound services. Industrial health, 2010. 48(3): p. 349-356.
[3] Rod, M. and N.J. Ashill, The impact of call centre stressors on inbound and outbound call-centre agent burnout. Managing Service Quality: An International Journal, 2013. 23(3): p. 245-264.
[4] Montgomery, D.C., Introduction to statistical quality control. 2009: John Wiley & Sons (New York).
[5] Evensen, A., F.X. Frei, and P.T. Harker, Effective call center management: Evidence from financial services. 1999: Division of Research, Harvard Business School.
[6] Staples, W., J. Dalrymple, and R. Bryar. Assessing call centre quality using the SERVQUAL model. in 7th International Conference on ISO. 2002. Citeseer.
[7] Dawson, K., The state of the call center industry-our annual overview of key trends the contact center professional needs to follow. Call Center Mag, 2006. 19(9): p. 24.
[8] Jaiswal, A.K., Customer satisfaction and service quality measurement in Indian call centres. Managing Service Quality: An International Journal, 2008. 18(4): p. 405-416.

[9] Budak, E.E., Analysis of a hospital call center. 2012, Bilkent University.
[10] Baraka, H.A., H.A. Baraka, and I.H. El-Gamily, Assessing call centers’ success: A validation of the DeLone and McLean model for information system. Egyptian Informatics Journal, 2013. 14(2): p. 99-108.
[11] Karakus, B. and G. Aydin. Call center performance evaluation using big data analytics. in Networks, Computers and Communications (ISNCC), 2016 International Symposium on. 2016. IEEE.
[12] Klungle, R. Simulation of a claims call center: a success and a failure. in Simulation Conference Proceedings, 1999 Winter. 1999. IEEE.
[13] Klungle, R. and J. Maluchnik. The role of simulation in call center management. in MSUG Conference. 1997.
[14] Wheeler, D.J. and D.S. Chambers, Understanding statistical process control. 1992: SPC press.
[15] Wheeler, D.J., Advanced topics in statistical process control. Vol. 470. 1995: SPC press Knoxville, TN.
[16] Young, T.M. and P.M. Winistorfer, The effects of autocorrelation on real-time statistical process control with solutions for forest products manufacturers. Forest Products Journal, 2001. 51(11/12): p. 70.
[17] Elevli, S., N. Uzgören, and M. Savas, Control charts for autocorrelated colemanite data. 2009.
[18] Noskievičová, D., Statistical analysis of the blast furnace process output parameter using ARIMA control chart with proposed methodology of control limits setting. Metalurgija, 2009. 48(4): p. 281-284.
[19] Wang, D.-S., et al. Statistical process control on autocorrelated process. in Service Systems and Service Management (ICSSSM), 2013 10th International Conference on. 2013. IEEE.
[20] Karaoglan, A.D. and G.M. Bayhan, Performance comparison of residual control charts for trend stationary first order autoregressive processes. Gazi University Journal of Science, 2011. 24(2): p. 329-339.
[21] Kandananond, K., Guidelines for Applying Statistical Quality Control Method to Monitor Autocorrelated Prcoesses. Procedia Engineering, 2014. 69: p. 1449-1458.
[22] Perzyk, M. and A. Rodziewicz, Application of Special Cause Control charts to green sand process. Archives of Foundry Engineering, 2015. 15(4): p. 55-60.
[23] Elevli, S., et al., Drinking water quality control: control charts for turbidity and pH. Journal of Water Sanitation and Hygiene for Development, 2016. 6(4): p. 511-518.
[24] Flagg, Brian J. (2013), “Using Statistical Process Control in the Call Center,” www.flaggandassociates.weebly.com, Retrieved July 17, 2018, from https://flaggandassociates.weebly.com/uploads/1/9/3/6/.../spc_in_the_call_center.pdf.
[25] Cleveland, Brad and Harne, Debbie (2003), “Call Center Metrics: Key Performance Indicators (KPIs),” www.icmi.com, Retrieved July 17, 2018, from https://www.icmi.com/files/StudentResourcePage/CCF/CCMetricsKPIs.pdf.
[26] IFC-International Finance Corporation (2018), “Measuring Call Center Performance Global Best Practices,” www.ifc.org, Retrieved July 17, 2018, from https://www.ifc.org/wps/wcm/connect/75ce96004cf85d4f8752c7f81ee631cc/Tool+9.4.+MeMeMeasu+Call+Center+Performance.pdf?MOD=AJPERES.

Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Hakan Öztürk This is me
0000-0003-0892-3013
Türkiye

Naci Murat This is me
0000-0003-2655-2367
Türkiye

Sermin Elevli This is me
0000-0002-7712-5536
Türkiye

Publication Date

December 1, 2019

Submission Date

January 18, 2019

Acceptance Date

September 13, 2019

Published in Issue

Year 2019 Volume: 37 Number: 4

IZ

https://izlik.org/JA99HN44YK

Cite

RIS / Bibtex

APA

Öztürk, H., Murat, N., & Elevli, S. (2019). QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER. Sigma Journal of Engineering and Natural Sciences, 37(4), 1396-1410. https://izlik.org/JA99HN44YK

AMA

1.Öztürk H, Murat N, Elevli S. QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER. SIGMA. 2019;37(4):1396-1410. https://izlik.org/JA99HN44YK

Chicago

Öztürk, Hakan, Naci Murat, and Sermin Elevli. 2019. “QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER”. Sigma Journal of Engineering and Natural Sciences 37 (4): 1396-1410. https://izlik.org/JA99HN44YK.

EndNote

Öztürk H, Murat N, Elevli S (December 1, 2019) QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER. Sigma Journal of Engineering and Natural Sciences 37 4 1396–1410.

IEEE

[1]H. Öztürk, N. Murat, and S. Elevli, “QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER”, SIGMA, vol. 37, no. 4, pp. 1396–1410, Dec. 2019, [Online]. Available: https://izlik.org/JA99HN44YK

ISNAD

Öztürk, Hakan - Murat, Naci - Elevli, Sermin. “QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER”. Sigma Journal of Engineering and Natural Sciences 37/4 (December 1, 2019): 1396-1410. https://izlik.org/JA99HN44YK.

JAMA

1.Öztürk H, Murat N, Elevli S. QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER. SIGMA. 2019;37:1396–1410.

MLA

Öztürk, Hakan, et al. “QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER”. Sigma Journal of Engineering and Natural Sciences, vol. 37, no. 4, Dec. 2019, pp. 1396-10, https://izlik.org/JA99HN44YK.

Vancouver

1.Hakan Öztürk, Naci Murat, Sermin Elevli. QUALITY CONTROL CHARTS FOR MONITORING PERFORMANCE OF HOSPITAL CALL CENTER. SIGMA [Internet]. 2019 Dec. 1;37(4):1396-410. Available from: https://izlik.org/JA99HN44YK