Pengukuran Beban Kerja Operator Call Center PT. X (Third Party Administrator) Untuk Menentukan Jumlah Operator Call Center Optimal

PT.X (PT.X) merupakan leading company dalam perusahaan third party administrator (TPA). PT.X menjalankan proses bisnisnya PT.X sangat mengandalkan peran Call Center sebagai penghubung antara peserta asuransi dengan rumah sakit. Karena itu peran operator Call Center sangat penting dalam proses bisnis PT.X Thesis ini akan melakukan penelitian workload analysis untuk menghitung jumlah operator Call Center di PT.X saat ini sudah cukup, ada indikasi bahwa beban kerja operator Call Center di PT.X besar. Penelitian ini akan menggunakan metode stopwatch time study dan NASA-TLX unuk beban kerja mental. Penelitian juga akan melihat perbandingan penggunaan metode Erlang-C dan Full Time Equivalent dalam menghitung jumlah pegawai yang dibutuhkan. Dari hasil penelitian akan diketahui bahwa beban kerja fisik dan mental akan berbeda di masing-masing tim dan masuk dalam kategori berat karena jumlah operator tidak optimal. Dalam penelitian ini juga akan diketahui bahwa dalam kasus PT.X lebih metode perhitungan lebih cocok menggunakan metode FTE dibandingkan dengan menggunakan metode Erlang-C dalam menghitung jumlah operator Call Center karena jumlah operator yang kecil sehingga membuat tingkat error metode Erlang-C lebih tinggi. ============================================================================================================== PT.X (PT.X) are leading company Third Party Administrator (TPA) businesses. PT.X services product is really broad and their business processes is really complex. PT.X very depends on their Call Center operator as their connector between insurance member and the hospital. Thats why Call Center operator performance is affected their company performance. In this thesis, will be conducted a research of workload analysis to measure the workload (physical and mental) using stopwatch time study and NASA-TLX .After the workload is measured it will be the pivot for calculating the numbers of operator needed based on the workload measurement result. And in this research there will be comparison between calculating Call Center operator needed using Erlang-C and Full Time Equivalent method. From the result of this study its know that some team have different workload (phsyical and mental) than the other team because the operator is not sufficient, and the best method for calculating operator needed in this case is using Full Time Equivalent method because Erlang-C method have higher error rate in small scale call center

Proactive IT Incident Prevention: Using Data Analytics to Reduce Service Interruptions

The cost of resolving user requests for IT assistance rises annually. Researchers have demonstrated that data warehouse analytic techniques can improve service, but they have not established the benefit of using global organizational data to reduce reported IT incidents. The purpose of this quantitative, quasi-experimental study was to examine the extent to which IT staff use of organizational knowledge generated from data warehouse analytical measures reduces the number of IT incidents over a 30-day period, as reported by global users of IT within an international pharmaceutical company headquartered in Germany. Organizational learning theory was used to approach the theorized relationship between organizational knowledge and user calls received. Archival data from an internal help desk ticketing system was the source of data, with access provided by the organization under study. The population for this study was all calls logged and linked to application systems registered in a configuration database, and the sample was the top 14 application systems with the highest call volume that were under the control of infrastructure management. Based on an analysis of the data using a split-plot ANOVA (SPANOVA) of Time 1, Time 2, treatment, and nontreatment data, there was a small reduction in calls in the number of reported IT incidents in the treatment group, though the reduction was not statistically significant. Implications for positive social change include reassigning employees to other tasks, rather than continuing efforts in this area, enabling employees to support alternative initiatives to drive the development of innovative therapies benefiting patients and improving employee satisfaction

Contact Center Employee Characteristics Associated with Customer Satisfaction

The management of operations for a customer contact center (CCC) presents significant challenges. Management\u27s direction is to reduce costs through operational efficiency metrics while providing maximum customer satisfaction levels to retain customers and increase profit margins. The purpose of this correlational study was to quantify the significance of various customer service representative (CSR) characteristics including internal service quality, employee satisfaction, and employee productivity, and then to determine their predictive ability on customer satisfaction, as outlined in the service-profit chain model. The research question addressed whether a linear relationship existed between CSR characteristics and the customers\u27 satisfaction with the CSR by applying ordinary least squares regression using archival dyadic data. The data consisted of a random sample of 269 CSRs serving a large Canadian bank. Various subsets of data were analyzed via regression to help generate actionable insights. One particular model involving poor performing CSRs whose customer satisfaction was less than 75% top box proved to be statistically significant (p = .036, R-squared = .321) suggesting that poor performing CSRs contribute to a significant portion of poor customer service while high performing CSRs do not necessarily guarantee good customer service. A key variable used in this research was a CSR\u27s level of education, which was not significant. Such a finding implies that for CCC support, a less-educated labor pool may be maintained, balancing societal benefits of employment for less-educated people at a reasonable service cost to a company. These findings relate to positive social change as hiring less-educated applicants could increase their social and economic status

Performance assessment in an interactive call center workforce simulation

In this paper a new performance assessment methodology for human-in-the-loop call center systems at the level of customer-agent interactions (CAI) is proposed We develop a team-in-the-loop simulation test bed to analyze CAI-level performance of a service system using a temporal performance measure with time windows The proposed framework should allow researchers to collect and analyze individual as well as team performance at a finer granularity than current call center efforts which focus on queue-centered analysis The software framework is object-oriented and has been designed to be configurable A sample simulation study in different scenarios is illustrated to provide the usages and advantages of the proposed method with index of Interactive Service Performance.close