Drei Einflußfaktoren im Incoming Call Center

1998 ◽  
pp. 24-34
Author(s):  
Brad Cleveland ◽  
Julia Mayben ◽  
Günter Greff
Keyword(s):  
Call Center ◽  
Incoming Call

Wie Incoming Call Center funktionieren

1998 ◽  
pp. 129-142
Author(s):  
Brad Cleveland ◽  
Julia Mayben ◽  
Günter Greff
Keyword(s):  
Call Center ◽  
Incoming Call

scholarly journals Two-way communication retrial queue with unreliable server and multiple types of outgoing calls

2020 ◽  
Vol 28 (1) ◽  
pp. 49-61
Author(s):  
Anatoly A. Nazarov ◽  
Svetlana V. Paul ◽  
Olga D. Lizyura
Keyword(s):  
Probability Distribution ◽  
Call Center ◽  
Poisson Point Process ◽  
Retrial Queue ◽  
Idle Time ◽  
High Rate ◽  
Exponential Distributions ◽  
Limit Condition ◽  
Different Types ◽  
Incoming Call

Retrial queue under consideration is the model of call center operator switching between input and outgoing calls. Incoming calls form a Poisson point process. Upon arrival, an incoming call occupies the server for an exponentially distributed service time if the server is idle. If the server if busy, an incoming call joins the orbit to make a delay before the next attempt to take the server. The probability distribution of the length of delay is an exponential distribution. Otherwise, the server makes outgoing calls in its idle time. There are multiple types of outgoing calls in the system. Outgoing call rates are different for each type of outgoing call. Durations of different types of outgoing calls follow distinct exponential distributions. Unsteadiness is that the server crashes after an exponentially distributed time and needs recovery. The rates of breakdowns and restorations are different and depend on server state. Our contribution is to obtain the probability distribution of the number of calls in the orbit under high rate of making outgoing calls limit condition. Based on the obtained asymptotics, we have built the approximations of the probability distribution of the number of calls in the orbit.

Two-way communication retrial queue with unreliable server and multiple types of outgoing calls

2020 ◽  
Vol 28 (1) ◽  
pp. 49-61
Author(s):  
Anatoly A. Nazarov ◽  
Svetlana V. Paul ◽  
Olga D. Lizyura
Keyword(s):  
Probability Distribution ◽  
Call Center ◽  
Poisson Point Process ◽  
Retrial Queue ◽  
Idle Time ◽  
High Rate ◽  
Exponential Distributions ◽  
Limit Condition ◽  
Different Types ◽  
Incoming Call

Retrial queue under consideration is the model of call center operator switching between input and outgoing calls. Incoming calls form a Poisson point process. Upon arrival, an incoming call occupies the server for an exponentially distributed service time if the server is idle. If the server if busy, an incoming call joins the orbit to make a delay before the next attempt to take the server. The probability distribution of the length of delay is an exponential distribution. Otherwise, the server makes outgoing calls in its idle time. There are multiple types of outgoing calls in the system. Outgoing call rates are different for each type of outgoing call. Durations of different types of outgoing calls follow distinct exponential distributions. Unsteadiness is that the server crashes after an exponentially distributed time and needs recovery. The rates of breakdowns and restorations are different and depend on server state. Our contribution is to obtain the probability distribution of the number of calls in the orbit under high rate of making outgoing calls limit condition. Based on the obtained asymptotics, we have built the approximations of the probability distribution of the number of calls in the orbit.

scholarly journals Analisis Pendistribusian Panggilan Masuk ke Call Center Telkomsel Medan

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Johana Sihol Marito Purba ◽  
Juliza Hidayati
Keyword(s):  
Performance Measurement ◽  
Call Center ◽  
Service Level ◽  
Actual Situation ◽  
June July August ◽  
Incoming Call ◽  
Minimum Number ◽  
Individual Needs ◽  
June July ◽  
Descriptive Method

Antrian panggilan yang masuk pada suatu call center merupakan hal yang sulit dihindari karena berkaitan dengan tingkat aktivitas pelanggan. Oleh karena itu, dalam hal ini diperlukan pengukuran performance call center yang dilakukan untuk mengetahui besar kinerja dari call center tersebut. Selain itu penelitian ini penting untuk menganalisis apakah pelanggan Telkomsel mendapatkan pelayanan sesuai dengan kebutuhan masing-masing, dilihat dari jumlah panggilan yang masuk ke sistem call center dan jumlah panggilan yang berhasil dilayani oleh agent call center. Tujuan dari penelitian ini adalah untuk mengendalikan ketersediaan agent call center sehingga target service level dapat terpenuhi. Penelitian ini menggunakan metode deskriptif, yaitu metode yang bertujuan mencatat, mengolah, dan nyajikan data untuk memberikan gambaran tentang keadaan yang sebenarnya tentang perusahaan beserta pelaksanaan. Data yang terkumpul dianalisa sesuai performansi call center berupa traffic harian, pencapaian service level dan menentukan jumlah agent minimum. Hasil yang didapatkan dari penelitian ini adalah pada bulan Juni, Juli, Agustus, dan November belum mencapai target Service Level (SL) sebesar 96%. Bila ditinjau dari ketersediaan agent, terdapat kelebihan agent pada Juni sebanyak 2 orang, namun dibulan berikutnya masih membutuhkan penambahan agent yaitu dibulan Juli sebanyak 13 orang, Agustus sebanyak 22 orang, September sebanyak 21 orang, Oktober sebanyak 3 orang dan November sebanyak 29 orang. Ketidakstabilan distribusi panggilan yang masuk ke call center mengharuskan managemen perusahaan untuk mengendalikan ketersediaan agent call center Telkomsel. Sedangkan dari peramalan call Offered didapatkan rata-rata jam sibuk yang terjadi yaitu sekitar pukul 19.00 20.00.   The queue of incoming calls at a call center is difficult to avoid because it relates to the level of customer activity. Therefore, in this case the call center performance measurement is needed to determine the performance of the call center. In addition, this study is important to analyze whether Telkomsel customers get services according to their individual needs, seen from the number of calls that enter the call center system and the number of calls successfully served by call center agents. The purpose of this study is to control the availability of call center agents so that service level targets can be met. This research uses descriptive method, a method that aims to record, process, and present data to provide an overview of the actual situation about the company and its implementation. The collected data is analyzed according to call center performance in the form of daily traffic, service level achievement and determine the minimum number of agents.The results obtained from this study are that in June, July, August, and November have not reached the Service Level (SL) target of 96%. When viewed from the availability of agents, there are excess agents in June as many as 2 people, but in the following month still need additional agents, namely in July as many as 13 people, August as many as 22 people, September as many as 21 people, October 3 people and November 29 people. The instability of incoming call distribution to the call center requires company management to control the availability of Telkomsel call center agents. While from Call Offered forecasting, the average rush hour that occurs is around 19.00-20.00.

Two-way communication retrial queue with unreliable server and multiple types of outgoing calls

2020 ◽  
Vol 28 (1) ◽  
pp. 49-61
Author(s):  
Anatoly A. Nazarov ◽  
Svetlana V. Paul ◽  
Olga D. Lizyura
Keyword(s):  
Probability Distribution ◽  
Call Center ◽  
Poisson Point Process ◽  
Retrial Queue ◽  
Idle Time ◽  
High Rate ◽  
Exponential Distributions ◽  
Limit Condition ◽  
Different Types ◽  
Incoming Call

Retrial queue under consideration is the model of call center operator switching between input and outgoing calls. Incoming calls form a Poisson point process. Upon arrival, an incoming call occupies the server for an exponentially distributed service time if the server is idle. If the server if busy, an incoming call joins the orbit to make a delay before the next attempt to take the server. The probability distribution of the length of delay is an exponential distribution. Otherwise, the server makes outgoing calls in its idle time. There are multiple types of outgoing calls in the system. Outgoing call rates are different for each type of outgoing call. Durations of different types of outgoing calls follow distinct exponential distributions. Unsteadiness is that the server crashes after an exponentially distributed time and needs recovery. The rates of breakdowns and restorations are different and depend on server state. Our contribution is to obtain the probability distribution of the number of calls in the orbit under high rate of making outgoing calls limit condition. Based on the obtained asymptotics, we have built the approximations of the probability distribution of the number of calls in the orbit.

Sign in / Sign up

Export Citation Format

Share Document