College of Science

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Browsing College of Science by Author "Abba, Kafui"

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    Modelling the queue in a call centre: (a case of IT Helpdesk, Vodafone Ghana)
    (2011) Abba, Kafui
    The motivation for carrying out this research was to add to the extensive study that has gone into call centre operations. Our focus was on minimizing staffing and waiting costs, by optimizing agent utilization, at a reasonable operational performance level. We model three kinds of queues that occur in a call centre. We examined the situation where callers do not wait in a queue but are either immediately served or blocked from entering service; then the situation where callers wait in a queue and none of the callers abandon the queue before being served; and lastly the situation where provision is made for callers in the queue who abandon their calls before they are served. The question we want to answer is, how many agents (servers) are required in order to minimize staffing and waiting costs. In answering this question, we proceeded with data collection at our case study call centre, IThelpdesk, through interviewing of the agents, observation and from performance reports. From the data gathered we developed a forecast of the rate at which calls arrived at the call centre and the average handling time. We then developed a simulation method for determining the minimum number of agents required. Using the forecasts developed as input we simulated the arrival and the service rendered to the callers by varying the number of agents attending to the calls from two to five. For the different numbers we run hundred simulations each taking note of average waiting time of callers, maximum waiting, and number of callers each agent served. From the simulation results and we conclude that four (4) agents could attend to the calls instead of the six agents being used. Based on this result we recommend the use of simulation approach to compliment other tools used to determine the required number of agents to serve at a call centre in order to minimizing staffing and waiting costs.