The Study On Scheduling Management Optimization In F Conmany

Call Center is a medium of enterprises directly facing their customers, which becoming more and more important in almost every profession and trade. Whereas in operating management of call centers, staff scheduling management is a significant measure and a primary standard on evaluating call centers operation performance. Scheduling management directly gives priority to corporate operation cost, staff comfort, customer call capture rate (CCR), indirectly related to collective service quality, staff turnover and etc. As the continuous development of call centers, a large proportion of call centers start researching on finding the superior balance among collective service level, staff comfort, and resources utilization rate, staff work-time equity, convenience and efficiency of management.This thesis based on physical operating performance of F Company, applying the qualitative and quantitative research on collective scheduling management of call centers, combined statistical prediction, linear rules of data model and human resources management theory with empirical data to consolidate and present a whole set of methodology, which contains data collection before scheduling, standards of service level, long-term/mid-term/short-term traffic forecasting, agent and trunk line forecasting, scheduling design, resources utilization and supporting mechanisms establishment after scheduling. Meanwhile, this article introduces several prediction methods according to different prediction periods while doing research on method of traffic forecasting, also compares the advantages and disadvantages of two prediction methods on agent forecasting, In the meantime, this article deeply study on supporting mechanisms after staff scheduling combined with author’s empirical experiences of call center management to guarantee the whole set of methodology are practical.The last chapter of this article verifies the data of F company’s performances have been promoted by using the whole set of methodology, which contains staff satisfaction, degree of human-fitting, scheduling equity, traffic forecasting accuracy and collective service level.