![]() The company has been using this call center simulation model for several years, and is still using it, applying modifications to reflect the changing environment. Due to the improvement of the call center business processes, it became possible to cut hiring and training costs. For example, the customer service index rose significantly due to reduced wait time, while the abandonment rate dropped down, which increased the revenue. The insights which were gained from call center simulation and optimization acted as a basis for some process improvement ideas. The AnyLogic call center simulation model represented the incorporation of calls, call center representatives and their skills, routing and abandonments in detail. The developers accounted for these pequliarities in the new model. Inability to take into account call and sales rep attributes, and attribute-based routing.Missing effects of abandonment behavior and multi-skilled call center representatives.Low granularity in terms of time and groups of people.Some of the deficiencies are listed below: However, because of deficiencies in utilized approaches, these models were neglected. These steps were aimed at improving call center overall performance and customer satisfaction rates, as well as lowering the abandonment rate.Ĭall center simulation models are quite widespread. The USAA representatives wanted to create a call center simulation model in order to optimize the headcount and the scheduling and routing of calls, by using aggregated data. USAA owns large call centers with highly complex infrastructures and sophisticated process management. ![]() This approach explains why the system will act in a certain manner and explores a wide range of outcomes.Ĭase #1: Call Center Optimization Problem Simulation modeling is used to visualize system behavior, processes inside the system, and their aftermaths, and prescribe a solution. It goes beyond analytical modeling, and combines business processes with assumptions that analysts make. USAA analysists found the answer in AnyLogic simulation modeling. Methodologies such as data-mining or machine learning do not respond to these questions. Is the business agile enough to handle sudden shifts?.What are the likely outcomes/business impacts if certain actions/decisions are considered?.Where is the breaking point/capacity limit of the business?. ![]() ![]()
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