Customer-centric optimal resource reconfiguration for service outlets

How to optimally configure its service resources is always a key for the service providers to improve efficiency and quality of service. Fail to optimize service capability often causes long queues in many on-site service outlets, for example, retail stores, bank branches or government agencies. A first step to do service capability configuration is to identify and understand customer demand and preference. In previous research, these metrics are often obtained by general high-level (e.g. city level or district level) surveys which are not detailed enough for modeling specific customer experience at a given site. Further more, customer satisfaction is not considered as a key objective compared to cost and profit, which often leads to decisions that do not accommodate customer experiences adequately. A deep understanding of customer behavior will greatly help service providers achieve the commercial transformation from product-centric to customer-centric and enhance their market share and competitive strength. In this paper, we propose a customer-centric service resource reconfiguration method which identifies customer demand and preference from internal historical transaction data. Agent simulation is adopted to model the stochastic service processes and customer behavior in optimizing service resources.