Achieving Zero Waiting Time in Public Institutions with a Focus on Postal Offices Using Smart Technology ( 'Zero Wait' Application)

Abstract

Companies rely on queues as a means of managing the flow of services over long periods. Despite the introduction of queue numbers and time-based appointments to enhance service, the problem of long queues remains unresolved. Within this startup, I developed a product centered around the concept of implementing queue management technology that allows users to wait remotely via a smartphone application. The new product enables customers to utilize their waiting time more effectively and reduces the gap between service request and delivery. The research focuses on developing new technology for remote queuing and updating service characteristics. The study provides a product development strategy and analyzes results related to user experiences. This research addresses the development of the "Zero Wait" system for managing queues in public service centers using artificial intelligence technologies to predict waiting times. The system aims to improve customer experience and reduce waiting times by proposing a new approach that leverages the powerful machine learning capabilities of AI to estimate waiting times. We tested how machine learning can be used to predict the waiting time for people in queues, starting with an industrial data set of wait times in banks. By training a neural network, the results showed how an online postal service queue management system could be revolutionary. This study significantly contributes to the growing topic of digital transformation in the service sector and provides valuable insights for companies looking to enhance customer experiences while increasing operational efficiency.