OPTIMIZING SALON SERVICES: REDUCING SCHEDULING ERRORS AND WAIT TIMES THROUGH AUTOMATION

Abstract

The​‍​‌‍​‍‌ aim of this research is the use of technology to increase the efficiency of salon services by eliminating conflicts in scheduling and long waiting times for services caused by manually booking appointments. By applying Business Process Reengineering (BPR) and simulation modeling, the function of an automated appointment management system was advanced to make service flow more efficient, staff utilization more productive, and customer experience more pleasant. Information on the situation was obtained through surveys, while experiments in simulation were conducted to compare different models: the traditional process, the automated (To-Be) process, and the AI-driven generative model. Through simulation, it was visible that the automated system had brought down the average service time to 20 minutes, and the AI-based generative model had further optimized the process, thus, appointments could be completed within 10 minutes only. The ANOVA statistical testing had found that the model with the AI feature had efficiency and user satisfaction levels increased significantly. On top of that, the introduction of self-service kiosks and online booking features has made the system more adaptable and user-friendly. This study highlights that digital transformation driven by AI and process simulation is an excellent solution to the problems faced by the salon industry, which leads to improved operational efficiency, better utilization of resources, and increased customer loyalty resulting from faster, more convenient and reliable service ​‍​‌‍​‍‌delivery.