Real-time Intelligence in Sustainable Restaurant Management

Abstract

Abstract: The growing field of real-time intelligence (RTI) in sustainable restaurant management addresses the imperative to enhance restaurant efficiency and sustainability through data-driven strategies. As the restaurant industry faces pressure to balance environmental impact with service quality, embracing modern technologies becomes crucial. This study aims to explore and assess the potential of RTI systems for managing reservations and predicting food demand in sustainable restaurants. The methodology involves rigorous desk-based research, drawing from reputable scholarly sources, industry reports, and credible online platforms. Findings highlight the multifaceted benefits of RTI, including data-driven optimization of labor, inventory, and green initiatives. RTI also optimizes table bookings and resource allocation, minimizing wait times and food waste for a more sustainable operation. However, data privacy concerns present challenges that demand comprehensive strategies, including privacy-by-design principles and adherence to regulatory standards. Future recommendations encompass cloud-based deployment, structural evolution, data and machine learning enhancements, and further refinements. This research contributes to advancing the integration of RTI systems to foster efficient, sustainable, and customer-centric restaurant management practices.