OPTIMIZATION OF HOTEL AND RESTAURANT SERVICES THROUGH BUSINESS ANALYTICS: CHALLENGES AND OPPORTUNITIES

Abstract

The relevance of the topic is driven by the fact that optimization of various managerial and service processes through business analytics is becoming increasingly important due to the expanding factors that ensure improved service quality, increased efficiency, and gaining a competitive advantage in the hospitality and restaurant services sector. According to the above, the study aims to identify the challenges and opportunities for optimizing hotel and restaurant services through business analytics. The research results demonstrate that hotel and restaurant services optimization should aim to improve operational processes and managerial strategies in business, focusing on enhancing service quality, efficiently utilizing resources, and achieving competitive advantages. The conclusion is drawn that optimization of hotel and restaurant services through business analytics provides the following opportunities for business entities: improvement of service quality (by understanding the needs and preferences of customers), efficient resource management (through the rationalization of resource utilization), increased competitiveness (by creating more attractive conditions for clients compared to competitors), customer attraction and retention (by attracting new clients and retaining existing ones), enhanced profitability (through increased production efficiency, optimization of prices, and other financial management strategies), adaptation to changing market conditions (through swift responses to changes in market conditions), and ensuring consistency and standards (by establishing and adhering to service standards). Noted that the optimization of hotel and restaurant services through business analytics is associated with several problems and challenges, including: issues related to data collection and quality assurance; concerns about confidentiality and data protection; challenges related to data heterogeneity; practical implementation issues; insufficient integration of business analytics systems with existing management and other business systems; ambiguity in measuring performance; and practical challenges in implementing solutions.