Bridging the Gap: Designing Decision-Support Tools for Small Hotel Management

Staff scheduling in small and medium-sized hotels looks simple from the outside, yet managers handle it almost entirely with spreadsheets, with no dedicated software support to speak of. Existing tools are either too costly, too complex, or built for enterprise contexts that bear little resemblance to the flexible, resource-constrained reality of an independent property. This thesis presents the requirements engineering, design, and evaluation of a prototype decision-support system built to close that gap. Following a requirements-first methodology, seven semi-structured interviews were conducted with hotel managers in northern Italy, six of which were retained and tagged into around forty candidate features, clustered into three design principles: standalone operation, eighty per cent automation with manager approval, and native support for hospitality shift patterns. These principles shaped a three-tier prototype: a React frontend, a Spring Boot backend running the Timefold constraint solver, MongoDB Atlas for persistence, and an AI-powered occupancy import module built with Spring AI and the Anthropic Claude API. The prototype generates constraint-based schedules, allows transparent manual override, and automates monthly payroll reporting. A System Usability Scale evaluation with five participants from the interview cohort yielded a mean score of seventy-eight point five, in the Good range, with four of the five participants scoring Good to Excellent.