Analýza nákupního chování a výkonnosti prodeje v podniku rychlého občerstvení

Bachelor’s thesis focuses on the analysis of sales and operational data in a selected fast-food restaurant. The aim of the thesis is to analyze shift operational data, identify typical operational regimes using cluster analysis, and detect potential anomalies occurring during work shifts. Based on exploratory data analysis and statistical testing, it was proven that customers at self-service kiosks spend significantly more than at traditional cash registers, and a positive correlation between longer service times and higher spending was confirmed. Using cluster analysis, shifts were successfully divided into three modes: Calm shifts, Busy shifts, and Quality sales. Anomaly detection revealed 41 specific deviations, which highlighted both hidden operational inefficiencies and exceptionally well-handled extreme workloads. The greatest practical contribution of this work lies in the application of these findings to real-world business processes. Outputs from the analytical models were transformed into an interactive dashboard, which company management uses as an objective basis for regular evaluation of employee competencies (the Crew Competency Assessment). Properly targeted feedback to employees, supported by objective data from the dashboard, thus represents an effective tool for employee motivation.