Digital management model for attendance and shifts to improve operational efficiency in gastronomic micro-enterprises

Abstract

Human resource management in micro-enterprises in the food service industry suffers from operational deficiencies due to the use of manual processes for attendance tracking, shift scheduling, and payroll calculations. This leads to administrative errors, delays, and limited decision-making. To address this problem, this study aims to propose and validate a conceptual model for digital attendance and shift management designed to improve operational efficiency. The research adopted a quantitative approach with a pre-experimental pretest-posttest design. The model was developed following the Rational Unified Process (RUP) and modeled using UML diagrams, integrating technological and process components. To evaluate its impact, indicators related to shift incidents, attendance records, and payroll calculation errors were used. Since the data did not follow a normal distribution, the Wilcoxon signed-rank test was applied with a significance level of 0.05. The results showed statistically significant operational improvements after the model's implementation, reflected in a reduction of administrative incidents, optimized operating time, and increased record accuracy. It is concluded that the proposed model constitutes a viable and replicable alternative for digitizing attendance and shift management in small food service businesses.