Propuesta de un sistema de gestión de inventario en supermercado Sompopo
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Date
2025-03-01
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad Tecnológica Centroamericana UNITEC
Abstract
En este estudio de investigación se planteó un modelo de pronóstico de demanda con el fin
de mejorar la gestión de inventario en el Supermercado Sompopo. El principal objetivo era
establecer una herramienta predictiva que pudiera ayudar a optimizar los niveles de inventario y
mejorar la falta o exceso de inventario, así como reducir los niveles de desperdicio; la metodología
utilizada tiene un enfoque cuantitativo con un diseño no experimental, transaccional/ transversal y
descriptiva haciendo uso de los métodos ABC y el promedio móvil simple para analizar las
variables planteadas. Los resultados del análisis determinaron las deficiencias del pronóstico
evidenciando que un 65% de los productos presentan variaciones estacionales, afectando
principalmente a categorías como frutas, verduras y congelados; además, se evidencia una
sobreestimación del 25% en la predicción de demanda durante los meses secos y una variación del
381% en los congelados, posiblemente relacionada con fallas en la cadena de frío. Además, se
identificó un error del 32% (MAPE) en las categorías clave; un sobreabastecimiento con un stock
de seguridad de hasta 7 días en categorías como los Snacks cuando debería ser un ideal de un día
y deficiencia en el control del tiempo real, reflejando un 70% del desperdicio de frutas, que
generalmente ocurre los viernes por falta de los debidos ajustes dinámicos. Se recomendó la
implementación de un sistema de pronóstico basado en análisis de datos históricos que permitan
una sincronización en tiempo real, con la finalidad de facilitar la toma de decisiones informadas y
reducir la incidencia de errores en la gestión de pedidos.
In this research study, a demand forecasting model was proposed in order to improve inventory management at the Sompopo Supermarket. The main objective was to create a predictive tool that could help optimize inventory levels and improve the lack or excess of inventory, as well as reduce waste levels; the methodology used has a quantitative approach with a non-experimental, transactional/cross-sectional and descriptive design, making use of the ABC and simple moving average methods to analyze the variables proposed. The results of the analysis determined the deficiencies of the forecast, showing that 65% of the products present seasonal variations, mainly affecting categories such as fruits, vegetables and frozen products; in addition, there is an overestimation of 25% in the demand prediction during dry months and a variation of 381% in frozen products, possibly related to failures in the cold chain. In addition, a 32% error (MAPE) was identified in key categories; an oversupply with a safety stock of up to 7 days in categories such as Snacks when it should be an ideal of one day and deficiency in the control of real time, reflecting 70% of fruit wastage, which generally occurs on Fridays due to lack of proper dynamic adjustments. It was recommended the implementation of a forecasting system based on historical data analysis that allows real-time synchronization, in order to facilitate informed decision making and reduce the incidence of errors in order management.
In this research study, a demand forecasting model was proposed in order to improve inventory management at the Sompopo Supermarket. The main objective was to create a predictive tool that could help optimize inventory levels and improve the lack or excess of inventory, as well as reduce waste levels; the methodology used has a quantitative approach with a non-experimental, transactional/cross-sectional and descriptive design, making use of the ABC and simple moving average methods to analyze the variables proposed. The results of the analysis determined the deficiencies of the forecast, showing that 65% of the products present seasonal variations, mainly affecting categories such as fruits, vegetables and frozen products; in addition, there is an overestimation of 25% in the demand prediction during dry months and a variation of 381% in frozen products, possibly related to failures in the cold chain. In addition, a 32% error (MAPE) was identified in key categories; an oversupply with a safety stock of up to 7 days in categories such as Snacks when it should be an ideal of one day and deficiency in the control of real time, reflecting 70% of fruit wastage, which generally occurs on Fridays due to lack of proper dynamic adjustments. It was recommended the implementation of a forecasting system based on historical data analysis that allows real-time synchronization, in order to facilitate informed decision making and reduce the incidence of errors in order management.
Keywords
Demanda, Inventario, Pronóstico, Supermecado, Gestión de inventario