Inventory control model based on Big Data, EOQ, ABC and forecast to increase productivity in a hardware SME

• Autores: Quiroz-Flores, Juan Carlos, Caceres-Paitan, Darien, Avila-Nolasco, Rocio
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Universidad Peruana de Ciencias Aplicadas
• Repositorio: UPC-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorioacademico.upc.edu.pe:10757/668736
• Enlace del recurso: http://hdl.handle.net/10757/668736
• Nivel de acceso: acceso embargado
• Materia: ABC analysis; Big Data; EOQ; Increased productivity; inventory control; SMEs; Commercial sector; SMEs (Small and Medium-sized Enterprises); GDP (Gross Domestic Product); Peruvian economy; Inventory management; Hardware sector; Profitability; Inventory control model; Distribution efficiency; Simulation

Within the commercial sector, SMEs represent more than 90% of all companies; they are responsible for 50% of GDP and generate between 60% and 70% of employment worldwide, which is why they are critical in the Peruvian economy. However, through an exhaustive review of the literature and sectoral analysis, we concluded they have a high risk of failure in the short term due to various problems, such as poor inventory management. In Peru, the provisions for carrying out inventories usually have a ratio of between 1% and 1.4% of the total inventory stock; thus, SMEs belonging to the hardware sector more frequently present this problem that affects the profitability of their companies. For this reason, the need arises to design an inventory control model that increases the productivity of hardware SMEs. After the pilot implementation of the first component, an increase in distribution efficiency of 11% is achieved, and its effectiveness is supported by simulating the entire model, obtaining the same results.