Distribution management in a peruvian wholesale sme by minimizing product returns: a case study

• Autores: Fernandez Armas, Carlos Alonso, Vera Herrera, Luis Alonso
• Formato: tesis de grado
• Fecha de Publicación: 2024
• Institución: Universidad de Lima
• Repositorio: ULIMA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.ulima.edu.pe:20.500.12724/21886
• Enlace del recurso: https://hdl.handle.net/20.500.12724/21886
• Nivel de acceso: acceso abierto
• Materia: Devolución de mercancías; Pequeñas y medianas empresas; Cadena de suministro; Comercio al por mayor; Six sigma (Norma de control de calidad); Producción eficiente; Logística empresarial; Estudios de caso; https://purl.org/pe-repo/ocde/ford#2.11.04

Small and medium-sized companies seek to improve and innovate in all their different processes, since there is more competition, and they all seek to be leaders in the sector in which they operate. However, a problem that involves the entire distribution chain, as well as the profitability of the business, is the return of merchandise. The main objective of this research study was to propose an improvement proposal in distribution management to enhance the number of returns in a wholesale company for the traditional channel using the SMED, Lean Six Sigma and Demand Forecasting. The secondary objectives of this implementation were to analyze and understand the root causes of this problem to address it in the best possible way using diagnostic tools such as the Pareto Diagram and Value Stream Mapping. Likewise, to quantify and measure the impact of this indicator within the company through indicators and statements of economic results. These results were only possible thanks to the implementation of the tools in the company's operations through simulations using Arena and Streamline software, giving us a reduction of 2.47% of distribution time on transport routes, as well as 19% of improvement in sales revenues thanks to the decrease of product returns. Thus, to conclude in a macro study of the economic impact of the project through sensitivity analysis using the MS Excel Risk tool, which detailed a 78.2% success rate to the investment.