Impact of Bayesian Approach to Demand Management in Supply Chains for the Consumption of Dynamic Products

• Autor: Taquía Gutiérrez, José Antonio
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Universidad de Lima
• Repositorio: ULIMA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.ulima.edu.pe:20.500.12724/18950
• Enlace del recurso: https://hdl.handle.net/20.500.12724/18950; https://doi.org/10.13053/CyS-27-2-4382
• Nivel de acceso: acceso abierto
• Materia: Supply chain management; Business logistics; Inventory control; Demand (Economic theory); Consumption (Economics); Sales forecasting; Time-series analysis; Bayesian statistical decision theory; Product life cycle; Perishable goods; https://purl.org/pe-repo/ocde/ford#2.11.04

Bayesian approach was applied to the management of the supply chain in a dynamic food product portfolio for a company in the retail sector. We propose a quasi-experimental method considering pre and posttest and a control group. The sample size of 93 products, out of a population of 120 products from two categories: classic sauces and gourmet sauces. R and Python programming languages were used and libraries for random sampling of the a priori distribution of the products to obtain posterior values area presented on the research. Forecast accuracy increased with the Bayesian approach by 10%. Likewise, it was possible to reduce the coverage inventory from 2 to 1.2 months and the discrepancy between the values of the Bayesian estimate with the traditional method was possible to reach a 5% error in the variation