Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
Descripción del Articulo
Pharmaceutical product trading companies generally face difficulties with inventory management due to inaccurate demand forecasts. This is the case with the company under study, which lacks an adequate demand forecasting method, as evidenced by its mean absolute percentage error (MAPE) of 25.65%, in...
Autores: | , , , |
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Formato: | artículo |
Fecha de Publicación: | 2024 |
Institución: | Universidad Peruana de Ciencias Aplicadas |
Repositorio: | UPC-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorioacademico.upc.edu.pe:10757/676310 |
Enlace del recurso: | http://hdl.handle.net/10757/676310 |
Nivel de acceso: | acceso embargado |
Materia: | ABC Classification Demand Forecasting ERP System Holt Winters |
Sumario: | Pharmaceutical product trading companies generally face difficulties with inventory management due to inaccurate demand forecasts. This is the case with the company under study, which lacks an adequate demand forecasting method, as evidenced by its mean absolute percentage error (MAPE) of 25.65%, indicating the need to improve its demand forecasting method. Given this issue, a methodological design is proposed that integrates ABC classification, aimed at segmenting products according to their economic impact, the Holt Winters forecasting method for better accuracy of demand fluctuations based on seasonality and trend; and in combination with the ERP system for integration and automation, obtaining optimal forecasts and reducing operational time. The application of the proposed design resulted in a significant reduction of MAPE to 2.60% using the Holt Winters forecasting method and in combination with the ERP system to 1.495%. These results demonstrate the effectiveness of the application of the proposed design. |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).