Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model

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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...

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Detalles Bibliográficos
Autores: Trujillo Palacio, Lyssetess, Raymundo Palomino, Anai, Perez Paredes, Maribel, Torres Sifuentes, Carlos
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
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dc.title.es_PE.fl_str_mv Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
title Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
spellingShingle Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
Trujillo Palacio, Lyssetess
ABC Classification
Demand Forecasting
ERP System
Holt Winters
title_short Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
title_full Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
title_fullStr Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
title_full_unstemmed Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
title_sort Forecast demand in a pharmaceutical trading company using ABC classification, Holt Winters method and ERP for an efficient business model
author Trujillo Palacio, Lyssetess
author_facet Trujillo Palacio, Lyssetess
Raymundo Palomino, Anai
Perez Paredes, Maribel
Torres Sifuentes, Carlos
author_role author
author2 Raymundo Palomino, Anai
Perez Paredes, Maribel
Torres Sifuentes, Carlos
author2_role author
author
author
dc.contributor.author.fl_str_mv Trujillo Palacio, Lyssetess
Raymundo Palomino, Anai
Perez Paredes, Maribel
Torres Sifuentes, Carlos
dc.subject.es_PE.fl_str_mv ABC Classification
Demand Forecasting
ERP System
Holt Winters
topic ABC Classification
Demand Forecasting
ERP System
Holt Winters
description 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.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-11-01T21:30:58Z
dc.date.available.none.fl_str_mv 2024-11-01T21:30:58Z
dc.date.issued.fl_str_mv 2024-01-01
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.doi.none.fl_str_mv 10.18687/LACCEI2024.1.1.1755
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10757/676310
dc.identifier.eissn.none.fl_str_mv 24146390
dc.identifier.journal.es_PE.fl_str_mv Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
dc.identifier.eid.none.fl_str_mv 2-s2.0-85203836236
dc.identifier.scopusid.none.fl_str_mv SCOPUS_ID:85203836236
identifier_str_mv 10.18687/LACCEI2024.1.1.1755
24146390
Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
2-s2.0-85203836236
SCOPUS_ID:85203836236
url http://hdl.handle.net/10757/676310
dc.language.iso.es_PE.fl_str_mv eng
language eng
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eu_rights_str_mv embargoedAccess
dc.format.es_PE.fl_str_mv application/html
dc.publisher.es_PE.fl_str_mv Latin American and Caribbean Consortium of Engineering Institutions
dc.source.none.fl_str_mv reponame:UPC-Institucional
instname:Universidad Peruana de Ciencias Aplicadas
instacron:UPC
instname_str Universidad Peruana de Ciencias Aplicadas
instacron_str UPC
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dc.source.journaltitle.none.fl_str_mv Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
bitstream.url.fl_str_mv https://repositorioacademico.upc.edu.pe/bitstream/10757/676310/1/license.txt
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