Supply chain risk mitigation through sales forecasting in a cosmetics company

Detalhes bibliográficos
Autor(a) principal: Frias, Daniella
Data de Publicação: 2020
Outros Autores: Muniz, Carolina Cavour Siqueira, Vieira, Pedro Senna, Sant’anna, Dominique Souza, Reis, Augusto da Cunha
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Independent Journal of Management & Production
Texto Completo: http://www.ijmp.jor.br/index.php/ijmp/article/view/1291
Resumo: Demand forecasting has become a fundamental tool for companies' strategic planning. Represented by one of the highest growth rates in the country, the cosmetics industry faces numerous challenges in meeting the demand of consumers with a high level of service. Correctly identifying demand is critical to avoiding unnecessary extra costs for the business, such as stockout or stock over. The sales data of shampoo franchises are real values, covering the period from January 2013 to December 2018. After data organization, open-time and fixed-time time series techniques were analyzed in order to find the best forecasting technique for the type of product analyzed, i.e. the method with the smallest difference in absolute values between the actual demanded. and the estimated. The models were successfully applied, and we concluded that one of the analyzed methods could be applied in the company, because it presented smaller Mean Absolute Percentage Error.
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spelling Supply chain risk mitigation through sales forecasting in a cosmetics companyRiskMitigationSupplyDemandForecastDemand forecasting has become a fundamental tool for companies' strategic planning. Represented by one of the highest growth rates in the country, the cosmetics industry faces numerous challenges in meeting the demand of consumers with a high level of service. Correctly identifying demand is critical to avoiding unnecessary extra costs for the business, such as stockout or stock over. The sales data of shampoo franchises are real values, covering the period from January 2013 to December 2018. After data organization, open-time and fixed-time time series techniques were analyzed in order to find the best forecasting technique for the type of product analyzed, i.e. the method with the smallest difference in absolute values between the actual demanded. and the estimated. The models were successfully applied, and we concluded that one of the analyzed methods could be applied in the company, because it presented smaller Mean Absolute Percentage Error.Independent2020-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttp://www.ijmp.jor.br/index.php/ijmp/article/view/129110.14807/ijmp.v11i5.1291Independent Journal of Management & Production; Vol. 11 No. 5 (2020): Independent Journal of Management & Production (Special Edition IFLOG); 1606-16232236-269X2236-269Xreponame:Independent Journal of Management & Productioninstname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)instacron:IJM&Penghttp://www.ijmp.jor.br/index.php/ijmp/article/view/1291/1430http://www.ijmp.jor.br/index.php/ijmp/article/view/1291/1431Copyright (c) 2020 Daniella Frias, Carolina Cavour, Pedro Senna, Dominique Sant’anna, Augusto Reisinfo:eu-repo/semantics/openAccessFrias, DaniellaMuniz, Carolina Cavour SiqueiraVieira, Pedro SennaSant’anna, Dominique SouzaReis, Augusto da Cunha2020-09-01T11:10:14Zoai:www.ijmp.jor.br:article/1291Revistahttp://www.ijmp.jor.br/PUBhttp://www.ijmp.jor.br/index.php/ijmp/oaiijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||2236-269X2236-269Xopendoar:2020-09-01T11:10:14Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)false
dc.title.none.fl_str_mv Supply chain risk mitigation through sales forecasting in a cosmetics company
title Supply chain risk mitigation through sales forecasting in a cosmetics company
spellingShingle Supply chain risk mitigation through sales forecasting in a cosmetics company
Frias, Daniella
Risk
Mitigation
Supply
Demand
Forecast
title_short Supply chain risk mitigation through sales forecasting in a cosmetics company
title_full Supply chain risk mitigation through sales forecasting in a cosmetics company
title_fullStr Supply chain risk mitigation through sales forecasting in a cosmetics company
title_full_unstemmed Supply chain risk mitigation through sales forecasting in a cosmetics company
title_sort Supply chain risk mitigation through sales forecasting in a cosmetics company
author Frias, Daniella
author_facet Frias, Daniella
Muniz, Carolina Cavour Siqueira
Vieira, Pedro Senna
Sant’anna, Dominique Souza
Reis, Augusto da Cunha
author_role author
author2 Muniz, Carolina Cavour Siqueira
Vieira, Pedro Senna
Sant’anna, Dominique Souza
Reis, Augusto da Cunha
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Frias, Daniella
Muniz, Carolina Cavour Siqueira
Vieira, Pedro Senna
Sant’anna, Dominique Souza
Reis, Augusto da Cunha
dc.subject.por.fl_str_mv Risk
Mitigation
Supply
Demand
Forecast
topic Risk
Mitigation
Supply
Demand
Forecast
description Demand forecasting has become a fundamental tool for companies' strategic planning. Represented by one of the highest growth rates in the country, the cosmetics industry faces numerous challenges in meeting the demand of consumers with a high level of service. Correctly identifying demand is critical to avoiding unnecessary extra costs for the business, such as stockout or stock over. The sales data of shampoo franchises are real values, covering the period from January 2013 to December 2018. After data organization, open-time and fixed-time time series techniques were analyzed in order to find the best forecasting technique for the type of product analyzed, i.e. the method with the smallest difference in absolute values between the actual demanded. and the estimated. The models were successfully applied, and we concluded that one of the analyzed methods could be applied in the company, because it presented smaller Mean Absolute Percentage Error.
publishDate 2020
dc.date.none.fl_str_mv 2020-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.ijmp.jor.br/index.php/ijmp/article/view/1291
10.14807/ijmp.v11i5.1291
url http://www.ijmp.jor.br/index.php/ijmp/article/view/1291
identifier_str_mv 10.14807/ijmp.v11i5.1291
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.ijmp.jor.br/index.php/ijmp/article/view/1291/1430
http://www.ijmp.jor.br/index.php/ijmp/article/view/1291/1431
dc.rights.driver.fl_str_mv Copyright (c) 2020 Daniella Frias, Carolina Cavour, Pedro Senna, Dominique Sant’anna, Augusto Reis
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Daniella Frias, Carolina Cavour, Pedro Senna, Dominique Sant’anna, Augusto Reis
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Independent
publisher.none.fl_str_mv Independent
dc.source.none.fl_str_mv Independent Journal of Management & Production; Vol. 11 No. 5 (2020): Independent Journal of Management & Production (Special Edition IFLOG); 1606-1623
2236-269X
2236-269X
reponame:Independent Journal of Management & Production
instname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
instacron:IJM&P
instname_str Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
instacron_str IJM&P
institution IJM&P
reponame_str Independent Journal of Management & Production
collection Independent Journal of Management & Production
repository.name.fl_str_mv Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
repository.mail.fl_str_mv ijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||
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