Supply chain risk mitigation through sales forecasting in a cosmetics company
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
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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Independent Journal of Management & Production |
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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|| |
_version_ |
1797220493019840512 |