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Collaborative model to reduce stock breaks in the peruvian retail sector by applying the s&op methodology

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Authors
Paredes-Torres, Franco
Almeyda-Crisostomo, Genesis
Viacava-Campos, Gino
Aderhold, Daniel
Issue Date
2021-01-01
Keywords
Forecast
Inventories
Processes
Retail
S&OP

Metadata
Show full item record
Publisher
Springer
Journal
Advances in Intelligent Systems and Computing
URI
http://hdl.handle.net/10757/656030
DOI
https://doi.org/10.1007/978-3-030-55307-4_81
Additional Links
https://www.springerprofessional.de/en/collaborative-model-to-reduce-stock-breaks-in-the-peruvian-retai/18251804
Abstract
The retail sector is a growing industry, however with serious problems associated with inventories such as stock breakage. This article proposes a collaborative model applying the S&OP methodology to reduce stock breakages in a Peruvian company in the retail sector through a purchasing plan designed by the interaction and participation of different actors in charge of the process. The results of the model are measured by the percentage of stock breaks, the demand forecast error and the increase in sales. In the diagnosis of the problem two factors were identified that cause the stock breaks. The first is caused by the delay that exists in the replenishment of inventories, due to the bad programming of delivery of products between the distribution center and the stores. The second is related to the insufficient amount of purchases caused by not properly categorizing the products, poor forecast and not having safety inventory policies. A simulation resulted in a 17% stock breakage reduction, a 17% forecast error decrease, and a 15% sales increase.
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
Description
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
ISSN
21945357
EISSN
21945365
ae974a485f413a2113503eed53cd6c53
https://doi.org/10.1007/978-3-030-55307-4_81
Scopus Count
Collections
Ingeniería Industrial

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