dc.creatorParedes-Torres, Franco
dc.creatorAlmeyda-Crisostomo, Genesis
dc.creatorViacava-Campos, Gino
dc.creatorAderhold, Daniel
dc.date.accessioned2021-05-18T12:21:13Z
dc.date.accessioned2024-05-07T02:04:52Z
dc.date.available2021-05-18T12:21:13Z
dc.date.available2024-05-07T02:04:52Z
dc.date.created2021-05-18T12:21:13Z
dc.date.issued2021-01-01
dc.identifier21945357
dc.identifier10.1007/978-3-030-55307-4_81
dc.identifierhttp://hdl.handle.net/10757/656030
dc.identifier21945365
dc.identifierAdvances in Intelligent Systems and Computing
dc.identifier2-s2.0-85089621625
dc.identifierSCOPUS_ID:85089621625
dc.identifier0000 0001 2196 144X
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9325063
dc.description.abstractThe 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.
dc.languageeng
dc.publisherSpringer
dc.relationhttps://www.springerprofessional.de/en/collaborative-model-to-reduce-stock-breaks-in-the-peruvian-retai/18251804
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.sourceUniversidad Peruana de Ciencias Aplicadas (UPC)
dc.sourceRepositorio Académico - UPC
dc.sourceAdvances in Intelligent Systems and Computing
dc.source1253 AISC
dc.source532
dc.source538
dc.subjectForecast
dc.subjectInventories
dc.subjectProcesses
dc.subjectRetail
dc.subjectS&OP
dc.titleCollaborative model to reduce stock breaks in the peruvian retail sector by applying the s&op methodology
dc.typeinfo:eu-repo/semantics/article


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