Bibliographic citations
Sixce, R., Alleca, A. (2024). Implementación del ERP Odoo para optimizar el pronóstico de la demanda en la cadena de suministro de una empresa importadora y comercializadora de equipos y accesorios para GLP en el Perú [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/683410
Sixce, R., Alleca, A. Implementación del ERP Odoo para optimizar el pronóstico de la demanda en la cadena de suministro de una empresa importadora y comercializadora de equipos y accesorios para GLP en el Perú [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/683410
@misc{renati/1300407,
title = "Implementación del ERP Odoo para optimizar el pronóstico de la demanda en la cadena de suministro de una empresa importadora y comercializadora de equipos y accesorios para GLP en el Perú",
author = "Alleca Ore, Anabel Nieves",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
The purpose of this research is to demonstrate the results of the Odoo ERP in a company that imports and markets LPG equipment and instruments, which presents problems of a deficiency in the demand forecast and poor inventory management. The qualitative methodology was used in the work, since international and national backgrounds were reviewed, interviews were conducted with company personnel and experts. With the data obtained from the literary review and the interviews, three possible solutions were identified: the application of the Odoo ERP, SAP Business One, and Machine Learning. With the development of the interviews with experts, it is identified that the most viable alternative for the solution to the identified problem is the Odoo ERP system, its application would help to have more effective control in the supply management, given that there is a better monitoring and an adequate management of inventories and orders, in addition to improving the bottlenecks generated by the poor demand forecast. It was concluded that the adoption of this system helps in the integration of data, minimizing storage costs, improving product rotation, having adequate stock control and optimizing purchase orders by knowing the inventory accurately.
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