Application of a CPFR (Collaborative Planning Forecasting and Replenishment) model in a pharmaceutical laboratory in the health sector
DOI:
https://doi.org/10.18041/1909-2458/ingeniare.30.7928Keywords:
Demand planning, forecasting, inventory classification, Supply chainAbstract
This article proposes to implement a methodology for the development of collaborative alliances between the pharmaceutical laboratory under study and a VIC (Very Important Customer) client of the chain channel; which seeks to reduce inventory costs and the percentage of error in projections and increase the level of service. The development of the project is divided into four phases: diagnosis, definition of key aspects and ABC multicriteria classification, preparation and conciliation of Forescast and, finally, evaluation of efficiency showing analysis of results, where it was found that the high variability of demand In the products selected in the characterization, it does not allow to define a single demand planning model and, although there are technological tools within the Laboratory to estimate the best model, they do not reach the level of detail per Client, their scope is more limited, even defining demand projections to the products it sells.
Downloads
References
Zilli, J., Volpato, D., & Vieira, A. Internacionalização de Empresas Brasileiras: O Caso de uma Exportadora de Arroz (Vol. 1). 2019.
Paulraj, A. Towards a unified theory in supply chain management: critical constructs and their effect on performance. Ph D Thesis, Cleveland State University. 2002.
Sepulveda, J. and Frein, Y. Coordination and demand uncertainty in supply chain. Production Planning and Control. Vol. 19, No. 7, pp. 712-721. 2008.
Karadayi-Usta S. Un análisis difuso estructural interpretativo para las barreras de implementación de CPFR: un caso práctico de la cadena de suministro de alimentos. Técnicas Inteligentes y Difusas en Análisis de Big Data y Toma de Decisiones. Avances en Sistemas Inteligentes y Computación, vol 1029. Springer, Cham. 2020.
Díaz Batista, J. A. & Perez Armador, D. Optimización de los niveles de inventario en una cadena de suministro. En: Ingeniería Industrial, vol. 33, No 2. pp. 126-132. 2012
Yao, Y., Kohli, R., Sherer, S. A., and Cederlund, J. Learning curves in Collaborative Planning, Forecasting, and Replenishment (CPFR) information systems: an empirical analysis from a mobile phone manufacturer. Journal of Operations Management, 31 (6), 285-297. 2013.
Danese, P. The extended VMI for coordinating the whole supply chain network. En: Journal of Manufacturing Technology Management, Vol. 17. No 7, pp. 888-907. 2006.
Singer, M. & Donoso, P. Internal supply chain management in the chilean sawmill industry. En: International Journal of Operations and Production Management. Vol. 27. No 5. pp. 524-541. 2007.
Panahifar, F., Byrne, P.J., & Heavey, C. A hybrid approach to the study of CPFR implementation enablers. Production Planning and Control, 26(13), 2015.
Cassivi, L. Collaboration planning in a supply chain. Supply Chain Management, 11(3), 249–258. 2006
Garcia Lopez, T. & Cano Flores, M. El FODA: una técnica para el análisis de problemas en el contexto de la planeación en las organizaciones, 2013
Ponce Talancón, H. “La matriz FODA: una alternativa para realizar diagnósticos y determinar estrategias de intervención en las organizaciones productivas y sociales" en Contribuciones a la Economía. 2006
Betancourt, D. F. Matriz de vester para la priorización de problemas. (30 de octubre de 2020), [en linea] de Ingenio Empresa: www.ingenioempresa.com/matriz-de-vester.
L. A. Otálora A, L. S. Murillo H, M. Á. Camacho O., E. L. Duarte F, y A. E. Ahumada P, «Evaluación de politicas de gestión de inventarios de medicamentos para un sistema multinivel y multiproducto en el hospital universitario de la samaritana (hus)», ingeniare, n.º 21, pp. 93–107, dic. 2016.
Laboratorio. Laboratorio farmacéutico. (15 mayo del 2020) [en línea] https://www.sanofi.com.co/
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Ingeniare

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.