Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study



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Background: Supply Chain partners often find themselves in rather helpless positions, unable to improve their firm’s performance and profitability because their partners although willing to share production information do not fully collaborate in tackling customer order variations as they don’t seem to appreciate the benefits of such collaboration. Methods: We use a two-player (supplier-manufacturer) System Dynamics model to study the dynamics to assess the impact and usefulness of supply chain partner collaboration on the supply chain performance measures. Results: Simulation results of supply chain metrics under varied customer order patterns viz., basecase, random normal, random uniform, random upwardtrend, and random downwardtrend under (a) basecase, (b) independent optimization by manufacturer, and (c) collaborative optimization by manufacturer and supplier, are obtained to contrast them to develop useful insights. Conclusions: Focus on obtaining improved inventory turns with optimization techniques provides some viable options to managers and makes a strong case for increased collaborative planning forecasting and replenishment (CPFR) in supply chains. Despite the differences in the inventory management practices that it was contrasted with, CPFR has proven to be beneficial in a supply chain environment for all SC partners.


© 2016 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. cc-by


CPFR, optimization, simulation modeling, supply chain performance metrics, systems dynamics


Janamanchi, B., & Burns, J.R.. 2016. Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study. Cogent Business and Management, 3(1).