Optimizing Demand and Forecasting in Supply Chain Management Using AI

Authors

  • Veer Singh Chandraul M.Tech. Scholar Bansal Institute of Science & Technology, Bhopal
  • Shyam Kumar Barode Assistant Professor Bansal Institute of Science & Technology, Bhopal

DOI:

https://doi.org/10.24113/ijoscience.v4i12.174

Abstract

This study demonstrates forecasting practices in supply chain management (SCM) at various areas, particularly Life science, Retail Chain, and FMCG. The authors depicts the scenario of forecasting practices based on secondary data and represents SCM role, demand management, collaborative coordination, etc. In addition, the study reveals the limitation and few practical solutions on forecasting to be useful in the business organization. Consequently the authors describe recommendation and proposes a model on forecasting management model. Though this paper highlights in intensive analysis, however, it unlocks further frontiers for the prospective researchers as well as practitioners in order to apply forecasting techniques.

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References

Chopra S., Meindil P. Supply Chain Management, 4th ed., Dorling Kindersley Pvt. Ltd, 2011

Dr. M. Habib, Supply Chain Management (SCM): Theory and Evolution, Intech 2011

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Haixia Sang's “A dynamic modeling simulation for supply chain management inventory service: a case study on a rental housing unit manufacturing and logistics company” Conference: the 2018 International Conference August 2018

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Published

12/10/2018

How to Cite

Chandraul, V. S., & Barode, S. K. (2018). Optimizing Demand and Forecasting in Supply Chain Management Using AI. SMART MOVES JOURNAL IJOSCIENCE, 4(12), 8–15. https://doi.org/10.24113/ijoscience.v4i12.174