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Does Artificial Intelligence (AI) -enabled demand forecasting improve supply chain efficiency?

AI-enabled demand forecasting is still at a relatively early stage of development.

By ·

Using artificial intelligence (AI) and machine learning to improve demand forecasting is one of the most promising applications of AI for supply chains. The technology “learns” from past experience and can analyze the multitude of complex relationships and factors that influence product demand.

However, AI-enabled demand forecasting is still at a relatively early stage of development. A key question for supply chain professionals is:

How do the non-traditional methods compare in performance with established forecasting practices? And, to what extent does it affect supply chain efficiency? A thesis research project at the Malaysia Institute of Supply Chain Innovation (MISI) made such a comparison. The project affirms the value of AI in demand forecasting for certain product types, and highlights areas where more research is needed.

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Latest News

Procurement is getting its digitized act together
Improving Forecast Accuracy Through Demand Sensing
Proposed Tariffs May Have Impact on Most U.S. West Coast Ports and Supply Chains
All U.S. West Coast Ports will bear the brunt of tariffs
Think small!
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Latest Resource

8 Ways to Master Your Supply Chain Labeling
Download the following report to learn how an Enterprise Labeling Solution can help you scale and add flexibility to your current supply chain labeling process, allowing you to adapt to evolving business requirements.
All Resources
By ·

Using artificial intelligence (AI) and machine learning to improve demand forecasting is one of the most promising applications of AI for supply chains. The technology “learns” from past experience and can analyze the multitude of complex relationships and factors that influence product demand.

However, AI-enabled demand forecasting is still at a relatively early stage of development. A key question for supply chain professionals is:

How do the non-traditional methods compare in performance with established forecasting practices? And, to what extent does it affect supply chain efficiency? A thesis research project at the Malaysia Institute of Supply Chain Innovation (MISI) made such a comparison. The project affirms the value of AI in demand forecasting for certain product types, and highlights areas where more research is needed.

 


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From the November 2018
New research from APICS, Supply Chain Management Review and Loyola University Chicago finds that operating a responsible supply chain is an increasing priority. But gaps remain between practice and the goal.
2018 Warehouse/DC Operations Survey: Labor Crunch Driving Automation
Shining a light on the “black box” of transportation
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Proposed Tariffs May Have Impact on Most U.S. West Coast Ports and Supply Chains
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