White Paper

The Self-Healing Supply Chain: Machine Learning in Service of Supply Chain Excellence

Supply chain perfection just got one step closer to reality

Supply chains are full of interdependent moving parts. They are modelled on static and often incorrect planning attributes resulting in chaos, poor performance and missed opportunities. Imagine if you could compare as-designed and as-demonstrated supply chain performance and automatically correct inaccurate design assumption. Now you can with the Self-Healing Supply Chain.

In his latest white paper, Kinaxis’ Self-Healing Supply Chain: Machine Learning in Service of Supply Chain Excellence, Josh Greenbaum, Principal at Enterprise Applications Consulting, explores:

  • What a Self-Healing Supply Chain is and its value to achieving supply chain excellence
  • The importance of aligning expected planning performance with what’s actually happening
  • How Self-Healing Supply Chains use machine learning to detect data discrepancies, analyze business impact, and automatically correct certain inputs

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Joshua Greenbaum, Principal, Enterprise Applications Consulting
Joshua Greenbaum is principal at Enterprise Applications Consulting. He is a seasoned IT expert, consultant and author with more than 30 years' experience in the industry. Joshua has expertise in enterprise applications, advanced technologies, software development, infrastructure, delivery and deployment technologies. He works closely with end-user organizations and major vendors helping to bridge the gaps between technology and business.

genzyme
Trinity Industries Inc.
AVAYA
Nikon
Ford
Lockheed Martin
NCR
Raytheon

Revolutionize your supply chain planning with Kinaxis RapidResponse®. Our concurrent planning capabilities connect your data, processes and people in a single platform across business functions.