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
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.