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Tuesday, September 24, 2019

Healing a Supply Chain with Machine Learning

Some instructive thoughts about direction.  Finding patterns in anything can be a first step to its improvement.

How machine learning can heal a supply chain   By Polly Mitchell-Guthrie

" ..... Machine learning opportunities in supply chain are abundant – improving forecast accuracy, inspection of physical assets, improved modeling for new product introductions, predictive asset maintenance, and great visibility across the collaborative supply chain network are a few. In fact, Deloitte has proclaimed that the days of “cognitive planning” are upon us, where computing advances, the maturation of machine learning, and the data available in connecting systems enable this step. They have christened it “synchronized planning,” a world in which data can constantly flow throughout the supply chain and allow organizations to far more accurately match production of supply to demand than ever before.

At my own company, Kinaxis, we use a related term, concurrent planning, to illustrate the importance of being able to plan, monitor and respond to changes across the supply chain in a single, harmonious environment. Based on the foundation of data in our in-memory database, we launched our own machine learning journey.

Our focus is to increase the efficiency of the supply chain for our customers, and when analysis of data from a major customer revealed that 53 percent of their lead times were wrong as designed, we started there.  ....  " 

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