Closest Thing to a Crystal Ball – Adexa ML Predictor

Adexa’s Machine Learning Predictor, GENIE^©, is designed to predict inefficiencies in the supply chain as well as identifying the main causes of late orders. The system examines millions of data variables in order to find patterns of behavior, in the past and future, that can increase cost, cause lateness or simply slow down the velocity of doing business.

In its analysis, GENIE^© examines not only the internal data but also exogenous data such as weather, season, supplier or customer locations and many others. It also combines data from other information systems such as MES and ERP in order to look for patterns that could be influencing delivery of the orders or even increasing cost, An example of the latter is the use of more expensive substitute material because of not having enough of the original one. The kind of data obtained from such systems is helpful to validate the accuracy of the supply chain model. For example, if a piece of equipment breaks down very frequently then its availability may not be the same as originally assumed. Hence GENIE^© can correct the model. Same is true for supplier delivery leadtimes. Over time they may deviate from what is assumed. By detecting the deviations a more realistic and accurate plan can be generated leading to a much better delivery performance.