Blue Yonder drives ahead in supply chain optimisation with One takeover
Blue Yonder has moved to establish a lead in multi-enterprise supply chain optimisation capabilities, with ...
AAPL: SHIFTING PRODUCTIONUPS: GIVING UP KNIN: INDIA FOCUSXOM: ANOTHER WARNING VW: GROWING STRESSBA: OVERSUBSCRIBED AND UPSIZEDF: PRESSED ON INVENTORY TRENDSF: INVENTORY ON THE RADARF: CEO ON RECORD BA: CAPITAL RAISING EXERCISEXPO: SAIA BOOSTDSV: UPGRADEBA: ANOTHER JUMBO FUNDRAISINGXPO: SAIA READ-ACROSSHLAG: BOUYANT BUSINESS
AAPL: SHIFTING PRODUCTIONUPS: GIVING UP KNIN: INDIA FOCUSXOM: ANOTHER WARNING VW: GROWING STRESSBA: OVERSUBSCRIBED AND UPSIZEDF: PRESSED ON INVENTORY TRENDSF: INVENTORY ON THE RADARF: CEO ON RECORD BA: CAPITAL RAISING EXERCISEXPO: SAIA BOOSTDSV: UPGRADEBA: ANOTHER JUMBO FUNDRAISINGXPO: SAIA READ-ACROSSHLAG: BOUYANT BUSINESS
This piece from Tech Target analyses the emerging predictive logistics trends in the supply chain and the concept of precise ETA (expected time of arrival). While the use of real-time information to find out where goods are in a supply chain is commonplace, the insight given here is on the use of machine learning to predict and provide more accurate ETAs.
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