consultancy lists ML-powered forecasting through advanced analytics among its choice methods for unlocking value in a modern supply chain .
Its research postulates that a 12 % overall increase in forecasting accuracy is possible when ML algorithms are used in conjunction with enterprise data , with brand and pack errors reduced by 66 %. This improvement can be attributed to the high volumes of historical , situational and environmental data factored together to produce a coherent report , thus allowing supply chain managers to make more informed decisions . Additionally ,
McKinsey notes that a European nonfood retailer was able to achieve a 15 % saving on operational costs by automating its warehouses , yet without incurring a reduction in service levels .
In a further examination – ‘ Most of AI ’ s business uses will be in two areas ’ Michael Chui , et al , estimated that AI could yield between US $ 3.5trn and $ 5.8trn in additional value across multiple sectors . Amongst those expected to gain the most are supply chain management and marketing and sales , which cover 66 % of the opportunity collectively ($ 1.2trn to $ 2trn potential value for supply chain ).
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