Supply chain challenges have grocers of all sizes reevaluating forecasting with the twin imperatives of slashing out-of-stocks and reducing food waste.  Being out of stock costs chains billions in lost revenue and negatively impacts customer experience and loyalty. Meanwhile, perishables account for 32.6% of the 10.5 million “surplus” tons grocers generate each year.

What can be done to bring confidence to ordering and to optimize store-level inventories?   What can you expect when machine learning and next-gen analytics are applied to your demand forecasts? This playbook illustrates how grocers are taking advantage of breakthrough weather-driven demand analytics to:

• Adjust inventories ahead of anticipated demand spikes to reduce out-of-stocks and improve shopper satisfaction levels
• Reduce perishable waste without hurting on-shelf availability by trimming inventories ahead of periods of lower demand
• Progress sustainability initiatives by lowering waste-related carbon emissions

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