[{"data":1,"prerenderedAt":136},["ShallowReactive",2],{"uc-kpi-forecast-accuracy-improvement":3},{"kpi":4,"question":11,"includeUnpublished":12,"indexable":8,"overall":13,"answer":39,"perUseCase":40,"useCasesTracking":132},{"id":5,"label":6,"unit":7,"higherIsBetter":8,"aggregate":8,"description":9,"howToMeasure":10},"forecast-accuracy-improvement","Forecast accuracy improvement","percent",true,"Relative reduction in forecast error, or relative improvement in forecast accuracy, against the method used before.","Forecast error (for example mean absolute percentage error) of the new model versus the previous method, on the same items, horizon and holdout period.","How much does AI improve forecast accuracy?",false,[14],{"kpi":5,"label":6,"unit":7,"aggregate":8,"higherIsBetter":8,"n":15,"nUpTo":16,"median":17,"min":18,"max":19,"byClaimant":20,"vendorOnly":12,"points":22},2,1,26.5,20,33,{"organization":16,"vendor":16,"regulator":21,"independent":21},0,[23,30,34],{"evidenceId":24,"organization":25,"value":26,"qualifier":27,"claimant":28,"grade":29,"pooled":12},"aeon-retail-ai-order-demand-forecasting","Aeon Retail",40,"up-to","organization","B",{"evidenceId":31,"organization":32,"value":19,"qualifier":33,"claimant":28,"grade":29,"pooled":8},"national-grid-eso-solar-forecast-accuracy","National Grid Electricity System Operator","exact",{"evidenceId":35,"organization":36,"value":18,"qualifier":33,"claimant":37,"grade":38,"pooled":8},"chilis-fourth-ai-labor-forecasting","Chili's Grill & Bar (Brinker International)","vendor","C",null,[41,80,110],{"useCase":42,"benchmark":76},{"slug":43,"title":44,"shortTitle":45,"definition":46,"status":47,"industries":48,"functions":50,"patterns":53,"audience":56,"autonomy":57,"adoptionStage":58,"evidenceCount":59,"publicEvidenceCount":59,"organizations":60,"bestGrade":29,"headline":69,"lastVerified":75,"indexable":8},"retail-demand-forecasting-and-replenishment","AI demand forecasting and automated replenishment for retail","Demand forecasting and replenishment","Demand forecasting and replenishment is machine learning that forecasts demand for every item in every store or fulfillment center, day by day, and turns that forecast into automatic orders. It draws on sales history, promotions, prices, weather and local events, and places store and warehouse orders within limits set by planners, who handle the exceptions.","published",[49],"retail-and-ecommerce",[51,52],"operations","analytics-and-reporting",[54,55],"prediction-and-scoring","anomaly-detection","back-office","supervised-agent","mainstream",9,[25,61,62,63,64,65,66,67,68],"Albert Heijn","Best Buy Canada","Dollar General","Morrisons","One Stop","OXXO","Philippine Seven Corporation","Walmart",{"kpi":70,"label":71,"unit":7,"n":16,"nUpTo":21,"kind":72,"value":73,"qualifier":74,"claimant":28,"organization":25,"vendorReported":12},"productivity-gain","Productivity gain","reported",50,"approximately","2026-09-27",{"kpi":5,"label":6,"unit":7,"aggregate":8,"higherIsBetter":8,"n":21,"nUpTo":16,"median":39,"min":39,"max":39,"byClaimant":77,"vendorOnly":12,"points":78},{"organization":21,"vendor":21,"regulator":21,"independent":21},[79],{"evidenceId":24,"organization":25,"value":26,"qualifier":27,"claimant":28,"grade":29,"pooled":12},{"useCase":81,"benchmark":106},{"slug":82,"title":83,"shortTitle":84,"definition":85,"status":47,"industries":86,"functions":88,"patterns":90,"audience":91,"autonomy":92,"adoptionStage":93,"segment":94,"evidenceCount":95,"publicEvidenceCount":95,"organizations":96,"bestGrade":29,"headline":101,"lastVerified":105,"indexable":8},"restaurant-demand-and-labor-forecasting","AI demand forecasting for restaurant labor and prep scheduling","Restaurant demand and labor forecasting","Restaurant demand and labor forecasting is a machine learning model that predicts sales and guest traffic per restaurant, per daypart and often per menu item, for restaurant managers. It uses point of sale history, local events and weather, so managers can build staff schedules and prep lists against a forecast instead of a manual guess or last week's numbers.",[87],"travel-and-hospitality",[51,89],"human-resources",[54],"employee-facing","copilot","early-adopters","back-of-house",5,[36,97,98,99,100],"Chipotle Mexican Grill","McDonald's Georgia","Papa Johns","Thai Leisure Group",{"kpi":102,"label":103,"unit":7,"n":16,"nUpTo":21,"kind":72,"value":104,"qualifier":33,"claimant":37,"organization":98,"vendorReported":8},"forecast-accuracy","Forecast accuracy",83,"2026-09-29",{"kpi":5,"label":6,"unit":7,"aggregate":8,"higherIsBetter":8,"n":16,"nUpTo":21,"median":18,"min":18,"max":18,"byClaimant":107,"vendorOnly":8,"points":108},{"organization":21,"vendor":16,"regulator":21,"independent":21},[109],{"evidenceId":35,"organization":36,"value":18,"qualifier":33,"claimant":37,"grade":38,"pooled":8},{"useCase":111,"benchmark":128},{"slug":112,"title":113,"shortTitle":114,"definition":115,"status":47,"industries":116,"functions":118,"patterns":119,"audience":56,"autonomy":120,"adoptionStage":93,"segment":121,"evidenceCount":122,"publicEvidenceCount":122,"organizations":123,"bestGrade":29,"headline":127,"lastVerified":105,"indexable":8},"renewable-generation-forecasting","AI forecasting of wind and solar generation for grid balancing and trading","Renewable generation forecasting","Renewable generation forecasting is AI that predicts how much power a wind or solar asset will generate over the next hours to a day ahead. It combines weather forecasts with historical turbine or panel output, so a grid operator or generator can commit to a delivery schedule instead of treating renewable output as unplannable.",[117],"energy-and-utilities",[51,52],[54],"assist","generation-and-trading",4,[124,32,125,126],"Google","Rajasthan Urja Vikas Nigam Limited (RUVNL)","Vattenfall",{"kpi":5,"label":6,"unit":7,"n":16,"nUpTo":21,"kind":72,"value":19,"qualifier":33,"claimant":28,"organization":32,"vendorReported":12},{"kpi":5,"label":6,"unit":7,"aggregate":8,"higherIsBetter":8,"n":16,"nUpTo":21,"median":19,"min":19,"max":19,"byClaimant":129,"vendorOnly":12,"points":130},{"organization":16,"vendor":21,"regulator":21,"independent":21},[131],{"evidenceId":31,"organization":32,"value":19,"qualifier":33,"claimant":28,"grade":29,"pooled":8},[133,134,135],{"slug":43,"title":44},{"slug":82,"title":83},{"slug":112,"title":113},1794503902675]