Alloy.ai Drives 35% YoY Forecast Accuracy Improvement at Ember
Alloy.ai’s software also helps Ember drive inventory efficiency, scale its access to retail point-of-sale data, and align internal functions around a single source of truth...
ViewThe three principles of modern demand forecasting, and the five data types needed for a best-in-class forecast
No matter what types of products you make or which technologies you use, a best-in-class forecast is based on one thing: unconstrained demand, or the amount that you would have sold if the product were always available on the shelf (physical or virtual), when and where a consumer wanted to buy it.
AI and machine learning, causal or seasonal factors, and more certainly help get you closer to a more accurate forecast, but they’re aren’t the biggest difference makers.
In The No-Nonsense Guide to Forecasting, we’ll dive into the three most important factors in building a more accurate forecasting process, including:
Alloy.ai’s software also helps Ember drive inventory efficiency, scale its access to retail point-of-sale data, and align internal functions around a single source of truth...
ViewJohn Buckley from SAP explores how COVID-19 reshaped the consumer goods landscape, the impact e-commerce had on brands and retailers, how brands can stay closer...
Keep readingNew AI features in Alloy.ai let companies predict out-of-stocks and warehouse product shortages, accurately forecast consumer demand, and discover sales and supply chain insights in...
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