The 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 software will help WM Barr automatically aggregate and find insights in their retail sales data, predict new sales opportunities and respond to changes in...
Visit siteHow automation and advanced metrics you won’t get in 84.51° can help you grow your sales at Kroger and avoid inventory headaches.
Read nowAlloy.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...
View
