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:
A proactive strategy for retail allocation can help candy and snacks brands stay ahead of holiday out-of-stocks and buy-backs.
Keep readingLarra Haftevani from Billie talks how she thinks about planning for a retail launch, and the value of retailer-provided forecasts and doing your own forecasting...
Keep readingAlloy CEO Joel Beal spoke with CBS MoneyWatch about the causes of product shortages facing consumer goods brands.
Visit site
