To make it easy to identify non-value adding areas, you can build a simple application using SAS® Visual Analytics software. Such an application lets you point and click your way through the organization’s forecasting hierarchy, and at each point view performance of the Naïve, Manual, Statistical, and Automated forecasts (or
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Automatic forecasting and FVA (Part 2 of 2)
Automatic forecasting and FVA (Part 1 of 2)
To properly evaluate (and improve) forecasting performance, we recommend our customers use a methodology called Forecast Value Added (FVA) analysis. FVA lets you identify forecasting process waste (activities that are failing to improve the forecast, or are even making it worse). The objective is to help the organization generate forecasts
Guest blogger Len Tashman previews Winter 2017 issue of Foresight
Preview of the Winter 2017 issue of Foresight Foresight begins the new year with our 44th issue since the journal began publishing in 2005, and in this Winter 2017 collection we’re showcasing a broad range of incisive and entertaining pieces. We’re looking at new research on the effectiveness of collaboration