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
Tag: FVA
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
Aphorism 6: The Surest Way to Get a Better Forecast is to Make the Demand Forecastable Forecast accuracy is largely dependent on volatility of demand, and demand variation is affected by our own organizational policies and practices. So an underused yet highly effective solution to the forecasting problem can be
Aphorism 3: Organizational Policies and Politics Can Have a Significant Impact on Forecasting Effectiveness We just saw how demand volatility reduces forecastability. Yet our sales, marketing, and financial incentives are usually designed to add volatility. We reward sales spikes and record weeks, rather than smooth, stable, predictable growth. The forecast
Academic Research In an approach akin to FVA analysis, Paul Goodwin and Robert Fildes published a frequently cited study of four supply chain companies and 60,000 actual forecasts.* They found that 75% of the time an analyst adjusted the statistical forecast. They were trying to figure out, like FVA does,
Typical Business Forecasting Process Let’s look at a typical business forecasting process. Historical data is fed into forecasting software which generates the "statistical" forecast. An analyst can review and override the forecast, which then goes into a more elaborate collaborative or consensus process for further adjustment. Many organizations also have
Journal of Business Forecasting columnist Larry Lapide is a longtime favorite of mine. As an industry analyst at AMR, and more recently as an MIT Research Affiliate, Larry's quarterly column is a perpetual source of guidance for the practicing business forecaster. No wonder he received IBF's 2012 Lifetime Achievement in
Last week I had the pleasure of attending (with six of my SAS colleagues) the IBF's Best Practices Forecasting Conference in Orlando. Some of the highlights: Charlie Chase and I were interviewed by Russell Goodman of SupplyChainBrain.com. The videos will be posted on SCB's website later this year. Meantime, enjoy
The SAS Business Knowledge Series now offers an online version of the "Forecast Value Added Analysis" course, taught via live web in two afternoon sessions, May 7-8. The instructor is my colleague Chip Wells, who expanded our original 1/2 day FVA workshop with new material, examples, and exercises based on his
The Institute of Business Forecasting's FVA blog series continued on March 2, with my interview of Steve Morlidge of CatchBull. Steve's research (and his articles in Foresight) have been a frequent subject of BFD blog posts over the last couple of years (e.g. The "Avoidability of Forecast Error (4 parts),