Forecast Value Added (FVA) is the change in a forecasting performance metric (such as MAPE or bias) that can be attributed to a particular step or participant in the forecasting process. FVA analysis is used to identify those process activities that are failing to make the forecast better (or may even be making it worse). This course provides step-by-step guidelines for conducting FVA analysis to identify and eliminate the waste, inefficiency, and worst practices in your forecasting process. The result can be better forecasts, with fewer resources and less management time spent on forecasting.
- map your forecasting process
- gather, organize, and store required data
- determine the volatility and forecastability of your demand patterns
- visualize the data
- create the "comet chart" relating forecast accuracy to volatility
- analyze the data using simple methods from statistical process control
- identify worst practices and other non-value adding activities
- report FVA results
- communicate results to management
- eliminate wasted efforts and streamline your forecasting process
- set reasonable forecasting performance objectives and expectations.
Who Can Benefit
- Forecasters, demand planners, and business analysts in any industry, as well as managers overseeing the business forecasting function
- Before attending this course, you should know very basic statistical concepts like mean and standard deviation, randomness, and variability.