Business Knowledge Series course

Presented by Michael Gilliland, author of The Business Forecasting Deal and Product Marketing Manager for SAS forecasting software, SAS; or Chip Wells, Ph.D., Manager, Analytical Education, Education Division, SAS

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.

Learn how to

• 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 should attend

Forecasters, demand planners, and business analysts in any industry, as well as managers overseeing the business forecasting function

Formats available	Standard duration
Classroom:	1.0 day
Live Web Classroom:	2 half-day session(s)

Before attending this course, you should know very basic statistical concepts like mean and standard deviation, randomness, and variability.

Introduction

• key ideas

Fundamental Issues in Business Forecasting

• introduction
• fundamental issues and worst practices in applied forecasting
• how not to excel at forecasting
• forecastability

Forecast Value Added Analysis

• what is forecast value added?
• why use FVA analysis?
• communicating the results
• FVA in industry

FVA Analysis: Practical First Steps

• first steps in implementing an FVA analysis
• volatility and forecastability assessment
• performance expectations and objectives
• reporting methods

Lean Approach to Forecasting

Bibliography

Sample SAS Code for Creating FVA Report