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　　Therearemanybooksthatdiscussstatisticalforecastingmodeling;thisbookisnotoneofthem.Thisbookprovidesapracticalapproachforthenonstatisticalproblemsthatforecastersface.

Chapter 1: Fundamental Issues of Business Forecasting (Basic Principles, Definition of Demand, What to Forecast, What Accuracy is Required, The Naive Forecast, The Politics of Forecasting) 

Chapter 2: The Problems of Business Forecasting (Demand Volatility, Performance Measurement, Forecasting Without History) 

Chapter 3: Alternative Solutions to the Forecasting Problem (Standard Forecasting Methods, Failings of the Statistical Approach, Evangelical Forecasting, Supply Chain Engineering, Collaborative Planning, Forecasting, and Replenishment, Demand Smoothing, Proactive Collaboration, Pruning) 

Chapter 4: Forecast Value Added Analysis (The Lean Approach to Forecasting, Data Requirements, Analysis and Reporting, Presenting Results to Management, Streamlining the Process) 

Chapter 5: Worst Practices in Business Forecasting (Inappropriate Performance Goals, Overfitting Statistical Models, Handling Outliers, Gaming the Metrics, Software Selection, Forecasting When You Shouldn't, Blaming the Forecast) 

Chapter 6: The Aphorisms of Business Forecasting 

Chapter 7: Practical First Steps

　　MICHAEL GILLILAND is Product Marketing Manager at SAS Institute and has worked in consu-mer products forecasting for more than twenty years. Prior to joining SAS in 2004, Mike held forecasting management positions in the food, electronics, and apparel industries and served as a consultant. He is a frequent speaker at industry events, has published articles in Supply Chain Management Review, Journal of Business Forecasting, Foresight, and APICS magazine, and was a columnist on Worst Practices in Business Forecasting for Supply Chain Forecasting Digest. Mike holds a BA in philosophy from Michigan State University, and master's degrees in philosophy and mathematical sciences from Johns Hopkins University.

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书籍介绍

There are many books that discuss statistical forecasting modeling; this book is not one of them. This book provides a practical approach for the nonstatistical problems that forecasters face (e.g., what needs to be forecasted, how often a forecast should take place, what is volatility, and problems in business forecasting). The tentative contents is: Chapter 1: Fundamental Issues of Business Forecasting (Basic Principles, Definition of Demand, What to Forecast, What Accuracy is Required, The Naive Forecast, The Politics of Forecasting) Chapter 2: The Problems of Business Forecasting (Demand Volatility, Performance Measurement, Forecasting Without History) Chapter 3: Alternative Solutions to the Forecasting Problem (Standard Forecasting Methods, Failings of the Statistical Approach, Evangelical Forecasting, Supply Chain Engineering, Collaborative Planning, Forecasting, and Replenishment, Demand Smoothing, Proactive Collaboration, Pruning) Chapter 4: Forecast Value Added Analysis (The Lean Approach to Forecasting, Data Requirements, Analysis and Reporting, Presenting Results to Management, Streamlining the Process) Chapter 5: Worst Practices in Business Forecasting (Inappropriate Performance Goals, Overfitting Statistical Models, Handling Outliers, Gaming the Metrics, Software Selection, Forecasting When You Shouldn't, Blaming the Forecast) Chapter 6: The Aphorisms of Business Forecasting Chapter 7: Practical First Steps