Business forecasting : practical problems and solutions

Intro -- Praise -- Series -- Title page -- Copyright -- Foreword -- Preface -- Chapter 1 Fundamental Considerations in Business Forecasting -- 1.1 Getting Real about Uncertainty -- 1.2 What Demand Planners Can Learn from the Stock Market -- 1.3 Toward a More Precise Definition of Forecastability -- 1.4 Forecastablity: A New Method for Benchmarking and Driving Improvement -- 1.5 Forecast Errors and Their Avoidability -- 1.6 The Perils of Benchmarking -- 1.7 Can We Obtain Valid Benchmarks from Published Surveys of Forecast Accuracy? -- 1.8 Defining "Demand" for Demand Forecasting -- 1.9 Using Forecasting to Steer the Business: Six Principles -- 1.10 The Beauty of Forecasting -- Chapter 2 Methods of Statistical Forecasting -- 2.1 Confessions of a Pragmatic Forecaster -- 2.2 New Evidence on the Value of Combining Forecasts -- 2.3 How to Forecast Data Containing Outliers -- 2.4 Selecting Your Statistical Forecasting Level -- 2.5 When Is a Flat-line Forecast Appropriate? -- 2.6 Forecasting by Time Compression -- 2.7 Data Mining for Forecasting: An Introduction -- 2.8 Process and Methods for Data Mining for Forecasting -- 2.9 Worst-Case Scenarios in Forecasting: How Bad Can Things Get? -- 2.10 Good Patterns, Bad Patterns -- Chapter 3 Forecasting Performance Evaluation and Reporting -- 3.1 Dos and Don'ts of Forecast Accuracy Measurement: A Tutorial -- 3.2 How to Track Forecast Accuracy to Guide Forecast Process Improvement -- 3.3 A "Softer" Approach to the Measurement of Forecast Accuracy -- 3.4 Measuring Forecast Accuracy -- 3.5 Should We Define Forecast Error as e = F - A or e = A - F? -- 3.6 Percentage Error: What Denominator? -- 3.7 Percentage Errors Can Ruin Your Day -- 3.8 Another Look at Forecast-Accuracy Metrics for Intermittent Demand -- 3.9 Advantages of the MAD/Mean Ratio over the MAPE.