Business forecasting : practical problems and solutions /

Business forecasting : practical problems and solutions /

"A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Άλλοι συγγραφείς: Gilliland, Michael (Επιμελητής έκδοσης), Sglavo, Udo, 1968- (Επιμελητής έκδοσης), Tashman, Len, 1942- (Επιμελητής έκδοσης)
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Hoboken : Wiley, 2015.
Σειρά:Wiley and SAS business series.
Θέματα:
Business forecasting.
BUSINESS & ECONOMICS / Forecasting.
Electronic books.
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Machine generated contents note: ch. 1 Fundamental Considerations in Business Forecasting
  • 1.1. Getting Real about Uncertainty (Paul Goodwin)
  • 1.2. What Demand Planners Can Learn from the Stock Market (Charles K. Re Corr)
  • 1.3. Toward a More Precise Definition of Forecastability (John Boylan)
  • 1.4. Forecastability: A New Method for Benchmarking and Driving Improvement (Sean Schubert)
  • 1.5. Forecast Errors and Their Avoidability (Steve Morlidge)
  • 1.6. The Perils of Benchmarking (Michael Gilliland)
  • 1.7. Can We Obtain Valid Benchmarks from Published Surveys of Forecast Accuracy? (Stephan Kolassa)
  • 1.8. Defining "Demand" for Demand Forecasting (Michael Gilliland)
  • 1.9. Using Forecasting to Steer the Business: Six Principles (Steve Morlidge)
  • 1.10. The Beauty of Forecasting (David Orrell)
  • ch. 2 Methods of Statistical Forecasting
  • 2.1. Confessions of a Pragmatic Forecaster (Chris Chatfield)
  • 2.2. New Evidence on the Value of Combining Forecasts (Paul Goodwin)
  • 2.3. How to Forecast Data Containing Outliers (Eric Stellwagen)
  • 2.4. Selecting Your Statistical Forecasting Level (Eric Stellwagen)
  • 2.5. When Is a Flat-line Forecast Appropriate? (Eric Stellwagen)
  • 2.6. Forecasting by Time Compression (Udo Sglavo)
  • 2.7. Data Mining for Forecasting: An Introduction (Chip Wells and Tim Rey)
  • 2.8. Process and Methods for Data Mining for Forecasting (Chip Wells and Tim Rey)
  • 2.9. Worst-Case Scenarios in Forecasting: How Bad Can Things Get? (Roy Batchelor)
  • 2.10. Good Patterns, Bad Patterns (Roy Batchelor)
  • ch. 3 Forecasting Performance Evaluation and Reporting
  • 3.1. Dos and Don'ts of Forecast Accuracy Measurement: A Tutorial (Len Tashman)
  • 3.2. How to Track Forecast Accuracy to Guide Forecast Process Improvement (Jim Hoover)
  • 3.3.A "Softer" Approach to the Measurement of Forecast Accuracy (John Boylan)
  • 3.4. Measuring Forecast Accuracy (Rob Hyndman)
  • 3.5. Should We Define Forecast Error as e = F
  • A or e = A
  • F? (Kesten Green and Len Tashman)
  • 3.6. Percentage Error: What Denominator? (Kesten Green and Len Tashman)
  • 3.7. Percentage Errors Can Ruin Your Day (Stephan Kolassa and Roland Martin)
  • 3.8. Another Look at Forecast-Accuracy Metrics for Intermittent Demand (Rob Hyndman)
  • 3.9. Advantages of the MAD/Mean Ratio over the MAPE (Stephan Kolassa and Wolfgang Schutz)
  • 3.10. Use Scaled Errors Instead of Percentage Errors in Forecast Evaluations (Lauge Valentin)
  • 3.11. An Expanded Prediction-Realization Diagram for Assessing Forecast Errors (Roy Pearson)
  • 3.12. Forecast Error Measures: Critical Review and Practical Recommendations (Andrey Davydenko and Robert Fildes)
  • 3.13. Measuring the Quality of Intermittent Demand Forecasts: It's Worse than We've Thought! (Steve Morlidge)
  • 3.14. Managing Forecasts by Exception (Eric Stellwagen)
  • 3.15. Using Process Behavior Charts to Improve Forecasting and Decision Making (Martin Joseph and Alec Finney)
  • 3.16. Can Your Forecast Beat the Naive Forecast? (Shaun Snapp)
  • ch. 4 Process and Politics of Business Forecasting
  • 4.1. FVA: A Reality Check on Forecasting Practices (Michael Gilliland)
  • 4.2. Where Should the Forecasting Function Reside? (Larry Lapide)
  • 4.3. Setting Forecasting Performance Objectives (Michael Gilliland)
  • 4.4. Using Relative Error Metrics to Improve Forecast Quality in the Supply Chain (Steve Morlidge)
  • 4.5. Why Should I Trust Your Forecasts? (M. Sinan Gonul, Dilek Onkal, and Paul Goodwin)
  • 4.6. High on Complexity, Low on Evidence: Are Advanced Forecasting Methods Always as Good as They Seem? (Paul Goodwin)
  • 4.7. Should the Forecasting Process Eliminate Face-to-Face Meetings? (J. Scott Armstrong)
  • 4.8. The Impact of Sales Forecast Game Playing on Supply Chains (John Mello)
  • 4.9. Role of the Sales Force in Forecasting (Michael Gilliland)
  • 4.10. Good and Bad Judgment in Forecasting: Lessons from Four Companies (Robert Fildes and Paul Goodwin)
  • 4.11. Worst Practices in New Product Forecasting (Michael Gilliland)
  • 4.12. Sales and Operations Planning in the Retail Industry (Jack Harwell)
  • 4.13. Sales and Operations Planning: Where Is It Going? (Tom Wallace).

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