Practical forecasting for managers /
Material type: TextPublication details: London : New York : Arnold ; Oxford University Press, 2001Description: xvi, 296 p. : illustrationsISBN: 9780340762387 ; 0340762381Subject(s): Business forecasting | ManagementDDC classification: 658.40355 Online resources: Click here to access online | Click here to access onlineItem type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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Lending Books | Main Library Stacks | Reference | 658.40355 NAS (Browse shelf(Opens below)) | Available | 008738 | ||
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658.40352 HAL Computer models for operations management | 658.40355 DEL Forecasting principles and applications | 658.40355 MAK Forecasting : methods and applications | 658.40355 NAS Practical forecasting for managers / | 658.4036 SCO Achieving consensus : tools and techniques | 658.4038 ASS Information Management & Application in Business - Intermediate Examination | 658.4038 AXE Management information for marketing decisions |
Ch. 1. Why forecast? --
Ch. 2. Planning the forecasting task --
Ch. 3. Measuring how well forecasting goals are met. Part 1 --
Ch. 4. Data search, gathering, documentation and management --
Ch. 5. Qualitative forecasting: long-term --
Ch. 6. Semi-quantitative methods --
Ch. 7. Forecasting, Risk, and Strategic Management --
Ch. 8. Measuring how well forecasting goals are met. Part 2 --
Ch. 9. Preliminary data analysis for forecasting --
Ch. 10. The preliminary forecast: concepts and examples --
Ch. 11. A strategy for performing forecasting data analysis --
Ch. 12. Forecasting trend and season I: Multiple regression --
Ch. 13. Forecasting trend and season II: Smoothing methods --
Ch. 14. Forecasting trend and season III: Time series decomposition --
Ch. 15. ARIMA and related models for forecasting --
Ch. 16. Using ARIMA models: other issues and examples --
Ch. 17. Comparing and combining forecasts --
Ch. 18. Variations on the theme of seasonal adjustment --
Ch. 19. Mixed and extended models --
Ch. 20. Nonlinear regression modelling --
Ch. 21. Artificial neural networks --
Ch. 22. Building the forecast report.
The key emphasis of this book is on the practical application of ideas, focusing on straightforward ideas that can be understood, explained, and put into action. More advanced methods are covered, but they are treated in the general context of forecasting and are easily understood and useable. Topics of stategic interest, such as long-term and qualitative forecasting for use in planning new products and services, as well as tactical and short-term quantitiative forecasting are presented in a clear and logical style. Many small tools and tricks to ease the job of actually preparing forecasts, expecially concerning the use of computers, are included and calculations are illustrated using spreadsheet software and a statistical package that is available on the internet.
In making decisions, we all make forecasts. We may not think that we are forecasting, but our choices will be directed by our anticipation of results of our actions or omissions. This book aims to help managers improve their forecasting skills.
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