Profit from your forecasting software : a best practice guide for sales forecasters /
With a focus on choice, interpretation, and judgement, this practical book goes beyond the technical manuals to help you truly grasp the more intangible skills of forecasting that lead to better accuracy. --
Clasificación: | Libro Electrónico |
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Autor principal: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Hoboken, New Jersey :
John Wiley & Sons, Inc.,
[2018]
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Colección: | Wiley & SAS business series
|
Temas: | |
Acceso en línea: | Texto completo Texto completo |
MARC
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100 | 1 | |a Goodwin, Paul, |e author. | |
245 | 1 | 0 | |a Profit from your forecasting software : |b a best practice guide for sales forecasters / |c Paul Goodwin. |
264 | 1 | |a Hoboken, New Jersey : |b John Wiley & Sons, Inc., |c [2018] | |
300 | |a 1 online resource | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
490 | 0 | |a Wiley & SAS business series | |
504 | |a Includes bibliographical references and index. | ||
505 | 0 | |a Cover; Title Page; Copyright; Contents; Acknowledgments; Prologue; Chapter 1: Profit from Accurate Forecasting; 1.1 The Importance of Demand Forecasting; 1.2 When Is a Forecast Not a Forecast?; 1.3 Ways of Presenting Forecasts; 1.3.1 Forecasts as Probability Distributions; 1.3.2 Point Forecasts; 1.3.3 Prediction Intervals; 1.4 The Advantages of Using Dedicated Demand Forecasting Software; 1.5 Getting Your Data Ready for Forecasting; 1.6 Trading-Day Adjustments; 1.7 Overview of the Rest of the Book; 1.8 Summary of Key Terms; 1.9 References. | |
505 | 8 | |a Chapter 2: How Your Software Finds Patterns in Past Demand Data2.1 Introduction; 2.2 Key Features of Sales Histories; 2.2.1 An Underlying Trend; 2.2.2 A Seasonal Pattern; 2.2.3 Noise; 2.3 Autocorrelation; 2.4 Intermittent Demand; 2.5 Outliers and Special Events; 2.6 Correlation; 2.7 Missing Values; 2.8 Wrap-Up; 2.9 Summary of Key Terms; Chapter 3: Understanding Your Software's Bias and Accuracy Measures; 3.1 Introduction; 3.2 Fitting and Forecasting; 3.2.1 Fixed-Origin Evaluations; 3.2.2 Rolling-Origin Evaluations; 3.3 Forecast Errors and Bias Measures; 3.3.1 The Mean Error (ME). | |
505 | 8 | |a 3.3.2 The Mean Percentage Error (MPE)3.4 Direct Accuracy Measures; 3.4.1 The Mean Absolute Error (MAE); 3.4.2 The Mean Squared Error (MSE); 3.5 Percentage Accuracy Measures; 3.5.1 The Mean Absolute Percentage Error (MAPE); 3.5.2 The Median Absolute Percentage Error (MDAPE); 3.5.3 The Symmetric Mean Absolute Percentage Error (SMAPE); 3.5.4 The MAD/MEAN Ratio; 3.5.5 Percentage Error Measures When There Is a Trend or Seasonal Pattern; 3.6 Relative Accuracy Measures; 3.6.1 Geometric Mean Relative Absolute Error (GMRAE); 3.6.2 The Mean Absolute Scaled Error (MASE). | |
505 | 8 | |a 3.6.3 Bayesian Information Criterion (BIC)3.7 Comparing the Different Accuracy Measures; 3.8 Exception Reporting; 3.9 Forecast Value-Added Analysis (FVA); 3.10 Wrap-Up; 3.11 Summary of Key Terms; 3.12 References; Chapter 4: Curve Fitting and Exponential Smoothing; 4.1 Introduction; 4.2 Curve Fitting; 4.2.1 Common Types of Curve; 4.2.2 Assessing How Well the Curve Fits the Sales History; 4.2.3 Strengths and Limitations of Forecasts Based on Curve Fitting; 4.3 Exponential Smoothing Methods; 4.3.1 Simple (or Single) Exponential Smoothing. | |
505 | 8 | |a 4.3.2 Exponential Smoothing When There Is a Trend: Holt's Method4.3.3 The Damped Holt's Method; 4.3.4 Holt's Method with an Exponential Trend; 4.3.5 Exponential Smoothing Where There Is a Trend and Seasonal Pattern: The Holt-Winters Method; 4.3.6 Overview of Exponential Smoothing Methods; 4.4 Forecasting Intermittent Demand; 4.5 Wrap-Up; 4.6 Summary of Key Terms; Chapter 5: Box-Jenkins ARIMA Models; 5.1 Introduction; 5.2 Stationarity; 5.3 Models of Stationary Time Series: Autoregressive Models; 5.4 Models of Stationary Time Series: Moving Average Models. | |
588 | 0 | |a Online resource; title from digital title page (viewed on May 31, 2018). | |
520 | |a With a focus on choice, interpretation, and judgement, this practical book goes beyond the technical manuals to help you truly grasp the more intangible skills of forecasting that lead to better accuracy. -- |c Edited summary from book. | ||
590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
650 | 0 | |a Sales forecasting. | |
650 | 0 | |a Sales management |x Data processing. | |
650 | 6 | |a Ventes |x Prévision. | |
650 | 6 | |a Ventes |x Gestion |x Informatique. | |
650 | 7 | |a BUSINESS & ECONOMICS |x Industrial Management. |2 bisacsh | |
650 | 7 | |a BUSINESS & ECONOMICS |x Management. |2 bisacsh | |
650 | 7 | |a BUSINESS & ECONOMICS |x Management Science. |2 bisacsh | |
650 | 7 | |a BUSINESS & ECONOMICS |x Organizational Behavior. |2 bisacsh | |
650 | 7 | |a Sales forecasting |2 fast | |
650 | 7 | |a Sales management |x Data processing |2 fast | |
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776 | 0 | 8 | |i Print version: |a Goodwin, Paul. |t Profit from your forecasting software. |d Hoboken, New Jersey : John Wiley & Sons, Inc., [2018] |z 9781119414575 |w (DLC) 2017059951 |
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