Demand-driven forecasting: a structured approach to forecasting
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, New Jersey
John Wiley & Sons, Inc.
[2013]
|
| Ausgabe: | Second edition |
| Schriftenreihe: | Wiley and SAS business series
|
| Schlagworte: | |
| Online-Zugang: | TUM01 Volltext |
| Beschreibung: | Includes bibliographical references and index Demand-Driven Forecasting; Contents; Foreword; Preface; Acknowledgments; About the Author; Chapter 1 Demystifying Forecasting: Myths versus Reality; DATA COLLECTION, STORAGE, AND PROCESSING REALITY; ART-OF-FORECASTING MYTH; END-CAP DISPLAY DILEMMA; REALITY OF JUDGMENTAL OVERRIDES; OVEN CLEANER CONNECTION; MORE IS NOT NECESSARILY BETTER; REALITY OF UNCONSTRAINED FORECASTS, CONSTRAINED FORECASTS, AND PLANS; NORTHEAST REGIONAL SALES COMPOSITE FORECAST; HOLD-AND-ROLL MYTH; THE PLAN THAT WAS NOT GOOD ENOUGH; PACKAGE TO ORDER VERSUS MAKE TO ORDER; "DO YOU WANT FRIES WITH THAT?"; SUMMARY; NOTES. Chapter 2 What Is Demand-Driven Forecasting?TRANSITIONING FROM TRADITIONAL DEMAND FORECASTING; WHAT'S WRONG WITH THE DEMAND-GENERATION PICTURE?; FUNDAMENTAL FLAW WITH TRADITIONAL DEMAND GENERATION; RELYING SOLELY ON A SUPPLY-DRIVEN STRATEGY IS NOT THE SOLUTION; WHAT IS DEMAND-DRIVEN FORECASTING?; WHAT IS DEMAND SENSING AND SHAPING?; CHANGING THE DEMAND MANAGEMENT PROCESS IS ESSENTIAL; COMMUNICATION IS KEY; MEASURING DEMAND MANAGEMENT SUCCESS; BENEFITS OF A DEMAND-DRIVEN FORECASTING PROCESS; KEY STEPS TO IMPROVE THE DEMAND MANAGEMENT PROCESS. WHY HAVEN'T COMPANIES EMBRACED THE CONCEPT OF DEMAND-DRIVEN?Key Points; SUMMARY; NOTES; Chapter 3 Overview of Forecasting Methods; UNDERLYING METHODOLOGY; DIFFERENT CATEGORIES OF METHODS; HOW PREDICTABLE IS THE FUTURE?; SOME CAUSES OF FORECAST ERROR; SEGMENTING YOUR PRODUCTS TO CHOOSE THE APPROPRIATE FORECASTING METHOD; New Products Quadrant; Niche Brands Quadrant; Growth Brands Quadrant; Harvest Brands Quadrant; SUMMARY; NOTE; Chapter 4 Measuring Forecast Performance; "WE OVERACHIEVED OUR FORECAST, SO LET'S PARTY!"; PURPOSES FOR MEASURING FORECASTING PERFORMANCE. STANDARD STATISTICAL ERROR TERMSSPECIFIC MEASURES OF FORECAST ERROR; OUT-OF-SAMPLE MEASUREMENT; FORECAST VALUE ADDED; SUMMARY; NOTES; Chapter 5 Quantitative Forecasting Methods Using Time Series Data; UNDERSTANDING THE MODEL-FITTING PROCESS; INTRODUCTION TO QUANTITATIVE TIME SERIES METHODS; QUANTITATIVE TIME SERIES METHODS; MOVING AVERAGING; EXPONENTIAL SMOOTHING; SINGLE EXPONENTIAL SMOOTHING; HOLT'S TWO-PARAMETER METHOD; HOLT'S-WINTERS' METHOD; WINTERS' ADDITIVE SEASONALITY; Multiplicative versus Additive Seasonality; SUMMARY; NOTES; Chapter 6 Regression Analysis; REGRESSION METHODS. SIMPLE REGRESSIONCORRELATION COEFFICIENT; COEFFICIENT OF DETERMINATION; MULTIPLE REGRESSION; DATA VISUALIZATION USING SCATTER PLOTS AND LINE GRAPHS; CORRELATION MATRIX; MULTICOLLINEARITY; ANALYSIS OF VARIANCE; F-TEST; ADJUSTED R2; PARAMETER COEFFICIENTS; t-TEST; P-VALUES; VARIANCE INFLATION FACTOR; DURBIN-WATSON STATISTIC; INTERVENTION VARIABLES (OR DUMMY VARIABLES); REGRESSION MODEL RESULTS; KEY ACTIVITIES IN BUILDING A MULTIPLE REGRESSION MODEL; CAUTIONS ABOUT REGRESSION MODELS; SUMMARY; NOTES; Chapter 7 ARIMA Models; PHASE 1: IDENTIFYING THE TENTATIVE MODEL; Stationarity Analysis of the Autocorrelation Plots An updated new edition of the comprehensive guide to better business forecasting Many companies still look at quantitative forecasting methods with suspicion, but a new awareness is emerging across many industries as more businesses and professionals recognize the value of integrating demand data (point-of-sale and syndicated scanner data) into the forecasting process. Demand-Driven Forecasting equips you with solutions that can sense, shape, and predict future demand using highly sophisticated methods and tools. From a review of the most basic forecasting methods to the most a |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 1118691865 111873551X 1118735579 1118735641 9781118691861 9781118735510 9781118735572 9781118735640 |
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| 245 | 1 | 0 | |a Demand-driven forecasting |b a structured approach to forecasting |c Charles W. Chase, Jr |
| 250 | |a Second edition | ||
| 264 | 1 | |a Hoboken, New Jersey |b John Wiley & Sons, Inc. |c [2013] | |
| 300 | |a 1 Online-Ressource | ||
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| 490 | 0 | |a Wiley and SAS business series | |
| 500 | |a Includes bibliographical references and index | ||
| 500 | |a Demand-Driven Forecasting; Contents; Foreword; Preface; Acknowledgments; About the Author; Chapter 1 Demystifying Forecasting: Myths versus Reality; DATA COLLECTION, STORAGE, AND PROCESSING REALITY; ART-OF-FORECASTING MYTH; END-CAP DISPLAY DILEMMA; REALITY OF JUDGMENTAL OVERRIDES; OVEN CLEANER CONNECTION; MORE IS NOT NECESSARILY BETTER; REALITY OF UNCONSTRAINED FORECASTS, CONSTRAINED FORECASTS, AND PLANS; NORTHEAST REGIONAL SALES COMPOSITE FORECAST; HOLD-AND-ROLL MYTH; THE PLAN THAT WAS NOT GOOD ENOUGH; PACKAGE TO ORDER VERSUS MAKE TO ORDER; "DO YOU WANT FRIES WITH THAT?"; SUMMARY; NOTES. | ||
| 500 | |a Chapter 2 What Is Demand-Driven Forecasting?TRANSITIONING FROM TRADITIONAL DEMAND FORECASTING; WHAT'S WRONG WITH THE DEMAND-GENERATION PICTURE?; FUNDAMENTAL FLAW WITH TRADITIONAL DEMAND GENERATION; RELYING SOLELY ON A SUPPLY-DRIVEN STRATEGY IS NOT THE SOLUTION; WHAT IS DEMAND-DRIVEN FORECASTING?; WHAT IS DEMAND SENSING AND SHAPING?; CHANGING THE DEMAND MANAGEMENT PROCESS IS ESSENTIAL; COMMUNICATION IS KEY; MEASURING DEMAND MANAGEMENT SUCCESS; BENEFITS OF A DEMAND-DRIVEN FORECASTING PROCESS; KEY STEPS TO IMPROVE THE DEMAND MANAGEMENT PROCESS. | ||
| 500 | |a WHY HAVEN'T COMPANIES EMBRACED THE CONCEPT OF DEMAND-DRIVEN?Key Points; SUMMARY; NOTES; Chapter 3 Overview of Forecasting Methods; UNDERLYING METHODOLOGY; DIFFERENT CATEGORIES OF METHODS; HOW PREDICTABLE IS THE FUTURE?; SOME CAUSES OF FORECAST ERROR; SEGMENTING YOUR PRODUCTS TO CHOOSE THE APPROPRIATE FORECASTING METHOD; New Products Quadrant; Niche Brands Quadrant; Growth Brands Quadrant; Harvest Brands Quadrant; SUMMARY; NOTE; Chapter 4 Measuring Forecast Performance; "WE OVERACHIEVED OUR FORECAST, SO LET'S PARTY!"; PURPOSES FOR MEASURING FORECASTING PERFORMANCE. | ||
| 500 | |a STANDARD STATISTICAL ERROR TERMSSPECIFIC MEASURES OF FORECAST ERROR; OUT-OF-SAMPLE MEASUREMENT; FORECAST VALUE ADDED; SUMMARY; NOTES; Chapter 5 Quantitative Forecasting Methods Using Time Series Data; UNDERSTANDING THE MODEL-FITTING PROCESS; INTRODUCTION TO QUANTITATIVE TIME SERIES METHODS; QUANTITATIVE TIME SERIES METHODS; MOVING AVERAGING; EXPONENTIAL SMOOTHING; SINGLE EXPONENTIAL SMOOTHING; HOLT'S TWO-PARAMETER METHOD; HOLT'S-WINTERS' METHOD; WINTERS' ADDITIVE SEASONALITY; Multiplicative versus Additive Seasonality; SUMMARY; NOTES; Chapter 6 Regression Analysis; REGRESSION METHODS. | ||
| 500 | |a SIMPLE REGRESSIONCORRELATION COEFFICIENT; COEFFICIENT OF DETERMINATION; MULTIPLE REGRESSION; DATA VISUALIZATION USING SCATTER PLOTS AND LINE GRAPHS; CORRELATION MATRIX; MULTICOLLINEARITY; ANALYSIS OF VARIANCE; F-TEST; ADJUSTED R2; PARAMETER COEFFICIENTS; t-TEST; P-VALUES; VARIANCE INFLATION FACTOR; DURBIN-WATSON STATISTIC; INTERVENTION VARIABLES (OR DUMMY VARIABLES); REGRESSION MODEL RESULTS; KEY ACTIVITIES IN BUILDING A MULTIPLE REGRESSION MODEL; CAUTIONS ABOUT REGRESSION MODELS; SUMMARY; NOTES; Chapter 7 ARIMA Models; PHASE 1: IDENTIFYING THE TENTATIVE MODEL; Stationarity | ||
| 500 | |a Analysis of the Autocorrelation Plots | ||
| 500 | |a An updated new edition of the comprehensive guide to better business forecasting Many companies still look at quantitative forecasting methods with suspicion, but a new awareness is emerging across many industries as more businesses and professionals recognize the value of integrating demand data (point-of-sale and syndicated scanner data) into the forecasting process. Demand-Driven Forecasting equips you with solutions that can sense, shape, and predict future demand using highly sophisticated methods and tools. From a review of the most basic forecasting methods to the most a | ||
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Datensatz im Suchindex
| _version_ | 1804174956268879872 |
|---|---|
| any_adam_object | |
| author | Chase, Charles W. |
| author_GND | (DE-588)138942536 |
| author_facet | Chase, Charles W. |
| author_role | aut |
| author_sort | Chase, Charles W. |
| author_variant | c w c cw cwc |
| building | Verbundindex |
| bvnumber | BV042742553 |
| classification_rvk | QH 237 |
| collection | ZDB-4-NLEBK |
| ctrlnum | (OCoLC)841518549 (DE-599)BVBBV042742553 |
| dewey-full | 330.01/12 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 330 - Economics |
| dewey-raw | 330.01/12 |
| dewey-search | 330.01/12 |
| dewey-sort | 3330.01 212 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| edition | Second edition |
| format | Electronic eBook |
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| id | DE-604.BV042742553 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:08:38Z |
| institution | BVB |
| isbn | 1118691865 111873551X 1118735579 1118735641 9781118691861 9781118735510 9781118735572 9781118735640 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028173424 |
| oclc_num | 841518549 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM |
| owner_facet | DE-91 DE-BY-TUM |
| physical | 1 Online-Ressource |
| psigel | ZDB-4-NLEBK ZDB-4-NLEBK TUM_PDA_EBSCOBAE_gekauft |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | John Wiley & Sons, Inc. |
| record_format | marc |
| series2 | Wiley and SAS business series |
| spelling | Chase, Charles W. Verfasser (DE-588)138942536 aut Demand-driven forecasting a structured approach to forecasting Charles W. Chase, Jr Second edition Hoboken, New Jersey John Wiley & Sons, Inc. [2013] 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Wiley and SAS business series Includes bibliographical references and index Demand-Driven Forecasting; Contents; Foreword; Preface; Acknowledgments; About the Author; Chapter 1 Demystifying Forecasting: Myths versus Reality; DATA COLLECTION, STORAGE, AND PROCESSING REALITY; ART-OF-FORECASTING MYTH; END-CAP DISPLAY DILEMMA; REALITY OF JUDGMENTAL OVERRIDES; OVEN CLEANER CONNECTION; MORE IS NOT NECESSARILY BETTER; REALITY OF UNCONSTRAINED FORECASTS, CONSTRAINED FORECASTS, AND PLANS; NORTHEAST REGIONAL SALES COMPOSITE FORECAST; HOLD-AND-ROLL MYTH; THE PLAN THAT WAS NOT GOOD ENOUGH; PACKAGE TO ORDER VERSUS MAKE TO ORDER; "DO YOU WANT FRIES WITH THAT?"; SUMMARY; NOTES. Chapter 2 What Is Demand-Driven Forecasting?TRANSITIONING FROM TRADITIONAL DEMAND FORECASTING; WHAT'S WRONG WITH THE DEMAND-GENERATION PICTURE?; FUNDAMENTAL FLAW WITH TRADITIONAL DEMAND GENERATION; RELYING SOLELY ON A SUPPLY-DRIVEN STRATEGY IS NOT THE SOLUTION; WHAT IS DEMAND-DRIVEN FORECASTING?; WHAT IS DEMAND SENSING AND SHAPING?; CHANGING THE DEMAND MANAGEMENT PROCESS IS ESSENTIAL; COMMUNICATION IS KEY; MEASURING DEMAND MANAGEMENT SUCCESS; BENEFITS OF A DEMAND-DRIVEN FORECASTING PROCESS; KEY STEPS TO IMPROVE THE DEMAND MANAGEMENT PROCESS. WHY HAVEN'T COMPANIES EMBRACED THE CONCEPT OF DEMAND-DRIVEN?Key Points; SUMMARY; NOTES; Chapter 3 Overview of Forecasting Methods; UNDERLYING METHODOLOGY; DIFFERENT CATEGORIES OF METHODS; HOW PREDICTABLE IS THE FUTURE?; SOME CAUSES OF FORECAST ERROR; SEGMENTING YOUR PRODUCTS TO CHOOSE THE APPROPRIATE FORECASTING METHOD; New Products Quadrant; Niche Brands Quadrant; Growth Brands Quadrant; Harvest Brands Quadrant; SUMMARY; NOTE; Chapter 4 Measuring Forecast Performance; "WE OVERACHIEVED OUR FORECAST, SO LET'S PARTY!"; PURPOSES FOR MEASURING FORECASTING PERFORMANCE. STANDARD STATISTICAL ERROR TERMSSPECIFIC MEASURES OF FORECAST ERROR; OUT-OF-SAMPLE MEASUREMENT; FORECAST VALUE ADDED; SUMMARY; NOTES; Chapter 5 Quantitative Forecasting Methods Using Time Series Data; UNDERSTANDING THE MODEL-FITTING PROCESS; INTRODUCTION TO QUANTITATIVE TIME SERIES METHODS; QUANTITATIVE TIME SERIES METHODS; MOVING AVERAGING; EXPONENTIAL SMOOTHING; SINGLE EXPONENTIAL SMOOTHING; HOLT'S TWO-PARAMETER METHOD; HOLT'S-WINTERS' METHOD; WINTERS' ADDITIVE SEASONALITY; Multiplicative versus Additive Seasonality; SUMMARY; NOTES; Chapter 6 Regression Analysis; REGRESSION METHODS. SIMPLE REGRESSIONCORRELATION COEFFICIENT; COEFFICIENT OF DETERMINATION; MULTIPLE REGRESSION; DATA VISUALIZATION USING SCATTER PLOTS AND LINE GRAPHS; CORRELATION MATRIX; MULTICOLLINEARITY; ANALYSIS OF VARIANCE; F-TEST; ADJUSTED R2; PARAMETER COEFFICIENTS; t-TEST; P-VALUES; VARIANCE INFLATION FACTOR; DURBIN-WATSON STATISTIC; INTERVENTION VARIABLES (OR DUMMY VARIABLES); REGRESSION MODEL RESULTS; KEY ACTIVITIES IN BUILDING A MULTIPLE REGRESSION MODEL; CAUTIONS ABOUT REGRESSION MODELS; SUMMARY; NOTES; Chapter 7 ARIMA Models; PHASE 1: IDENTIFYING THE TENTATIVE MODEL; Stationarity Analysis of the Autocorrelation Plots An updated new edition of the comprehensive guide to better business forecasting Many companies still look at quantitative forecasting methods with suspicion, but a new awareness is emerging across many industries as more businesses and professionals recognize the value of integrating demand data (point-of-sale and syndicated scanner data) into the forecasting process. Demand-Driven Forecasting equips you with solutions that can sense, shape, and predict future demand using highly sophisticated methods and tools. From a review of the most basic forecasting methods to the most a BUSINESS & ECONOMICS / Economics / Theory bisacsh Business forecasting fast Economic forecasting fast Forecasting fast Business forecasting Economic forecasting Forecasting Wirtschaft Prognosemodell (DE-588)4125215-9 gnd rswk-swf Prognose (DE-588)4047390-9 gnd rswk-swf Nachfrageverhalten (DE-588)4200451-2 gnd rswk-swf Theorie (DE-588)4059787-8 gnd rswk-swf Nachfrageverhalten (DE-588)4200451-2 s Prognose (DE-588)4047390-9 s Theorie (DE-588)4059787-8 s 1\p DE-604 Prognosemodell (DE-588)4125215-9 s 2\p DE-604 Erscheint auch als Druck-Ausgabe, Hardcover 978-1-118-66939-6 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=609377 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Chase, Charles W. Demand-driven forecasting a structured approach to forecasting BUSINESS & ECONOMICS / Economics / Theory bisacsh Business forecasting fast Economic forecasting fast Forecasting fast Business forecasting Economic forecasting Forecasting Wirtschaft Prognosemodell (DE-588)4125215-9 gnd Prognose (DE-588)4047390-9 gnd Nachfrageverhalten (DE-588)4200451-2 gnd Theorie (DE-588)4059787-8 gnd |
| subject_GND | (DE-588)4125215-9 (DE-588)4047390-9 (DE-588)4200451-2 (DE-588)4059787-8 |
| title | Demand-driven forecasting a structured approach to forecasting |
| title_auth | Demand-driven forecasting a structured approach to forecasting |
| title_exact_search | Demand-driven forecasting a structured approach to forecasting |
| title_full | Demand-driven forecasting a structured approach to forecasting Charles W. Chase, Jr |
| title_fullStr | Demand-driven forecasting a structured approach to forecasting Charles W. Chase, Jr |
| title_full_unstemmed | Demand-driven forecasting a structured approach to forecasting Charles W. Chase, Jr |
| title_short | Demand-driven forecasting |
| title_sort | demand driven forecasting a structured approach to forecasting |
| title_sub | a structured approach to forecasting |
| topic | BUSINESS & ECONOMICS / Economics / Theory bisacsh Business forecasting fast Economic forecasting fast Forecasting fast Business forecasting Economic forecasting Forecasting Wirtschaft Prognosemodell (DE-588)4125215-9 gnd Prognose (DE-588)4047390-9 gnd Nachfrageverhalten (DE-588)4200451-2 gnd Theorie (DE-588)4059787-8 gnd |
| topic_facet | BUSINESS & ECONOMICS / Economics / Theory Business forecasting Economic forecasting Forecasting Wirtschaft Prognosemodell Prognose Nachfrageverhalten Theorie |
| url | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=609377 |
| work_keys_str_mv | AT chasecharlesw demanddrivenforecastingastructuredapproachtoforecasting |