Demand-driven forecasting : a structured approach to forecasting

291 Pages·2009·10.485 MB·English

by  Charles W. Chase Jr

(continued from front fl ap) CHASE $60.00 USA / $72.00 CAN
PRAISE FOR
• Forecasting methods using causal data DEMAND-DRIVEN DEMAND-DRIVEN
• Sensing, shaping, and linking demand to
FORECASTING
supply FORECASTING
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• Combining analytics and domain knowledge
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in a structured framework A Structured Approach to Forecasting
A Structured Approach to Forecasting
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As a forecast practitioner, it’s up to you to
Many companies still view quantitative
demonstrate the value of analytics to senior-level “There are authors of advanced forecasting books who take an academic approach to explaining A
forecasting methods as a “black box”
managers. Filled with real-life examples to build forecast modeling that focuses on the construction of arcane algorithms and mathematical proof D E M A N D - D R I V E N
N or unknown approach that adds little value to
a business case for the justifi cation of demand-
that are not very useful for forecasting practitioners. Then, there are other authors who take a improving overall demand forecast accuracy.
driven forecasting, Demand-Driven Forecasting: A
D
general approach to explaining demand planning, but gloss over technical content required of Fortunately, there is a new awareness emerging
Structured Approach to Forecasting is your detailed
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blueprint to better understand this new structured modern forecasters. Neither of these approaches is well-suited for helping business forecasters S- FORECASTING across many industries of the value of integrating
approach and add signifi cant improvement to critically identify the best demand data sources, effectively apply appropriate statistical trD demand data into the demand forecasting process.
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demand forecast accuracy. forecasting methods, and properly design effi cient demand planning processes. In Demand- ctR Equipping you with solutions that can sense, shape,
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Driven Forecasting, Chase fi lls this void in the literature and provides the reader with concise r and predict demand using highly sophisticated
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CHARLES W. CHASE, JR., explanations for advanced statistical methods and credible business advice for improving ways dV methods and tools, internationally renowned
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is the Business Enablement author and thought leader Charles Chase provides
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S Institu dfoerleivcearsitningg dseomluatniodn sp laton niimngp raonvde ForO From a review of the most basic forecasting
teSAS customers’ supply chain effi ciencies. He has “Charlie Chase has given forecasters a clear, responsible approach for ending the timeless tug of ecR methods, to the most advanced time-series
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more than twenty-six years of experience in the war between the need for ‘forecast rigor’ and the call for greater inclusion of ‘client judgment.’ s methods, and innovative techniques in use today,
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consumer packaged goods industry, and is an expert By advancing the use of ‘domain knowledge’ and hypothesis testing to enrich base-case in this guide defi nes demand-driven forecasting,
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C uniquely offering a fundamental understanding
in sales forecasting, market response modeling, forecasts, he has empowered professional forecasters to step up and impact their companies’
of the quantitative methods used to sense, shape,
econometrics, and supply chain management. business results favorably and profoundly, all the while enhancing the organizational stature A
and predict demand within a structured process.
of forecasters broadly.” S
—Bob Woodard, Vice President, Global Consumer T A must-read for CEOs, CMOs, CFOs, supply
chain managers, sales managers, marketing brand
and Customer Insights, Campbell Soup Company
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managers, and demand forecasting analysts,
N
Demand-Driven Forecasting: A Structured Approach
G to Forecasting covers:
• Myths versus realities of forecasting
• Causes of forecast error
The Wiley and SAS Business Series
presents books that help senior-level • Purposes for measuring forecasting
managers with their critical performance
management decisions CHARLES W. CHASE, J .
R
(continued on back fl ap)
ISBN: 978-0-470-41502-3 4-COLOR GLOSSY
E1FTOC_1 06/15/2009 8
E1FFIRS 06/16/2009 8:21:18 Page1
Demand-Driven
Forecasting
E1FFIRS 06/16/2009 8:21:18 Page2
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The Wiley & SAS Business Series presents books that help senior-level
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E1FFIRS 06/16/2009 8:21:18 Page3
Demand-Driven
Forecasting
A Structured Approach
to Forecasting
Charles Chase
JohnWiley &Sons,Inc.
E1FFIRS 06/16/2009 8:21:18 Page4
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LibraryofCongressCataloging-in-PublicationData:
Chase,Charles.
Demand-drivenforecasting:astructuredapproachtoforecasting/CharlesChase.
p.cm.–(Wiley&SASBusinessseries)
Includesbibliographicalreferencesandindex.
ISBN978-0-470-41502-3(cloth)
1. Economicforecasting. 2. Businessforecasting. 3. Forecasting. I. Title.
HB3730.C482009
330.01012–dc22
2009015527
PrintedintheUnitedStatesofAmerica
10 9 8 7 6 5 4 3 2 1
E1FTOC_1 06/15/2009 5
&
Contents
Foreword ix
Preface xiii
Acknowledgments xvii
CHAPTER1 DemystifyingForecasting:MythsversusReality 1
DataCollection,Storage,andProcessingReality 4
‘‘ArtofForecasting’’Myth 6
End-CapDisplayDilemma 7
RealityofJudgmentalOverrides 9
OvenCleanerConnection 11
MoreIsNotNecessarilyBetter 12
RealityofUnconstrainedForecasts,Constrained
Forecasts,andPlans 14
NortheastRegionalSalesEquation 15
Hold-and-RollMyth 16
ThePlanthatWasNotGoodEnough 18
Summary 19
CHAPTER2 WhatIsDemand-DrivenForecasting? 21
‘‘DoYouWantFrieswithThat?’’ 22
DefinitionofDemand-DrivenForecasting 24
WhatIsDemandSensing? 26
DataRequirements 27
RoleofSalesandMarketing 30
WhatIsDemandShaping? 31
IntegratingDemand-DrivenForecastingintothe
ConsensusForecastingProcess 34
ImportanceofBusinessIntelligencePortals/Dashboards 37
RoleoftheFinanceDepartment 40
Demand-DrivenForecastingProcessFlowModel 41
KeyProcessParticipants 44
BenefitsofDemand-DrivenForecasting 48
Summary 49
v
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vi contents
CHAPTER3 OverviewofForecastingMethods 51
UnderlyingMethodology 53
DifferentCategoriesofMethods 57
HowPredictableIstheFuture? 61
SomeCausesofForecastError 65
SegmentingYourProductstoChoosetheAppropriate
ForecastingMethod 67
Summary 74
CHAPTER4 MeasuringForecastPerformance 77
‘‘WeOverachievedOurForecast,SoLet’sParty!’’ 79
PurposesforMeasuringForecastingPerformance 80
StandardStatisticalErrorTerms 81
SpecificMeasuresofForecastError 84
Out-of-SampleMeasurement 89
ForecastValueAdded 92
Summary 96
CHAPTER5 QuantitativeForecastingMethodsUsingTime
SeriesData 99
UnderstandingtheModel-FittingProcess 100
IntroductiontoQuantitativeTimeSeriesMethods 104
QuantitativeTimeSeriesMethods 109
MovingAveraging 110
ExponentialSmoothing 115
SingleExponentialSmoothing 116
Holt’sTwo-ParameterMethod 120
Holt’s-Winters’Method 121
Winters’AdditiveSeasonality 123
Summary 125
CHAPTER6 QuantitativeForecastingMethodsUsingCausalData 129
RegressionMethods 130
SimpleRegression 130
MultipleRegression 136
Box-JenkinsApproachtoARIMAModels 163
Box-JenkinsOverview 173
ExtendingARIMAModelstoIncludeExplanatoryVariables 174
UnobservedComponentsModels 177
Summary 184
CHAPTER7 WeightedCombinedForecastingMethods 189
WhatIsWeightedCombinedForecasting? 191
DevelopingaVarianceWeightedCombinedForecast 194
Summary 197
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contents vii
CHAPTER8 Sensing,Shaping,andLinkingDemandtoSupply:
ACaseStudyUsingMTCA 199
LinkingDemandtoSupplyUsingMulti-Tiered
CausalAnalysis 202
CaseStudy:TheCarbonatedSoftDrinkStory 205
Summary 220
Appendix8AConsumerPackagedGoodsTerminology 222
Appendix8BAdstockTransformationsfor
AdvertisingGRP/TRPs 223
CHAPTER9 StrategicValueAssessment:AssessingtheReadiness
ofYourDemandForecastingProcess 227
StrategicValueAssessmentFramework 229
StrategicValueAssessmentProcess 230
SVACaseStudy:XYZCompany 232
Summary 259
SuggestedReading 261
Index 263
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