行业分析overviewonanalysis1

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1、Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-1-A Primer on AnalysisOverviewConfidential DocumentLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-2-TABLE OF CONTENTSIntroductionGeneral analytical techniquesG

2、raphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elast

3、icityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-3-LOGIC AND ANALYSIS CRITICAL TOSTRATEGY DEVELOPMENTKey to strategy development is laying out “logic” toUnderstand what makes business work-econo

4、mics-interactions across competitors, segments, time, . Conceptually organize client goalsDevise ways to achieve clients goalsHelp client “make it happen”A tightly developed piece of this logic is analysisReducing complex reality to a few salient pointsIsolating important economic elementsLeft Heade

5、rRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-4-ANALYSIS IS MORE THAN NUMBER CRUNCHINGAnalysis is. Integrating quantitative and qualitative knowledgeSeeing the bigger pictureThinking-creatively-conceptuallyNot . . .Endless calculationsLetting statistics dictate/

6、rule“Classic” scientific rigorLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-5-ANALYTICAL BIAS“Everything can be quantified”Not really, butMost “qualitative” effects are based in economics-explicit or opportunity costs-accurately quantifiable or notClie

7、nt hires us to analyze and objectifyQuantitative analysis is the basisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-6-CREATIVITY AND ANALYTICAL PERSEVERANCE AREIMPORTANT TRAITS FOR SUPERIOR ANALYSTS Strive to address a problem using different approache

8、s to test hypotheses and find inconsistenciesTriangulate on answersNever believe a data series blindlyNever stop at first obstacleClients often stop short of good analysis because they quickly surrender in the absence of good, readily available dataWe never surrender to the unavailability of dataYou

9、r case leader does not want to hear that “there is no data,” but rather what can be developed, in how much time, and at what costLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-7-WHERE THIS PRIMER FITSNo document can teach you to be a great analystAnswer

10、s look easy, but process of getting there painfulEach problem somewhat different from examplesA primer canGive flavor of expected analysesShow which analyses have been most productive historicallyExplain basic techniques and warn of common methodological errorsBest training comes fromExperience in p

11、roject team workDiscussions with John Tang and othersYou are expected to locate knowledge on your own initiativeLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-8-DONT LIMIT YOURSELF TO THESE TOOLSThey are a sample of the most commonly used toolsOthers wi

12、ll be of use in specific situationsValue management (CFROI, asset growth, etc.)Additionally, no tool can substitute for a new creative approachLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-9-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGra

13、phsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elastic

14、ityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-10-RELATIONSHIPS HAVE MOST IMPACT WHEN DISPLAYED VISUALLYGraphs and charts should be easily understandable to a “nonquantitative” clientDisplay one

15、 main idea per graphMake the point as directly as possibleDemonstrate clear relevance to accompanying material and clients businessClearly label title, axes, and sourcesTailor graph to its audience and purposeExplorationPersuasionDocumentationLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston

16、Consulting Group All rights reserved-11-CHOOSE GRAPH SCALE THOUGHTFULLYMatch chart boundaries to relevant range of the data as closely as possibleSelect scale to facilitate thinking about proposed relationshipsUse same scale across charts if you intend to compare themLeft HeaderRight HeaderShadow Bo

17、xSource: 1994 The Boston Consulting Group All rights reserved-12-LINEAR VS. LOGOn a linear scale, a given difference between two values covers the same distance anywhere on the scaleOn a logarithmic scale, a given ratio of two values covers the same distance anywhere on the scale124816One CycleLinea

18、rLogLogThe ratio of anything to zero is infinite. Zero cannot appear on a log scale.Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-13-DATA RELATIONSHIP DETERMINES SELECTION OF SCALEThree Scales Most CommonLinearLogLogLinearLinear (usually time)LogLinear

19、Semi-LogLog-LogConstant Rate of ChangeConstant Growth RateConstant “Elasticity”Given no prior expectation about the form of a relationship, plot it linearlyy = mx + blog y = mx + blog y = mlog x + bLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-14-WHEN

20、SHOULD A LINEAR GRAPH BE USED?Linear graphs are best when the change in unit terms is of interest, e.g.,Market share over timeProfit margin over timeForty-five degree downward sloping lines on linear graph represent points whose x and y values have constant sumRays through origin represent points wi

21、th common ratioMarket Share (%)Linear GraphHardwareSoftwareLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-15-WHEN SHOULD A SEMI-LOG PLOT BE USED?Semi-log graphs are generally used to illustrate constant growth rates, e.g.,Volume of sales growth over tim

22、eYearSource: Agricultural StatisticsU.S. Corn Yield (Bushels/ Acre)R=.95Semi-Log GraphLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-16-WHEN SHOULD A LOG-LOG PLOT BE USED?Log-log graphs are generally used to plot “elasticities,” e.g.,Price elasticity of

23、 demandScale slopeForty-five degree downward sloping lines show points with common productSalaried and Indirect hourly Employees/ Billion Impressions of CapacityPrinting Capacity (Billions of Impressions)78% Scale SlopeR=.6361,00010010Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulti

24、ng Group All rights reserved-17-CIRCLE OR BUBBLE CHARTS OFTEN USED TO SHOW A THIRD DIMENSIONThird dimension should be related to x and y axesCommon examples include:Market sizeAssetsCost flowCircle area (not diameter) is proportionalLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting

25、 Group All rights reserved-18-BUBBLE CHART EXAMPLECategory Growth Versus Gross Margin Versus Size1980-84Real CAGR (%)Gross Margin (%)= $1B salesConsumer ElectronicsToysHousewares/GiftsJewelrySportingGoodsSmallAppliancesCamera/PhotoSource: Discount MerchandiserLeft HeaderRight HeaderShadow BoxSource:

26、 1994 The Boston Consulting Group All rights reserved-19-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer

27、 understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-20-DEFLATORS CORRECT EFFECTS

28、OF INFLATIONConverts Variables from “Nominal” to “Real”Time series data in dollars with high or widely fluctuating inflation rates distort picture of growthDeflating data removes some of the distortionUsing a deflator index list, currency data are multiplied by the ratio of the base year deflator in

29、dex to the data year deflator index, e.g.,1979 sales (1993 $) = 1979 (1979 $) x Deflator 1993Deflator 1979Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-21-SELECT APPROPRIATE DEFLATOR DEPENDING ONTHE QUESTION YOURE TRYING TO ANSWERG.N.P. deflator is bes

30、t for expressing dollars in terms of average real value to the rest of the economyCurrent (variable) weightsMeasured quarterlyC.P.I. is best only for expressing value in relation to consumer spending on a fixed market basket of goods (1973 base)Measured monthlyIndustry or product-specific indices ar

31、e best for converting dollars into measures of physical outputAvailable from Commerce Dept. for broad industry categoriesCan be constructed from client or industry data for narrow categoriesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-22-BE CAREFUL WH

32、EN MIXING EXCHANGERATES AND INFLATION ACROSS COUNTRIESFirst convert each countrys historical data to constant local currencyE.g., Japan1993 yenW. Germany1993 DMU.S.A.1993 dollarsThen convert to single currency (dollars, for example) at fixed exchange rateLeft HeaderRight HeaderShadow BoxSource: 1994

33、 The Boston Consulting Group All rights reserved-23-EXAMPLE: AN INTEGRATED CIRCUIT MANUFACTURERReported SalesG.N.P. DeflatorAverage I.C.Average I.C.Year($M)(1987 = 1.00)Price ($)Transistor Price ()19877861.0001.001.0519885951.033.92.7219897301.075.99.4919908331.119.98.3419911,0621.161.90.2419921,423

34、1.193.98.1819931,8381.2271.14.16Reported sales $15.2%Real sales $11.4%I.C. unit sales8.9%Transistor sales52.4%Growth Rates (per year)Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-24-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflat

35、orsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand

36、 forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-25-REGRESSION ANALYSIS IS A POWERFUL TOOL FORUNDERSTANDING RELATIONSHIP BETWEEN TWOOR MORE VARIABLESRegression analysis:Explains variation in one variable (

37、dependent) using variation in one or more other variables (independent)Quantifies and validates relationshipsIs useful for prediction and causal explanationBut . . .Must not substitute for clear independent thinking about a problemUse as single element in portfolio of analytical techniquesCan be mor

38、ass-“lose forest for trees”Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-26-ANY RELATIONSHIP BETWEEN VARIABLES X AND Y?Used alone, graphical methods provide only qualitative and general inferences about relationshipsPercentACV80%70%60%50%40%30%20%10%0%

39、Annual Number of Purchases by ConsumerX:Annual number of purchases by buyerY:Percent ACVPercent ACV is the volume weighted average percent of grocery stores which carry the category.Sources: ScanTrack; IRI Marketing Factbook; BCG AnalysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consu

40、lting Group All rights reserved-27-REGRESSION ANALYSIS ANSWERS THESE QUESTIONSWhat is relationship between X and YHow big an effect does X have on Y?What is the functional form?Is effect positive or negative?How strong is relationship?How well does X “explain” Y?How well does my model work overall?H

41、ow well have I explained Y in general?Are there other variables that I should be including?Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-28-WHAT IS RELATIONSHIP BETWEEN X AND Y?PercentACVAnnual Number of Purchases by CustomerRegression fits a straight

42、line to the data pointsPercent ACV = -0.2790 + 0.2606 annual purchasesOne more annual purchase will raise percent ACV by 0.2606 percentage pointsSlope of line (here 0.2606) indicates size of effect; sign of slope (here positive) indicates whether effect is positive or negativeR2 = 0.69Multiple R0.83

43、354R Square (%)69.48Adjusted R Square (%)68.35Standard Error0.10394Observations29Regression StatisticsRegression10.664000.6640061.4641.98146E-08Residual270.291680.01080Total280.95568Analysis of VariancedfSum of SquaresMean SquareFSignificant FIntercept(0.27901)0.06286(4.439)0.00013(0.40799)(0.15003)

44、X10.260560.033247.8401.5372E-080.192370.32876CoefficientsStandard Errort StatisticP-valueLower 95%Upper 95%Sources: Scantrack; IRI Marketing Factbook (1990); BCG AnalysisMicrosoft Excel Regression OutputLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-29-

45、HOW STRONG IS RELATIONSHIP?t-statistic measures how well X explains YSimply calculated as slope divided by its standard error Closer slope is to zero, and/or higher standard error (variability), the weaker the relationshipA short-cut: t-statistic greater in magnitude than 2 means relationship is ver

46、y strong (i.e., roughly 95% confidence level). Between 1.5 and 2, relationship is relatively strong (i.e., roughly 85-95% confidence level). Under 1.5, relationship is weak.Multiple R0.83354R Square (%)69.48Adjusted R Square (%)68.35Standard Error0.10394Observations29Regression10.664000.6640061.4641

47、.98146E-08Residual270.291680.01080Total280.95568Regression StatisticsdfSum of SquaresMean SquareFSignificance FIntercept(0.27901)0.06286(4.439)0.00013(0.40799)(0.15003)x10.260560.033247.8401.5372E-080.192370.32876CoefficientsStandard Errort StatisticP-valueLower 95%Upper 95%Analysis of VarianceLeft

48、HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-30-HOW WELL DOES MY MODEL WORK OVERALL?R2 measures proportion of variation in Y that is explained by the variables in the model - here just XIndicates overall how well model explains YBased on how dispersed the

49、data points are around the regression lineR2 measured on scale of 0 to 100% 100% indicates perfect fit of regression line to the data pointsLow R2 indicates current model does not fit the data well-suggests there are other explanatory factors, besides X, that would help explain YMultiple R0.83354R S

50、quare (%)69.48Adjusted R Square (%)68.35Standard Error0.10394Observations29Regression10.664000.6640061.4641.98146E-08Residual270.291680.01080Total280.95568Regression StatisticsdfSum of SquaresMean SquareFSignificance FIntercept(0.27901)0.06286(4.439)0.00013(0.40799)(0.15003)x10.260560.033247.8401.53

51、72E-080.192370.32876CoefficientsStandard Errort StatisticP-valueLower 95%Upper 95%Analysis of VarianceLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-31-USE MULTIPLE REGRESSION TO SORT OUT EFFECTSOF SEVERAL INFLUENCESUseWhen several factors have an impac

52、t simultaneouslyTo help distinguish cause from correlationDont use as “fishing expedition”Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-32-MULTIPLE REGRESSION CAN ENHANCEPREDICTIVE ABILITY% ACV with Features and/or DisplaysBrand SizePercent of Househol

53、ds BuyingAnnual Number of Purchases per Year% ACV with Features and/or Displays% ACV with Features and/or DisplaysBrand Size ($M)Percent of Households BuyingAnnual Number of Purchases/YearR=.67R=.51R=.69R=.87Predicted % ACV with Features and/or DisplaysActual % ACV with Features and/or DisplaysBrand

54、 Size, Reach, andPurchase FreqencySources: Scantrack; IRI Marketing Factbook 1990; BCG AnalysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-33-OTHER REGRESSION EXAMPLESVery Low R*PercentACVU.S. Corn Yield (Bushels/ Acre)U.S. Corn Yield (Bushels/ Acre)

55、Retailer Margin on DealAverage Number of Days on DealTotal Annual Purchases (M)Negative Slope*Nonlinear Raw Data*After Log Transformation* Sources: IRI Marketing Factbook; Certified Price Book; Nielsen; BCG Analysis* Source: Agricultural StatisticsR=.64R=.002R=.95Left HeaderRight HeaderShadow BoxSou

56、rce: 1994 The Boston Consulting Group All rights reserved-34-QUESTIONS TO ASK BEFORE RUNNING A REGRESSIONWhich variable is the predictive (or dependent) variable?Often straightforward but sometimes requires thoughtConsider direction of causationWhat explanatory variables do I believe are appropriate

57、 to include?Avoid spurious correlationsthink independently about what factors are logical to includeAvoid including explanatory variables that are highly correlated with each otherShould the regression have an intercept term?How far can the data be reasonably extrapolated?Should the regression line

58、cut through the origin?Does a zero value of explanatory variable imply a zero value for predictive variable?Have I plotted the data?Watch out for outliersLook for form of data (linear, exponential, power, etc.)Do I have enough observations?Rough rule of thumb: 10 observations for each explanatory va

59、riableLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-35-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utiliz

60、ationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All

61、 rights reserved-36-Define relevant competitive environmentBasis of advantage (profit levers)Relative strengths/weaknesses of competitorsBarrier to new competitorsEffect of changes over time (technology, scale)Predict effect of one firms actions onCompetitors (short term, reaction)Profit and cash fl

62、ow of clientNotCost systemsCorrecting average costing for its own sakeWHY DO COST ANALYSIS?Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-37-WHICH COSTS?Competitive cost analysisUse actual costs, not standardsUse fully absorbed costs, since expenses are

63、 often the most sensitive to scale/experience, etc.Identify costs and expenses with individual models/product linesTherefore, competitive cost analysis involvesAllocation of variancesAllocation of expensesCapitalization of nonrecurring costs and expensesLeft HeaderRight HeaderShadow BoxSource: 1994

64、The Boston Consulting Group All rights reserved-38-IN MOST SUPPLY SIDE ANALYSIS, FIRSTLAY OUT THE CLIENTS COST STRUCTUREFocus on Key Cost ElementsProfitOverheadSelling and DistributionVariable ManufacturingRaw MaterialsFixed Manufacturing8%8%16%18%40%10%8%10%35%11%18%18%GainRaw materialsSelling and

65、distributionAdvantageBackward integrationRelated diversification to further Throughuse sales force?Purchasing scaleSales focus, toolsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-39-COST DATA CAN BE FOUND IN CLIENTACCOUNTING SYSTEMS . . .Client account

66、ing systems good forControl/audit of short-term evolutionNot for strategic analysisGenerally broken down by type of costDirectIndirectOverheadsEmphasis is on efficiency, not on understanding long-term cost dynamics as a function of scale, run length, etc.Left HeaderRight HeaderShadow BoxSource: 1994

67、 The Boston Consulting Group All rights reserved-40-. . . BUT OFTEN REQUIRES RECASTINGMaterials30Manufacturing costs40Direct15Indirect10Overheads15Commercial costs30Variable10Fixed20Total cost100Materials30Manufacturing costs40Metalworking15Painting8Assembly12Overheads5Distribution costs7Logistics5W

68、arehousing2Selling costs9Salesmen6After-sales3 serviceMarketing costs10Advertising3Overheads7G&A4Total cost100Accounting SystemStrategic Cost ElementsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-41-MANY VARIABLES AFFECT COSTSMaterialsVolumeLocation of

69、 suppliersDesignManufacturingPlant outputTechnologyExperienceDesignRun lengthComplexityFactor costsLogisticsVolumeDrop sizeSellingVolumeNumber of outletsMarketingVolumeVolume/brandLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-42-TABLE OF CONTENTSIntrod

70、uctionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional

71、scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-43-DESIGN DIFFERENCES CAN BE A MAJOR DRIVEROF PRODUCT COST DIFFERENCESAffect raw material costs as well as ma

72、nufacturing value addedUsually requires a “teardown” of competitor products to understand real differencesRequires client involvement-design engineers-manufacturing engineers-purchasing agentsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-44-FIRST STEP

73、IS TO IDENTIFY DESIGN DIFFERENCES - 1Example: Design AnalysisTorque Converters29 blades, .77mm thickE-beam weld hub to shellRoll tabbed18 bladesDie castingRoller clutch2 needle thrust bearing31 bladeslonger and thinnerRoll tabbed and stakedHub part of stamping.82mm8 springs4 big, 4 medium (nested)Cl

74、ose to center3 lugs welded245 MM23.0 lbs.27 blades, .82mm thickRivet hub to shell (10 rivets)Roll tabbed15 bladesPlasticRoller clutch31 bladesshorter and fatterRoll tabbedHub part of stamping1.04mm12 springsAttached directly to cover4 studs welded235 MM22.8 lbs.Misc DataTurbineStatorPumpDamperCoverM

75、odel AModel BDesign differences translate into cost differencesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-45-FIRST STEP IS TO IDENTIFY DESIGN DIFFERENCES - 2Example: Digital Line Card Comparisons8 ports2 transformers2 custom ICs (DCPFs)No standard T

76、TL ICs2 layer PWB1253 discretesSM/TH2Time-slot interchangingConferencingGain controlParallelserial conversionSanity scanningControl channel interface16 ports1 transformerNo custom ICs11 standard TTL ICs2 layer PWB (foreign sourced)150 discretesAll THOff-board(More centralized)16 ports1 transformer1

77、hybrid IC3 custom ICs46 standard TTL ICs6 layer PWB210 discretesSM/THGold fingers attached to PWB (no separate connector)Off-board(More centralized)Port interface with terminalsControl switchingBoard overheadOther “on-board” functionality1Printed wiring board2Surface mount and through holeMajor Func

78、tionClientCompetitor XCompetitor YLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-46-NEXT, WORK WITH CLIENT PURCHASING AGENTSTO DETERMINE MATERIAL COSTSExample: Client Material Costs per Digital Port Are HighFunctionClient(8/board)Competitor X(16/board)C

79、ompetitor Y(16/board)Additional functionality assumedOnly 32.65/card if redesigned digital card is assumedPortControlOverheadAdditional functionalityTotal material cost per boardPortsTotal material cost per portCost indexCost index excluding functionality47.7624.5834.7951.85158.98819.8710010068.604.

80、9439.49 113.03167.07365396.2863.8276.06 236.161614.7674110Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-47-DESIGN DIFFERENCES MAY SUGGEST FOCUSFOR COST REDUCTION EFFORTSExample: Cost Reduction of Additional OpportunityAppears in Control Unit, Digital L

81、ineControl unitTrunk modulesAnalog lineDigital lineSwitch TotalTelsetsTotal System5,2351,3211,0802,1609,7965,44115,237ComponentClientCompetitor3,0461,7701,1401,3767,3326,07213,404Cost ($/Component)Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-48-TABLE

82、OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-m

83、ulti-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-49-FACTOR COSTS USUALLY DONT REQUIREANALYTICAL TOOLS, BUT CAN RESULT INDIFFERENT COST POSITI

84、ONSFactor cost differences can affect most elements of the cost structureRaw materialsEnergyLabor (direct and overhead)CapitalFactor cost differences are generally additive or multiplicative and can be incorporated directly into the cost analysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Bost

85、on Consulting Group All rights reserved-50-FACTOR COST EXAMPLEForest Products Industry, 1981United States14.954.733.112.241.113.30Canada13.952.972.542.240.962.77Sweden11.514.814.81France10.514.595.214.60Brazil5.504.544.542.722.273.73Labor Rate($/Hour)OilGasCoalOtherAverageEnergy Prices ($/MMBTU)Left

86、 HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-51-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSuppl

87、y curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights re

88、served-52-SCALE, EXPERIENCE, COMPLEXITY, AND UTILIZATIONHAVE DISTINCT COST EFFECTS - 1Scale, experience and utilization tend to be confusedAll are conceptually separateScaleRelates unit cost or price to production volumeGenerally applies to machines or facilities of different sizes at a point in tim

89、eExperienceRelates unit cost or price to cumulative productionBest to think in terms of entire industry experience over long periodsArises for a variety of economic reasonsIs used a lot less frequently than you may thinkLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All ri

90、ghts reserved-53-ComplexityRelates unit cost to some measure of complexityEither-over time-over different facilities at a point in timeUtilizationRelates unit cost or profitability to utilization as a percentage of capacityApplies to different volumes or output from given facilities over timeSCALE,

91、EXPERIENCE, COMPLEXITY, AND UTILIZATIONHAVE DISTINCT COST EFFECTS - 2Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-54-BCG SLOPE DESCRIBES THE RELATIONSHIPBETWEEN UNIT COST AND VOLUMEBCG Slope Equals Percent of Base Remaining When Independent Variable D

92、oubledScale Two similar facilities with comparable utilization, but one four times the production of the otherUnit cost of smaller facility $10.00 and larger facility $8.10“Slope” = 90%ExperienceCumulative output increases from 100K units to 200K unitsUnit cost falls from $1.20 to $.97“Slope” = 81%U

93、tilizationOutput increases from 750 to 1,500Amortizable fixed costs of $5MFixed cost per unit falls from $6,667 to $3,333“Slope” = 50%Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-55-b isSlope (negative) of log Y = a - b Log XElasticity (negative) of Y

94、 with respect to XBCG slope = 2-bTherefore log BCG slope log 2FROM MATHEMATICAL SLOPE TOBCGS SLOPE AND VICE VERSABCG SlopeValue of b90.15280.32270.515Note: You can use log (base 10) or ln (base e). Answers are unaffected.BCG Slope Takes Log-Log FormBCG Slope Mathematically Implies b Value-b =Left He

95、aderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-56-CALCULATING NEW COST FROM OLD COSTAND VOLUMESExampleOld CostBCG SlopeOld VolumeNew VolumeNew Cost10070%47?OrYt + 1 = YtXt + 1Xtlog BCG Slope log 2Yt + 1 = YtXt + 1Xt( -b )Left HeaderRight HeaderShadow BoxSource

96、: 1994 The Boston Consulting Group All rights reserved-57-CALCULATING BCG SLOPE FROM COSTSAND VOLUMESExampleOld Cost100New Cost60Old S S Volume4New S S Volume10Slope?BCG Slope = Antilog Yt + 1 Yt log 2* Xt + 1 XtloglogLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All righ

97、ts reserved-58-SCALE MEANS COST PER UNIT ISLOWER FOR LARGER SUPPLIERSTypically Charted on Log vs. LogCost/UnitVolume100% Slope75% Slope50% SlopeEconomies of Scale Observed in MostCost Structure ElementsElementManufacturing scaleAutomated lineJob shopAdvertisingTelevisionDirect mailSellingFragmented

98、customersConcentrated customersEngineeringStandard productCustom productEffect of ScaleHighLowHighLowHighLowHighLowExampleEngine blocksAssembled componentsFoodMail-order specialty apparelBooks to bookstoreTruck componentsAutomobilesHybrid microelectronicsLeft HeaderRight HeaderShadow BoxSource: 1994

99、 The Boston Consulting Group All rights reserved-59-SCALE EXAMPLESPaper Machine LaborAdvertising CostsMan-hours/Ton1.00.80.60.40.240 6010020040080058%BCGSlopeAdvertising/Sales0.050.040.030.020.018162432Machine Capacity (TPD)Sales ($M)60%BCGSlopeLeft HeaderRight HeaderShadow BoxSource: 1994 The Bosto

100、n Consulting Group All rights reserved-60-LARGE SCALE PLANTS HAVE A SIGNIFICANTUNIT COST ADVANTAGEOverhead Cost/000 Equivalent32s ($)2520151075001,0002,0004,000Annual Capacity (000 Equivalent 32s)DanvilleOld SaybrookLos AngelesGlasgowMattoon70% SlopeLeft HeaderRight HeaderShadow BoxSource: 1994 The

101、Boston Consulting Group All rights reserved-61-HOWEVER, THINK BEYOND THE DATAFirst Cut of Data Would Show Wide DispersionSalaried andIndirect Employees/Sales ($M)10.05.03.02.01.00.52510205010020010030Plant Sales/Product Family ($M)= Traditional Approach= Cost-based Management Approach= Time-based Ma

102、nagement ApproachSource: BCG Analysis70Automotive Component SuppliersLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-62-DIFFERENT VOLUME LEVELS CAN JUSTIFYSUPERIOR TECHNOLOGIES - 1Hydraulic Component CastingPrice/Unit402010864501005001,0005,000Monthly Vo

103、lumeNote: Includes full amortization of tooling costsSlope across technologies 75%Slope within technologies 90-95%Sand MoldGravity Die Cast/Single DieHigh Pressure Die CastTwin DiesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-63-DIFFERENT VOLUME LEVEL

104、S CAN JUSTIFYSUPERIOR TECHNOLOGIES - 2Conventional Lathes by Mechanical DesignMachiningCost/PieceManualUniversal MachineManualCopy LatheManualChuckerAutomaticSingle SpindleAutomaticMultispindleLot SizeLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-64-EX

105、PERIENCE RELATES UNIT COST TO CUMULATIVE VOLUME - 1Experience is an empirical observation about very long-term price behavior for manufactured goods and servicesTrend line around which there is significant deviationDriven by technology improvements and changesIn both primary production processes and

106、 secondary processes (converting)Necessary to understand components of cost to project evolution of pricesIndicator of competitive cost differencesExperience and scale often interact, but are not the sameProper experience analysis should adjust for scale effectsLeft HeaderRight HeaderShadow BoxSourc

107、e: 1994 The Boston Consulting Group All rights reserved-65-EXPERIENCE RELATES UNIT COST TO CUMULATIVE VOLUME - 2Experience curves are most often modeled by a logarithmic relation:Log UC = b log V + awhere V = cumulative volumeUC = unit costThe “slope” of an experience curve is interpreted as “BCG sl

108、ope”Calculated in a similar way to scale slope-BCG slope =AntiloglogUCUC*log2logVV2121Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-66-WHY THE RELATIONSHIP WORKSMany factors work together to reduce real costs over timeIncreased purchasing scale (quanti

109、ty discounts)Increased productivityIncreased scale of facilityIncreased substitution of capital for laborTechnology evolutionCosts dont just “come down,” they are managed downLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-67-IMPLICATIONS OF EXPERIENCEIf

110、 prices decline, then costs must also decline over timeThe dynamic of constant change in business competitionAs a result of changing costs, different competitors will have different costs at any given timeDifferent cost positions will generate different levels of profitabilityAlso influenced by pric

111、e realizationProject competitive implications of aboveLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-68-WHOSE GROWTH DETERMINES COST/PRICE EVOLUTION:CHOICE OF EXPERIENCE BASESPrice data can be plotted against different experience bases:The industrysThe

112、technologysThe companysThe leadersThe fastest growing competitorsEtc.Correct choice depends on:Economics of the businessCompetitive dynamicsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-69-EXPERIENCE EXAMPLE: LEARNING RESTRICTEDWITHIN COMPANIESDirect C

113、ost/MW38034030026051550Allis-ChalmersWestinghouseGeneral ElectricFirm Cumulative Megawatts (M)Direct Costs Per Megawatt Steam Turbine Generators1946-1963Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-70-EXPERIENCE EXAMPLE: LEARNING IS SHAREDBY ENTIRE IN

114、DUSTRYCrushed and Broken Limestone Prices1.5234567810Industry Accumulated Experience (B Tons)1929193819451952197180% Slope2.502.001.50Price/Ton($ Constant)Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-71-IN CONSUMER ELECTRONICS, PRICE DECLINES 15-35%EA

115、CH TIME CUMULATIVE VOLUME DOUBLESPrice Experience CurvePrice(Constant1989 $)10,0001,0001001010.11101001,000Slope* (%)YearsPortable Color TV7668-89VCR8376-89Handheld Calculator6474-84Digital Watch7574-84Cellular Telephone7785-89Answering Machine7875-89Cumulative Volume (M)*For each doubling of cumula

116、tive volume, unit prices fall by (100 - slope)%Sources: Merchandising; Dealerscope Merchandising; BCG AnalysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-72-EXPERIENCE EFFECT CAN BE DIFFICULT TO MEASUREExperience effect normally applies only to the v

117、alue the firm adds to the productCost allocation in multiproduct plant creates problems in measuring the experience effectDifferences in factor costs make comparison difficultInflation must be eliminatedSignificant changes in product design must be taken into accountRelevant experience unit not alwa

118、ys obviousLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-73-Complexity gives rise to unit costs that increase with the scope of activityScope in manufacturing: parts, models, product lines, etc. . . .Scope in administration: businesses, countries, etc.

119、. . .Complexity often works against scaleExample: the cost of connecting every two people in a communication network with a dedicated connection at $1 per connection210.5510210454.5501,22524.51004,95049.5COMPLEXITY COSTS ARISE FROM PROBLEMS ANDCOSTS INVOLVED IN COORDINATING MANY ACTIVITIESNumberNumb

120、er of Connections of People ()(N)(N-1)/2Cost/Person ($)Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-74-COMPLEXITY ARISES IN INDUSTRY DUE TOMANY FACTORSPlant makes so many products that machines spend substantial time changing over between productsSale

121、smen sell too many products to master any one of them properlyMultiproduct plant has high administrative costs of coordination and trackingLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-75-COMPLEXITY EXAMPLESMachine ManufacturingOther ManufacturingIndir

122、ectCost(% ofTotal Cost)139%IndirectCost(% ofTotal Cost)302010551020405030201045 68 1015 2030 4050# of Product Families Produced# of ModelsSource: BCG Interviews and Analysis8 FactoriesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-76-SCALE AND COMPLEXIT

123、Y TYPICALLYWORK AGAINST EACH OTHERSignificant Value in Learning How to Manage ComplexityOverhead Cost/UnitVolumeCombined ImpactComplexity ImpactReduced Complexity CostScale ImpactLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-77-UTILIZATION MEANS UNIT C

124、OSTS ARELOWER WHEN CAPACITY IS FULLUtilization is important whenCapital intensity is highEnergy consumption is major part of costsStartup costs are highLabor force is not flexibleDifferent from scaleFrequently the two phenomena interactLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consult

125、ing Group All rights reserved-78-UTILIZATION EXAMPLESHealth Care ServicesPrinting PressesCost/Procedure($)140408060100201612234 520Number of Professionals/OfficeNote: Assumes 2,000,000 Run LengthFullyLoadedCost($/1,00032s)DailyProcedures/Professional5101520New TechnologyStandard GravureAggressive Gr

126、avureLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-79-UTILIZATION AND SCALE - 1Glasswool SmeltingCostIndex/t30020015010075 3 5 10 20 50100%50 kt100%25 kt50%50%CapacityCapacity UtilizationAnnual Production (kt)Source: Clients Database and SimulationsLef

127、t HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-80-UTILIZATION AND SCALE - 2Cost Added(/Lb)504030252015101,0002,0003,0004,0005,000 6,00010,0008,000Total Monthly Shipments (000 Lbs)Guelph78%Columbiana78%Stillwater75%90% Scale SlopeNote: Costs adjusted for wa

128、ge and energy factor cost differencesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-81-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, ex

129、perience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994

130、The Boston Consulting Group All rights reserved-82-SUPPLY CURVES DESCRIBE THE CASH COSTPOSITION OF COMPETITION IN COMMODITY INDUSTRIESUsed to make predictions for an industry aboutPriceEntry and exitProfitabilityUsed mainly for commodity industries where all producers make the same product and there

131、 is one market priceDisplay the sum of the components of competitive cost position across all competitorsVertical axis, displaying cash cost per unit of production versusHorizontal axis, laying out each competitors capacity, in some appropriate measure of capacity-by plant-by machineLeft HeaderRight

132、 HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-83-COMMENTS ON THE SUPPLY CURVEThe return on assets is not necessarily the highest for the left-most facilityCan often follow a humped patternIn using the supply curve to predict prices and exit upon the entry of new capac

133、ity, consider the followingMarginal firms may resist exit because their assets are nontransferable to other industriesThe industry demand curve, often assumed to be inelastic in the short term, may be elastic in the long termBCG supply curve assumesEach firm operates at full capacityMarginal costs f

134、or a firm equal variable cash costs per unit of volumeLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-84-BCGS SUPPLY CURVE IS AKIN TO THE SUPPLYCURVE OF NEOCLASSICAL MICROECONOMICSAssumptionsEach firm i maximizes profit by taking P as given and choosing

135、Vi so that MCi = PIndustry supply curve is horizontal sum of each firms marginal cost curve -Vs = V1 + . . . + Vi + . . . + VnPrice is determined by interaction of industry supply and demand curvesFirms Marginal Cost CurvesMCiMCiMCnViViVnVolumeVsIndustryDemandCurveIndustry SupplyCurvePrice,CostPLeft

136、 HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-85-PAPER INDUSTRY SUPPLY CURVECost($/Ton)Annual CapacityLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-86-SUPPLY CURVE CAN BE USED TO EXPLAIN PROFITABILITY . . .Co

137、st($/Ton)Annual CapacityPriceIndustryDemandContribution toward fixedcosts and profitLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-87-. . . AND TO PREDICT PRICES AND ENTRY/EXIT BY FIRMSIndustry Demand CurveIndustry Demand CurveIf new firm enters, price

138、drops to P1New firm enters only if contribution A covers fixed costs + expected returnMarginal firms drop out if new firm entersP0P0AP1New EntrantQuantityQ0Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-88-HOWEVER, DONT LET IT LEAD YOU TONONSENSICAL RES

139、ULTS . . .Bostons Most Prestigious Hospitals Are High Cost$/Patient Day1,000900800700600500400300012345678910111213Cumulative Beds (000)Sources: AHA; Local Interviews; BCG AnalysisWill they be first to exit as market shrinks?Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group A

140、ll rights reserved-89-RATHER USE IT TO UNDERSTAND MARKET FURTHERBostons Hospital Segments Have BothHigh/Low Cost Suppliers$/Patient DayCumulative Beds (000)Source: BCG AnalysisBasicSecondaryAspirant TertiaryTertiaryLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights

141、reserved-90-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-c

142、onjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-91-FROM PRODUCT TO MARKET FOCUS:UNDERSTANDING THE CUSTOMERSee the Market T

143、hrough the Eyes of the Customer“I wish,” “I want,” “I need,” “I hope,” answered with new products and services can substantially increase revenue, profit growth and organizational vitalityCustomer NeedImplicationConceptScreenDevelopmentExecutionLeft HeaderRight HeaderShadow BoxSource: 1994 The Bosto

144、n Consulting Group All rights reserved-92-WHAT KINDS OF INFORMATION ARE IMPORTANTFOR UNDERSTANDING CUSTOMERS?Customer profitabilityCustomer economicsKey driversClient impactAttribute values and tradeoffsSatisfactions/dissatisfactions/product gapsBuying processUsageSwitching costs and substitutionShi

145、fts in purchasingLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-93-AggregateCumulative customers/cumulative revenueFully loaded cost to serveCumulative customers/cumulative profitValue of attributes/tradeoffsSatisfactions/dissatisfactionsEnd-user usage/

146、dissatisfactionsOverall product development requirementsMajor segmentSegmentation dimensionsSegment sizingSegment attractivenessSegment cost to serveSegment economicsSegment product development requirementsSegment of oneValue of a customerValue of company to customerKey business driversOpportunities

147、 for expansionSatisfactions/dissatisfactions/needsRelationship managementProduct development requirementsCUSTOMERS CAN BE UNDERSTOOD ON THREE LEVELSInternal financial recordsCost deaveraging, benchmarking, mappingInterviews, focus groups, structured surveys, conjointInterviews, plant visits, usable

148、tests, surveys, focus groupsInterviews, focus groups, structured surveysD&B, trade associations, SIC code databases, interviewsInternal financial/translation data, interviews, public financial dataInterviews, perceptual mapping (MDS)Internal financial records, cost deaveraging, customer databaseDisc

149、overy, interviews, plant visitsInterviews, customer database, DiscoveryLevelKey IssuesSource of DataAnalysis often conducted concurrently at three levelsAnalysis often conducted concurrently at three levelsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-

150、94-COST-TO-SERVE SCHEMATICMarginDistributor SupportLocal Account ManagersTechnical SupportCustomer Service/SupportDistrictG&ADevelopmentCOGSIndustrial SalesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-95-UNDERSTANDING THE CUSTOMERAGGREGATE EXAMPLESCum

151、ulative sales(%)Cumulative variable margin(%)Cumulative fully allocated profit(%)# of customers# of customers# of customersSatisfaction index(Top 2 Box)Five major drivers of customer satisfaction; Two are software related.with significant opportunity for improvementUser-friendlyDocumentationCompatab

152、ilityBug-freeRelative importance (SBW)Major Dissatisfactions100% FAP = $446KReliabilityDurabilityFeatures/FunctionsWarrantyProgramming softwaredunc. 1-27-94/srdLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-96-TABLE OF CONTENTSIntroductionGeneral analyt

153、ical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume

154、curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-97-WHY DO SEGMENTATION?No such thing as a homogeneous marketDifferent customer needsDifferent structural economicsFind the most a

155、ttractive customer setsQuantify and prioritizeDevelop an action plan for each targeted “cell”Find new “space” for successive product launchesUse as the foundation for sustained, profitable growthIncreasingly “granular” as a company builds its capability setLeft HeaderRight HeaderShadow BoxSource: 19

156、94 The Boston Consulting Group All rights reserved-98-SEGMENTATION GOAL IS TO MAXIMIZECOMPETITIVE ADVANTAGEAccounting systems and conventional industry classifications rarely provide sufficient quantifications of segment size, growth rate, share, etc.Good segmentation schemes explain client performa

157、nce and competitive positioningSegmentation schemes that cannot be tied to a program of client actions are uselessLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-99-MARKET SEGMENTATION EXAMPLE - 1Purchase RelatedLocal or national customerwith local decis

158、ion-making authorityNational customers withcentral/HQ decision-making authorityComplex systemsSimple systemsExisting clientsiteNew site,or weakcompetitorStrongcompetitorsiteExistingclientsiteNew site,or weakcompetitorExistingclientaccountPurchaseCriteria:Vendorloyalty,productperformanceProductperfor

159、mance,priceVendorloyalty,productperformanceVendorloyalty,pricePriceVendorloyalty,priceVendorloyaltyVendorloyaltyOther*Preferredvendor* Mixed sites, likely to be moving to one preferred vendorStrongcompetitorsiteStrongcompetitoraccountLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consultin

160、g Group All rights reserved-100-MARKET SEGMENTATION EXAMPLE - 2Customer RelatedCompanies within an industry (across some) behave similarly and have essentially the same needsApplication expense drives purchaseCustomers looking for full solutionsLarge customers require greater resources and concessio

161、ns than small customersDiffering purchase criteriaOEMs have different, requirements, criteria, and needs than end usersCentralized customers are more price and specification driven than decentralized customersEngineering-oriented customers are specification focused and value technical sales capabili

162、tyNonengineering oriented rely on OEMs and Sis for specificationPull through versus pushEasier/cheaper to sell to our customers Marketing and sales structureChannel strategyPackaging and promotionsProduct developmentProduct developmentPricing/bundling strategyMarketing structure (resource deployment

163、)Channel deploymentPricing/POV strategyProduct developmentMarketing structureChannel deploymentPricing strategyChannel deploymentPricingChannel deploymentSupport/marketing supportProduct packaging (full solutions)Pricing/deploymentBy IndustryBy ApplicationLarge versus SmallOEM versus End UserCentral

164、ized versus DecentralizedHigh Internal Engineering Capability versus Limited Engineering CapabilityOur Customer versus CompetitorsTraditionalNontraditionalSegmentation DimensionDescriptionHas Impact OnLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-101-M

165、ARKET SEGMENTATION EXAMPLE - 3Cost-to-Serve RelatedHigh25%36%Low25%16%LowHighShare by SegmentProductionEconomics“Cost toManufacture”% NewsstandDistribution Economics“Cost-to-Serve”Annual MagazineVolumeLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-102-S

166、EGMENTS ARE FREQUENTLY THE COMPOSITEOF SEVERAL DIMENSIONS“Decision Tree” SegmentationAutomotiveFoodPharmaceuticalHydrocarbonCentralizedDecentralizedCentralizedDecentralizedCentralizedDecentralizedCentralizedDecentralizedHighLowHighLowHighLowHighLowHighLowHighLowHighLowHighLowOursTheirsOurTheirsOursT

167、heirsOursTheirsOursTheirsOursTheirsOursTheirsOursTheirsOursTheirsOurTheirsOursTheirsOursTheirsOursTheirsOursTheirsOursTheirsOursTheirsExample:Centralized vs.High vs. LowOur CustomerIndustry DecentralizedEng. Capabilityvs. CompetitorDimension OneDimension TwoDimension ThreeDimension FourLeft HeaderRi

168、ght HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-103-SEGMENTATION: BASIC DATA REQUIREMENTS - 1What are the relevant market segments?Who are the key players within each market segment?For each segment and subsegmentWhat is the attractiveness?-size, growth rates, margin

169、s, current penetration levels, share, etc.What are the economics to serve (vis-a-vis competitors)?-costs to sell, project win rates, life cycle economicsWhat are the key success factors?-key purchase criteria-unmet needsproducts, marketing, distribution, support, etc.Left HeaderRight HeaderShadow Bo

170、xSource: 1994 The Boston Consulting Group All rights reserved-104-SEGMENTATION: BASIC DATA REQUIREMENTS - 2The previous three dimensions of segment analysis (attractiveness, economics to serve, key success factors) can now be rolled together to create an overall segment prioritizationHighSegmentAttr

171、activenessLowEconomics to ServePoorGoodSegment Prioritization1.C2.D3.B4.I5.E6.H7.A8.F9.GKey Success FactorRequirementsMost attractiveLeast attractivemmooAEBDCFGIHmmmmmmooooooFurthermore, beyond just prioritizing across market segments, there is now enough information to optimize performance within e

172、ach segment via the levers of price, mix, share, and expensesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-105-SEGMENTATION IS ALSO A CREATIVE ARTWITH MANY APPLICABLE FRAMEWORKSUser targetPsychographic (personality, behavior, socialization)Demographic

173、(age, income, lifestyle, family structure)GeographicCustomer attitudesCurrent behavior and beliefsTarget substitutionsOccasionProduct attributesRealPerceptualOthersVariety, ease of use, cost, system attributesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserv

174、ed-106-QUESTIONHow would you understand usage behavior and dissatisfactions for laundry products (stain remover)?Qualitative?Quantitative?Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-107-ANSWER: 50 IN-HOME INTERVIEWS WATCHINGCONSUMERS SORT, TREAT, WAS

175、H, AND DRY LAUNDRYClothes WornStain OccursSSRPlace Items in Hamper or ClosetLaundry Gathered, Taken to Laundry RoomCheck for StainsDry CleanSet Machine Controls and Start WaterPretreat, Presoak Stained ItemsAdd DetergentAdd ClothesCheck Clothes at End of CycleStain Gone?Dryer/ Clothes LineBack in Wa

176、shCheck StainDryer/ Clothes LineEvaluated ResultsSocial/ School (1)Around the House/ Play (2-3)Rag Bag ( 4)Re-treatPresoakSpecial treatmentSSRAddOtherProductsPretreat,PresoakStainedItemsPresoakTreatImmedi-atelySortLaundryYesMy best clothes-something I really like or care about?Intervention points in

177、 current laundry protocol define theopportunity and provide options for stream of new productsOccurs some of the timeOccurs most of the timeIn-Homes Show Four Intervention Points in Current Laundry Protocol Treat immediately presoak treat at beginning of wash cycle retreatSegment by load-by new high

178、ly valued-by wearer: husband, kids, own-by fabric-towels are separate-colors-jeans, lights, delicatesPerceptions vary about washing-which stains are tough-cottons/blends; cold/hotDry cleaner substitutes for pressingFine fabric stain removalHome remedy acceptanceInvolved are willing to scrub, use mul

179、tiple productsSeek sanitizing benefit-bed wetters, underwearLimited stain penetration outside of laundryRepeated washings to get cleanCombination usageSpecial treatments for specific stainsNo stain HH: adultsWith kids: many stainsLaundry involved; neatnick-multiple products-developed routine, home r

180、emediesConvenience driven deteriorating standardsBlue collar, C&D countyHeavy userSkeptical about performanceStain awareness for involvedSegmented products for involvedConvenience for uninvolvedKids-involvementHeavy user programHeavy duty presoakBoosterSanitizerFine fabric stain removerHeavy duty st

181、ain remover-grease and oil-work clothesStain seekerProduct holder for stickKids stick promotionRejuvenator for loved clothesIn-home dry cleaningBaby ShoutNon-chlorine bleach/ booster2 in 1 deliveryGel with brushPost-foaming . . . visual cuesScotch-guard for predictable stainsWash in cold waterFor co

182、ttonsRetards mildewDual positioning no wasteHousehold SegmentationWashing HabitsProduct OpportunitiesA Number of Observations from In-HomesComplete ListYields segmentation by usage behaviorLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-108-DOMINOS PIZZA

183、 SEGMENTED ON A TIME CLAIM# of LocationsSources: Chicago Tribune; D&BLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-109-CUSTOMER “DISCOVERY” MOVES A STEPBEYOND SEGMENTATIONDiscovery is a continuous, dynamic, analytical process of understanding the econo

184、mics and capabilities of the customers business and leveraging that knowledge into ideas, products, and services of mutual benefitThe result is a defensible, win-win partnershipDisciplined AnalyticalUnderstanding CapabilitiesCreativityPartnership Valueand Growth+Left HeaderRight HeaderShadow BoxSour

185、ce: 1994 The Boston Consulting Group All rights reserved-110-DISCOVERY FINDS NEW MATCHESBETWEEN CUSTOMER NEEDS AND CAPABILITIESNew Opportunities with a CustomerNew Opportunities Across CustomersCustomerNeedsCompanyCapabilitiesNew OpportunityUnmet NeedsCustomer #1Customer #2Customer #3CustomerNeedsCo

186、mpanyCapabilitiesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-111-UNDERSTANDING THE CUSTOMERDISCOVERY EXAMPLES - 1Net Result Would be More MailingsEstimated BreakdownCompanys Value Delivery SystemFrames New IdeasNational gift registry programPromotion

187、 to counter the negative perception of jewelry qualityMothers Day reminder laser letter to best customersMDA sponsorRadio/TVPOS household database collection-20MM+ customers-identify and address-recency and frequency-sales by SKU and merchan- dise category-Promotional and response history-payment me

188、thod-sales and margin per customerScoring methodsDirected program at locations where a competitor such as “Best” is closing a store, inviting their customers to switchBuyer reactivation covers for custom- ers who havent purchased recentlyMarriage compilation for target mailingsPreprinted flyer sent

189、immediately to new customers featuring merchan-dise attractive on their second visit to the showroomGrand opening zoned mailerBarcoded coupon promotionInk jet message directing customer to nearest storeFree jewelry cleaning for lifetimeROP for special store promotionsStore location cylinder versions

190、Drive thru serviceSilent Sam electronic ordering systemPreferred jewelry customer mailings for big-ticket buyersPrice versioning to meet competition in certain geo- graphic areasEfficient region- alization plan allowing different products in different geographic areasHardlines conver- sion flyer to

191、con- vert a low margin hardlines buyer to a high margin jewelry buyerPrice elasticity testing and trackingJapanese market opportunitiesMail order serviceCycle time reductionJuly “Price Busters” sale flyer to reduce inventoryInk jet messages calling attention to “overstocks”Selectronic gathering to p

192、ut “overstock” signature into certain customers flyersComputer inventory system connects all stores; customer is directed to nearest store in stockArchive perform. system will allow company to put an overstock flyer together quickerCycle time reductionAdvertising and Image ManagementCustomerCapture

193、andRetentionStoreTrafficPricingandMerchandisingInventory ManagementResponse Rate of House Customers (%)Marginal Response RateCustomer RankingCumulative Average Response RateSingle Event BreakevenLifetime Value BreakevenParts of FileNot MailedLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston C

194、onsulting Group All rights reserved-112-UNDERSTANDING THE CUSTOMERDISCOVERY EXAMPLES - 2Implementing the New Program Could IncreaseProfits by 15 Percent and InventoryTurns by 10 PercentLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-113-TABLE OF CONTENTS

195、IntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimens

196、ional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-114-WHAT IS CONJOINT ANALYSIS?Conjoint analysis is a market research technique which uses consumer pref

197、erences for product or service attributes to derive a “utility value” for the whole product offeringConjoint analysis begins with the premise that goods and services are “bundles” of attributesEach attribute has a certain importance to the consumer-e.g., color and engine size of a carAttributes can

198、be presented in two or more levels-e.g., price of a car may be $10,000, $10,001 - $15,000, $15,001 - $20,000The relative importance of individual attributes and their levels determine consumer preference for the composite product or service Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Co

199、nsulting Group All rights reserved-115-HOW IS CONJOINT ANALYSIS USED? - 1Conjoint analysis allows users to focus on key attributesCompanies beliefs about consumer preferences often off baseTypically administer survey to managementResults very helpful in developing a blueprint for organizational chan

200、geConjoint analysis improves segmentation effortsMost segmentation schemes based on demographic information“Dissimilar” groups may behave similarly-use conjoint to identify other segments-e.g., purchasing behaviorLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights re

201、served-116-HOW IS CONJOINT ANALYSIS USED? - 2Conjoint analysis can be used for simulationsMarket share projectionsNew product introductionsCompetitive actionsMarketing promotions/programsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-117-WHEN SHOULD YOU

202、 USE CONJOINT(Instead of Only Market Interviews)Need a quantitative understanding of the decision-making processMeasure the tradeoffsThe decision is a complex one, with many attributes to considerNot dominated by a single itemWant to play “what-ifs” with new or existing productsCan decompose product

203、s into individual featuresLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-118-THREE PHASES TO CONJOINT ANALYSISAttribute selectionConjoint has practical limit of 10-12 attributesChoosing attributes most important in decision processcritical to achieving

204、meaningful resultsData collectionSignificant number of interviews required to ensure valid surveyRequires outside interviewers (Research Pros, market research firms)Data analysisTransforming raw data into meaningful recommendationsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting G

205、roup All rights reserved-119-PHASE ONE: CHOOSING ATTRIBUTESMust Understand Buying Decision and Products LimitsA few days of market interviews with current customersUnderstand major criteria in buying decisionStart to develop potential segmentations-make sure demographics to derive segmentations are

206、included in questionnaireInternal interviews/meetings to understand potential products and ensure client buy-inAfter interviews started, cannot change questionsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-120-CAREFUL ATTRIBUTE SELECTION KEY TOMAXIMIZI

207、NG CONJOINT EFFECTIVENESSInclude all major decision-making criteria, as well as product features and business-level attributesBut keep list short10 attributes is practical limit, 6 to 9 most desirable (corroborated in conversations with conjoint experts)-assumes use of adaptive techniquesLong survey

208、s result in more incomplete surveys, less consistent answers as interviewees tire-need more respondentsFewer questions per attribute lessens accuracySince attribute list limited, must carefully choose most relevant attributesLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group A

209、ll rights reserved-121-PHASE TWO: SURVEY ADMINISTRATIONAND DATA COLLECTIONTelephone surveys often usedEasiest to set up and administerRapid data collectionSurvey administration subcontracted to market research firm to control costs. Team overseesTrains research firm personnelMonitors progress to see

210、 that the sample size is sufficientEnsures quality controlAs data becomes available, team performs interim analyses to provide early insight into findingsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-122-BCG USES SPECIALIZED SOFTWARE TO COLLECTAND ANAL

211、YZE CONJOINT DATASeveral packages on market to perform conjointACAused by BCGOthers include Bretton-Clark and a specialized SSPS for doing full profile conjointsACA must be used to conduct adaptive interviewsSince tradeoff analysis is adaptive, computer must analyze previous responses real timeACA a

212、lso computes utility value for attributes and performs market simulationsData normally is exported to databases and spreadsheets for further analysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-123-STATISTICAL FORMULAS DEFINE SAMPLE SIZEFOR EACH DEMOG

213、RAPHIC GROUPThe number of interviews required for each demographic group increases with the number of attributes selected and the level of confidence requiredBecause conjoint is a statistical hybrid, true confidence intervals can only be determined after data has been gatheredGiven a fairly homogene

214、ous group, and 6 to 9 attributes, estimated sample sizes would be as follows:9910,000982,500954009010085447516ConfidenceInterval (%)Number of Interviews per SegmentLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-124-PHASE THREE: DATA ANALYSIS AND INTERPR

215、ETATIONMany ways to analyze conjoint dataMore than can ever be doneExtremely important to prioritize and continually check the sense of analysesSeveral analyses almost always doneAbsolute importance of attributesDemographic segmentationHypothetical market responses to various product offeringsOther

216、analyses also very powerful where appropriateBehavioral segmentation (cluster analysis)Comparison of internal responses to actual customersLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-125-CONJOINT QUANTIFIES THE VALUE OF ATTRIBUTESThe basic output of

217、conjoint analysis is a numerical rating of each attributes value to customersEach respondent has an equal number of “utility points” in total, but divides them differently among the various attributes70 for price, 30 for performance vs. 40 for price and 60 for performanceUtility points are added tog

218、ether to calculate the total attractiveness of a specified hybridLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-126-SAMPLE OUTPUT FROM A CONJOINT ANALYSISExample comes from a mid-sized long distance telephone companyUnsuccessful in current efforts: losi

219、ng customers and moneyNeed to reposition “product,” refocus effortsConjoint allowed them to determineWhat customers they should be serving-fit with internal capabilities-fit with cost to serveHow they could best serve those customers by giving them what they wantLeft HeaderRight HeaderShadow BoxSour

220、ce: 1994 The Boston Consulting Group All rights reserved-127-USER SURVEY FOCUSED ON EIGHT PRODUCTAND CARRIER ATTRIBUTESWithin 2 hoursWithin 4 hoursWithin 8 hoursCustomStandard invoiceLeading edge (video, ISDN, ANI)Advanced (dedicated access, virtual network, data lines)Basic (direct dial, 800, trave

221、l cards)Line problemresponse timeBilling optionsProducts10% below5% belowCurrent5% aboveClearNoisyNationalRegionalResellerSame daySame weekSame billing cycleLocal teamLocal single personNational centerPriceLine qualitySize of carrierBilling problemresponse timeService typeAttributeLevelsAttributeLev

222、elsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-128-CUSTOMERS VALUE QUALITY, RESPONSIVENESSAND SERVICE OVER PRICEUtility PointsFrom:To:NoisyClear8 Hours4 Hours4 Hours2 HoursStd.Custom5% AboveCurrentNatl CtrTeamResellReg.5% Below10% BelowWeekDayCurrent

223、5% BelowBasicAdv.Adv.LeadingCycleWeekReg.NatlPersonTeamChange in Attribute LevelsSources; Analysis of 448 Interviews, SIC WeightedLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-129-CUSTOMERS SELECT CARRIERS BASED ONDIFFERENCES BETWEEN ATTRIBUTE LEVELSPr

224、iceLine qualitySize of carrierLine problem res.Bill problem res.Service contactProductsBillingTotal utility pointsCurrentHighNationalWithin 4 hoursSame bill cycleTeamAdvancedStandardCurrentHighRegionalWithin 4 hoursSame bill cycleTeamAdvancedStandardCurrentHighRegionalWithin 2 hoursSame bill cycleTe

225、amAdvancedStandard4077475684419029140773956844190283407739102844190329AttributeLevelValueLevelValueLevelValueCarrier 1Carrier 2Carrier 3Carrier preference is determined by differential between packagesNote: Based on average, SIC-weighted customer; not specific segmentSource: Analysis of 448 Intervie

226、wsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-130-USER PREFERENCES DIFFER SIGNIFICANTLYBY INDUSTRY SEGMENT AND SIZEOF LONG DISTANCE BILLGreat Opportunity in Medium/Small Users SegmentTradesServiceManufacturingPublic/GovtSmall/medium userService drive

227、n,Less price sensitiveIndifferent to carrier sizeSmall/medium userPrice drivenLocal serviceLargeusers,valueprice,nationalcarrier,advancedproductsIndustry15,000Long Distance Bill/($/Month)Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-131-TABLE OF CONTEN

228、TSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dime

229、nsional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-132-WHAT IS MULTI-DIMENSIONAL SCALING?Multi-dimensional scaling (MDS) is a method for identifying the

230、 characteristics which underlie product positioningUsed to reposition products or develop new products based on market perceptionsShould be used after segmentation is completeMDS generally uses market surveys to pairwise compare products to determine the degree of similarity for each pairOutput is a

231、 map which displays similar products close to one another, and dissimilar products relatively far apartMDS is an alternative or supplementary technique to focus groups or a carefully structured program of market interviewsLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All

232、rights reserved-133-EXAMPLE OF MULTI-DIMENSIONAL SCALINGHousehold Cleaners*DuckVanishTilexSoft ScrubFantastixCloroxCometPine SolLysolLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-134-MDS MAPS SHOULD BE USED TO THINKABOUT PRODUCT POSITIONING QUESTIONSCo

233、nsumer MagazinesWhat are the axes/dimensions which underlie the map?Which products compete with one another?How do I interpret open space?Is there value to repositioning any products? developing new products?PlayboyPenthouseOmniEsquireVogueCosmoGlamourMademoiselleUSSavvyPeopleLadies Home JournalFami

234、ly CircleBetter Homes & GardensTV GuideScientificAmericanPractical MechanicsBusiness WeekEconomistSports IllustratedUS NewsDiscoverNewsweekTimeLifeFortuneForbesMoneyLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-135-MDS DESERVES SEVERAL CAUTIONARY NOTES

235、MDS map axes have no necessary definitionDefining axes is subjectiveEach segment should be analyzed separatelyConsumer perceptions may differ from nonconsumer perceptionsBlended perceptions across heterogeneous groups dilute value of MDSUmbrella brands should be unbundled to avoid confusion (e.g., C

236、oke becomes Diet Coke and Coca-Cola Classic)Consumer purchase decisions do not necessarily follow consumer perceptionsRepositioning a product to fill a “hole” in the MDS map does not ensure profitability or even economic viabilityLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Gr

237、oup All rights reserved-136-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation a

238、nd “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-137-V = V (E, P , P , . . . , P )WhereV=Quantity demandE=R

239、eal expenditures on thisand competitive goodsP=Price of this goodP.= Prices of n competitive goodsPPRICE-VOLUME CURVE BASED ONMICROECONOMIC DEMAND CURVE001n1nAdjusts product demand forOwn/others priceExpenditureEstimates volume change when faced with movement on cost sideExperience effectsScale effe

240、ctsTechnological changeLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-138-PRICE-VOLUME CURVE IS USUALLY EXPRESSEDIN ONE OF TWO FORMS1.To express level of demandFor general application2.To express change ( or D D) in demandFor emphasizing elasticities or

241、 implicit scale slopeWhere:All else constantEPPKV VE EV VV VP PV VP PEPP Total Expenditures Own Price Other s Price Constant Income Elasticity Own Elasticity Cross Elasticity = = = = = = = = = = =01001110e ee ee eD DD DD DD DD DD D( )D D( )( ) ( ) ( )( ) ( )Left HeaderRight HeaderShadow BoxSource: 1

242、994 The Boston Consulting Group All rights reserved-139-PRICING DECISIONS SHOULD BE BASED ON EXPECTEDCONTRIBUTION MARGIN FROM INCREMENTAL SALESPricing (low) for volume in variable cost products is often counterproductiveVolume gains dont help muchForegone margin can be enormousPricing (low) for volu

243、me in fixed cost products is often advisableVolume gains do helpCompetitive position is maintained by amortizing fixed costsPricing (low) for high experience curve products also advisablePreemptiveLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-140-PRICE

244、-VOLUME CURVE DEFINES AREASOF ELASTICITY/INELASTICITY% D D V% D D PIf 1: elastic lower priceIf 1: inelastic raise priceIf = 1: unit elasticity no change in price will change revenuePriceInelasticElasticUnit ElasticityVolumeCaution: Do not confuse “inelastic buyers” with inelastic portion of the dema

245、nd curveElasticityLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-141-PRICE ELASTICITYDoes changing the price grow or shrink the market (unit volume)?To be price elastic, a market mustHave buyers who change their purchase frequency due to price changes-p

246、urchase cycle-number kept on handContain products which substitute for one another-the tradeover point between products is within relevant pricing range-price changes (almost) alone will cause substitutionLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-1

247、42-MEASUREMENTS OF ELASTICITYD DP0 0D DVRelative VolumeRelative PriceWin RateRelative PriceLevelInitial PriceLife Cycle CostsSupportInstallationDeliveryCustomizationAttributeConjoint Utility0 0Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-143-RELATIVE

248、PRICE AND VOLUME OF GASOLINE:CHICAGO 1983Relative Price (Client/ Competitor Group)Relative Volume (Client/Competitor Group)Sources: Lundberg Survey; Purchase Behavior SurveyCompany AIndependentsMajorsMarchNov.MaySept.Jan.MarchJan.Sept.Nov.MayMayMarchSept.Nov.Jan.Left HeaderRight HeaderShadow BoxSour

249、ce: 1994 The Boston Consulting Group All rights reserved-144-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCust

250、omer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-145-BCG USES A VARIETY OF

251、 TOOLS FORFORECASTING DEMANDForecasting demand requires a clear understanding of the underlying demand drivers, e.g., population growth, fashion changes, etc.Forecasting demand for existing products is most often done by extending historical volume trends into the futureRegression analysis most comm

252、on approachForecasting demand for new products or technologies may require other toolsSubstitution curvesConjoint analysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-146-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegress

253、ion analysisSupply side analysisCost structuresDesign differencesFactor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasti

254、ng-technology/substitution curvesWrap-upLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-147-TECHNOLOGY SUBSTITUTION MODELBasic Assumptions“Many technological advances can be considered as competitive substitutions of one method of satisfying a need for a

255、nother.”“If a substitution has progressed as far as a few percent, it will proceed to completion.”“The rate of substitution of new for old is proportional to the remaining amount of the old left to be substituted.”Source: Fisher & PryLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consultin

256、g Group All rights reserved-148-CHARACTERISTICS OF SUBSTITUTION CURVESAn S curve will result if the rate of substitution is proportional to The amount substitutedThe potential market remainingS curves yield different growth rates for different stages of substitutionOften more realistic than linear o

257、r exponential growthShould be used to model systems in disequilibriumConverging to new equilibriumLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-149-TECHNOLOGY SUBSTITUTION MODELP2L-P2ln()-P1L-P1ln()= bTWhereP1 = penetration at t1P2 = penetration at t2T

258、 = time to go from P1 to P2L= final penetration %Plot on semi-log graphTime on x axisPL-P()orshare of newshare of old()on log(y) axisFormulaCritical assumption: substitution will proceed to “completion”Graphical Displays*F = fraction of newPL-PLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston

259、 Consulting Group All rights reserved-150-PRODUCT/TECHNOLOGY SUBSTITUTION EXAMPLES - 1Share of NewShare of OldYear0.020.10.050.20.512510(%)9580502010Diesel Class 8Gas Class 8Trona Soda AshSolvay Soda AshSouthern PlywoodWestern PlywoodAtmospheric SilNonatmosphericDuPont Chloride TiO2Non-DuPontBOPP Fi

260、lmCellophane FilmMonolithic CapacitorsDisc CapacitorsNC Machine ToolsNon-NC Tools1.2.3.4.5.6.7.8.Source: BCG Analysis12345678Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-151-PRODUCT/TECHNOLOGY SUBSTITUTION EXAMPLES - 2HouseholdPenetrationHouseholdPene

261、trationCompact DiscColor TVVCRNintendoInternetGrowth indistribution channelCritical massSource: BCG AnalysisLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-152-MODEL CAN BE USED TO FORECAST FUTURE GROWTH3-4 Years Historical Data RequiredCD/ROM Penetratio

262、n in Libraries . . . . . and the Scientific, Technical, and Medical FieldLibraryPenetration(%)Penetrationof STMCommunity(%)Left HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-153-TECHNIQUE MUST BE APPLIED CAREFULLYAdvantages“Neutral” basis for projection, re

263、quiring no qualitative judgmentPowerful predictor, if all conditions underlying past trend remain constantCautionsDo not lose sight of fact that substitution is driven most often by relative economics-if underlying economics change, so will rate of penetrationApply on a segment-by-segment basisDo no

264、t assume final penetration will be 100% of total marketLeft HeaderRight HeaderShadow BoxSource: 1994 The Boston Consulting Group All rights reserved-154-TABLE OF CONTENTSIntroductionGeneral analytical techniquesGraphsDeflatorsRegression analysisSupply side analysisCost structuresDesign differencesFa

265、ctor costsScale, experience, complexity and utilizationSupply curvesDemand side analysisCustomer understanding-segmentation and “Discovery”-conjoint analysis-multi-dimensional scalingPrice-volume curves and elasticityDemand forecasting-technology/substitution curvesWrap-upLeft HeaderRight HeaderShad

266、ow BoxSource: 1994 The Boston Consulting Group All rights reserved-155-THREE FINAL POINTSBCG does not formally document its analytical techniquesBut there is an active “oral tradition”Use itOur clients need our judgments “yesterday”Dont get too involved with the elegance of what you doLearn to execute “quick cuts”We often must make something out of (almost) nothingConsider case team needs and available information in choosing an analytic techniqueBe flexible