成本与管理会计（第15版） 课件 GE-hca15-ch10

CHAPTER10DeterminingHowCostsBehaveChapter10learningobjectivesDescribelinearcostfunctionsandthreecommonwaysinwhichtheybehaveExplaintheimportanceofcausalityinestimatingcostfunctionsUnderstandvariousmethodsofcostestimationOutlinesixstepsinestimatingacostfunctionusingquantitativeanalysisDescribethreecriteriausedtoevaluateandchoosecostdrivers10-2Chapter10learningobjectives,concludedExplainnonlinearcostfunctions,inparticularthosearisingfromlearningcurveeffectsBeawareofdataproblemsencounteredinestimatingcostfunctions10-3CostFunction,defined Acostfunctionisamathematicaldescriptionofhowacostchangeswithchangesinthelevelofanactivityrelatingtothatcost.Managersoftenestimatecostfunctionsbasedontwoassumptions:Variationsinthelevelofasingleactivity(thecostdriver)explainthevariationsintherelatedtotalcosts,andCostbehaviorisapproximatedbyalinearcostfunctionwithintherelevantrange.10-4CostTerminologyFrompriorchapters,wearefamiliarwiththedistinctionbetweenvariableandfixedcostsandinthischapterintroducemixedcosts.Variablecosts—coststhatchangeintotalinrelationtosomechosenactivityoroutput.Fixedcosts—coststhatdonotchangeintotalinrelationtosomechosenactivityoroutput.Mixedcosts—coststhathavebothfixedandvariablecomponents;alsocalledsemivariablecosts.10-5LinearCostFunctiony=a+bXThedependentvariable:thecostthatisbeingpredictedTheindependentvariable:thecostdriverTheintercept:fixedcostsTheslopeoftheline:variablecostperunit10-6BridgingAccountingandStatisticalTerminologyAccountingStatisticsVariableCostSlopeFixedCostInterceptMixedCostLinearCostFunction10-7LinearCostFunctionsIllustrated10-8CriteriaforClassifyingVariableandFixedComponentsofaCostChoiceofcostobject—differentobjectsmayresultindifferentclassificationofthesamecost.Timehorizon—thelongertheperiod,themorelikelythecostwillbevariable.Relevantrange—behaviorispredictableonlywithinthisbandofactivity.10-9CauseandEffectasItRelatesto

CostDriversThemostimportantissueinestimatingacostfunctionisdeterminingwhetheracause-and-effectrelationshipexistsbetweenthelevelofanactivityandthecostsrelatedtothatlevelofactivity.Withoutacause-and-effectrelationship,managerswillbelessconfidentabouttheirabilitytoestimateorpredictcosts.10-10CauseandEffectasItRelatesto

CostDrivers,cont’dAcause-and-effectrelationshipmightariseasaresultof:AphysicalrelationshipbetweenthelevelofactivityandthecostsAcontractualagreementKnowledgeofoperationsNote:Ahighcorrelation(connection)betweenactivitiesandcostsdoesnotnecessarilymeancausality.Onlyacause-and-effectrelationship–notmerelycorrelation–establishesaneconomicallyplausiblerelationshipbetweenthelevelofanactivityanditscosts.10-11Costdrivers&thedecisionmakingprocessTocorrectlyidentifycostdriversinordertomakedecisions,managersshouldalwaysusealongtimehorizon.Managersshouldfollowthefive-stepdecision-makingprocessoutlinedinChapter1toevaluatehowchangescanaffectcostsandproductdecisions.10-12CostEstimationMethodsIndustrialengineeringmethodConferencemethodAccountanalysismethodQuantitativeanalysismethodsHigh-lowmethodRegressionanalysisThesemethodarenotmutuallyexclusiveandoftenmorethanoneisused.10-13IndustrialEngineeringMethodEstimatescostfunctionsbyanalyzingtherelationshipbetweeninputsandoutputsinphysicalterms.Includestime-and-motionstudies.Verythoroughanddetailedwhenthereisaphysicalrelationshipbetweeninputsandoutputs,butalsocostlyandtime-consuming.Alsocalledthework-measurementmethod.10-14ConferenceMethodEstimatescostfunctionsonthebasisofanalysisandopinionsaboutcostsandtheirdriversgatheredfromvariousdepartmentsofacompany.Poolsexpertknowledge,increasingcredibility.Relianceonopinionsmakesthismethodsubjective,thoughoftenquickerandlessexpensive.10-15AccountAnalysisMethodEstimatescostfunctionsbyclassifyingvariouscostaccountsasvariable,fixed,ormixedwithrespecttotheidentifiedlevelofactivity.Typically,managersusequalitativeratherthanquantitativeanalysiswhenmakingthesecost-classificationdecisions.Widelyusedbecauseitisreasonablyaccurate,cost-effective,andeasytouse,butissubjective.10-16QuantitativeAnalysisUsesaformalmathematicalmethodtofitcostfunctionstopastdataobservations.Advantage:resultsareobjective.Advantage:mostrigorousapproachtoestimatecosts.Challenge:requiresmoredetailedinformationaboutcosts,costdrivers,andcostfunctionsandisthereforemoretime-consuming.10-17StepsinEstimatingaCostFunctionUsingQuantitativeAnalysisChoosethedependentvariable.(thecosttobepredictedandmanaged)Identifytheindependentvariable.(thelevelofactivityorcostdriver)Collectdataonthedependentvariableandthecostdriver.Plotthedatatoobservethegeneralrelationship.Estimatethecostfunctionusingtwocommonformsofquantitativeanalysis:thehigh-lowmethodorregressionanalysis.Evaluatethecostdriveroftheestimatedcostfunction.10-18SampleCost—ActivityPlot10-19High-LowMethodSimplestmethodofquantitativeanalysis.Usesonlythehighestandlowestobservedvalues.“Fits”alinetodatapointswhichcanbeusedtopredictcosts.Threestepsinthehigh-lowmethodtoobtaintheestimateofthecostfunction.10-20StepsintheHigh-LowMethod10-21Calculatevariablecostperunitofactivity.Ifwehadhighactivityof100atcostof$2,500andlowactivityof80atcostof$2,100,ourformulaforvariablecostperunitofactivitywouldbe:(2500-2100)/(100-80)or400/20or$20.00StepsintheHigh-LowMethod10-22Calculatetotalfixedcosts.Continuingourexample,let’scalculatefixedcostsusingboththehighandlowlevelsofactivity:High-$2500–($20x100)=$500(fixedcosts)Low-$2100–($20x80)=$500(fixedcosts)StepsintheHigh-LowMethodFinally,wecansummarizeourcalculationsintotheequation:Y=$500+($20xX)Ifwewonderedwhatcostswouldbeata120levelofactivity,we’llsimplyplugthatnumberforXinourequation:Y=$500+($20x120)orY=$2,90010-23Summarizebywritingalinearequation.RegressionAnalysisRegressionanalysisisastatisticalmethodthatmeasurestheaverageamountofchangeinthedependentvariableassociatedwithaunitchangeinoneormoreindependentvariables.Ismoreaccuratethanthehigh-lowmethodbecausetheregressionequationestimatescostsusinginformationfromallobservationswhereasthehigh-lowmethodusesonlytwoobservations.10-24TypesofRegressionSimple—estimatestherelationshipbetweenthedependentvariableandoneindependentvariable.Multiple—estimatestherelationshipbetweenthedependentvariableandtwoormoreindependentvariables.Regressionanalysisiswidelyusedbecauseithelpsmanagersunderstandwhycostsbehaveastheydoandwhatmanagerscandotoinfluencethem.10-25SampleRegressionModelPlot10-26Regressionanalysis:TerminologyGoodnessoffit—indicatesthestrengthoftherelationshipbetweenthecostdriverandcosts.Residualterm—measuresthedistancebetweenactualcostandestimatedcostforeachobservation.Thesmallertheresidualterm,thebetteristhefitbetweentheactualcostobservationsandestimatedcosts.10-27Evaluatingandchoosing

CostDriversHowdoesacompanydeterminethebestcostdriverwhenestimatingacostfunction?Anunderstandingofbothoperationsandcostaccountingishelpful.Herearethethreecriteriaused:EconomicplausibilityGoodnessoffitSignificanceoftheindependentvariable.10-28Evaluatingandchoosing

CostDrivers–significanceofQUESTION:Whyischoosingthecorrectcostdrivertoestimatecostsimportant?ANSWER:Identifyingthewrongdriversormisestimatingcostfunctionscanleadmanagementtoincorrectandcostlydecisionsalongavarietyofdimensions.10-29Costdriversandactivity-basedcostingEstimatingcostdriversinanactivity-basedcostingsystemdoesn’tdifferingeneralfromwhat’sbeendiscussed.However,sinceABCsystemshaveagreatnumberandvarietyofcostdriversandcostpools,managersmustestimatemanycostrelationships.Theywilldosousingthesamemethods,takingspecialcarewiththecosthierarchy.Ifacostisbatch-level,forexample,onlybatch-levelcostdriverscanbeused.10-30Nonlinearcostfunctions,definedCostfunctionsarenotalwayslinear.Anonlinearcostfunctionisacostfunctionforwhichthegraphoftotalcostsisnotastraightlinewithintherelevantrange.Someexamplesofnonlinearcostfunctionsfollow.10-31NonlinearCostFunctions,examplesEconomiesofscale(producedoublethenumberofadvertisementsforlessthandoublethecost).Quantitydiscounts(directmaterialcostsrisebutnotindirectproportiontoincreasesinquantityduetothenonlinearrelationshipcausedbythequantitydiscounts).Stepcostfunctions—resourcesincreasein“lot-sizes”,notindividualunits.10-32NonlinearCostFunctions,examplescont’dLearningcurve—afunctionthatmeasureshowlabor-hoursperunitdeclineasunitsofproductionincreasebecauseworkersarelearningandbecomingbetterattheirjobs.Experiencecurve—measuresthedeclineinthecostperunitofvariousbusinessfunctionsastheamountoftheseactivitiesincreases.Itisabroaderapplicationofthelearningcurvethatextendstootherbusinessfunctionsinthevaluechainsuchasmarketing,distributionandcustomerservice.10-33NonlinearCostFunctionsIllustrated10-34TypesofLearningCurvesCumulativeaverage-timelearningmodel—cumulativeaveragetimeperunitdeclinesbyaconstantpercentageeachtimethecumulativequantityofunitsproduceddoubles.Incrementalunit-timelearningmodel—incrementaltimeneededtoproducethelastunitdeclinesbyaconstantpercentageeachtimethecumulativequantityofunitsproduceddoubles.10-35SampleCumulativeAverage-TimeModel10-36SampleIncrementalUnit-TimelearningModel10-37TimeLearningModelComparativePlots10-38PredictingCostsUsingAlternativeTimeLearningModels10-39DatacollectionandadjustmentissuesTheidealdatabasehastwocharacteristics:Thedatabaseshouldcontainnumerousreliablymeasuredobservationsofthecostdriverandtherelatedcosts.Thedatabaseshouldconsidermanyvaluesspanningawiderangeforthecostdriver.10-40DataProblemsThetimeperiodformeasuringthedependentvariabledoesnotproperlymatchtheperiodformeasuringthecostdriver.Fixedcostsareallocatedasiftheyarevariable.Dataareeithernotavailableforallobservationsorarenotuniformlyreliable.10-41DataProblems,cont’dExtremevaluesofobservationsoccur.Thereisnohomogeneousrelationshipbetweenthecostdriverandtheindividualcostitemsinthedependentvariable-costpool.(Ahomogeneousrelationshipexistswheneachactivitywhosecostsareincludedinthedependentvariablehasthesamecostdriver.)10-42DataProblems,concludedTherelationshipbetweenthecostdriverandthecostisnotstationary.