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MeasurePerformance,IntroductionandDetermineWhattoMeasure,2,VersionNov2002,Page,1.0DefineOpportunities,2.0MeasurePerformance,3.0AnalyzeOpportunity,4.0ImprovePerformance,5.0ControlPerformance,1.1ValidateBusinessOpportunity1.2DocumentandAnalyzeProcesses1.3DefineCustomerRequirements1.4BuildEffectiveTeams,2.1Determinewhattomeasure2.2Managemeasurement2.3Understandvariation2.4DetermineSigmaPerformance2.5Excellentteamperformance,3.1processstratificationandAnalysis3.2determinerootcauses3.3validaterootcauses3.4managecreativity,4.1Generateimprovementideas4.2evaluateandselectsolution4.3presentrecommendations4.4Implementchange,5.1DevelopandExecutepilotplan5.2planandimplementsolution5.3processintegration5.4closureandrecognition,3,VersionNov2002,Page,ReviewandTransition,InSection1.4,welearnedhowto:Understandtheroleofeffectiveteamsinprocessimprovement.Applyteamevaluationtoolstoidentifyopportunitiestoimproveteameffectiveness.Section2.0,MeasurePerformance,coversthefollowingareas:,PreparedTeam,2.1Determinewhattomeasure,2.2ManageMeasurement,2.4DetermineSigmaperformance,2.3UnderstandVariation,2.5ExcellentTeamPerformance,4,VersionNov2002,Page,Summaryof2.0“MeasurePerformance”,2.1DetermineWhattoMeasureUnderstandtherolethatdataplaysinprocessimprovementUnderstandthecauseandeffectrelationshipsthatoccurinsidetheteamsprocessDeterminetheindicatorsneededtoevaluatecurrentprocessperformance2.2ManageMeasurementUnderstanddifferenttypesofdataandhoweachtypecanprovidetheteamwithdifferentinsightsandknowledgeofaprocessDevelopoperationaldefinitionsanddatacollectionplansthatbuildvalidityandconsistencyinthedatawhichtheteamgathers2.3UnderstandVariationUnderstandtheconceptofvariationandhowaprocesscanbeevaluatedbyassessingitsvariationovertimePlotandcalculatethevariationoftheteamsbusinessprocessGainhandsonexperiencewiththeuseofthestatisticalsoftwarepackageMINITABTM2.4DetermineSigmaPerformanceUnderstandthevariouscalculationsassociatedwithdeterminingprocesssigmaCalculatethesigmaperformanceoftheteamsprocessCalculatetherolled-upSigmaforthebusiness2.5ExcelTeamPerformanceUnderstandtheroleofhigh-performanceworkteamsinprocessimprovementUseteamdiagnosticsandassessmentstoevaluatetheteamstrengthsandopportunitiesforimprovingitsownperformance,MeasurePerformance-2.1,DetermineWhattoMeasure,6,VersionNov2002,Page,2.1DetermineWhattoMeasure,ObjectiveToidentifydifferenttypesofmeasuresandanunderstandingofhowthemeasuresrelatetocriticalcustomerrequirements.KeyTopicsPerformanceMeasurementInput,Process,andOutputIndicatorsIndicatorRelationships,7,VersionNov2002,Page,PerformanceMeasures-CustomerValueAchieved?,8,VersionNov2002,Page,ProcessElementsandIndicatorRelationships,Effectiveimprovementrequiresinformationfromtheentiresupplier-customer,causeandeffectrelationship.,Process,StartBoundary_,EndBoundary_,9,VersionNov2002,Page,Input,ProcessandOutputIndicators,EfficiencyMeasuresCostpertransactionTimeperactivityAmountofreworkTurnaroundtimeVariabilityofanactivity,EfficiencyMeasuresPercentdefectiveNumberoferrorsTotalresponsetimeInvoice/billingaccuracyRevenue,InputIndicators,ProcessIndicators,OutputPerformanceIndicators,CTQSCTPS,10,VersionNov2002,Page,ProcessOutputIndicatorsincludeCTQsthestandarddeviationofsis1.2minutes;andcriticalcustomerrequirementorCCRis10minutes.,116,VersionNov2002,Page,SigmaCalculationTable,*note:Thistabledoesnotincludea1.5shift.Ifyouenterthistablewithlong-termdatathenyoucalculatelong-termSigmaandifyouenterwithshort-termdatathenyoucalculateshort-termSigmaBothMotorolaandGECapitalassumethatyouentertheirAbridgedSigmaTablewithlong-termdataandexitwithashort-termSigma.Inordertodothis,theyassumeashiftof1.5Sigmabetweenshort-andlong-termSigma.Therefore,iflong-termyieldequatestoastandardnormalareaof4.5Sigma(or3.4DPMO)thentheyassumea1.5shiftandreportshort-termSigmaof6.0.,*,*,117,VersionNov2002,Page,UpperandLowerCCRs,118,VersionNov2002,Page,Combineintoasingleyield,CalculationsDefectsgreaterthanUSL=0.299(29.9%)AreafromzerotoUSL=1-0.299=(0.711(71.1%)DefectslessthanLSL=0.013(1.3%)AreafromzerotoLSL=0.013(1.3%)Yield=0.711-.013=0.70(70%)LookupYieldof0.70inSigmaTableZ=0.5(approximately),119,VersionNov2002,Page,4.CalculateSigmaPerformance,IContinuous,IIDPMOMethod,Discrete,VSigmaRoll-up,IIIHighVolume,IVLowVolume,CalculatingProcesssigma,Selecttheappropriatemethod,120,VersionNov2002,Page,BreakfastExample,Nowletsreviewanexampleofhowprocessoutputs,criticalcustomerrequirements,andthestandardnormaldistributionarecombinedtodeterminetheprocesssigma.Ahotelprovidesroomservicemealstoitsguests,andfromnumerousguestsurveysandresearch,hasdesignedaservicethatguaranteesabreakfastmealdeliverywithin10minutesofthetimerequestedbyitsguest.Theyhavedeterminedanearlydeliverywillinconveniencetheguestaswellasalatedelivery,especiallyinthemorning.Datafromaoneweekoperationhasbeengatheredandisshownhere.Whatistheprocesssigmaofthebreakfastdelivery?,100,0,Frequency,DeliveryTimeDeviation,LowCustomerLimit,UpperCustomerLimit,Target,Defects,121,VersionNov2002,Page,CalculatingSigmawithDiscreteData,Takinganotherlookatthe“BreakfastDelivery”datawevebeenusing,letsexamineaverydirectwaytocalculateprocessyield.Byexaminingtherawdata,wecancountthenumberofdeliverytimesthatdonotmeetcustomerrequirementsandtranslatethatdirectlyintoadefectcalculationreferredtoasDefectsPerMillionOpportunities,orDPMO。,122,VersionNov2002,Page,DPMODefined,DPMO=DefectsPerMillionOpportunities=1Mxwhere:D*=totalnumberofdefectscountedinthesample:adefectdefinedasfailuretomeetaCCRorCriticalCustomerRequirementN=numberofunitsofproductorserviceO=numberofopportunitiesperunitofproductorserviceforacustomerdefecttooccurM=million*Theremustbeatleast5defectsand5non-defectstousetheDPMOformula.,123,VersionNov2002,Page,DPMOExample,Usingthepreviousexample,letscalculatetheDPMOandtheprocesssigmaUsingthismethodfromthedatasetonbreakfastdeliverytimes:D=205N=725O=1(Thereisonlyoneopportunityforadefectperbreakfastdelivery.Eitherthedeliveryiswithinthecustomerlimitsornot.)DPMO=UsingtheSigmaCalculationtable,entertheDPMOcolumnandlookuptheprocesssigmadirectly.TherelationshipbetweenDPMOandprocesssigmaisasfollows:ProcessYield=1-DPUWhereDPU=Defects/unitInourexample,ProcessYield=1-.2826=0.7174or71.74%sigma=.058,124,VersionNov2002,Page,SigmaCalculationforBreakfastExample,Objective:TopracticecalculatingSigmaInformationProvided:Mean=5minutesStandard=10minutesUSL=+10minutesLSL=-10minutesQ.DeterminetheSigmaforcontinuousdata,125,VersionNov2002,Page,ReviewandTransition,In2.4DetermineSigmaPerformance,welearned:Thevariouscalculationsassociatedwithdeterminingprocesssigma.Howtocalculatethesigmaperformanceoftheteamsprocess.In2.5,ExcelTeamPerformance,wewilllearn:Theroleofhigh-performanceworkteamsinprocessimprovement.Howtouseteamdiagnosticsandassessmentstoevaluatetheteamstrengthsandopportunitiesforimprovingitsownperformance.,ProcessPerformanceBasedonCustomerRequirement,MeasurePerformance2.5,ExcelTeamPerformance,127,VersionNov2002,Page,2.5ExcelTeamPerformance,ObjectiveToenabletheteamtoreachahighlevelofperformancefullyutilizingteammemberskills,knowledge,andexperienceworkingcollaboratively.KeyTopicsNormingStageTeamingTechniquesPerformingStage,ProductiveTeamAtmosphere,128,VersionNov2002,Page,Summaryof2.0“MeasurePerformance”,2.1DetermineWhattoMeasureUnderstandtherolethatdataplaysinprocessimprovementUnderstandthecauseandeffectrelationshipsthatoccurinsidetheteamsprocessDeterminetheindicatorsneededtoevaluatecurrentprocessperformance2.2ManageMeasurementUnderstanddifferenttypesofdataandhoweachtypecanprovidetheteamwithdifferentinsightsandknowledgeofaprocessDevelopoperationaldefinitionsanddatacollectionplansthatbuildvalidityandconsistencyinthedatawhichtheteamgathers2.3understandVariationUnderstandtheconceptofvariationandhowaprocesscanbeevaluatedbyassessingitsvariationovertimePlotandcalculatethevariationoftheteamsbusinessprocessGain
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