1IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGContentsofModuleVIntroductionDecision-making•Decisiontree•GametheoryLong-termscenarios•Scenarioplanning•EndgameGenericstrategyframeworks•Threegenericstrategies•Gainingstrategicadvantage•Thegrowthmatrix2IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGDecision-makingtechniquesareusefulforselectingamongstrategicalternativesSource:A.T.KearneyDecisionMakingTechniquesAlternative#1Alternative#2Alternative#3OptimalsolutionfortheclientDecision-makingIntroduction3IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGTheoptimalsolutionmustbehighlysatisfactoryalongtwomaindimensionsValuecreationOptimalsolutionHighLowLowHighCoherencewithclient/shareholdercriteriaSource:A.T.KearneyDecision-makingIntroduction4IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGContentsofModuleVIntroductionDecision-making•Decisiontree•GametheoryLong-termscenarios•Scenarioplanning•EndgameGenericstrategyframeworks•Threegenericstrategies•Gainingstrategicadvantage•Thegrowthmatrix5IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGAdecisiontreeisusefulforvisualizingacompany’sbusinessdecisionsandcategoricallyconsideringalllogicalpossibilitiesassociatedwiththemDefinition•Anillustration,inasequentialform,ofthedecisionsfacedbyacompanyinagivensituation,withexpectedpayoffsandprobabilitiesassociatedwiththepotentialoutcomeofeachdecision•AquantitativemethodofanalyzingandevaluatingavailablealternativesSource:A.T.KearneyDescriptionDecisiontreeDecision-making6IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGDecisiontreesenableacomprehensiveandthoroughevaluationofavailablealternativesSource:A.T.Kearney;Bird,M.(1992);ProblemSolvingTechniquesthatReallyWorkUsefulwhen•Twoormorecoursesofactionexist•Onechoicecanresultinalternativechoices•ExpectedresultsamongchoicesvarygreatlyintermsoflikelihoodordurabilityIllustratingasequenceofdecisionsandresultingeventsAnalyzingandevaluatingavailableoptionsEvaluatingpotentialactions/reactionsofcompetitorsEvaluatingtheeconomicsofabusinessplanReviewingafunctionalstrategyImposingdisciplineonthestrategicplanningfocusesBriefingcolleaguesaboutasequenceofdecisionsSuchasUsageDecisiontreeDecision-making7IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGAdecisiontreecanbeusedqualitativelytoillustrateasequenceofdecisionsSource:A.T.Kearney;Moore,P.G.(1983);TheBusinessofRisk3AnautomakerdecideswhetherornottoinvestUSD130,000inaoneyearR&DprojecttodevelopanewproductlineSource:A.T.KearneyAX0BMediummarket(0.3)ZHighpayoffHighpayoffModeratelossVeryhighpayoffLowlossLargelossMediummarket(0.3)Outcomenodes-USD130kQualitativeassessmentsofoutcomesaremadeasthistreeservestoillustratechoicesandtostructurethinkingNotethatdecisionnodesaremarkedbysquares,andoutcomenodesbycirclesThesumoftheprobabilitiesshouldequalone,asallpossibilitiesshouldbeshownAmountreflectstheinvestmentinR&DDecisionnodesYExampleDecisiontreeDecision-making8IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGAdecisiontreecanalsobeusedquantitativelytovalueasequenceofdecisions*EMV=estimatedmonetaryvalueSource:A.T.Kearney;Moore,P.G.(1983);TheBusinessofRisk3AnautomakerdecideswhetherornottoinvestUSD130,000inaoneyearR&DprojectSource:A.T.KearneyAX0BYZ170k=-130k-200k+500k170k=-130k-200k+500k-80k=-130k-200k+250k470k=-130k-400k+1,000k-30k=-130k-400k+500k-280k=-130k-400k+250kDecisiontoproceedtooutcome50k=0.6(170k)+0.4(-130k)170k=0.5(470)+0.3(-30)+0.2(-280)DecisiontoproceedtooutcomeY(notZ)DecisionnodesOutcomenodesPVofnetcashflowsoflifeoftheplant:Highmarket=1,000kMediummarket=500kLowmarket=250kMediummarket(0.3)Mediummarket(0.3)USD50kUSD50kUSD170kUSD170kUSD90k-USD130k90k=0.5(170)+0.3(170)+0.2(-80)Begincalculationattheendofthetree,findingtheEMV*ofeachpossibleoutcomeCalculatethevalueatoutcomenodesbysummingtheEMVofthepossibleoutcomes.WeighttheoutcomesbytheirprobabilitiesThevalueofadecisionnodeisequaltothegreatestEMVofthefollowingoutcomenodesBecausetheEMVforthefirstdecisionnodeisgreaterthanzero,thedecisionismadetogoaheadwiththeR&DprojectExampleDecisiontreeDecision-makingCostofaplant:Largeplant=400kSmallplant=200kCostofR&D(sunk)=130k9IntroductionA.T.KEARNEYBUSINESSUNITSTRATEGYTRAININGMethodologyforusingadecisiontree1Gatherandgroupdata2Sequencedecisions3Interpret4SensitivityanalysisInputOutput•Allcriticaldecisionsintheplanningperiodforaspecificissuemustbeincluded-thedatashouldbeexhaustivewithrespecttotheconsideredalternatives•Applyprobabilitiesandvaluestothealternatives•Themainissueisthefirstnode,witheachbranchstemmingfromthenoderepresentinganalternative•Theprocessisappliedsequentiallyfromlefttoright,untilallofthepossiblefinaloutcomesandrelatedpay-offsarereached•Probabilitiesassignedtobranchesstemmingfromonenodemustaddupto1(andalternativesmustbeexhaustive)•Foreveryoutcomenodecomputetheexpectedpay-offsastheproductoftheexpectedvalueandprobability•Foreverydecisionnodechoosetheoutcomenodewiththehighestexpectedpay-off•Determinetheroutewiththehighestpay-off•Studythevariabilityofthejudgementsmadealongthetree•Reexaminethemostsubjectivecomponents•Alterth