数据挖掘在管理会计中运用的重要意义The significance of data mining in management accounting.docx
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数据挖掘在管理会计中运用的重要意义The significance of data mining in management accounting.docx
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数据挖掘在管理会计中运用的重要意义Thesignificanceofdatamininginmanagementaccounting
数据挖掘在管理会计中运用的重要意义(Thesignificanceofdatamininginmanagementaccounting)
Abstract:
dataminingistheprocessofdiscoveringandextractingknowledgeandinformationfromhugeamountsofdata.Applicationofdataminingtechnologyinthefieldofmanagementaccounting,seekandfindmorebusinesscustomers,suppliers,marketandinternalprocessoptimizationinformationforenterprisedecisionmakerstoprovidemoreextensiveandeffectivedecisionmaking,improvethestrategiccompetitionability.Thispaperbrieflyintroducesthebasicconceptsandmethodsofdatamining,basedontheanalysisofdataminingtechnologyintheroleofcostandvaluechain,applicationproducts,customersandmarketanalysisandfinancialriskpreventionetc..
Datamining,informationmanagement,accountingapplication
Introduction
Inrecentyears,dataminingtechnologyhasattractedgreatattentioninthefieldofinformationindustry,themainreasonisthattherearealotofdata,canbewidelyused,andisinurgentneedofthesedataintousefulinformationandknowledge.AccordingtotheGAO(GeneralAccountingOffice)report,thefederalgovernmenthasplayedahugeroleinimprovingthelevelofgovernmentservices,analysisofscientificdata,humanresourcemanagementandsurveillanceofcriminalandterroristactivitiesbyusingdataminingtechnology.Especiallyafter9~11,theUnitedStatesanti-terrorismactivitiesneedtosearchforusefulinformationfromalargeamountofdata,anddataminingtechnologycannotbedonewithout.Inaddition,dataminingisalsowidelyusedincommercialactivities.AccordingtoThomasG,John,J,andIl-woonKim'ssurveyofCFO,afortune500company,65%ofcompaniesareusingdataminingtechnologyinthecontextofeffectivefeedbackreceived.Companiesthatsupportdataminingsaytheefficientuseofdataminingtechnologycancreate2000to24millionofcorporateprofits.Inthesurveyoftheuseofdatamining,wefound:
24%usedinthefieldofaccounting,42%usedinthefinancialsector,usedininformationsystemsandmarketareasaccountedfor19%and5%,respectively.Atpresent,theapplicationofdataminingtechnologyismoreconcentratedinfinance,insurance,healthcare,retailandtelecommunicationssectors.Andtheapplicationofdatamininginimprovingenterpriseinternalmanagementandbuildingcompetitiveadvantagesofenterprisesisrarelymentioned.
First,themeaningofdataminingtechnology
Dataminingistheprocessofdiscoveringtrendsandpatternsfromdata.Itcombinesmultidisciplinaryknowledgesuchasmodernstatistics,knowledgeinformationsystems,machinelearning,decisiontheory,anddatabasemanagement.Itcaneffectivelyfromlarge,incomplete,fuzzydata,extractusefulinformationandknowledgewhichrevealthecomplexandhiddenrelationshipsinalargeamountofdata,provideausefulreferencefordecisionmaking.
Two,dataminingmethodsandbasicsteps
(1)themainmethodsofdatamining
Amajordecisiontreedataminingmethodcommonlyused(DecisionTree),geneticalgorithm(GeneticAlgorithms)(AssociationAnalysis),correlationanalysis,clusteranalysis(ClusterAnalysis),sequencepatternanalysis(SequentialPattern)andneuralnetwork(NeuralNetworks).
(two)basicstepsofdatamining
SEMMASASmethodproposedisapopulardataminingmethod,thegeneralprocessofdataminingisdescribedincludingsampling(Sample),(Explore),toexplorethechanges(Modify),model(Model)andevaluation(Assess).
1.datasampling
Beforedatamining,wemustselecttherelevantdatabaseaccordingtothetargetofdatamining.Samplingbycreatingoneormoredatatables.Thesampleddataislargeenoughtocontainmeaningfulinformationandnottoolargetohandle.
2.dataexploration
Thedataexplorationprocessiscarriedoutin-depthinvestigationofthedata,throughathoroughinspectionofthedatatofindhiddeninthedataintheexpectedorunexpectedrelationshipandabnormal,soastoobtaintheunderstandingofthingsandconcepts.
3.dataadjustment
Onthebasisoftheabovetwosteps,thedataisaddedanddeletedandmodifiedtomakeitmoreexplicitandeffective.
4.modeling
Usingartificialneuralnetworks,regressionanalysis,decisiontree,timeseriesanalysistoolstobuildmodel,fromthedatafoundthatthosewhocanpredicttheresultsofreliablepredictionmodel.
5.evaluation
Istoassesstheusefulnessandreliabilityoftheinformationfoundinthedataminingprocess.
Three,theapplicationofdatamininginmanagementaccounting
(1)theimportanceofdatamininginmanagementaccounting
1.providestrongdecisionsupport
Facingtheincreasinglyfiercecompetitionenvironment,enterprisemanagershavemoreandmorehighdemandfordecision-makinginformation.
Managementaccounting,asanimportantcomponentofenterprisedecisionsupportsystem,providesmoreandmoreeffectiveusefulinformation.Therefore,miningandseekingknowledgeandinformationfromvastamountsofdataandprovidingstrongsupportfordecision-makinghasbecomeapowerfuldrivingforceformanagementaccountantstousedatamining.Forexample,dataminingcanhelpcompaniesstrengthencostmanagement,improveproductandservicequality,increasethesalesratioofgoods,designbettertransportationanddistributionstrategies,andreducebusinesscosts.
2.,apowerfulweapontowinstrategiccompetitiveadvantage
Practicehasprovedthatdataminingcannotonlysignificantlyimprovetheinternalprocess,butalsotoanalyzethecompetitiveenvironment,market,customersandsuppliersfromastrategicheight,toobtainvaluablebusinessintelligence,maintainandimprovetheenterprisecompetitiveadvantage.Forexample,thecustomervalueanalysiscandistinguishbetween20%ofthecustomerswhocreate80%ofthevalueoftheenterprise,andprovidebetterservicestomaintainthispartofthecustomer.
3.preventionandcontroloffinancialrisks
Usingdataminingtechnology,wecansetuptheearly-warningmodelofenterprisefinancialrisk.Theoccurrenceofenterprisefinancialriskisnotastepbystep,butanaccumulationandgradualprocess.Bysettinguptheearly-warningmodeloffinancialrisk,wecanmonitortheenterprise'sfinancialsituationatanytimeandpreventtheoccurrenceoffinancialcrisis.Inaddition,wecanalsousedataminingtechnologytomonitorthebehaviorofenterprisesintheprocessoffinancingandinvestment,topreventmaliciouscommercialfraud,andtosafeguardtheinterestsofenterprises.Especiallyinfinancialenterprises,throughdatamining,youcansolvethebankingindustryfacessuchascreditcardmaliciousoverdraftandsuspiciouscreditcardtransactionsfraud.AccordingtotheSECreport,severalbanks,suchasBankofAmerica,America'sfirstbankandFederalHomeLoanMortageCorporation,haveadopteddataminingtechniques.(two)applicationofdatamininginmanagementaccounting
1.activity-basedcostingandvaluechainanalysis
ABChasattractedgreatinterestbecauseofitsaccuratecalculationofcostsandthefulluseofresources,butitscomplexoperationshavedeterredmanymanagers.Themethodsofregressionanalysisandclassificationanalysisindataminingcanhelpmanagementaccountantsdeterminecostdriversandcalculatecostmoreaccurately.Atthesametime,wecanalsoanalyzetherelationshipbetweenoperationandvaluetodeterminevalue-addedactivitiesandnonvalueaddedoperations,andcontinuouslyimproveandoptimizetheenterprisevaluechain.InthesurveyofThomas,G,John,JandIl-woonKim,dataminingwasusedinactivity-basedcostingmanagement,accountingforonly3%.
2.forecastanalysis
ManagementAccountantsinmanycasesneedtopredictthefuture,whichisbasedonalargeamountofhistoricaldataandappropriatemodels.Dataminingautomaticallysearchesforpredictiveinformationinlargedatabases,usingtrendanalysis,timeseriesanalysismethod,tosetupaforecastingmodelsuchassales,cost,capital,scientificandaccuratepredictionofcorporateindicators,asabasisfordecision-making.Forexample,theanalysisofmarketsurveydatacanhelppredictsales;accordingtohistoricaldata,theestablishmentofsalesforecastingmodel.
3.investmentdecisionanalysis
Investmentdecisionanalysisitselfisaverycomplexprocess,oftenwiththeaidofanumberoftoolsandmodels.Dataminingtechnologyprovidesaneffectivetool.Fromthecompany'sfinancialreports,macroeconomicenvironmentandthebasicsituationoftheindustryandotherlargeamountsofdata,mininganddecision-makingrelatedsubstantiveinformation,toensurethecorrectnessandeffectivenessofinvestmentdecisions.Suchastheuseoftimeseriesanalysismodeltopredictstockpricesforinvestment;onlineanalysisandprocessingtechnologytoanalyzethecompany'screditrating,inordertopreventinvestmentrisks.
4.customerrelationshipmanagement
Customerrelationshipmanagementisapowerfulweapontoenhancethecompetitiveadvantageofenterprises.First,classifythecustomergroups.Throughclassificationandclusteringanalysisofthedatawarehouse,canfindthebehaviorofcustomergroups,whicharegroupedtocustomers,theimplementationofdifferentiatedservice;secondly,toanalyzethecustomervalue,accordingtoPareto'slaw,20%ofcustomerscreateenterprisevalueof80%.Inviewofthissituation,thecompanycandigoutthispartofthecustomerfromthecustomerdatabase,thispartofthecustomerbehavior,demandandpreferencefordynamictrackingandmonitoring,andprovidethecorrespondingproductsandservicesaccordingtodifferentcharacteristicsofdifferentcustomers,andestablish
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