[Webinar Slides] How to Increase Your Profits by Improving Your Data Accuracy
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Transcript of [Webinar Slides] How to Increase Your Profits by Improving Your Data Accuracy
Underwri(enby: Presentedby:
#AIIMInforma(onIsYourMostImportantAsset.LearntheSkillstoManageIt.
Underwri(enby: Presentedby:
HowtoIncreaseYourProfitsbyImprovingYourDataAccuracy
PresentedMarch7,2017
Underwri(enby: Presentedby:
SethMaislinPrincipalConsultantEarleyInforma(on
Science
GregCouncilVP,Marke4ng&
ProductManagementParascript
Host:TheresaResek,CIPDirectorAIIM
Today’sSpeakers
Underwri(enby: Presentedby:
SethMaislin
PrincipalConsultant
EarleyInforma(onScience
IntroducingourSpeaker
Underwri(enby: Presentedby:
Qualityvs.Profitability:AnObserva(on
Features:• poordata=businessloss• diminishingreturns• “goodenough”exists• culturema(ers
Underwri(enby: Presentedby:
Correla(onorCausa(on?
§ MostorganizaKonsacknowledgethecorrelaKonbetweendataqualityandbusinessvalue,butfewcansaywhichmetricsofdataqualitymaRermost.
§ Withdata,“goodenough”isastrategicchoice.
Ifyoucanextract… Thenyoucanimprove…
zipcodes geographicalanalysis
namesofdependents frauddetecKon
dollaramounts arithmeKcvalidaKon,workflow
everythingoverKme UnitedStatestaxandfinancialsystems
anything savings,speed,capability,growth,…
U.S.FederalTaxForm
Underwri(enby: Presentedby:
GoverningData“ARrac(veness”
§ DataqualityismulKdimensional.§ Whichfeaturesma(ermost?Why?(Howdoyousettargets?)§ It’snearlyimpossibletoopKmizealldimensionsatonce.
• accurate• available• certain/precise• clean• complete• consistentacrosssources
• integrity
• formaRed(conformity)
• reasonable/logical• relevant/valid• reliable• (mely/current• traceable/audited
Underwri(enby: Presentedby:
Underwri(enby: Presentedby:
DataIsanAsset
• somethingyoucansell• directinputforabusinessprocess• contextualinputformakingabusinessdecision• workflowtrigger• macro-levelself-awareness(governance)
Toknowifyourdataaregoodenough,youdon’tmeasurethedata.Youmeasureitseffects.
DatagovernancerequiresanintegratedsystemofmetricsandKPIs.
Underwri(enby: Presentedby:
ProcessesenableobjecKves
LINKAGE
EnterpriseStrategy RevenueGrowth
Contentsupportsprocesses
ObjecKvesalignwithstrategy
CEO:“Howwillthisincreaserevenue?”
BusinessProcessesMeasuringhere
(processindicators) Sessions SearchRelevance
Leads ConversionRatesProcessScorecards
BusinessUnitObjecKves
Measuringhere(businessoutcomes)
NewBusinessOpportuni(es
AverageOrderSize TotalAccountRevenue
OutcomeScorecards
DigitalTeam:“HowdoIknowtaxonomy/content/searchisworking?”
DigitalContent
Working&Measuringhere(content,IA,taxonomy,search,productdata,etc.) Site
Search
DigitalContent&SEO
WebAnaly(cs
ContentScorecards
CTR DataFill Content etc.
Metrics&KPIsFocusGovernance
Underwri(enby: Presentedby:
GedngDataQualitytoPayOff
EnterpriseStrategy
BusinessProcesses
BusinessUnitObjecKves
DigitalContent
• deliverables quality• goodreturnonITspending cost/profit• increasedthroughput growth• prioriKzedteambehaviors produc4vity• errorreducKon/compliance liability
LINKAGE
• brandpercepKon,reputaKon quality• revenuedollars cost/profit• customers,marketshare growth• businessstrategyrealizaKon produc4vity• marketawareness liability
Underwri(enby: Presentedby:
UseCases:HowtoLeverageFinancialData
• accurateandKmelyaccountsmanagement• be(erspendalignmentwithbusinessstrategy;innovaKonrecogniKon• improveddecisionmakingfromdata-drivenROI;smarterR&D• acKveassetmanagement(human,technology,physical,digital)• smartbusinessculturedesign• intelligentassetandpartneracquisiKon,compeKKveprocurement• strongriskmanagement• improvedcompliance• customerandmarketplaceintelligence(correlaKons,shocks,trends,gaps)• streamlinedoperaKons
Underwri(enby: Presentedby:
Buildingthelinkageisthehardestpart.
1. Establishasystemofcompany-widegovernance.§ IdenKfyandunderstandthecompany’sdatadomains§ DocumentprocessesandassignaccountabiliKes§ EstablishaCenterofDataExcellence,andsocialize§ Implementmetricstomeasuregovernanceitself
2. Decidewhatma(ersatyourlevel.§ KnowthestrategicKPIsforeachpartofthebusiness§ IdenKfygapsbetweenexisKngandnecessarymetrics§ Inventoryandprofileyourdata;calculatebaselines§ SettargetscollaboraKvelyandfindsynergies
3. Buildyourdataprojectsroadmap.
LINKAGE
Underwri(enby: Presentedby:
OtherResourcesandContact
§ TheEvolvingRoleoftheChiefDataOfficer:IncreasingInfluenceintheC-suite(on-demandwebcast)
§ DigitalGovernance:It’saNumbersGame(Metrics,KPI’s,andROI,thatis)(arKcle)
781-775-0684@sethmaislin
www.earley.com
Underwri(enby: Presentedby:
GregCouncil
VP,Marke(ng&ProductManagement
Parascript
IntroducingourSpeaker
Underwri(enby: Presentedby:
Func(onalandPerformanceAbili(es
FUNCTIONALABILITYPERFORMANCEABILITY
SystemDataFlow
Underwri(enby: Presentedby:
Observa(onsandQues(ons
PERFORMANCEABILITY
ManyorganizaKonsfocustoomuchonfunc8onalcapabiliKesofthesystem,andnottheperformanceofthesystem.
§ Whatistheerrorrateofyourstaff?§ Whatistheerrorrateofyoursystems?§ Whatistheactualuplio/costcreatedbyyoursystems?
Isitwrongtoask“howaccurateisyoursystem”?(Forexample,OCRaccuracy?)
§ YesandNo–Knowwhattoaskfor
Whatisthebestwaytomeasureperformance,andhowcanhighperformancebeachieved?
SystemDataFlow
Underwri(enby: Presentedby:
Func(onal:HowtoAssignDocumentstoTypes
UsingVisualElements
TextstaKsKcallyorbasedonNLP
BusinessRulesManualvsAutomated
FUNCTIONALCAPABILITIES
Underwri(enby: Presentedby:
Func(onal:RangeofDataSupported
Languagesthatcanbesupported
Typesofdatasupported
Formats:text,constrainedhandprint,unconstrainedhandwriKng,electronic,image-based
Structure:standardized,parKallystandardized,
nostandard
RANGEOFDATASUPPORTED
Underwri(enby: Presentedby:
Self-DrivingCars&ManualVerifica(on
…AndcompaniessKllmanuallyverifytheirrecogniKon
results?
Underwri(enby: Presentedby:
WRONGWAY-ManualDataEntry
RECOGNITION
INPUTIMAGES
MANUALDATAVERIFICATION&MANUALENTRY
Underwri(enby: Presentedby:
RIGHTWAY:FullAutoma(on
ACCEPTED
99.5%CORRECT
INPUTIMAGES
Error
RECOGNITION
Underwri(enby: Presentedby:Underwri(enby: Presentedby:
Discussing“Accuracy”
§ IsOCRaccuracyrelevant?Yesbut….• Itdoesn’ttellyoudata-levelerrorofasystem;typicallyonlycharacter-levelaccuracy.• Itdoesn’tinformyouofthecostsavingsorproducKvitygains.
o Forexample,“HowmanydataelementsdonotrequireanyintervenKonorreview?”
§ YourdataaccuracyisnotthesameastheOCRaccuracy.
§ Most(orallof)OCRaccuracyismeasuredatthecharacterlevel.
§ Yourformdataisimportantatawordorfieldlevel.
IfOCRoutputis99%accurateatthecharacterlevel,thenconsideringapagewith500wordswithanaverageof6le(ersperword,30characterswillbeincorrect.Those30errorscanbedistributedacrossmulKplewordsleadingtoahigheractualerrorrate.Aword-levelerrorratecouldbe6%,not1%.Ifpartofthe6%
errorincludesanaccountnumberofSSN,that’sabigproblem.
Underwri(enby: Presentedby:
GedngatActualDataAccuracy
Howmuchdataislocatedandwhatistheerrorratefield-by-field?WiththisinformaKon,youcanhaveasolidunderstandingofgains.
§ SSNhasareadrateof85%anderrorof.5%translatesto:Only15%ofdatarequiresanyreviewatall.
§ Theremaindercangostraightthrough.
READ
RAT
E
ERRORRATE
100%
100%
Confidencethreshold=15
Confidencethreshold=50
FuncKonal-onlySystem
SSN OtherData
Underwri(enby: Presentedby:
WhenItComestoPerformance
PERFORMANCEABILITY
Classifica(on:§ Recallandprecision.AdocumentclassifierwillnotcorrectlyidenKfy
alldocumentsandperformanceiskey.• Precision(Relevance).IfthesystemidenKfied8invoicesinabatchof20
documents,where5arecorrectand3areincorrect,precisionis5/8or62.5%.
• Recall(Completeness).Iftherewereactually15invoicesinthebatchof20,recallis5/15or33.3%
DataLoca(on/Extrac(on:§ ReadRate.Thepercentageofdatathatislocatedandextracted.§ ErrorRate.Thepercentageofthatlocated/extracteddatathatisnot
correct.§ ConfidenceThreshold.ThestaKsKcally-significantpointthatallowsfor
datatomovestraightthroughthesystem.§ Allatthedataelementlevel
SystemDataFlow
Underwri(enby: Presentedby:
TechnologyKnowhow&StaffExper(se
SignificantuniqueexperiencewithAIandpa(ernrecogniKonexperKsethatsetstheteamapart.
AppliedExperKse ExperKseLevel DomainExperKseY
AbilitytoperformsophisKcatedanalysisofdocuments,datasets,anddevelopsoluKonswithtunedperformance.
In-depthexperiencewithdataextracKondeploymentsandtrackrecordofdeliveringhighqualityresultson-Kme.
TypicalsoowarevendorsuseinformaKonsystemsandsoowaredevelopmentstaffwithgeneralsoowareskillstobuildsoluKons What to Look For:
Underwri(enby: Presentedby:
ParascriptEnterpriseEnablementProgram
EnterpriseEnablement
IdenKfydiscrepanciesbetweendataqualityexpectaKonsandrealresults
Implementconsistentmeasurementsthroughouttheworkflowprocessforongoingdataqualityassessments
Fillthegapsinthecurrentdeliverymodel,opKmizeprocessestoensurehigh-qualitydataresultsandincreaseefficiencyofoperaKons
MonitorResults
Underwri(enby: Presentedby:
ParascriptAcceleratorProgramforBPOsMonitorResults
SignificantlyreducecoststhroughautomaKonofdataentry-intensiveprocessesusingprecisiontechnologyandaprovenconsultaKveapproachthatidenKfiesbaselineperformanceandconcrete,acKonableareasforperformanceimprovement.
Herearethephasesoftheprogram:
1. Onsitediscovery2. Baselineperformanceanalysis3. CostreducKonopportunityidenKficaKon
4. Businessacceleratoranalysisreportdelivery5. Comprehensivein-personbriefingoftheresults
Underwri(enby: Presentedby:
ThankYou!
GregCouncilVicePresident
Marke(ng&ProductManagement
888-225-0169
Underwri(enby: Presentedby:
WanttoLearnMore?
www.parascript.com
(888)225-0169
YOURSOLUTIONSTRANSFORMBUSINESSES.LETOURSOLUTIONSDELIVERYOURDATA.
Underwri(enby: Presentedby:
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Visit:AIIM.org/CaptureTraining
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AIIMbelievesthatinforma(onisyourmostimportantasset.Learntheskillstomanageit.
OurmissionistoimproveorganizaKonal
performancebyempoweringacommunityofleaderscommi(edto
informaKon-driveninnovaKon.
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