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2017 DATA MANAGEMENTINDUSTRY BENCHMARK SUMMARY
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DATA MANAGEMENT ASSESSMENT 2017
The 2017 benchmarking study consists of 22 DCAM-derived questions that highlight the most essential concepts in data management. The results include comparison to the previous study performed in 2015.
Participants included the full spectrum of financial services companies (universal, buy, sell, asset servicing, insurance) with an emphasis on G-SIBs and Tier 1 firms. We hand selected a “control group” of companies that we knew had demonstrated an organizational commitment to data management as the baseline for evaluating overall industry progress.
The good news is that the financial industry has made steady progress in establishing data management programs and implementing foundational governance. Data management is a “known objective” and the strategies and organizational structures are advancing. But beyond regulatory compliance and BCBS 239 adherence, questions still remain about the “why” of data management.
We acknowledge the industry’s efforts in working to establish data management as a core operational requirement. We have created a functional collaboration with IT and with the other control functions. The industry has made headway on governance-related mechanisms (i.e. setting up the ODM, implementing policies, establishing stewardship functions) and all are hard at work mapping lineage, reconciling glossaries, identifying CDEs and documenting data flows.
The results are not so encouraging from a “fix the data” perspective. Many firms are making some progress using labor-intensive (short-term)
approaches that fill immediate needs by pulling data from standard file paths that unfortunately break because data is not aligned to meaning … it resides in multiple repositories (often with little documentation) … and it is held together by rigid legacy systems with fragile business logic. The result is that we are collectively adding more strings to the Gordian Knot - and we are hesitant to change these vertically aligned systems for fear of creating operational chaos.
Many firms are still mired in tactical mapping of data from physical repositories to applications and reports – and we have not yet escaped from the tyranny of manual reconciliation. Trust and confidence remains the elusive goal of data management – and are still the essential prerequisites for both reporting and business analytics. Without adopting a trusted and harmonized content infrastructure, there is little point to implementing data policy and governance.
There are clearly some bright spots for the practice of data management. We have made progress in overcoming the inertia of organizational change management. But the underlying truth remains. We can’t respond to regulatory pressure, achieve automation or put data to work until we fix the underlying data challenges. The EDM Council believes these obstacles can be addressed.
Michael Atkin, Managing Director EDM Council, June 2017
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BENCHMARKING PROFILE (NEW)
ProfileSummary
• More consolidatedresponses:betterreflectionoffirm-widecapability
• ControlGroup(organizationalcommitment)andbuy-side(learnfromindustryexperience)showconsistentprogress
• G-SIBs= scoresdownoverall(gradingwithmorerigorbasedonexperience)
• AssetServicing=continuetoleadasthedatamanagementstarsoftheindustry
• Overall understanding ofdatamanagementlowerthanexpected(outsideofrisk)
• Globalcoveragesupportsfederatedgovernance(empoweringregionaldatateams)
• Enterprise-widescopeisapositiveindicatorthatdataisasharedresourceacrossthefulllifecycle(althoughdatamanagementisstillsilo-based)
7%
21%
72%
No Formal Program LOB, Group, DivisionEnterprise-Wide
86%
14%
76%
24%
79%
21%
Global Regional
2%
7%
10%
12%
24%
45%
InsuranceAsset Serving
Buy-SideRetail/Commerical …
Sell-SideUniverisal Bank
Control
General
Industry
ProgramScope ProgramRegion
2%
22%
76%
9%
20%
71%
5%
6%
13%
19%
19%
38%
Insurance
Asset Serving
Sell-Side
Retail/Commerical Bank
Buy-Side
Univerisal Bank
5%
8%
10%
21%
22%
34%
Asset Serving
Insurance
Sell-Side
Retail/Commerical Bank
Buy-Side
Univerisal Bank
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BENCHMARKING PROFILE (CONTINUED)
Control
General
Industry
3%
15%
51%
31%
NotActive
Planning
Formed
FullyOperational
3%
17%
52%
28%
NotActive
Planning
Formed
FullyOperational
0%
9%
45%
46%
NotActive
Planning
Formed
FullyOperational
GovernanceImplemented
9% 22%
19% 5%
10% 35%
0%
Risk
Other
Operations
Marketing
LineofBusiness
InformationTechnology
Finance
14% 10%
32% 1% 0%
31% 6%
Risk
Other
Operations
Marketing
LineofBusiness
InformationTechnology
Finance
13% 14%
28% 2%
7% 32%
4%
Risk
Other
Operations
Marketing
LineofBusiness
InformationTechnology
Finance
WheretheCDOResides
73%
27%
FundingModel
Annual Multi-Annual
54%
49%
50%
21%
25%
24%
25%
26%
26%
Industry
General
Control
ProgramFunding
CorporateFunding
LOBCont
Project-Based
14%
21%
19%
67%
53%
58%
14%
22%
19%
Industry
General
Control
CDOLengthofTime
<1Year
1-3Years
>3Years
14%
21%
19%
67%
53%
58%
14%
22%
19%
5%
4%
4%
Industry
General
Control
ODMYearsofOperation
<1Year
1-3Years
>3Years
5+Years
100%
81%
86%
19%
14%
Industry
General
Control
OfficeOfDataManagement
Yes
No
23%16%
Control Industry
GlossaryOperation
70%ofthe
IndustrygrouphasaChiefDataOfficer
90%ofthe
ControlgrouphasaChiefDataOfficer
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DATA MANAGEMENT DRIVERS
DataManagementDrivers(citedasaprimarydriver) Control General Industry1. RiskManagement(BCBS239/FRTB)BCBS 69% 65% 66%2. TrustinData(fit-for-purpose)BCBS 60% 58% 59%3. OtherRegulatory(GDPR/KYC) 36% 38% 38%4. OperationalEfficiency(costcontainment/automation) 26% 43% 38%5. BusinessInsight(analytics) 40% 36% 37%6. StressTesting(CCAR,BaselIII) 41% 36% 37%7. Transparency(derivatives,CATS,MiFID)BCBS 17% 24% 22%
• Data Quality: trusted and fit-for-purpose data is the primary objective of data management• Analytics: If you have to fix your data for regulatory purposes, do it right and get business value• Efficiency: Cost containment is a by-product of good data management, not a driver• Regulation: most regulatory goals have the same data management prerequisites (precise
identification, shared language based on obligation, ability to unravel aggregates, ability to analyze interdependencies, creation of links across processes)
Systemic Risk à Stress Testing à Exposure à Concentration à Collateral Flow à Best Execution à Real-Time Valuation à Audit Trails à Privacy
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DATA MANAGEMENT PRIORITIES
DataManagementPriorities(highpriority) Control General Industry
1. DefiningCDEsBCBS(complexanddependentonapplication) 71% 75% 74%2. ImprovingDataQualityBCBS(manualreconciliationisstillaproblem) 69% 72% 71%3. GovernanceImplementationBCBS(precipiceofimplementation) 64% 74% 71%4. Roles&ResponsibilitiesBCBS(needcompetenceholdingthereins) 59% 63% 62%5. EnterpriseGlossaryBCBS(fundamental(apriori)pre-requisite) 67% 59% 61%6. ImplementingPolicyBCBS(datamanagementenforcedbypolicy) 50% 62% 58%7. DocumentingLineageBCBS(untanglingtheGordianKnotissignificant) 71% 52% 57%8. Metrics(essentialforsustainablecommitment) 55% 46% 48%9. CommitmentfromStakeholders(commitmentindangerofwaning) 50% 47% 48%10. ImplementingStewardshipBCBS(datamanagementperformedbyLOB) 40% 50% 47%11. ResolvingPainPoints 45% 44% 44%12. EcosystemCollaboration 38% 44% 42%13. TechnicalIntegrationBCBS 36% 36% 36%14. Messaging(LOBbuy-in) 40% 33% 35%15. VerifyingRequirementsBCBS 22% 34% 31%16. ReduceManualReconciliationBCBS 33% 23% 25%17. SustainableFundingBCBS 28% 23% 24%18. HiringDataManagementStaff 21% 25% 23%19. Adaptability(scenario-basedanalysis)BCBS 12% 14% 13%
Regulation
OPS
Sustainability
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BENCHMARK SCORING CRITERIA
Score Category Description
1 Not Initiated Ad hoc (performed by heroes)
2 Conceptual Initial Planning (white board sessions)
3 DevelopmentalEngagement Underway (stakeholder recruitment; project-based activity)
4 Defined
Performed and Verified (roles and responsibilities structured; policy and standards implemented; content infrastructure established; sustainable funding)
5 AchievedAdopted and Enforced (executive management sanctioned; activity coordinated; adherence audited; strategic funding)
6 Enhanced Integrated (continual improvement)
Scoring Criteria
EngagementRight people at the right levels with organizational influence involved in the
data program
ProcessEstablished, structured,
standardized and repeatable
EvidenceCapabilities supported by
auditable evidence of adherence
Line of Demarcation• 3.75+ (well on way)• 3.40↓ (work to do)
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SIX AREAS OF OPERATIONAL ACTIVITY
Data Management Program
Stakeholder Commitment Governance Implementation
Content Infrastructure Data Quality Control
Eco-System
ALIG
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PRO
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CON
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CAPA
BILIT
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TECH
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L ARC
H
LOW
Medium
High
3.75
2.0
3.0
4.0
5.0
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q8 Q21 Q22
2015-Industry 2015-Control 2015-Buy-Side 2015-SellSide 2015-G-SIB
2017-Industry 2017-Control 2017-Buy-Side 2017-SellSide 2017-G-SIB
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ResultsandObservationsDataManagementProgram
Setting Up Program (Questions 1,2,3):
Thefinancialindustryismakingsteadyprogress.Datamanagementisa“knownobjective”andthestrategiesarebeingdefined.Itisstillunclearwhetherthestrategiesarefullyunderstoodandfunctionallyendorsedbystakeholders.TheauthorityoftheODMtoimplementthedataprogramisstillbeingdefined.Datamanagement(asacorepartofthewayfinancialinstitutionsoperate)isgrowingbutstillnotfullyentrenched.
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Q1:DATA MANAGEMENT STRATEGYQuestion1:Ourorganizationhasadefinedandendorseddatamanagementstrategy
Implications: Definestheobjectivesofthedatamanagementprogramincludinghowitwillbeimplementedandgoverned.Thegoalisconfidenceinprogramobjectives,approachandimplementation
KeyObservations
• Flatprogressondatamanagementstrategy.Atthispointinthecyclewewouldexpectasignificantincrease
• Datamanagementisarecognizedconceptwithsignificantimprovementfromthebuy-side(footholdestablished)
• G-SIBscoresrecalibrated(downward)basedonimplementationexperience;regulatorytriageisatacticalactivityandbyitselfisnotadatamanagementstrategy
BCBSRequirement:Strategyisacoreobjective.Strategydefineshowthefirmisapproachingandimplementingdatamanagement(defined,shared,aligned,enforceable)
Opinion/Trend Achieved Capability
18%+2%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 4% 5% 2% 4% 3% 2% 7% 3% 4% 5% 3% 6%Planning(2) 12% 10% 11% 10% 10% 5% 19% 10% 10% 8% 11% 14%Underway(3) 29% 30% 31% 29% 30% 24% 29% 40% 29% 31% 22% 17%Performed(4) 39% 37% 37% 41% 40% 38% 36% 25% 40% 38% 43% 47%Achieved(5,6) 16% 18% 19% 16% 17% 31% 10% 23% 16% 18% 21% 17%
High
Low
Medium3.5 3.6
3.93.6 3.6 3.6
3.5 3.6 3.6 3.2 3.5 3.72.0
3.0
4.0
5.0
55%
30%
15%
69%
24%
7%
17%
64%
20%
57% 48%56%
29% 40% 31%
14% 13% 13%
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Question2:Thegoals,objectivesandauthoritiesofthedatamanagementprogramarewellcommunicated
Implications: Communicationsisnotasidelineactivity.Theobjectiveisenhancedawarenessandalignmentbystakeholdersonthegoals,scope,prioritiesandpoliciesforthedataprogram
KeyObservations
• CommunicationaboutthegoalsandauthorityoftheDMPisstilldevelopingandishamperedbyorganizationaldynamicsandinternalpolitics
• RiskandtopmanagementunderstandtheDMPobjectivebecauseofregulatorypressure(executivesintheLOBlag)
• Controlgroupcommunicationfirmlyestablished(authorityincreasedandroleformalized),buy-sidetakesabigstepforwardandG-SIBsscoresfallslightly
Opinion/Trend Achieved Capability
20%+5%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 6% 6% 5% 6% 5% 3% 10% 5% 6% 6% 6% 8%Planning(2) 17% 13% 16% 13% 13% 5% 29% 15% 11% 10% 7% 11%Underway(3) 35% 32% 33% 30% 42% 17% 31% 28% 39% 36% 33% 35%Performed(4) 28% 28% 30% 29% 30% 38% 26% 38% 25% 27% 31% 29%Achieved(5,6) 15% 20% 17% 23% 10% 36% 5% 15% 19% 21% 24% 18%
High
Low
Medium3.4 3.5
4.03.5 3.5 3.4
3.3 3.4 3.3 2.9 3.4 3.62.0
3.0
4.0
5.0
74%
48% 47%
32%
17%
35%
19%8%
19%
Q2:STRATEGY COMMUNICATED
52%
30%
19%
53%
28%
20%
48%
36%
16%
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Question3:Thedatamanagementprogramisestablishedandhastheauthoritytoenforceadherence
Implications: TheOfficeofDataManagementneedstheformalandofficialauthoritytoimplementthedatamanagementprogram.Thegoalistomakesurethestakeholdersunderstandthatadherenceismandatory
KeyObservations
• AuthorityoftheODMisstillbeingdefined(stakeholderrequirementsunderdebate)
• Datamanagementasanorganizationalconstructnotfullyentrenched• Noticeableshift(downward)from“achieved”to“defined”forG-SIBs• Controlgrouppassesthe“lineofdemarcation”
BCBSRequirement:AuthorityofODMismandatorytoensureadherence
Opinion/Trend Achieved Capability
20%-2%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 10% 6% 6% 5% 7% 3% 12% 5% 12% 5% 6% 6%Planning(2) 11% 13% 11% 10% 12% 7% 14% 20% 8% 11% 8% 11%Underway(3) 31% 31% 30% 31% 32% 22% 33% 40% 28% 31% 26% 26%Performed(4) 27% 30% 26% 31% 30% 34% 26% 23% 27% 32% 29% 41%Achieved(5,6) 22% 20% 26% 23% 20% 33% 14% 13% 25% 21% 31% 17%
High
Low
Medium3.5 3.6 3.9
3.23.5 3.5
3.4 3.6 3.5 3.2 3.5 3.72.0
3.0
4.0
5.0
50%
19%
31%
67%
22%
10%
58%
26%
17%
Q3:AUTHORITY
15%25%
16%
31%
40%
31%
54%46%
53%
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ResultsandObservationsStakeholderCommitment
Data Management Program
Stakeholder Commitment Governance Implementation
Content Infrastructure Data Quality Control
Eco-System
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CAPA
BILIT
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TECH
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L ARC
H
LOW
Medium
High
3.75
2.0
3.0
4.0
5.0
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q8 Q21 Q22
2015-Industry 2015-Control 2015-Buy-Side 2015-SellSide 2015-G-SIB
2017-Industry 2017-Control 2017-Buy-Side 2017-SellSide 2017-G-SIB
Commitment from Stakeholders (Questions 4,5,6,7):
Theindustryhasmadelittlemeasurableprogressinfullyunderstandingthe“why”ofdatamanagement.Thereisgoodnewshowever.Creatingatruedatamanagementcultureisdifficult,butitcanbeachievedoncetheprogramtakeshold.Thebuy-sidecontinuestotakeboldstepsforward.
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Q4:STAKEHOLDERS UNDERSTAND
Question4:Stakeholdersunderstand(andbuyinto)theneedforthedatamanagementprogram
Implications: Theconceptofdatacontentaspartoftheoperationalinfrastructureoftheorganizationisnewtomanystakeholders.Theindustrystillfaceschallengesadoptingadatamanagementculture.
KeyObservations
• Stakeholderunderstanding(andbuy-in)ontheneedfordatamanagementisstable
• Some“whyarewedoingdatamanagement”questionsremainamongG-SIBs
• LOBexecutivesarestillnotcompletelyonboardwiththegoalsandimportance
• UnderstandingofBCBS239objectiveisnotthesameasunderstandingthedatamanagementmandate
Opinion/Trend Achieved Capability
21%+1%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 4% 5% 4% 4% 7% 2% 5% 0% 5% 4% 3% 8%Planning(2) 11% 12% 8% 12% 5% 7% 19% 10% 8% 13% 8% 6%Underway(3) 32% 29% 33% 28% 28% 22% 31% 40% 32% 29% 26% 27%Performed(4) 33% 33% 32% 34% 37% 33% 33% 28% 35% 35% 35% 39%Achieved(5,6) 20% 21% 23% 23% 23% 36% 12% 23% 20% 19% 28% 20%
High
Low
Medium3.5 3.6
3.9 3.6 3.5 3.6
3.5 3.6 3.7 3.3 3.6 3.82.0
3.0
4.0
5.0
54%
29%
69%
17%
22%
9%
59%
27%
14%
57%
28%
16%
51%
40%
10%
54%
29%
17%
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Q5:FUNDING MODEL
Question5:Thefundingmodelforthedatamanagementprogramisestablishedandsanctioned
Implications: Fundingforthedatamanagementprogramcan’tbeoptional.Thereisadifferencebetween“seedfunding”and“sustainablefunding”forthedataprogram
KeyObservations
• Industrycontinuestoimprovewiththecontrolgroupandassetservicingmovingtowardsustainablemulti-yearfunding
• Buy-sidesurpassesindustryaverageand“ridingthecurve”offundingtoestablishtheOfficeofDataManagement
• Euphoriaof“seedfunding”iswearingoffamongG-SIBswithadropinscores(warningsignandfearthatwithoutsustainablefunding,datamanagementwillwane)
BCBSRequirement:Fundingisessentialtodrivedatamanagementprograms(defined,authorizedandenforced)
Opinion/Trend Achieved Capability
30%+1%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 11% 8% 7% 8% 10% 3% 19% 13% 10% 5% 3% 6%Planning(2) 16% 16% 16% 14% 15% 9% 19% 10% 14% 17% 15% 18%Underway(3) 24% 19% 25% 19% 27% 19% 24% 15% 21% 23% 18% 15%Performed(4) 21% 28% 21% 28% 20% 21% 17% 23% 22% 30% 24% 30%Achieved(5,6) 29% 30% 32% 31% 28% 48% 21% 40% 33% 25% 40% 30%
High
Low
Medium3.6 3.6
4.13.7 3.6 3.6
3.4 3.6 3.5 3.1 3.6 3.92.0
3.0
4.0
5.0
58%
19%
24%
69%
19%
12%
60%
15%
24%
59%
19%
22%
63%
15%
23%
55%
23%
22%
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Q6:METRICS ON COSTS AND BENEFITS
Question6:Thecostsof(andbenefitsassociatedwith)thedatamanagementprogramarebeingmeasured
Implications: Youcan’tmanagewhatyoucan’tmeasure.AstandardmethodologyforcapturingexpensesandbenefitsbeyondtraditionalROIisnecessaryforlong-termorganizationalbuy-in.
KeyObservations
• Thelowestofthescoresfromlastyeardroppedevenlower• Metricsaboutdatamanagement(whichareneededtobecomeestablishedasanoperationalactivity)arestillelusive
• Acrosstheboard– wearestillonlybarelyoutoftheconceptualrealm
Opinion/Trend Achieved Capability
7%-0.5%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 15% 16% 13% 16% 17% 14% 17% 13% 16% 16% 11% 23%Planning(2) 23% 27% 21% 25% 20% 17% 29% 30% 19% 26% 18% 26%Underway(3) 39% 34% 40% 33% 38% 36% 33% 38% 42% 34% 39% 26%Performed(4) 16% 16% 18% 17% 18% 17% 14% 18% 16% 15% 18% 14%Achieved(5,6) 8% 7% 8% 9% 7% 16% 7% 3% 8% 9% 14% 12%
High
Low
Medium 2.7 2.8 3.02.7 2.7 2.7
2.8 2.9 2.8 2.7 2.8 3.12.0
3.0
4.0
5.0
23%
34%
43%
33%
36%
31%
26%
49%
26%
26%
33%
41%
21%
38%
43%
24%
34%
42%
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Q7:SUFFICIENT RESOURCESQuestion7:Thedatamanagementprogramissufficientlyresourced
Implications: Datamanagementrequirescommitmentfromawidevarietyofstakeholders.Thegoalisalignmentofobjectiveswithprojectdelivery,funds,staffcapabilityandtimeallocation
KeyObservations
• Scoresrisefor“achieved”butdropoverallacrosstheindustryincludingamongTier1andG-SIBs
• Resourcesarederivedbasedondefineddeliverables,stakeholdercommitmentandfundingalignmenttoroadmapsandworkstreams
• Governanceimplementationwascitedasoneofthetopprioritiesfortheindustry
BCBSRequirement:Stakeholdersneedtobeaccountablewithresourcesandoperationalfunding
Opinion/Trend Achieved Capability
19%+6%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 8% 8% 5% 8% 3% 5% 14% 8% 8% 7% 6% 9%Planning(2) 13% 19% 12% 18% 17% 17% 19% 25% 9% 17% 10% 18%Underway(3) 38% 34% 40% 31% 42% 29% 38% 38% 40% 37% 32% 33%Performed(4) 27% 20% 29% 22% 22% 21% 21% 10% 27% 22% 35% 17%Achieved(5,6) 13% 19% 14% 21% 17% 28% 7% 20% 16% 16% 18% 23%
High
Low
Medium 3.2 3.3 3.53.1 3.2 3.3
3.3 3.4 3.4 2.9 3.4 3.52.0
3.0
4.0
5.0
39%
34%
27%
49%
29%
22%
40%
27%
33%
43%
31%
26%
30%
38%
33%
38%
37%
24%
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ResultsandObservationsGovernanceImplementation
Data Management Program
Stakeholder Commitment Governance Implementation
Content Infrastructure Data Quality Control
Eco-System
ALIG
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L ARC
H
LOW
Medium
High
3.75
2.0
3.0
4.0
5.0
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q8 Q21 Q22
2015-Industry 2015-Control 2015-Buy-Side 2015-SellSide 2015-G-SIB
2017-Industry 2017-Control 2017-Buy-Side 2017-SellSide 2017-G-SIB
Governance Implementation (Questions 9,10,11,12):
Progressontheestablishmentoffoundationalgovernanceissubstantial.Theorganizationalstructuresaredefined.Stewardshipisbeingassigned.Thedevelopmentofpolicyisprogressing.Practicalimplementationishighonthelistofindustrypriorities.Signsarepositive– althoughwerecognizethatchangingthewayorganizationsoperateisnotsimple.
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Q9:GOVERNANCE STRUCTURE IMPLEMENTED
Question9: Datagovernancestructureandauthorityisimplementedandcommunicated
Implications: Turnsdatamanagementobjectivesintooperationalreality.HireCDO…establishPMO…definegovernanceroutines…establishprojectreviewprocedures…makefundingoperational
KeyObservations
• Wehaveestablishedfoundationalgovernanceandthecapabilityismaturing.
• Theentireindustryiswellonthewaytoachievement(inchingabovethelineofdemarcation)
• Buy-sidelagsslightlyreflectiveofthelackofmaturityoftheOfficeofDataManagement
BCBSRequirement:ODMisneededtoimplementthedatamanagementprogram
Opinion/Trend Achieved Capability
25%+7%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 8% 6% 6% 6% 3% 2% 10% 8% 10% 3% 6% 3%Planning(2) 14% 10% 10% 8% 18% 5% 26% 8% 12% 10% 7% 6%Underway(3) 26% 28% 28% 28% 23% 10% 24% 40% 25% 27% 21% 24%Performed(4) 34% 31% 36% 28% 38% 33% 33% 33% 34% 32% 43% 35%Achieved(5,6) 18% 25% 21% 31% 17% 50% 7% 13% 19% 28% 24% 32%
High
Low
Medium3.6 3.7
4.3
3.43.7 3.9
3.4 3.6 3.5 3.0 3.4 3.72.0
3.0
4.0
5.0
56%
28%
16%
83%
10%7%
67%
24%
9%
59%
28%
14%
46%
40%
16%
60%
27%
13%
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Q10:OWNERS AND STEWARDS IN PLACE
Question10: Governance“owners”and“stewards”areinplacewithclearlydefinedrolesandresponsibilities
Implications: Appointmentofindividualswithinthelinesofbusinessandcontrolfunctionswithdirectresponsibilityfordatamanagement(requirementscapture,qualitycontrol,datameaning,transformationprocesses,dataflow,coordinationacrossfunctions)
KeyObservations
• Strongpositivescores(milestoneachievement)acrosstheindustry• Lineofbusinessgovernanceisapproachingthedefined,communicatedandstaffedlevel
• DatastewardsinG-SIBsalignedwithriskdatamanagementobjectives
BCBSRequirement:Operationalgovernanceishowdatamanagementbecomesareality
Opinion/Trend Achieved Capability
23%+7%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 7% 6% 6% 4% 3% 2% 12% 3% 7% 4% 6% 5%Planning(2) 18% 14% 15% 14% 17% 9% 24% 18% 19% 13% 13% 11%Underway(3) 37% 30% 39% 26% 37% 22% 29% 33% 34% 31% 39% 30%Performed(4) 22% 27% 22% 28% 28% 29% 26% 28% 24% 28% 26% 23%Achieved(5,6) 16% 23% 18% 28% 15% 38% 10% 20% 16% 24% 17% 32%
High
Low
Medium3.5 3.7 4.0
3.5 3.6 3.7
3.2 3.3 3.4 3.0 3.2 3.42.0
3.0
4.0
5.0
50%
30%
20%
67%
22%
11%
55%
30%
16%18% 21% 17%
26%33% 31%
56%48% 52%
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Q11:POLICIES AND STANDARDS IMPLEMENTED
Question11: Datapoliciesandstandardsaredocumented,implementedandenforced
Implications: Datamanagementisgovernedviapolicyandimplementedbasedonorganizationalstandards.Implementationofthe“rulesoftheroad”withconsequencesandagreementfromstakeholdersisapre-requisiteforeffectivedatamanagement.
KeyObservations
• ThehighestscoresacrossthefullbenchmarkingstudyforbothG-SIBsandtheControlgroup
• Entireindustryisnearingthelineofdemarcation(majormilestoneachievement)
• Dramaticimprovementsillustratethecommitmentoftheindustrytomeetingregulatoryrequirements(adoptionofpolicyisaBCBS239requirement)
BCBSRequirement:“Controlenvironment”isenforcedbycorporatepolicy.Essentialcomponent.
Opinion/Trend Achieved Capability
26%+10%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 8% 5% 6% 4% 5% 2% 17% 0% 7% 3% 4% 3%Planning(2) 15% 13% 13% 11% 17% 7% 26% 18% 12% 12% 4% 9%Underway(3) 35% 30% 35% 29% 35% 17% 33% 43% 36% 27% 33% 23%Performed(4) 26% 26% 27% 27% 30% 31% 19% 25% 28% 27% 32% 24%Achieved(5,6) 16% 26% 19% 30% 13% 43% 5% 15% 18% 31% 26% 41%
High
Low
Medium3.6 3.7
4.13.4
3.8 4.0
3.3 3.4 3.3 2.7 3.4 3.82.0
3.0
4.0
5.0
52%
30%
18%
74%
17%
9%
65%
23%
12%15% 18% 15%
29%
43%
27%
57%40%
58%
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Q12:ADHERENCE TO STANDARDSQuestion12: Theendusercommunityisadheringtothedatagovernancepolicyandstandards
Implications: Adherencefollowsadoption.Adoptionfrequentlyrequiresa“burn-in”periodtoenablestakeholderstoadjustandaddressgapsindatamanagementcapability.Adherencealsorequiresenforcementmechanismsandthepresenceofcontrolprocesses(i.e.checkpoints,formalreviewprocesses,auditengagement)
KeyObservations
• Industryhasmadeconsiderableprogressmovingadherencealongthecapabilitycurve
• Adherencetopolicyusuallylagsimplementationandisafinalstagemetric
• Fillingthegapfromlow“developmental”to“achieved”isnoteasy
BCBSRequirement:Accountabilitytopolicyistheauditstandard.
Opinion/Trend Achieved Capability
9%+4%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 18% 11% 15% 9% 13% 9% 24% 8% 15% 10% 10% 11%Planning(2) 21% 21% 21% 21% 23% 14% 26% 33% 21% 18% 26% 20%Underway(3) 38% 36% 40% 34% 42% 36% 33% 33% 42% 37% 40% 32%Performed(4) 18% 23% 18% 26% 18% 22% 17% 20% 17% 26% 17% 26%Achieved(5,6) 5% 9% 6% 9% 3% 19% 0% 8% 5% 9% 7% 12%
High
Low
Medium 3.0 3.1 3.32.9 3.1 3.1
2.7 2.8 2.8 2.4 2.8 2.82.0
3.0
4.0
5.0
32%
36%
32%
41%
36%
23%
38%
32%
31%30%41%
28%
34%33%
37%
35%28% 35%
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ResultsandObservationsContentInfrastructure
Data Management Program
Stakeholder Commitment Governance Implementation
Content Infrastructure Data Quality Control
Eco-System
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2017-Industry 2017-Control 2017-Buy-Side 2017-SellSide 2017-G-SIB
Content Infrastructure (Questions 13,14,15,16,17):
ThisisaboutPrinciple2ofBCBS239– thebuildingblockforachievingadatacontrolenvironment.Withoutatrustedandharmonizedcontentinfrastructure,thereislittlepointtoimplementingdatapolicyandgovernance.Workisunderwayonlineage,CDEdesignationandglossaryreconciliation,butthetasksaresignificantandprogressisslow.
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Q13:DATA HARMONIZATION ACROSS REPOSITORIESQuestion13: Thebusinessmeaningofdataisdefined,harmonizedacrossrepositoriesandgoverned
Implications: Oneoftheprincipleobjectivesofdatamanagement.Withoutachievingthiscapability,theindustrywillnotbeabletounravelinterconnections,managecomplexity,automateprocessesormanagelinkedriskacrossthefinancialsystem
KeyObservations
• SomeprogressamongControlandG-SIBsduetoBCBS239• Scoresremaininthe“conceptual”tolow“developmental”level.• Workisunderwaybutglossaryreconciliationisamoresignificanttaskthananticipated.
• Thechallengethatstartswithdefinitionswillgetmorecomplicatedastermsandrelationshipsaremappedfromphysicalrepositoriesandlinkedtologicaldatamodels.
BCBSRequirement:Thisistheprimedirectiveforharmonization,comparabilityandscenario-basedanalysis
Opinion/Trend Achieved Capability
8%+1%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 10% 7% 9% 6% 7% 5% 14% 5% 10% 6% 7% 3%Planning(2) 20% 23% 21% 24% 22% 14% 29% 25% 15% 23% 19% 24%Underway(3) 46% 40% 44% 39% 52% 43% 33% 40% 50% 41% 49% 38%Performed(4) 18% 22% 19% 22% 15% 22% 19% 20% 18% 23% 18% 21%Achieved(5,6) 7% 8% 7% 9% 5% 16% 5% 10% 7% 7% 7% 14%
High
Low
Medium 3.0 3.0 3.3 3.1 3.0 3.2
2.9 2.9 2.9 2.7 3.0 3.02.0
3.0
4.0
5.0
30%
40%
30%
38%
43%
19%
35%
38%
27%30% 30% 29%
39% 40% 41%
31% 30% 30%
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Q14:CRITICAL DATA ELEMENTS
Question14: Criticaldataelementsareidentifiedandmanaged
Implications: :Unravelingthedataattributesthathaveamaterialimpactonbusinessfunctionsisanessentialcomponentofthedatamanagementequation.Ithelpstoestablishprioritiesanddeterminewheretofocuslimitedresources.CDEsarederivedfromlineageandfrequentlyhavetobereverseengineeredfromcalculatedandaggregationprocesses.
KeyObservations
• Progressfromallsegmentsoftheindustry(recognitionoftheimportance)
• DeterminationofCDEcriteriaisthenumber1priorityoftheindustry• Muchoftheindustryprogressisfocusedoncriticaldatainputsforriskreporting
• Estimationofthiscapabilityislikelyoverstatedwhenputintooverallcontext.
BCBSRequirement:Datathatsupportscriticalbusinessfunctionsmustbedefinedandmanaged
Opinion/Trend Achieved Capability
14%+2%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 8% 6% 5% 5% 7% 2% 7% 3% 9% 5% 6% 6%Planning(2) 14% 14% 11% 13% 22% 3% 29% 20% 13% 13% 11% 14%Underway(3) 41% 39% 44% 40% 37% 43% 33% 35% 43% 38% 46% 33%Performed(4) 25% 27% 26% 28% 20% 26% 17% 30% 25% 26% 29% 26%Achieved(5,6) 12% 14% 14% 15% 15% 26% 14% 13% 10% 17% 8% 21%
High
Low
Medium3.3 3.4
3.73.3 3.4 3.5
3.2 3.4 3.2 3.0 3.2 3.32.0
3.0
4.0
5.0
41%
39%
20%
52%
43%
5%
47%
33%
20%18% 23% 18%
40% 35% 38%
43% 43% 43%
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Q15:LOGICAL DATA DOMAINS
Question15: Logicaldatadomainshavebeendeclared,prioritizedandsanctioned
Implications: :Dataneedstobecharacterizedandorganizedasanearlystepinthedatamanagementprogram.Managingthisacrossacomplexenterpriseisadifficultpropositionandisbasedonanunderstandingofhowthebusinessfunctionsandhowdataismanufacturedacrosslinkedprocesses.
KeyObservations
• ProgressisrelativelyflatapartfromtheControlgroup• Logicaldomainsareeasytounderstand,buthardtoimplement• Implementationoflogicaldomainsviaauthorizedprovisioningpointsandchangingdataaccessmechanismsexacerbatesthechallenges
BCBSRequirement:Anothercorecomponentofthe“controlenvironment”
Opinion/Trend Achieved Capability
11%-3%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 8% 7% 6% 7% 7% 3% 12% 3% 8% 7% 4% 8%Planning(2) 15% 17% 15% 16% 15% 9% 17% 15% 14% 16% 8% 6%Underway(3) 32% 39% 36% 38% 28% 34% 10% 38% 38% 41% 40% 42%Performed(4) 31% 26% 30% 28% 32% 33% 43% 30% 27% 25% 33% 26%Achieved(5,6) 14% 11% 13% 13% 18% 21% 19% 15% 13% 10% 14% 18%
High
Low
Medium 3.2 3.23.6 3.4 3.2 3.4
3.3 3.3 3.4 3.4 3.2 3.42.0
3.0
4.0
5.0
37%
39%
24%
54%
34%
12%
44%
42%
14%23% 18% 23%
38% 38%41%
41% 45%35%
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Q16:END-TO-END LINEAGEQuestion16: End-to-enddatalineagehasbeendefinedacrosstheentiredatalifecycle
Implications: DocumentinglineagestartswithdatadiscoveryandincludesreverseengineeringcriticalmeasuresandunravelingtheflowofdataacrossverticallyalignedITenvironments.Itisanessentialpartofthedataquality(andrequirements)verificationprocess– butwiththousandsofapplicationsandhundredsofdatamodels– theprocessisdaunting.
KeyObservations
• UnravelingtheGordianKnotremainsasignificantchallenge• Theindustryisstillgenerallyhoveringinthelate“conceptual”stageofthiscapability
• Dataforensicsisnotasimpletaskandisthesecondhighestdatamanagementpriorityfortheindustry
BCBSRequirement:Mustunderstandhowdataflowsacrosslinkedprocessesbasedonreverseengineeringofapplicationsthroughcalculationtosystemsofrecord
Opinion/Trend Achieved Capability
6%+1%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 12% 14% 9% 14% 8% 5% 19% 15% 10% 13% 8% 14%Planning(2) 26% 27% 27% 25% 35% 17% 31% 33% 26% 25% 22% 26%Underway(3) 44% 36% 44% 34% 35% 38% 38% 35% 47% 35% 46% 27%Performed(4) 13% 17% 14% 20% 15% 26% 12% 13% 11% 19% 18% 21%Achieved(5,6) 5% 6% 5% 7% 7% 14% 0% 5% 6% 8% 6% 12%
High
Low
Medium 2.8 2.83.3
2.6 2.9 2.9
2.7 2.8 2.8 2.4 2.8 2.92.0
3.0
4.0
5.0
23%
36%
41%
40%
38%
22%
33%
27%
40%39%48%
38%
34%
35%
35%
27% 18% 27%
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Q17:TECHNICAL ARCHITECTUREQuestion17: Technicalarchitectureisdefinedandintegrated
Implications: Translationofdatamanagementobjectivesintothepathwayfortechnicalimplementation.Thisisacollaborativeactivitytodefinethedatabasestrategies,analyticsplatforms,middlewaresolutionsandprocesscontrolconsiderationsneededtosupportthedataobjectivesoftheorganization
KeyObservations
• Industryisintheprocessofdefiningtheintegratedarchitecturestrategy
• RealityisaverticallyalignedITinfrastructurethatwasindependentlydeveloped
• Theimportanceofanenterprisetechnologygovernancetoprovideauthoritativecontentisrisingasapriority
Opinion/Trend Achieved Capability
14%NEW
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
100%
Industry Tier1 Control Buy-Side SellSide G-SIB
2017- Low. 2017- Medium. 2017- High.
Industry Tier1 Control Buy-Side SellSide G-SIB2017 2017 2017 2017 2017 2017
NotInitiated(1) 8% 8% 5% 8% 6% 8%Planning(2) 17% 16% 17% 10% 20% 21%Underway(3) 34% 33% 31% 48% 32% 20%Performed(4) 26% 29% 33% 15% 27% 30%Achieved(5,6) 14% 14% 14% 20% 14% 21%
High
Low
Medium 3.2 3.3 3.3 3.3 3.2 3.4
2.0
3.0
4.0
5.02017
40%
34%
25%
47%
31%
22%
51%
20%
29%
New Question
24% 18% 26%
33% 48% 32%
43%35% 41%
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ResultsandObservationsDataQualityData Quality (Questions 18,19,20):
Wehaven’tescapedthetyrannyofmanualreconciliation.Overalltheindustryisstillmiredinthetacticalmappingofdatafromphysicalrepositoriestoapplicationsandreports.Trustandconfidenceremainstheelusivegoalofdatamanagement– andistheessentialprerequisiteforbothreportingandbusinessanalytics.Thereisastronglinkbetweenenhancingqualityandimplementingthecontentinfrastructure.
Data Management Program
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Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q8 Q21 Q22
2015-Industry 2015-Control 2015-Buy-Side 2015-SellSide 2015-G-SIB
2017-Industry 2017-Control 2017-Buy-Side 2017-SellSide 2017-G-SIB
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Q18:DATA PROFILINGQuestion18: AlldataundertheauthorityoftheDataManagementProgramisprofiled,analyzedandgraded
Implications: Profilingcreatesaqualitybenchmarkfortheorganizationtosupportthedeliveryoffit-for-purposedataacrossalldataqualitydimensions.Thisincludesthedefinitionofbusinessrulesandthecaptureofprofilingresultsasmetadata
KeyObservations
• Stillamongthelowestcompositescoresacrosstheentirebenchmark
• Notmuchprogresswithdataqualitydimensionsstillbeingdefinedandprioritized
• Controlgrouptakesasmallstepforward
BCBSRequirement:Evaluationofqualityagainstalldimensionsofquality(drivesremediation)
Opinion/Trend Achieved Capability
5%+1%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 20% 21% 18% 20% 13% 16% 26% 18% 18% 21% 14% 27%Planning(2) 21% 19% 20% 19% 27% 14% 21% 25% 23% 18% 19% 17%Underway(3) 38% 39% 40% 38% 40% 38% 38% 40% 39% 37% 36% 26%Performed(4) 18% 16% 17% 18% 20% 22% 12% 15% 16% 18% 22% 20%Achieved(5,6) 4% 5% 5% 6% 0% 10% 2% 3% 4% 6% 8% 11%
High
Low
Medium2.6 2.7 3.0
2.6 2.7 2.72.7 2.7 2.7 2.4 2.7 2.9
2.0
3.0
4.0
5.0
21%
39%
40%
32%
38%
30%
26%
44%
31%
39% 43% 39%
38%40%
37%
24% 18% 24%
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Q19:DATA QUALITY PROCESSESQuestion19: Proceduresformanagingdataqualityaredefined,implementedandmeasured
Implications: Demonstratesthepresenceofadataqualitystrategyincludingtheidentificationofaccountableparties,assignmentofDQresponsibilitiesandtheimplementationofadataqualitycontrolprocess.
KeyObservations
• Controlmechanismsandcheckpointsaredefinedandbeingimplementedacrosstheindustry
• Implementationisunevenandbifurcatedatbothearlyandadvancedcapability
• Dataqualityimprovementislinkedtogovernanceimplementationandwhiletherearesomebrightspotsthisremainsapriority
BCBSRequirement:Managementofchainofsupplyandcorecomponentof“controlenvironment”
Opinion/Trend Achieved Capability
13%+3%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 11% 7% 9% 7% 8% 2% 21% 8% 10% 6% 6% 8%Planning(2) 19% 23% 18% 21% 20% 21% 19% 23% 21% 21% 15% 20%Underway(3) 38% 33% 40% 33% 37% 34% 31% 33% 39% 34% 38% 32%Performed(4) 22% 24% 21% 25% 27% 22% 19% 28% 21% 25% 32% 23%Achieved(5,6) 10% 13% 11% 14% 8% 21% 10% 10% 8% 14% 10% 18%
High
Low
Medium 3.1 3.2 3.4 3.1 3.2 3.3
3.0 3.1 3.1 2.8 3.0 3.32.0
3.0
4.0
5.0
37%
33%
30%
43%
34%
23%
41%
32%
28%28% 31% 27%
33% 33% 34%
39% 38% 39%
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Q20:ROOT CAUSE ANALYSISQuestion20: Rootcauseanalysisisperformedandcorrectivemeasuresarebeingimplemented
Implications: Tacticalapproachestofixingmisalignedorcorrupteddatadonotidentifyoraddresssystemicdataqualityissues.Addressingrootcausereducestheneedforongoingremediationandimprovesconfidenceasdataflowsacrossprocessesandamongcounterparties
KeyObservations
• Notmuchprogressinidentifyingandaddressingtherootcauseofdataqualityproblems
• Industryisstillengagedindefiningtheapproachtodeterminingthecauseoferrors
• Managingrootcauseremediationrequiresstrongcollaborationacrossthesupplychain
BCBSRequirement:Mustfixtheunderlyingproblemofinconsistentdataorremainmiredinreconciliation
Opinion/Trend Achieved Capability
14%+2%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 14% 11% 13% 9% 13% 7% 19% 8% 12% 10% 8% 14%Planning(2) 16% 20% 17% 21% 17% 24% 17% 23% 18% 15% 8% 12%Underway(3) 37% 31% 36% 28% 40% 26% 21% 35% 42% 31% 49% 30%Performed(4) 21% 24% 20% 26% 18% 21% 21% 20% 16% 27% 19% 23%Achieved(5,6) 12% 14% 15% 16% 12% 22% 21% 15% 12% 16% 15% 21%
High
Low
Medium 3.1 3.2 3.3 3.1 3.2 3.3
3.0 3.1 3.0 3.1 3.0 3.32.0
3.0
4.0
5.0
38%
31%
31%
43%
26%
31%
44%
30%
26%30% 31% 25%
28% 35%31%
42% 35% 43%
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ResultsandObservationsEcosystemCollaboration
Data Management Program
Stakeholder Commitment Governance Implementation
Content Infrastructure Data Quality Control
Eco-System
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2015-Industry 2015-Control 2015-Buy-Side 2015-SellSide 2015-G-SIB
2017-Industry 2017-Control 2017-Buy-Side 2017-SellSide 2017-G-SIB
Ecosystem Collaboration (Questions 8,21,22):
Abrightspot.DataisasharedresourceandcollaborationacrossITandtheothercontrolfunctionscontinuestomoveforward.ThisisatributetoorganizationalcohesionwithinthefinancialindustryandthematurityofIT.
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Q8:COLLABORATION WITH CONTROL FUNCTIONS
Question8:Datamanagementoperatescollaborativelywithexistingenterprisecontrolfunctions
Implications: EffectivedatamanagementisbuiltoncollaborationacrossIT,operations,controlfunctionsandlinesofbusiness
KeyObservations
• Abrightspotwithscoresrisingsignificantlyacrosstheindustry• Datamanagementisacollaborativeactivityandtheothercontrolfunctionsaredependentontrustindata
• Anothertipofthehattotheregulatorydriver(GDPR,KYC,informationsecurity)
Opinion/Trend Achieved Capability
18%+7%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 13% 7% 10% 7% 13% 5% 19% 3% 13% 7% 10% 12%Planning(2) 22% 18% 24% 16% 28% 10% 21% 30% 26% 15% 25% 11%Underway(3) 28% 32% 27% 31% 20% 24% 26% 28% 27% 34% 21% 33%Performed(4) 26% 25% 27% 26% 33% 28% 26% 25% 24% 27% 31% 21%Achieved(5,6) 11% 18% 12% 21% 5% 33% 7% 15% 10% 17% 14% 23%
High
Low
Medium3.3 3.4 3.7
3.2 3.3 3.4
3.0 3.1 2.9 2.8 2.9 3.22.0
3.0
4.0
5.0
43%
32%
25%
24%
61%
28%
44%
33%
23%23%15%
33%22%
31% 34%
47%40% 44%
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Q21:TECHNOLOGY STANDARDS AND GOVERNANCEQuestion21: Technologystandardsandgovernanceareinplacetosupportdatamanagementobjectives
Implications: Technologyinfrastructuregovernanceguaranteesadherencetoplatformandtoolstandards.ThegoalistoensurealignmentofITwiththedataneededforapplicationsalongwiththeabilitytocomplywithSLAsanddatacontentrequirements.
KeyObservations
• NoteworthyprogressinthealignmentofITgovernancewithdatamanagementstrategy(ITisnotthebarrier)
• CapabilityenhancementsobservedforboththeControlgroupandtheG-SIBs
• CollaborationunderwaytoensureITstandardsandgovernanceprocessesarealignedwiththegoalsofthedatamanagementprogram
Opinion/Trend Achieved Capability
12%+3%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 11% 9% 9% 8% 8% 2% 19% 10% 10% 7% 10% 8%Planning(2) 15% 21% 15% 21% 13% 17% 17% 20% 15% 21% 13% 18%Underway(3) 42% 30% 41% 30% 43% 33% 31% 38% 45% 28% 46% 27%Performed(4) 23% 28% 24% 28% 30% 28% 24% 23% 21% 30% 21% 24%Achieved(5,6) 9% 12% 11% 14% 5% 21% 10% 10% 9% 14% 11% 23%
High
Low
Medium 3.2 3.2 3.53.1 3.2 3.4
3.1 3.1 3.1 2.9 3.0 3.12.0
3.0
4.0
5.0
30%
40%
30%
49%
33%
19%
47%
27%
26%29% 30% 28%
30% 38%28%
42%33%
44%
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Q22:CAPABILITY ALIGNMENT
Question22: Thedatamanagementprogramisalignedwithinternaltechnicalandoperationalcapabilities
Implications: EnsuresthattheobjectivesstatedinthedatamanagementstrategyareconsistentwithandachievablegiventheresourcesandcapabilitiesoftheITarchitecture(includingoperationalimplementationrequirements)
KeyObservations
• ImplementationconceptsarebeingalignedandverifiedbyITandoperationalstakeholders
• DoubledigitcapabilityenhancementsobservedforboththeControlgroupandtheG-SIBs
• PartnershipbetweenITanddatamanagementsolidifying
Opinion/Trend Achieved Capability
13%+4%
Industry Tier1 Control Buy-Side SellSide G-SIB2015 2017 2015 2017 2015 2017 2015 2017 2015 2017 2015 2017
NotInitiated(1) 13% 6% 10% 5% 5% 2% 14% 5% 13% 5% 14% 8%Planning(2) 14% 21% 15% 20% 18% 19% 19% 25% 12% 19% 13% 12%Underway(3) 38% 35% 39% 38% 35% 31% 29% 43% 40% 35% 39% 33%Performed(4) 26% 25% 27% 24% 32% 21% 26% 13% 27% 32% 25% 30%Achieved(5,6) 9% 13% 9% 13% 10% 28% 12% 15% 8% 9% 10% 17%
High
Low
Medium 3.2 3.2 3.53.1 3.2 3.4
3.1 3.1 3.2 3.0 3.1 3.12.0
3.0
4.0
5.0
38%
35%
27%
49%
31%
21%
47%
33%
20%25% 30%24%
38%43%
35%
37%28%
41%
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BENCHMARK ADVISORY TEAM
MichaelAtkinCEO
EDMCouncil
Mike is a professional facilitator and has beena financial information industry advocate forover 25 years. He is an active participant inindustry initiatives, provides consultation toglobal market authorities on the dataimplications of financial regulatory reform andis a subject matter expert on reference datastrategy, governance, data quality andstandards.
JohnBottegaSeniorAdvisor,
ChiefDataOfficerForumEDMCouncil
John is a senior strategy and data managementexecutive with more than 30 years of experiencein the industry. Over his career, John has heldvarious positions in supporting a firm’s datamanagement functions. Since 2006, John hasheld the title of Chief Data Office in both theprivate and public sectors, serving as CDO forCiti and Bank of America, and holding the post ofCDO for the Federal Reserve Bank of New York.Today, John is the Principal and ManagingMember of his own consulting firm, DataManagement Advisory Services, LLC, and issupporting the Enterprise Data ManagementCouncil as Senior Advisor and Consultant,responsible for the Council’s CDO Forum andData Management Practices.
PredragDizdarevicManagingPartner
Pellustro
Predrag is an established entrepreneur withextensive experience in managing anddeveloping services and softwareorganizations within financial services andinformation technology industries. Predragadvises financial services companies on datamanagement and technology strategies, andprivate equity firms on investment selectionand the creation of new businesses within thefinancial technology and data space. He wasone of the stakeholders in the design andpositioning of the Pellustro platform.
GavinKaimowitzGlobalDataPracticeLead
SapientConsulting
Gavin leads Sapient Consulting’s DataManagement Practice across the capital andcommodity sectors, comprising of more than500 active consultants. Gavin is responsible fordelivery quality and oversight, collation andgeneration of best practices, thought leadershipand strategy for data management-relatedinitiatives. He has a proven track record in thefinancial services data domain of solutiondesign, delivery, business case definition,strategic roadmap design and in building datamanagement-related products. He also leadsthe Sapient Synapse product offering.
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