This document discusses linking data governance to business goals. It begins with an example of a typical governance program that loses business support over time. It then advocates taking a business-first approach to accelerate programs and increase ROI. Successful programs link governance to business goals, outcomes, stakeholders and capabilities. The document provides examples of how different business goals map to governance objectives and capabilities. It emphasizes quantifying value at strategic, operational and tactical levels. Finally, it discusses Jean-Paulotte Group's Chief Data Officer implementing a working approach driven by business value through an iterative process between a Data Management Committee and Working Groups.

1. Linking Data
Governance to
Business Goals

2. “We need to
govern our data!”
2
A Typical Governance Story
LEADERSHIP
DATA
GOVERNANCE
TEAM
BUSINESS
USERS
DATA
GOVERNANCE
TEAM
BUSINESS
USERS
LEADERSHIP
INCITING
EVENT
Governance
spends more
time fighting
data fires.
Business
quickly loses
interest; stops
attending
meetings
Program
investment is
deprioritized
Asked to
help with
definitions,
approvals, and
ownership.
Team is
tasked with
putting
program in
place
Exec calls for
a data
governance
program
“We need to get the
business involved!”
“How does this help
me do my job?”
“We’re spending a lot more
time fighting data fires.
We need more meetings…”
“These meetings are
a waste of time!”
“I’m not seeing
the ROI”

3. Benefits of a
business-first
approach
Accelerate program
roll-out by 18-40%
Increase likelihood of
reinvestment by over 75%
Generate 2-7x greater ROI

4. Successful programs
link Data Governance to business goals

5. Business goals inform your steps
REPORTING & COMPLIANCE ANALYTICS & INSIGHTS OPERATIONAL EXCELLENCE
Data protection
Risk and fraud
Privacy
Safety
Regulatory compliance
Internal reporting
Net Promoter Score
Website traffic
Targeted marketing
Customer retention
Buying patterns
Customer 360° view
Optimize working capital
Enhance customer care
Facilitate M&A
Lower operating expenses
Increase service levels
Reduce attrition

6. How data drives Business Outcomes
REPORTING & COMPLIANCE ANALYTICS & INSIGHTS OPERATIONAL EXCELLENCE
Data protection
Risk and fraud
Privacy
Safety
Regulatory compliance
Internal reporting
Net Promoter Score
Website traffic
Targeted marketing
Customer retention
Buying patterns
Customer 360° view
Optimize working capital
Enhance customer care
Facilitate M&A
Lower operating expenses
Increase service levels
Reduce attrition

7. Mapping data governance to business value
Goal Org Stakeholders Expected Outcomes DG Objective DG Capabilities
Improve
personalization of
customer products
and services
• Marketing
• Sales
• Finance
• Increase NPS by 5%
• 17%+ repeat customer
purchases
• 11% reduced churn
• Establish a common
view of trusted
customer data assets
• Data Catalog
• Data Lineage
• Approval Workflow
• Data Integrity rules
Accurate and timely
credit-risk analysis
• Underwriting
• Loan office
• Finance
• 10% reduction in
expected loss
• 20% lower Probability
of Default
• Establish stage gates,
rules, policies, and
quality measures
across credit risk
analysis process
• Analytics governance
• Model analysis
• Data quality metrics
Increase user
productivity by
improving time-to-
insights
• Business Analytics
• IT
• Data Office
• Improve decision-
accuracy by 22%
• Reduce time-to-insight
by 45%
• Launch data literacy
campaign across
business data SMEs
• Data lineage
• Data Catalog
• Automated workflow
Mitigate risk and
facilitate regulatory
compliance and
reporting
• Compliance Office
• Finance
• IT
• 10% improvement to
Reputation Index
• 15% reduction in
regulatory fines and
settlements
• Establish risk and
control framework
for regulatory
drivers
• PII detection
• Data monitoring
• Access control

8. Governance as a “painkiller” and “vitamin”
Goal DG Objective DG Capabilities
Improve
personalization of
customer products
and services
• Establish trusted view
of customer data
assets
• Data Catalog
• Data Lineage
• Approval Workflow
• Data Integrity rules
Accurate and
timely credit-risk
analysis
• Underwriting
• Loan office
• Finance
• •10% reduction in
expected loss
• •20% lower
Probability of Default
Increase user
productivity by
improving time-to-
insights
• Launch data literacy
campaign across
business data SMEs
• Data lineage
• Data Catalog
• Automated workflow
Mitigate risk and
facilitate regulatory
compliance and
reporting
• Establish risk and
control framework for
regulatory drivers
• PII detection
• Data monitoring
• Access control
Centralized collection
of customer data
elements used for
marketing and
promotion
Data profile providing
additional context on
volume, counts,
location, and contents
Data lineage flow of
upstream/downstream
relationships
Impact analysis to
business processes,
metrics, and analytics
Approved governance
ownership indicating
data is certified for
access and use
Automated approval
workflow to grant
access to data at
source
Data integrity metrics
to indicate data that is
accurate, consistent,
and trusted
Quality monitoring to
trigger notifications
below acceptable
values
P A I N K I L L E R
“ M u s t H a v e s ”
V I T A M I N
“ B o n u s ”

9. Prioritizing what matters
Goal Org Stakeholders Expected Results DG Objective DG Capabilities
Improve
personalization
of customer
goods and
services
Marketing
Sales
Finance
• Increase referrals
by 5%
• 17%+ repeat
customer
purchases
• 11% reduced churn
• Establish a
common view of
trusted customer
data
• Data Catalog
• Data Lineage
• Approval
Workflow
• Data Integrity
rules
“We need to
personalize our
outreach to
reduce churn.”

10. Operational
Bridging the gap between business & IT
Strategic
Tactical
e.g., KPIs / metrics,
strategic programs,
data privacy & protection
e.g., product development,
planning, sourcing,
manufacturing
e.g., data migrations, system
implementations, data
science & engineering
Critical data that drives
business processes
and operations
Grow the Business
Critical data assets that have
operational, compliance and
analytical business impacts
Run the Business
Critical information driving
business goals, objectives,
KPIs, and metrics
Transform the Business

11. Value metrics across three levels
Strategic
• Business Transformation Lead
• CDO / Data & Analytics Lead
• CIO
Value Metrics: Business Impact / ROI
• Process enablement
• KPI’s / PPI’s
Value Metrics: Performance Improvement
• Data Quality
(e.g. Accuracy)
• # of touches
Value Metrics: Efficiency & Effectiveness
• Volume / counts
• Completeness
• Accessibility
• Curation times
• Scale (# Systems managed)
• Data Error % (Rework %)
• Cycle time vs SLA’s
• Timeliness / availability
• Customer sentiment
• Project acceleration
Operational
• Business Process Lead
• Data Governance Lead
• Data Management Lead
• Information Architect
Tactical
• Business Data SME
• Data Analyst / Scientist
• Data Steward
• Data Maintenance & Quality
• Data Engineer

12. The Value Story
• Catalog assets
• Terms defined
• Quality rules developed
• Data owners identified
• Issue requests
Tactical Value Metrics (Inputs)
• FTE Productivity
• Data Literacy index
• Adoption / NPS
• Cycle time
• Data sharing
Strategic Value Metrics (Outcomes)
• Our customer onboarding process has
decreased by 25%...
• We’re able to identify 33% more customers
to cross-sell of lending products…
• And we’ve increased FTE productivity
by 20% due to data self-service …
• We’ve catalogued 10,000 supplier data assets…
• Defined the top 50 critical customer data assets …
• Aligned on key rules and policies for each…
• And our data quality is showing 90+% accuracy
and consistency for customer objects…
Lead to

13. Takeaways
• Link data governance program initiatives
to higher-level business goals, stakeholders,
and business outcomes
• Deploy data governance capabilities that
directly serve as both painkillers and
vitamins to protect and grow the business
• Communicate Governance Value across
three levels – Strategic, Operational, and
Tactical
• Quantify business impact with value
metrics that resonate across each level

14. Linking Data Governance to Business goals in practice
J E A N - P A U L O T T E
G R O U P C H I E F D A T A O F F I C E R @ D E G R O O F P E T E R C A M

15. 15
Key figures
experience and solid results
150 years
professionals
1,495
total clients assets
84 billion euro
international presence
8countries
capital ratio (CET1)
21%

16. The mission of CDO Office is threefold…
Ensure
Trusted and Governed Data
Enable implementation of an
Harmonized Data Environment
Materialize Data value through
BI and Analytics Enablement
Deploy Data Governance
framework within the
organization
 Data management process
 Data quality monitoring &
continuous improvement
 Roles & Responsibilities
 Supporting platform
Translate Business Data requirements
into a Business Information Model
(BIM)
 Data architecture backbone
 Single source of truth for Data
integration patterns and Data
models
Train, coach and support power
users on Data visualization &
analysis
 Best practices
 Tools usage
 Data Governance and Data
Quality integration 16

17. Ensure Trusted and Governed Data
Guiding Principles
Focus on critical data
• Key to enable strategic ambitions
• High impact on risk mitigation and regulatory compliance
Iteratively reach target maturity staying focused on business
objectives, embedding data management best practices in our
“business as usual” activities
Empower sustainable hands-on role on business side (Data
Steward)​
• Continuous improvement​
• Maturity growth​
• Ambassador of the Data Strategy
Data Management Committee is playing an active role​
• Data initiatives priorities in line with business objectives​
• Resources assignment​
• Sponsorship of improvement initiatives​
Facilitate Business-IT collaboration and act cross businesses and
cross countries
 Business Value
 Sustainability
 Business Drive
 Active
Sponsorship
 Transversality
“Data Governance encompasses the people and organization, processes and
technology required to manage data as an enterprise asset”
17

18. Concrete working approach
18
A working approach driven by business value through an iterative process between DMC and Working Group.
Data Management Committee (Accountable)
Data Management Working Groups (Responsible)
Data
Initiative 1
Data
Initiative 2
Data
Initiative 3
Data
Initiative 4
Data Office : Champions the implementation and application of the Data topics across all of the
organization’s including IT and business domains.
Business
0. Share data issues and
define data Projects
1. Prioritize the data
initiatives
2. Establish KPI’s to
monitor progress
3. Launch Working
Groups and adapt
resources to reach
KPI’s
4. Report on progress
6. Bring Business Value
5a. Support
Data
Initiative 5
5b. Supervise the
DMC through the
CDO

19. Define
Discover
Qualify
Improve
Control Define
Discover
Discover
Qualify
Improve
Define
Discover
Qualify
Improve
Control
 Assess risks as a result of the data issue
 Identify root causes
 Identify and assess improvements to be
implemented
 Document data lineage
 Profile data
 Refine data definitions and
rules
 Implement technical data
quality rules
 Identify existing and
potential data issues
 Monitor data quality trend
 Monitor data governance scores
 Monitor data initiative objectives
 Identify, define and classify enterprise-
wide (critical) data, with its business
impact (processes, regulation, …)
 Define top-down business data quality
rules and data quality thresholds
 Launch and follow-up
improvement
• people (training,
communication, …)
• process
• technology
Data Territory
Bus. Domain
Concept
Term
Metric
Root Cause
Solution DMC Sponsor
…..
Application
API
Report
Data Source
Regulation
Business
Process
Personal Data
Record of
Processing
Capability
Strategic
Ambition
Bus. Objective
Bus. Initiative
Data Initiative
19
focusing on continuous improvement enriching over time a data centric knowledge base
Implementing a business-driven data management process
Data Steward
Process Owner
Quality Rule
IT Custodian
Architect
Result
Issue
Data Quality
Management
Functional
Landscape
Community
Business
Glossary
Strategy
Regulatory
Framework
Processes
Capabilities

20. 20
Where do we stand ?

21. Drive the entire organization to leverage data to get its targets
21
“In God we trust. All others must bring data.” – W. Edwards Deming,
CDO Office

22. Thank you