Data Governance, like a relationship, requires a strong foundation and commitment to make it work.  In this presentation, Esther Lim, Sales Engineering Manager, explores the main reasons why Data Governance initiatives fail and the key components that are necessary to build a sustainable program with long-term engagement within your organization.

1. Data Governance:
From Speed Dating to a
Lifelong Partnership
Esther Lim | Sales Engineering Manager

2. The Need for Business-First Governance
of governance
initiatives fail to
deliver expected
outcomes
80%
Source: Gartner
Unrealistic
Expectations
Lack of
Leadership
and
Ownership
Overlooking
Cultural
Factors
Regulatory
and
Compliance
Challenges
Insufficient
Resources
and
Support
Poor
Training
and
Education
Resistance
to
Change
Inadequate
Communication
and
Engagement
Lack of
Continuous
Monitoring
and
Improvement
Lack of
Data Quality
and
Management

3. How to Build a Data Governance
Program That Lasts

4. Business-First
Data Governance
Link to Organisational Goals
Goal
P A I N K I L L E R S
V I T A M I N S

5. Business-First
Data Governance
Prioritise What Matters

6. Business-First
Data Governance
Build Engagement Across 3 Levels
Operational
Strategic
Tactical

7. Key Components to a Sustainable Program
Decision Tree to identify
critical data
Business Accountability for
data with ‘fit for purpose’
operating models/processes
Data Integrity Framework
that ensures the availability,
usability, integrity, and
sustainability of our most
critical data
Data Performance
Measures that organises
critical data quality and
governance metrics
Successful
Data
Programs

8. Data Integrity Framework
Policies, processes, standards
• Operating model
• Roles & responsibilities
• Data governance team
• Ownership
• Escalation structure
Structure
• Operating model
• Roles & responsibilities
• Data governance team
• Ownership
• Escalation structure
Strategy
• Vision statement
• Objectives & goals
• Building business case
• Building high level roadmap
• Alignment to data strategy
Technology
• Glossaries
• Metadata repository
• Business & technical lineage
• Workflows
• Enable collaboration
Metrics
• Statistics & analysis
• Progress tracking
• Issues monitoring
• Data governance scores
• Data quality scores
Communication
• Rollout Plan
• Communication Plan
• Training Plan
• Onboarding Data Stewards Plan
• Program Management
Data Integrity

9. Operating Models
Governance operating models
typically established for …
• Data governance artifacts
(business glossary, data dictionary,
data standards, business rules)
• Data profiling/analysis
• Data cleansing/remediation
• KPI’s and business metrics

10. Decision Tree Drives Prioritisation
Establishing a structured, repeatable decision tree to
identify and evaluate Critical Data Elements and determine
the appropriate governance strategy, method and
ownership model.
It ensures Critical Data Elements are tied to business value
drivers and dictates impact and prioritization.
What do we
govern?
How should we
govern?
Governance
Model
Who should
govern?
Where should
we govern?

11. Data Governance Metrics Model
Business impact
• Analytics enablement
• Process enablement
• KPI’s / PPI’s
• Project acceleration
Performance and value
• Data Quality (e.g. accuracy)
• # of touches
• Data error % (Rework %)
• Cycle time vs SLA’s
• Timeliness / availability
Efficiency & effectiveness
• Volume / counts
• Cycle time (Timeliness)
• Completeness
• Accessibility
• Scale (# Systems managed)
Ideal data quality metrics
Metrics are organised and managed in
three (3) main levels or categories
Every metric has a purpose (tells us a story)
• What are we doing?
• How are we doing?
• What’s changing (trends)?
• Are we making an impact?
Metrics are dimensionalized for
proper analysis and action

12. Proper Data Governance Removes Friction
Why aren’t people
coming to my monthly
governance meetings?
• Meetings
• Surveys
• Approvals
• Procedures

13. Data Catalog
Scavenger Hunt
Increased platform
adoption by 36%
Explainer Videos
Improved DG Council
attendance by 52%
Steward
Gamification
Increased workflow
speed by 18%
Craig

14. Key Components to a Sustainable Program
Decision Tree to identify
critical data
Business Accountability for
data with ‘fit for purpose’
operating models/processes
Data Integrity Framework
that ensures the availability,
usability, integrity, and
sustainability of our most
critical data
Data Performance
Measures that organises
critical data quality and
governance metrics
Successful
Data
Programs

15. Cloud / VPC / On-Premises
Data
Integration
Data
Observability
Data
Quality
Geo
Addressing
Spatial
Analytics
Data
Governance
Data
Enrichment
APIs and SDKs
Enterprise Business
Systems
• Enterprise apps
• Analytics tools
• Precisely industry
apps
• BI dashboards
• AI/ML
Enterprise Data
Sources
• Business Intelligence
• CRM
• Workforce mgmt.
• Data warehouse
• ERP
• Billing
Data Integrity Services
Data Integrity Foundation Data catalog Intelligence Agents

16. Questions?
precisely.com/solution/data-governance-solutions