Governance has little to do with governance…it’s about delivering and demonstrating value. It’s one thing for your colleagues to intellectually believe in the value of data, good data, and governed data, but it’s another thing entirely to have them emotionally engaged and excited to be involved. In this presentation from the CDO Sit-Down series, Shaun Connolly, Vice President of International Strategic Services, shares his thoughts and experience on approaches to win over reluctant leaders and business teams and describe the key components of successful programs.

1. Data Integrity:
From speed dating
to lifelong
partnership
Shaun Connolly | VP, International Strategic Services

2. Data Strategy
Leverage our team of career data
leaders and professionals to define,
implement and optimize your data
program using proven and leading
practices and data solutions
- Recognized Data Thought Leadership
- 100% Referenceable Client Success
- Strategy Through Execution
- SAP Preferred Delivery Partner
- Business Value Delivery Model
- Proven Industry Knowledge
“Top choice for clients looking for a
well-rounded data governance
solution with solid data quality
capabilities and data strategy
consulting services”
The Forrester Wave™
Data Execution
Implement proven approaches to
ensure critical data is prioritized and of
high quality to deliver business results
and enable strategic priorities
Organization Enablement
Instill a data-driven culture and
accountability mindset for trusted
decision-making and ensure business
adoption of data-centric mentality
using proven data operating models
Value Realization
Clearly align data initiatives to
business value drivers with meaningful
performance measures that quantify
their value and drive followership and
adoption within the organization.
Who are we?
Precisely - Strategic Services

3. “I took the road less traveled by…”
HIGH-TECH
MANUFACTURING
LOGISTICS
DATA (BI, Analytics, Data Science,
Strategy, …)
Tech Move,
Inc.

4. Let’s define data integrity

5. Data integrity
is…
data with maximum
accuracy,
consistency, and
context for
confident business
decision-making

6. Supply Side Management & Exchange Demand Side
Data Enrichment, Curation,
Control & Improvement
Data Utilization, Consumption
& Leverage
Applications
Mobile
Various Data
Types (semi…)
Transactional/
Operational
Systems
Data Integrity
Operations
Metadata Management
Data Quality
Management
Data Preparation &
Engineering
Data Intelligence
Data Monetization
Metrics /
KPI’s
Analytics
Data Science
& Predictive
Analysis
Data Creation, Capture
and Collection
Data
Products
Building blocks of success throughout the
data lifecycle

7. Now, back to this speed dating thing

8. How on earth did you come
up with “speed dating to
lifelong partnership”?…
• It’s Valentines Day?!?
• The average “life expectancy” of a CDO is 31
months
• I believe, we’ve spoken the wrong language,
focused on what matters to us, not “them”
• So, how do you quickly win hearts & minds,
ensure long-term success and deliver value?

9. Despite all the
talk about data …
• …data and data
integrity for most
is still a “have
to,” not a “want
to.”
Time
they
will
spend
Number of things they pay attention to
What someone will
do because they
have to
What someone will
do because they
want to
Likeability gap*
*Rohit Barghava, Likenomics
Understanding the
likeability gap

10. Why is this so challenging?
Data Integrity, BI and Analytics are just,
well, different…
“If I had asked people what
they wanted, they would
have said faster horses.”
― Henry Ford
You had lost me at hello when you asked:
• What data is important to you?
• How do you want to use your data?
• What are your CDE’s (critical data elements)?
• Do you want to be a data owner?

11. Bridging the Gap
The challenge is that ‘Data governance’ is perhaps
the least sexy term on the planet…
and yet, data is
everything.
But the point of governance integrity is NOT
governance

12. The point is delivering outcomes
So, what I hear you saying is you’re are frustrated
because…
Value
New Acquisition
Data captured
Intelligence delivered
Missed Opportunity
Event
Action
taken
Time
Business Opportunity!
Data
latency
Analysis
latency Decision
latency
• It takes too long to get pricing, negotiate a contract and onboard a new
customer
• It’s nearly impossible to know profitability of a given customer,
product, industry segment, etc.
• It’s too difficult to evaluate & integrate a new acquisition to quickly
get the value expected
You can help me reach my 2023 objectives!!

13. Business / Program Goals
(e.g., GTM Optimization, Digital Enablement)
Objectives, Metrics and Reports
(e.g., Critical Performance Measures)
Data Integrity Framework
& Operating Model
(e.g., Data Ownership, Data stewardship)
Information (business terminolo
(e.g., business glossary enabling self-service)
Data
(e.g., critical data)
G Glossary
C Data
G Goals
O Objectives M Metrics
R Rules
S Standards P Processes
Translation into Data Integrity
Framework: Connecting critical data to
business objectives

14. From Data to Business Value
Bottom
Up
Top
Down
Middle
Out
TOP DOWN: Critical information driving business
goals, objectives, KPIs, and business performance
MIDDLE OUT: Critical data that drives business
processes, operations, and reporting
BOTTOM UP: Critical data assets that have
operational, compliance and analytical business
impacts.

15. Core Components
Required for Successful Data Integrity Programs
Decision Tree to identify critical
data and ensure governance actions
are always based on value drivers and
follow a repeatable and scalable
model with metrics aligned to
business objectives
Business accountability for
data with ‘fit for purpose’ operating
models/processes and a
complementary org construct to
provide a structured & repeatable
process for sustained data integrity
and value creation
Data Quality & Integrity
Framework that ensures the
availability, usability, integrity, and
sustainability of our most critical
data in support of analytics,
business operations and compliance
Data Architecture and
Applications that are directly
aligned to business objectives,
integrate seamlessly, scale and
promote data collaboration,
efficiency and literacy
Successful
Data
Programs

16. Evidence of a lifelong partnership

17. Value
creation:
Data Integrity
programs deliver
ROI
63%
Higher revenue growth
when data is treated as a
strategic key asset &
governed
48%
Fewer project delays (IT
related) and over budget
when leveraging a Data
Governance Operating
Model
50%
Reduction in key
customer failures due to
data
37%
Lower organizational
initiatives over budget when
Data Stewards ensure data
consistency
20%
Improvement in
syndicated data

18. Three Customer Examples
Cycle Time Reduction
New Product
Introduction
• A manufacturer of Industrial
HVAC products wanted to
reduce cycle-time for product
manufacture.
• Evaluated data across the key
business processes. Linked data
quality conditions to each step
• Cycle-time dashboards included
data quality levels and trends to
guide data stewardship
activities for data improvement.
• ROI: 30% improvement in cycle
time
• Global CPG wanted to reduce
their time-to-market with new
product introductions
• Completed process
transformation strategy and
leadership, enabling
workstream leads vision for
change at high levels, while
diving deep into the task-level
critical data and data lineage
• Data rules, transformation rules,
data quality and governance.
• Business impact: 50% less
process touches and 50% faster
to market
Single View of
Customer
• Global Bank needed a single
view of customer across
disparate systems.
• Required business rules to be
instantiated through advanced
data cleansing,
sophisticated/complex
customer consolidation and
“house-holding”
• Result: Now understand
current and future value of each
customer, what services they
use, and target marketing
opportunities

19. Fail! Why data programs/initiatives
fail?
• “The main reasons why relationships
fail are poor communication, a
difference in priorities, loss of
trust, lack of respect, and little
intimacy”
– Barbara Field and Rachel Goldman, PhD,
FTOS
Other than the last point..
just sayin’

20. Session Takeaways
• Speak their language. Talk business challenges & objectives
• Transformation comes unlocking the value of data – from “have to” to “want to”
• 4 components to successful programs
1. Framework
2. Operating model & organization
3. Fact-based model for critical data and metrics
4. Data architecture & applications
• Lifelong partnerships and data integrity journeys are not that different

21. precisely.com/solution/data-governance-solutions
Thanks!