DataEd Webinar: Implementing Successful Data Strategies - Developing Organizational Readiness and Framework

Micheline Casey & Peter Aiken, PhD
Developing Your Data Strategy
Ensuring Alignment with Business Strategy, and Making it Practical and Actionable
1

Micheline Casey
• Micheline Casey is a senior executive with over 20 years  
experience helping organizations use data and  
information technology to grow and achieve strategic  
objectives. She is passionate about pushing boundaries  
with data, analytics, and tech, and applying design  
thinking to improve data product and service delivery.  
As principal at CDO, LLC, she works with a variety of  
organizations in multiple industries advising on the role  
of the chief data officer, data and analytics strategy,  
and organizational design considerations.
• Ms. Casey was the first Chief Data Officer at the Board of Governors of the Federal
Reserve System. She headed the Office of the Chief Data Officer (OCDO) and was
responsible for the FRB enterprise data strategy and innovation; overseeing data
governance policy development; transforming data management practices; and,
integrating data architecture. Ms. Casey was the first state government Chief Data
Officer in the country, and part of the Governor’s Office in the State of Colorado. Prior
to her work in public service, Ms. Casey worked for several technology companies,
including ChoicePoint (now LexisNexis), iXL Holdings, and IBM Global Services.
• Ms. Casey has been profiled in several industry articles on the role of the chief data
officer. She was named to DC’s Top 50 Women in Tech by FedScoop magazine and
on the 2011 Top 25 Information Managers list by Information Management magazine.
2Copyright 2016 by Data Blueprint Slide #

• 30+ years in data management
• Repeated international recognition
• Founder, Data Blueprint (datablueprint.com)
• Associate Professor of IS (vcu.edu)
• DAMA International (dama.org)
• 9 books and dozens of articles
• Experienced w/ 500+ data
management practices
• Multi-year immersions:
– US DoD (DISA/Army/Marines/DLA)
– Nokia
– Deutsche Bank
– Wells Fargo
– Walmart
– …
Peter Aiken, Ph.D.
• DAMA International President 2009-2013
• DAMA International Achievement Award 2001 (with
Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
PETER AIKEN WITH JUANITA BILLINGS
FOREWORD BY JOHN BOTTEGA
MONETIZING
DATA MANAGEMENT
Unlocking the Value in Your Organization’s
Most Important Asset.
The Case for the
Chief Data Officer
Recasting the C-Suite to Leverage
Your MostValuable Asset
Peter Aiken and
Michael Gorman

Copyright 2016 by Data Blueprint Slide #
Developing Your Data Strategy:  
• What is a Data Strategy?
• Implementing a Data Strategy
• Why is it so hard?
• Q&A
Data Strategy
It Should Be Concise,
Actionable, and
Understandable by Business
and IT!
Peter J. Aiken • Todd Harbour
4
Peter Aiken • Todd Harbour 
Forward by Micheline Casey, CDO#1

Data Strategy
Actionable, and
and IT!
• Q&A

IT Business
Data
As Is State of Data (as Perceived)
|————— Project-based —————| |——— Program-based ———|

|——————————————— Program-based ——————————————|
IT Business
Data
|————— Project-based —————|
Desired To Be State of Data (as Understood)

Data Strategy Framework
• Benefits & Success Criteria
• Capability Targets
• Solution Architecture
• Organizational Development
Solution
• Leadership & Planning
• Project Dev. & Execution
• Cultural Readiness
Road Map
• Organization Mission
• Strategy & Objectives
• Organizational Structures
• Performance Measures
Business Needs
• Organizational / Readiness
• Business Processes
• Data Management Practices
• Data Assets
• Technology Assets
Current State
• Business Value Targets
• Capability Targets
• Tactics
• Data Strategy Vision
Strategic Data Imperatives
Business
Needs
Existing
Capabilities
ExecutionBusiness
Value
New
Capabilities

What is a Strategy?
• Current use derived from military
• "a pattern in a stream of decisions" [Henry Mintzberg]

Former Walmart Business Strategy
Every
Day Low
Price

Guiding Principle
Strategy must be
the Business and
the Business must
be the Strategy

Simon Sinek: How great leaders inspire action
• “It’s not what you do,  
it’s why you do it”
• “People don't buy what
you do - they buy why
you do it”
http://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action.html
 
 
 
 
 
 
 
 
 
What
 
 
 
 
 
 
How
Why

Mike Tyson
• “Everybody has
a plan until they
get punched in
the face.”
– http://f--f.info/?p=23071

Organizational Assets
• Cash & other financial instruments
• Real property
• Inventory
• Intellectual Property
• Human
– Knowledge
– Skills
– Abilities
• Financial
• Organizational reputation
• Good will
• Brand name
• Data!!!

We believe ...
Data  
Assets
Financial  
Assets
Real 
Estate Assets
Inventory
Assets
Non-
depletable
Available for
subsequent
use
Can be  
used up
Can be  
used up
Non-
degrading √ √ Can degrade 
over time
Can degrade 
over time
Durable Non-taxed √ √
Strategic
Asset √ √ √ √
• Today, data is the most powerful, yet underutilized and poorly
managed organizational asset
• Data is your
– Sole
– Non-depletable
– Non-degrading
– Durable
– Strategic
• Asset
– Data is the new oil!
– Data is the new (s)oil!
– Data is the new bacon!
• Our mission is to unlock business value by
– Strengthening your data management capabilities
– Providing tailored solutions, and
– Building lasting partnerships
Asset: A resource controlled by the organization as a result of past events or transactions and from which
future economic benefits are expected to flow [Wikipedia]

Data Strategy
Actionable, and
and IT!
• Q&A

What is a data strategy and why
have one?
✤ A data strategy aligns with these priorities, goals, and objectives
to scope and prioritize key data and analytics initiatives and
activities. Ensures investment strategy into the right data
capabilities and technologies.
✤ A data strategy is about leveraging data to create business value.
✤ Data is your competitive advantage - you need a strategy for
ensuring it stays that way!
✤ “deepen the moat”
✤ change what it means for companies to compete against you

High-performing companies are
more data driven
✤ Companies that put data at the center of marketing and sales decision improve marketing ROI by 15-20%
(McKinsey, “Big Data, Analytics, and the Future of Marketing and Sales”, 2013)
✤ Companies that successfully use data outperform peers by up to 20% (EY, “Ready for takeoff?”, 2014)
✤ Firms that adopt data-driven decision making have output and productivity that is 5-6% higher than what
would be expected given other investments and, in other performance measures such as asset utilization,
ROE, and market value (MIT, “Strength in Numbers: How does DDD Affect a Firm’s Performance”,
Brynjolfsson/Hitt/Kim, 2011)
✤ High performing organizations report signiﬁcantly more advanced capabilities across all data capability areas
(McKinsey, “The need to lead in data and analytics”, 2016):
✤ Five times likelier than their low-performing peers to have tools and expertise to work with unstructured
and real-time data
✤ Twice as likely to make data accessible across the organization
✤ More diligent in measuring results
Industry leaders who do more with data and analytics deliver the following value:

What are key characteristics of a
good data strategy?
✤ aligns with business goals and
objectives
✤ is actionable, measurable, and
relevant
✤ identiﬁes key support, resources,
and constraints
✤ is a living document
✤ adds value to the organization!

Data strategy development - the
process
✤ pre-planning
✤ alignment with organization
strategy
✤ components and prioritization
✤ development
✤ lessons learned
Gather
inputs and
ar.facts
Conduct
interviews
and
assessments
Develop and
iterate
strategy
Socialize
ﬁnal plan
Finalize
strategy and
budget
Conduct
stakeholder
reviews

The pre-planning process
✤ What will the data strategy
development process look like
and how will it be gated?
✤ Identify key stakeholders and
participants
✤ Create communications plan
✤ Have an idea before you set out
of when it’s ‘good enough’

Align with organizational strategic
planning processes
✤ Most organizations have a formal strategic planning
process and cycle - understand it, leverage it!
✤ All organizations have a budgeting process - you need
it!

Development process
Gather
inputs and
ar.facts
Conduct
interviews
and
assessments
Develop and
iterate
strategy
Socialize
ﬁnal plan
Finalize
strategy and
budget
Conduct
stakeholder
reviews

Key components of a data strategy
✤ Background
✤ Vision, business case, and beneﬁts
✤ Goals, objectives, strategies, and
initiatives
✤ Implementation roadmap and priorities
✤ Risks and success enablers
✤ Budgets estimates
✤ KPIs and Metrics

Prioritizing initiatives
✤ Value add to the organization based on
business goals and objectives
✤ Key data capabilities or products your
organization needs
✤ Look at existing projects to identify what
is leverageable or creates multiplier
effects
✤ Other dimensions could include: business unit-
focused work; data domain work; functional
work; systems work
✤ Identify key value points along the way!

Tell the story!
✤ Promote empathy - design
thinking construct
✤ What are the narratives that will
strike a chord with your
stakeholders?
✤ What are the user personas or
use cases that will get people
excited?
✤ Stories reveal the hopes, dreams,
and aspirations of organizations

Perform a post-mortem
✤ What worked?
✤ What didn’t work?
✤ Where can we improve next time?
✤ Gather lessons learned

Data Strategy
Actionable, and
and IT!
• Q&A

Seven Deadly Data Sins
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic Means of
Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data  
Strategy Implementation
7. Failing To Address  
Cultural And Change  
Management  
Challenges

Critical Factors
• There Are No Unicorns
• Changing is Hard
• Compensate for the Lack of Data Competencies

Changing is Hard
adapted from the Managing Complex Change model by Dr. Mary Lippitt, 1987
Culture is the biggest impediment to a
shift in organizational thinking about data

The Enterprise Data Executive Takes One for the Team

Two Phase Approach to Data Strategy
1. Not Understanding Data-Centric Thinking
2. Lacking Qualified Data Leadership
3. Not implementing a Robust, Programmatic  
Means of Developing Shared Data
4. Not Aligning The Data Program with IT Projects
5. Failing to Adequately Manage Expectations
6. Not Sequencing Data Strategy Implementation
7. Failing To Address Cultural And Change  
Management Challenges

My Barn had to pass a foundation inspection
• Before further construction could proceed
• No IT equivalent in most organizations

You can accomplish
Advanced Data Practices
without becoming proficient
in the Foundational Data
Practices however  
this will:
• Take longer
• Cost more
• Deliver less
• Present  
greater 
risk 
(with thanks to  
Tom DeMarco)
Data Management Practices Hierarchy
Advanced  
Data  
Practices
• MDM
• Mining
• Big Data
• Analytics
• Warehousing
• SOA
Foundational Data Practices
Data Platform/Architecture
Data Governance Data Quality
Data Operations
Data Management Strategy
Technologies
Capabilities

• Q&A
Data Strategy
Actionable, and
and IT!
39

Two Books
PETER AIKEN WITH JUANITA BILLINGS
FOREWORD BY JOHN BOTTEGA
MONETIZING
DATA MANAGEMENT
Unlocking the Value in Your Organization’s
Most Important Asset.

10124 W. Broad Street, Suite C
Glen Allen, Virginia 23060
804.521.4056
Copyright 2016 by Data Blueprint Slide # 42

DataEd Webinar: Implementing Successful Data Strategies - Developing Organizational Readiness and Framework

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