This document outlines a presentation on developing a data-centric strategy and roadmap. It discusses the importance of aligning data management goals to business needs through frameworks like Porter's competitive strategies and operating models. Metrics and success criteria must be defined by collaborating with business partners to measure improvements in specific opportunities. An example shows how a chemical company measured reductions in testing time and increases in researcher productivity after implementing a solution to integrate data across disparate systems.

1. Copyright 2014 by Data Blueprint
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Data-centric Strategy & Roadmap
Date: January 13, 2015
Time: 2:00 PM ET
11:00 AM PT
Presenters: Peter Aiken,
Lewis Broome

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Commonly Asked Questions
1) Will I get copies of the slides
after the event?
2) Is this being recorded so I
can view it afterwards?
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Data Management & Business Intelligence

4. Building a Data-centric Strategy &
Roadmap
What needs to be done… avoiding a haphazard
approach
Presented by Peter Aiken, Ph.D. and Lewis Broome

5. Copyright 2014 by Data Blueprint
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• 30+ years DM
experience
• 9 books/
many articles
• Experienced with
500+ data
management
practices
• Multi-year
immersions: US DoD,
Nokia, Deutsche
Bank, Wells Fargo, &
Commonwealth of VA
Lewis Broome Peter Aiken
• CEO Data Blueprint
• 20+ years in data
management
• Experienced leader driving
global solutions for
Fortune 100 companies
• Creatively disrupting the
approach to data
management
• Published in multiple
industry periodicals
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Outline
• Data Strategy Overview
• Determining the Business Needs
• Measurement & Success Criteria
• Current State Analysis
• Developing a Solution to Address Needs
• Developing a Roadmap and Plan
• Q&A

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"The significant
problems we
face cannot be
solved at the
same level of
thinking we
were at when
we created
them."
- Albert Einstein

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Wayne Gretzky’s
Definition of Strategy
He skates to where he
thinks the puck will be ...

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The
Importance
of Strategy
Organizational
Strategy
IT Strategy
Data Strategy

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Summary: Enterprise Data Strategy Choices
Q3
Using data to create
strategic opportunities
Q4
Both (Cash Cow)
Q1
Keeping the doors open
(little or no proactive data
management)
Q2
Increasing organizational
efficiencies/effectiveness
Improve Operations
Innovation
Only 1 in 10 organizations has a
board approved data strategy!

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Understanding WHY Data is Important to the Business
• Data linked to, and part of, the products & services
being offered
• Information is power (Analytics!)
• Data creatively destructs how we work; skills & the
workforce needed are drastically different
• Data volume, velocity & variety exerting
pressure on operating models
& infrastructure
“…it’s not what you do, it’s why you do
it” – Simon Sinek
http://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action.html
Why
Vision
How
Process
What
Outcome

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Putting the Data Strategy Together
Comprehend your organization’s competitive advantage,
operating model & business goals
Define specific business opportunities that impact these
Define the metrics that measure improvement in business
performance
Requires people, process, data and technology while
recognizing strengths and limitations of culture & capability
Outline an achievable implementation plan in a roadmap with
timelines, milestones and level of effort estimates
Get on the same
page with
business partners
Measure
Business Value
Develop a holistic
solution and
approach
Note: For many organizations this requires a transformation in how they think and
operate – this is the greatest challenge in becoming a ‘data-driven’ organization

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Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– Example Data Strategy Goals
• Measurement & Success Criteria
• Current State Analysis
• Developing a Solution to Address Needs
• Developing a Roadmap and Plan
• Q&A

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Aligning Data Management Goals to the Business
• Competitive Advantage
– Its not about being the best, its about being different
• Operating Models
– The interactions across processes, business units, customers
and products
• Business Strategy and Goals
– Short and Long Term; Leadership’s Dynamic
priorities and investments
• Use Frameworks for Understanding
Start with Analyzing the Business…..

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Porter’s Competitive Strategic Framework
Cost: Are you
competing on cost?
How cost-sensitive is
your market?
Market Scope: Are you
focused on a narrow
market (i.e. niche) or a
broad market of
customers?
Overall Low-Cost
Leadership
Strategy
Broad
Differentiation
Strategy
Focused
Low-Cost
Strategy
Focused
Differentiation
Strategy
Blue Ocean
Brands
Lower Cost Differentiation
Broad
Range of
Buyers
Narrow
Buyer
Segment
Product Differentiation: How specifically focused are your
products?
Note: (Typically) Can’t be all things to all consumers –
where are you?

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Competitive Strategic Framework - Example
Overall Low-Cost
Leadership
Strategy
Broad
Differentiation
Strategy
Focused
Low-Cost
Strategy
Focused
Differentiation
Strategy
Blue Ocean
Brands
Lower Cost Differentiation
Broad
Range of
Buyers
Narrow
Buyer
Segment
• Its all about how value is created!
• Works for Non-profits as well (Substitute ‘Mission’ for Value)

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Porter’s Five Forces Framework
Bargaining Power of Buyers: The degree
of leverage customers have over your
company
Bargaining Power of Suppliers: The
degree of leverage suppliers have over your
company
Threat of New Entrants: How hard is it for
new competition to enter the market?
Threat of Substitute Products: How easy
(or hard) is it for customers to switch to
alternative products?
Competitive Rivalry: How competitive is
the market place?
Once you find your place in the four quadrants…What is your competitive
advantage?
http://www.strategy-keys.com/michael-porter-five-forces-model.html

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Five Forces - Example
Whole Foods
• Customers (weak influence) will seemly pay any price for specially sourced commodities
• Fewer suppliers (strong influence) to support Whole Foods’ customer demands
5 Forces Whole Foods Wal-mart
Threat of New Entrants Weak Weak
Bargaining Power of Buyers Weak to Moderate Moderate to Strong
Bargaining Power of Suppliers Moderate to Strong Very Weak
Threat of Substitutes Strong Moderate to Strong
Competitive Rivalry Moderate Weak
Wal-mart
• Price-sensitive customers. Use strength over suppliers to maintain low costs.
• Heavy investment in keeping operational cost low. Highly efficient internal processes

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Operating Model Framework
Coordination
• Shared customers, products or suppliers
• Impact on other business unit transaction
• Operationally unique business units or functions
• Autonomous business management
• Business unit control over process design
• Consensus processes for designing IT infrastructure
services
• IT application decisions made in business units
Unification
• Customers and suppliers may be local or global
• Globally integrated business processes often with
support of enterprise systems
• BU’s with similar or overlapping operations
• Centralized management often applying functional/
process/business unit matrices
• Centrally mandated databases
• IT decisions made centrally
Diversification
• Few, if any, shared customers or suppliers
• Independent transactions
• Operationally unique business units
• Autonomous business management
• Business unit control over business process design
• Few data standards across business units
• Most IT decisions made within business units
Replication
• Few, if any, shared customers
• Independent transactions aggregated at high level
• Operationally similar business units
• Autonomous BU leaders with limited discretion over
processes
• Centralized control over business process design
• Standardized data definitions but locally owned
• Centrally mandated IT services
Business Process Standardization
Low High
HighLow
BusinessProcessIntegration
*Source: Gartner

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Operating Model - Examples
Coordination Unification
Diversification Replication
Business Process Standardization
Low High
HighLow
BusinessProcessIntegration
*Source: Gartner

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Business Strategy and Goals
• A cohesive declaration of organizational direction, strategies,
goals, targets, objectives, approaches and plans
• Usually tied to a time frame
• Constrained by competitive advantage and operating models
• Dynamically created as a result of
opportunities and challenges
• Aligns to overall mission and brand

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Business Strategy and Goals - Example
Strategy for a large publicly traded logistics company
“We forge long-term partnerships with key customers that include supply-chain
management as an integral part of their strategy. Working in concert, we drive out cost,
add value and function as an extension of their enterprise. Our strategy is based on
utilizing an integrated, multimodal approach to provide capacity-oriented solutions
centered on delivering customer value and industry-leading service. We believe our
unique operating strategy can add value to customers and increase our profits and
returns to stockholders.”
Brand Promises to their Customers
• Undeniable Flexibility
• Unmatched Capacity
• Unrivaled Service
• Undisputed Experts
• Unprecedented Control

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Data Strategy Goals – Example-1
Enterprise
Divisional
• An 360° enterprise level understanding of customers, capacity, orders & vendors
• Asset and driver utilization maximized across the enterprise
• IT solutions leveraged across the enterprise to reduce costs and cycle-time
• Customers seamlessly leverage services across divisions
• A 360° divisional level understanding of customers, capacity, orders & vendors
• IT solutions leveraged to support operational uniqueness of each division
• Minimize cost and maximize revenue per load per division
Division A Division B Division C Division D
Enterprise
Rolls Up To

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Data Strategy Goals – Example-2
Increase
Operational
Efficiencies
As-IsTo-Be
As-Is Efficiency Challenges
• Complex & un-integrated business processes
• Suboptimal data structures & controls creates poor data
quality
• Lack of transparency and controls creates work-around’s
To-Be Efficiency Improvements
• Eliminate non-value added manual work-around’s
• Maximize auto-accepts (i.e. straight-through-processing)
• Simplify & automate workflows
• Create transparency to enable proactive processes
Increasing operational efficiencies will…
• Lower cost per order/load
• Increase capacity utilization within & across divisions

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Summary: Aligning Data Management Goals to the Business
A Data Strategy must be Business Focused
• Understand the business fundamentals of your organization
• Develop a common language and shared perspective with your
business partners – enabling collaboration
• Identify specific business opportunities or areas of improvement
• Focus the data strategy solution on improving those
specific business needs
Next Step:
• Measuring business value of
making improvements:
• Metrics, Object of Measurement and Methods

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Outline
• Data Strategy Overview
• Determining the Business Needs
• Measurement & Success Criteria
– An Overview
– An Example
• Current State Analysis
• Developing a Solution to Address Needs
• Developing a Roadmap and Plan
• Q&A

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Measuring Business Value
If something is important to the business it can be observed. If it can
be observed, it is measureable!
• Understanding ‘measurement’; reducing uncertainty, not necessarily
an exact value
• Object of Measurement; often too ambiguously defined
• Methods of Measurement; become familiar with multiple methods and
apply in the right context
Define success criteria as specific metrics
• Not always intuitive and at first seems difficult
• Must be done in collaboration with your business partners

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Great point of initial
inspiration ...
• Formalizing stuff forces
clarity
• Special shout out to
Chapter 7
– Measuring the value of
information
– ISBN: 0470539399
– http://www.amazon.com/
How-Measure-Anything-
Intangibles-Business

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Measuring Business Value – An Example
• $1billion (+) chemical company
• Develops/manufactures additives
enhancing the performance of oils
and fuels ...
• ... to enhance engine/machine
performance
– Helps fuels burn cleaner
– Engines run smoother
– Machines last longer
• Tens of thousands of
tests annually ($25K to $250K each)
International Chemical Company Engine Testing

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Objects of Measurement & Metrics
• Test Execution: Number of tests per customer
product formulation. Grouped by product types
and product complexity.
• Customer Satisfaction: Amount of time to
develop a certified custom formulated product;
time from initial request to certification
• Researcher Productivity: Tested and certified
formulations per researcher
Note: Baseline measures were taken from historical data and anecdotal
information

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Overview of Existing Process
1. Manual transfer of digital data
2. Manual file movement/duplication
3. Manual data manipulation
4. Disparate synonym reconciliation
5. Tribal knowledge requirements
6. Non-sustainable technology

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Solution and Business Value Results
• Solution:
– Business process improvements
– Data Architecture Development
– Data Quality Improvements
– Integrated System Development
• Results:
– Reduced the number of tests needed to develop products
– Increase the number of tests per researcher
– Reduce the time to market for new product development
• According to our client’s internal business case development,
they expect to realize a $25 million gain each year thanks to
this data integration

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Summary – Measuring Business Value
• If it’s important to the business, it’s measureable
• Learning to measure business value requires:
– Understanding fundamentally what it means to ‘measure’
– Being clear about what is going to be the object of
measurement and the specific metrics
– Methods that will ensure the metrics captured are
meaningful and consistent
• The old adage – “if you don’t measure it, it can’t be
managed” is true
Next Step:
• Develop a holistic solution and approach to address the
business needs identified in the data strategy

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Outline
• Data Strategy Overview
• Determining the Business Needs
• Measurement & Success Criteria
• Current State Analysis
– Analysis Framework Overview
– Examples
• Developing a Solution to Address Needs
• Developing a Roadmap and Plan
• Q&A

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Analyzing the Current State (ACS)
Why we are analyzing the current state…
• Identify existing assets to be
leveraged
• Identify gaps in assets and
capabilities
• Identify constraints &
interdependencies in the operating
environment
• Measure Cultural Readiness –
scope of change management efforts
• Ensures solutions are achievable

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Data Strategy Framework (DSF)
Business
Need
Current
State
Solution
Target Source
Value Capabilities
DATA STRATEGY
Road Map
• Org. Readiness
• Bus. Processes
• Bus. & Data
Practices
• Data Assets
• Tech Assets
• Bus. Strategy &
Objectives
• Competitive
Advantage
• Bus. Structures
• Bus. Measures

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Analyzing the Current State (ACS)-1
What we are analyzing…
• People and Organization
• Business Processes
• Data Management Practices
• Data Assets
• Technology Assets
Note: Scope of the analysis, across all facets of the current state environment, is
constrained by the business needs definition. This mitigates the risk of over
analyzing the current state.

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Analyzing the Current State (ACS)-2
People &
Organization
Data Assets
Technology Assets
Data Mgmt. Practices
Business Processes
Business
Goals and
Objectives
Creates
Enables
Informs
Enables
Enables
Measures
Delivers
Enables
Enables
Provides
Context

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Typical Thinking: Application-Centric
• In support of strategy, organizations develop specific
goals/objectives
• The goals/objectives drive the development of specific
systems/applications
• Development of systems/applications leads to network/
infrastructure requirements
• Data/information are typically considered after the
systems/applications and network/infrastructure have
been articulated
• Problems with this approach:
– Ensures data is formed to the applications and not
around the organizational-wide information
requirements
– Process are narrowly formed around applications
– Very little data reuse is possible Data/Information
Network/Infrastructure
Systems/Applications
Goals/Objectives
Strategy

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New Thinking: Data-Centric
• In support of strategy, the organization develops specific
goals/objectives
• The goals/objectives drive the development of specific
data/information assets with an eye to organization-wide
usage
• Network/infrastructure components are developed to
support organization-wide use of data
• Development of systems/applications is derived from the
data/network architecture
• Advantages of this approach:
– Data/information assets are developed from an
organization-wide perspective
– Systems support organizational data needs and
compliment organizational process flows
– Maximum data/information reuse
Data/Information
Network/Infrastructure
Systems/Applications
Goals/Objectives
Strategy

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ACS: People
What we are looking for…
• Organizational Structures
• Skills and capabilities
• Culture
Why we look at People…
• Understand current roles, responsibilities & accountability
• Assess skills & capabilities to determine what’s achievable
• Determine how adaptable the organization is to change
• How the cultural nuances drive the operating environment

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2005
2006
2007
2008
2009
2010
20110.000
0.200
0.400
0.600
0.800
IT/InformationSecurity/Privacy
Virtualization
Datacenter/IT
efficiencies/Cloud
SocialMedia
Improvingpeople/leadershipBI/analytics
Standardization/consolidation
IT
workforcedevelopment
IT
governance
Riskmanagement
Mobileapplications/technologies
InformationSharing
Implementingplans/initatives/achievingresults
Acquisition/projectmgt
Process/system
integration
Strategicplanning
CDO Reporting
1. Dedicated solely to
data asset leveraging
2. Unconstrained by an
IT project mindset
3. Reporting to the
business
Top
Operations
Job
Top Job
Top Finance
Job
Top
Information
Technology
Job
Top
Marketing
Job
Data Governance Organization
Chief
Data
Officer

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ACS: Business Process
What we are looking for…
• Process flows (Diagrams) from a business perspective
• Process actors, including data creators and data consumers
• Pain points in the existing business processes
• Existing performance measures of business processes
Why we want to look at business processes…
• Business value of data is realized via a business process
• Most important events in the life of data – when it is created
and when it is used (Dr. Tom Redman)
• Describes the activities underpinning the competitive
advantage

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ACS: Automating Business Process Discovery
Benefits
• Obtain holistic perspective on roles
and value creation
• Customers understand and value
outputs
• All develop better shared understanding
Results
• Speed up process
• Cost savings
• Increased compliance
• Increased output
• IT systems documentation

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ACS: Data Management Practices-1
What we want to look at…
• Level of importance of data and information in
organizational strategy – is it explicitly identified as an
asset to be leveraged?
• How data requirements are derived
• Degree to which data is shared across organization
• How data quality issues identified and remediated.
• How data assets are designed and implemented
• How data assets are controlled, protected and maintained
once they are operational – e.g. compliance, security,
business continuity

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ACS: Data
Management
Practices
Analyzing your
Data Management
Practices will be
critical in
developing
achievable
solutions

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4
7
Copyright 2013 by Data Blueprint
<- CMM Level 2

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4
8
Copyright 2013 by Data Blueprint
Assessment Components
Data Management Practice Areas
Data program
coordination
DM is practiced as a
coherent and coordinated
set of activities
Organizational data
integration
Delivery of data is support
of organizational objectives
– the currency of DM
Data stewardship
Designating specific
individuals caretakers for
certain data
Data development
Efficient delivery of data via
appropriate channels
Data support
Ensuring reliable access to
data
4
Capability Maturity Model
Levels
Examples of practice maturity
1 – Initial
Our DM practices are ad hoc and
dependent upon "heroes" and heroic
efforts
2 - Repeatable
We have DM experience and have the
ability to implement disciplined processes
3 - Documented
We have standardized DM practices so
that all in the organization can perform it
with uniform quality
4 - Managed
We manage our DM processes so that the
whole organization can follow our
standard DM guidance
5 - Optimizing
We have a process for improving our DM
capabilities

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4
9Copyright 2013 by Data Blueprint
49

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Data Management Practices Hierarchy
You can accomplish
Advanced Data Practices
without becoming
proficient in the Basic
Data Management
Practices but this will:
• Take longer
• Cost more
• Deliver less
• Present
greater
risk
5
0Copyright 2013 by Data Blueprint
Basic Data Management Practices
Advanced
Data
Practices
• MDM
• Mining
• Big Data
• Analytics
• Warehousing
• SOA
50
Data Program Management
Data Stewardship Data Development
Data Support Operations
Organizational Data Integration

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ACS: Data Assets-1
What we are looking for…
• Broad view of the data assets (Structure and unstructured)
– Business Entity Inventory
– Business Entity Diagram
– Data Ecosystem
– Enterprise data architecture
– Application architecture describing systems and their relationships
• Narrow view of data assets in the context of the business needs
– Not all data impacts the business needs equally
– Data Dictionary
– Data Profiling
– Data models
– Tools to automate discovery such as Global ID’s

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ACS: Data Assets – Data Quality Considerations
Prevention at Source
Find and Fix
Ad-Hoc Processes
An interpretation from Dr. Tom Redman’s ‘Three Approaches to Data Quality’

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ACS: Data Assets-2
Why we want to look at data assets…
• Trying to find pain points
• Set the boundaries for what data and information is
possible under current conditions
• Understand how well the organization understands what
data exists
• Compartmentalize and decouple data from systems
• Provides a data-centric business perspective that cannot
be seen easily from business processes
• Provides a measure of complexity and potential risk of the
current operating environment

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ACS: Technology Assets-1
What we want to look at…
• Broad view of technology assets
– Enterprise and application architecture artifacts
– Inventory of technology, software, tools and environments
– Current standards vs. legacy vs. “bolt-on” technology
– Process for buying technology
– Pain points and constraints
• Narrow view of technology assets in the context of business
needs
– Identify specific systems, technology, etc… in scope
– Assess capabilities and constraints
– Implementation approach – e.g. customized or off the shelve
– Ability to non-functional requirements – e.g. performance, capacity
Why we want to look at technology assets…
• ….

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ACS: Technology Assets-2
Why we want to look at technology assets…
• What technology assets are currently available for the
solution
• What technology standards needs to be considered in the
solution
• Informs as to the complexity of the current environment
• Highlights ‘shadow’ technology solutions

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How to Analyze the Current State
• Interviews
• Surveys
• Document and artifact review
• Intranet and wiki reviews
• Facilitated sessions – i.e. Workshops
• Leverage existing organizational structures – i.e.
working groups, governance teams
• Requisite Skills: Critical Thinking, Inquisitiveness,
Collaboration, Tenacity, Organization and Technical
Writing

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Outline
• Data Strategy Overview
• Determining the Business Needs
• Target Measurement & Success Criteria
• Current State Analysis
• Developing a Solution to Address Business Needs
– Closing Foundational Gaps
– Solving for Specific Business Needs
• Developing a Roadmap
• Q&A

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Data Strategy Framework (DSF)
Business
Need
Current
State
Solution
Target Source
Value Capabilities
DATA STRATEGY
Road Map
• People & Org.
• Bus. Processes
• Data Mgmt.
Practices
• Data Assets
• Tech Assets
• Bus. Strategy &
Objectives
• Competitive
Advantage
• Bus. Structures
• Bus. Measures

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Expected Results
Data Strategy Solution should…
• Be tailored to solve specific business needs
• Be measureable against set targets
• Develop organizational capabilities, as necessary,
to ensure the solution is sustainable
• Be achievable given the current state capabilities
• Define a solution with enough specificity to
develop an implementation road map

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Data Strategy Solution Framework (DSSF)
People &
Organization
Data Assets
Technology Assets
Data Mgmt. Practices
Business Processes
Business
Goals and
Objectives
Enables
Enables
Informs
Creates
Enables
Measures
Delivers
Enables
Enables
Provides
Context
The solution architecture and change management plans result from this framework

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Change in a Complex Environment

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Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– An Example
• Measurement & Success Criteria
– An Overview
– An Example
• Developing a Solution to Address Needs
– Closing Foundational Gaps
– Solving for Specific Business Needs
• Developing a Roadmap and Plan
• Q&A

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How To: Creating a Roadmap
• Outputs from…
– Business Needs Assessment
– Current State Analysis
• In support of the Business Strategy
– Inextricably Linked
• Come up with a reasonable way to ID and close the
gaps within the solution framework
– Outline a long-term vision and implementation milestones
– Achievable, realistic plans
– Build momentum with specific, short-term win projects
• Approach: Crawl, Walk, Run

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The Approach of Crawl, Walk, Run
• Crawl:
– Identify business opportunity and determine a scope that fosters
early learning yet delivers measureable value
• Walk:
– Develop foundational &
technical data management
practices ensuring they are
repeatable. Enlarge the
scope of projects that
expand capabilities
• Run:
– Continuous improvement and expanded application of maturing
data management practices

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The Benefits of Crawl, Walk, Run
• ‘Pilot-like’ projects create a unique opportunity for
organizational learning while providing measureable
value
• Builds support for new approaches to data management
– i.e. supports change management activities
• More achievable approach to managing data as an asset
• Allows for foundational components to be developed
while concurrently executing more tactical solutions

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Road Map Framework
• High-level Road Map
• Road Map Activities
• Align Activities to Business Value Targets (i.e.
Traceability)
• Road Map Activity Details
• Level Of Effort Estimates (where possible)
• Budget Estimates (where possible)

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Sessions:
• Data Strategy 2.0: Focus on the
Roadmap and Implementation
• 3 hour workshop with Lewis Broome
• Addressing Data Challenges
using the Data Management
Maturity Model
• Melanie A. Mecca, CMMI Institute
Peter Aiken, Data Blueprint
• 120+ thought leaders
• 800 attending Senior IT
Managers, Architects, Analysts,
Architects & Business Executives
• 5 full days of in-depth education
and networking opportunities
• … and more!!!
• Register here:
www.edw2015.dataversity.net

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Questions?
+ =
It’s your turn!
Use the chat feature or Twitter (#dataed) to submit
your questions now.

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Upcoming Events
Business Value from MDM
February 10, 2015
@ 2:00 PM ET/11:00 AM PT
Data Architecture Requirements
March 10, 2015
@ 2:00 PM ET/11:00 AM PT

71. 10124 W. Broad Street, Suite C
Glen Allen, Virginia 23060
804.521.4056