Forget Big Data. It's All About Smart Data

Forget Big Data. It's All
About Smart Data
Alan McSweeney
http://ie.linkedin.com/in/alanmcsweeney

Smart Data, Not Big Data
• Smart Data is about not getting mesmerised by the hype
around Big Data but being intelligent and rational about
the possibilities, benefits and requirements
January 18, 2017 2

Purpose And Objective
• Proposes an initial framework and structure to allow the
nuggets of value contained in the deluge of largely
irrelevant and useless data to be isolated and extracted
• Enables your organisation to ask the questions to
understand where it should be in terms of its data state
and profile and what it should do to achieve the desired
skills level across the competency areas of the framework
January 18, 2017 3

Organisational Data Landscape
January 18, 2017 4

Organisational Data Landscape
• Every organisation operates within a data landscape with
multiple sources of data relating to its activities that is
acquired, transported, stored, processed, retained,
analysed and managed
• Interactions across the data landscape generate primary
data
• Multiple dimensions of data
− Raw, primary data
− Secondary, derived or generated data
− Static data about data
− Dynamic data about data
January 18, 2017 5

Organisational Data Landscape And Data
Interactions
• When you extend the range of possible interactions
business processes outside the organisation you generate
a lot more data
January 18, 2017 6

Organisational Data Landscape – Interaction
Dimensions
• External Parties Participating in Data Interaction/
Collaboration Landscape – who of the many parties in
your organisation landscape do you interact with digitally
• Numbers and Types of Interactions/ Collaborations and
Business Processes Included in Data Interaction
Landscape – which types of interactions and associated
business processes do you digitally implement
• Channels Included in Data Interaction Landscape – what
digital channels do you interact over
• Combination of dimensions leads to a large number of
potential interactions and associated data
January 18, 2017 7

From Lots Of
Different Sources
And Providers Both
Internal And
External
In Many
Different
Formats
With
Different
Content
Generated At
Different
RatesAt Different Times
With Different
Measurements
With
Variable
Accuracy
And
Calibrations
That
Changes
Constantly
Of
Different
Utility And
Value
Data Explosion
January 18, 2017 8

Primary And Secondary Data
• Primary data is generally a record of what has happened in
the past – an interaction, a transaction, an event, a usage,
a measurement
• Primary data retention is concerned with recording and
control
• Need to maintain a log of activity for audit purposes
• Secondary data is largely derived from or generated by
analysis of primary data
• Secondary data can generate insights through techniques
such as segmentation, propensity analysis
January 18, 2017 9

Date States - In Transit, At Rest, Being Processed
• Data exist in multiple states through the many stages of its
multiple journeys
January 18, 2017 10

• Primary source data and secondary processed/derived
data
− Standard data such as that from direct dealings with entities -
customers, partners, suppliers or measurement of events
− Data from external service providers
• Not all primary data has the same value
• Not all primary data can be easily obtained and processed
• Not always necessary to store data centrally
• So there is a need to be able to decide what data is useful,
how much automation is desirable or recommended in a
smart way
January 18, 2017 11

January 18, 2017 12
Why It Happened?
Why Is Likely To Happen
In The Future?
What Is Currently
Happening?
What Happened?
Reporting
Insight/
Forecast
Monitoring Analysis
From
Primary
Data …
… To
Secondary
Data …

• Primary data is not a stage to better data …
• … It is an essential foundation
January 18, 2017 13

Trailing/Lagging And Leading Indicators
Reporting
• Report on Gathered Information On What Happened
To Understand Pinch Points, Quantify Effectiveness,
Measure Resource Usage And Success
Monitoring
• Gather Information In Realtime To Understand
Activities, Respond And Make Reallocation Decisions
Analysis
• Understand Reasons For Outcomes and Modify
Operation To Embed Improvements
Insight and Forecast
• Quantify Propensities, Forecast Likely Outcomes,
Identify Leading Indicators, Create Actionable
Intelligence
January 18, 2017 14
Trailing
Indicators
Leading
Indicators

Every Organisation Needs An Effective Enterprise
Data Strategy
January 18, 2017 15
Data Operations Management
Data Quality Management
Data Development
Metadata Management
Document and Content Management
Reference and Master Data Management
Data Security Management
Data Warehousing and Business Intelligence
Management
Data Governance
Data Architecture
Management
Reporting
Insight/
Forecast
Monitoring Analysis
Solid
Data
Management
Foundation
and
Framework
} You Cannot
Have This ...
... Without
This

Primary And Secondary Data Framework Iceberg
January 18, 2017 16
To Do This ...
... You Need To
Do This ...
... Which
Requires This ...
... Which In Turn
Needs This ...
... And So On ...
...
...
...
Be Able To Take
Action Based on
Reliable Information
Measure What is
Important
Know What Is
Important In Order
To Measure It
Define
Measurements
Define Consistent
Units of
Measurements
Define
Measurement
Processes
Define Operational
Framework
Define Collection
Process
Define Data Storage
Model
Define
Transformation And
Standardisation
Install Data
Collection Facilities
Collect Data
Monitor Data
Collection
Manage Data
Collection
Validate And Store
Data
Report And Analyse
Stored Data
Define Reports
Run And Distribute
Reports
Define Analyses
Run And Distribute
Analyses
Provide Realtime
Access To Collected
Data
Define Data Tools
And Infrastructure

Smart Data Means Being …
January 18, 2017 17

Smart Data Means Being …
• Smart in what data to collect, validate and transform
• Smart in how data is stored, managed, operated and used
• Smart in taking actions based on results of data analysis
including organisation structures, roles, devolution and
delegation of decision-making, processes and automation
• Smart in being realistic, pragmatic and even sceptical about
what can be achieved and knowing what value can be derived
and how to maximise value obtained
• Smart in defining an achievable, benefits-lead strategy
integrated with the needs business and in its implementation
• Smart in selecting the channels and interactions to include –
smart data use cases
January 18, 2017 18

Smart Means …
• More focussed investment in achieving better business
and organisation results
• Greater confidence by the business and organisation in
justifying and approving investment and resource
allocation
• Quicker delivery of results
• What are your Smart Data use cases?
January 18, 2017 19

Smart Data Use Cases In The Organisational Data
Landscape
January 18, 2017 20
Use
Case
Use
Case
Use
Case
Use
Case
Use
Case
Use
Case
Use
Case

Business Model Canvass
• Consider using the Business Model Canvas to analyse each use case
• Divides business into nine elements in four groups
− Infrastructure
• Key Partners - the key partners and suppliers needed to achieve the business model
• Key Activities - the most important activities the business must perform to ensure the
business model works
• Key Resources - the most important assets to make the business model work
− Offering
• Value Propositions - the value, products and services provided to the customer
− Customers
• Customer Relationships - the customer relationships that need to be created
• Channels - the channels through which the business reaches its customers
• Customer Segments - the types of customers being targetted by the business model
− Finances
• Cost Structure - the most important costs incurred by the business model
• Revenue Streams - the sources through which the business model gets revenue from
customers
January 18, 2017 21

Business Model Canvass
January 18, 2017 22
Key Partners
• Who are our key partners?
• Who are our key suppliers?
• What Key Resources do we acquire
from partners?
• What Key Activities do partners
perform?
MOTIVATIONS FOR
PARTNERSHIPS
• Optimisation and economy
• Reduction of risk and uncertainty
• Acquisition of resources and skills
Key Activities
• What key activities do our value
propositions require
• What are our distribution channels?
• What are our customer relationships?
• What are our revenue streams?
CATEGORIES
• Production
• Problem Solving
• Platform/Network
Value Propositions
• What value do we deliver to our
customers?
• Which of our customers’ problems are
we helping to solve?
• What bundles of products and
services do we offer to each customer
segment?
CHARACTERISTICS
• Novelty
• Performance
• Customisation
• “Getting the Job Done”
• Design
• Brand
• Status
• Cost Reduction
• Risk Reduction
• Accessibility
• Convenience/Usability
Customer Relationships
• What type of relationship does each of our
customer segments expect us to establish
and maintain with them?
• What ones have we already established?
• How are they integrated into our business
model?
• How much do they cost?
EXAMPLES
• Personal assistance
• Dedicated personal assistance
• Self-service
• Automated services
• Communities
• Co-creation
Customer
Segments
• For whom are we creating
value?
• Wo are our most important
customers?
• Mass market
• Niche market
• Segmented
• Diversified
• Multi-sided platform
Key Resources
What key resources are required by our
Value propositions Distribution channels
Customer relationships
Revenue streams
TYPES OF RESOURCES
Physical
Intellectual
Human
Financial
Channels
• Through which channels do our customer
segments want to be reached?
• How are we reaching them now?
• How are our channels integrated?
• Which ones are most cost-efficient?
• How are we integrating them with customer
processes?
CHANNEL PHASES
• Awareness - How do we raise awareness
about our products and services
• Evaluation – How do we help customers
evaluate our value proposition?
• Purchase – How do we allow customers
purchase specific products and services?
• Delivery – How do we deliver a value
proposition to customers?
• After Sales – How do we provide post-
purchase customer support?
Cost Structure
• What are the most important costs inherent in the business model?
• Which key resources are the most expensive?
• Which key activities are the most expensive?
IS THE BUSINESS MORE:
• Cost Driven – leanest cost structure, low price value proposition, maximum automation, extensive
outsourcing
• Value Driven – focussed on value creation, premium value proposition
SAMPLE CHARACTERISTICS
• Fixed costs
• Variable costs
• Economies of loading
• Economies of scale
Revenue Streams
• What value are customers really willing to pay for?
• What are they currently paying for?
• How are they currently paying?
• How would they prefer to pay?
How much does each revenue stream contribute to overall revenue?
TYPES FIXED PRICING DYNAMIC PRICING
• Asset sale • List price • Negotiation/bargaining
• Usage fee • Product feature dependent • Yield management
• Subscription fees • Customer segment dependent • Real-time market
• Lending/renting/leasing • Volume dependent
• Licensing
• Brokerage fees
• Advertising

Business Model Canvass And Use Case Identification
• Locate each use case within the Business Model Canvass to
understand its context and potential contribution to the
business
• This approach provides an understanding of the benefits of
implementing a use case and assists with their definition
January 18, 2017 23

Smart Means …
• Having a Chief Smart Data Officer and not just a Chief Data
Officer
January 18, 2017 24

Smart Data Competency Areas
• Areas of smart data competencies that comprise a
complete set of required skills and abilities to design,
implement and operate an appropriate smart data
programme
• Complete and generalised set of competencies that will be
more or less relevant to different organisation types
• Enables your organisation develop an focussed data
strategy
January 18, 2017 25

Smart Data
Strategy, Management and Governance
Organisation and Structure
Data Infrastructure and Data Landscape
Operations
Data And Resource Asset Management
Smart Data Technology Planning and
Implementation
External Party Involvement and
Interaction
Smart Data Value Addition And Derivation
Smart Data Standards Contribution and
Development
January 18, 2017 26

Linkages Between Smart Data Competencies
• Competencies do not
exist in isolation
• Each competency area
is linked to the others
• Improving skills in
competency area will
increase the
organisation’s skill and
ability in others
January 18, 2017 27
Data
Infrastructure
And Data
Landscape
Operations
Data And
Resource
Asset
Management
Smart Data
Standards
Contribution And
Development
External Party
Involvement
And
Interaction
External Party
Involvement
And
Interaction
Smart Data
Technology
Planning And
Implementation
Organisation
And
Structure
Strategy,
Management
And
Governance

Smart Data Competency Areas And Skill Levels
January 18, 2017 28
Strategy,
Management And
Governance
Organisation And
Structure
Data Infrastructure
And Data
Landscape
Operations
Data And Resource
Asset Management
Smart Data
Technology
Planning and
Implementation
External Party
Involvement And
Interaction
Smart Data Value
Addition And
Derivation
Smart Data
Standards
Contribution And
Development
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5

Competency Areas Coverage
Strategy, Management and
Governance
1. Smart data strategy development and delivery
2. Governance procedures and processes
3. Establishment of management structures
4. Leadership
5. Communications management
6. Relationship management
Organisation and Structure 1. Design and implement the required organisational structures including cross-
functional structures
2. Create delivery structures
3. Decision making
4. Design training
5. Knowledge acquisition, management and transfer
Data Infrastructure and Data
Landscape Operations
1. Reliable, cost-effective, secure and efficient data operations
2. Automation of data operations
3. Flexibility in data operations
4. Knowledge of the status and performance of data operations
Data And Resource Asset
Management
1. Management of data assets and personnel resources
2. Capacity planning
3. Fault and error detection and correction
January 18, 2017 29

Competency Areas Coverage
Smart Data Technology Planning 1. Effective strategic planning for smart data technology
2. Evaluation, selection, integration, and testing of new data technologies
3. Knowledge and application of relevant standards
4. Using the data platform to innovate and contribute to the success of the
organisation
Interaction
1. Definition of strategy to involve external parties from data collection to providing
external parties with access to appropriate data and to interact with the
organisation
Smart Data Value Addition And
Derivation
1. Creating the organisational capabilities to enable value to be derived from data to
achieve business goals
2. Enabling effective decision making
3. Enabling dynamic and real time analyses
Smart Data Standards Contribution
and Development
1. Contribution to the wider smart data community and the development of smart
data standards
2. Development of reference implementations
3. Development of standards
January 18, 2017 30

Smart Data Competency Areas - Skill Levels
January 18, 2017 31
Foundational Skill Level
Establishment Of Base Structures and Processes
For Deciding On And Progressing Initiatives
Extension And Linkage Of Completed Base Structures And
Delivery Of Results and Performance Improvements
Embedding, Operationalising And Measuring Usage And Results
Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community
5
4
3
2
1

Skill Levels
• Represent a progression of effort and investment in
competency areas
January 18, 2017 32

Smart Data Competency Areas Skill Levels
January 18, 2017 33
Cost And Time
Of Achieving
Skill Levels
Extent And Cost
Of
Implementation
And Operation
Likely Return
And Results That
Can Be Achieved
And Benefits
Obtained

Smart Data Competency Areas Skill Levels
• Need to balance cost and time of achieving skill levels in
competency areas, extent and cost of implementation and
operation with likely return and results that can be
achieved from using smart data
January 18, 2017 34

Skill Level 1 - Foundational
• Awareness of the need for a smart data strategy exists and
strategy being defined
• Potential performance improvements identified
• Programme of knowledge acquisition started
• Investment requirements recognised and investment plans
being prepared
• Metrics to assess performance improvements defined
• Smart data implementation initiatives being defined
• Renovation of data infrastructure started
• Management commitment to analysis, investigation and
planning in place
January 18, 2017 35

Skill Level 2 - Establishment Of Base Structures and
Processes For Deciding On And Progressing Initiatives
• Initial high-level strategy has been agreed
• High-level integrated architecture that includes performance
and security has been defined
• Initial value measurement framework has been defined
• Data source inventory has been created
• Organisation data model has been created
• Investment plans, programme and schedule in place
• Management commitment to initial implementations in place
• Initial implementations have started and lessons are being
learned
January 18, 2017 36

Skill Level 3 - Extension And Linkage Of Completed Base
Structures And Delivery Of Results and Performance
Improvements
• Initial implementations are being combined in the context of
the integrated architecture
• Wider and deeper data implementations are in progress
• Architecture has been refined an extended
• Results are being delivered and value is being measurably
derived from data implementations
• A value measurement framework is in place and operational
• Processes to exploit data has been defined
• The organisation structures needed to derive value from data
have been defined, agreed and are being implemented
January 18, 2017 37

Skill Level 4 - Embedding, Operationalising And
Measuring Usage And Results
• An organisation-wide data architecture has been
implemented and is operational
• The organisation-wide data implementation is being used
effectively across all business functions
• Data-based actions and decision-making is operation
• Data-based decision-making is automated as much as
possible
• There is a data correction feedback process
• Data use is extended outside the organisation to
appropriate external interacting partners
January 18, 2017 38

Skill Level 5 - Innovate, Lead, Invent, Collaborate
With Other Organisations And Wider Community
• The organisation is contributing to the development of
data standards
• The organisation is sharing its experiences with other
organisations
• The organisation is developing and actively participating in
partnerships to develop and implementation data
standards, reference architectures and standard
implementations
January 18, 2017 39

Choosing The Most Suitable Skill Level
January 18, 2017 40
Foundational
Skill Level
Establishment
Of Base
Structures and
Processes For
Deciding On And
Progressing
Initiatives
Extension And
Linkage Of
Completed Base
Structures And
Delivery Of
Results and
Performance
Improvements
Embedding,
Operationalising
And Measuring
Usage And
Results
Innovate, Lead,
Invent,
Collaborate
With Other
Organisations
And Wider
Community
General
Characteristics
Of Skill Level
Specific
Competency
Area Actions
General
Characteristics
Of Skill Level
Specific
Competency
Area Actions
General
Characteristics
Of Skill Level
Specific
Competency
Area Actions
General
Characteristics
Of Skill Level
Specific
Competency
Area Actions
General
Characteristics
Of Skill Level
Specific
Competency
Area Actions
1 2 3 4 5

January 18, 2017 41
General
Characteristics
Of Skill Level
What the skill level
for the specific
competency area
looks like
Specific
Competency
Area Actions
What actions
should be taken
to be at the skill
level

• Decision based on:
− Importance of competency area to your organisation
− Current skill level within the competency area
− Optimum skill level to deliver greatest benefit
− Benefit in achieving improvement
• Use current levels of skills and importance of competency
areas to identify those areas at which getting better will
yield the greatest return
• Targeted investment of resources
• Get good at what matters to your organisation
• Get the biggest return for your investment
January 18, 2017 42

• Three-way balancing act
January 18, 2017 43
Importance
Benefits
Current
And Target
Skill Level

• Profile will be different for each organisation
• Not all areas have the same importance for everyone
• You cannot get better at every competency at the same
time
January 18, 2017 44

Take A Planned And Systematic Approach To
Increasing Skills In Competencies
January 18, 2017 45
Assess Current Skill Levels Across Competencies
What Is The Desired Or Necessary Activity Skill Level
Agree Core Competency Levels
Set Prioritised Improvement Competency Areas
Define Improvement Programme
Deliver Improvement Programme

Foundational
Skill Level
Establishment Of
Base Structures and
Processes For
Deciding On And
Progressing
Initiatives
Extension And
Linkage Of
Completed Base
Structures And
Delivery Of Results
and Performance
Improvements
Embedding,
Operationalising
And Measuring
Usage And Results
Innovate, Lead,
Invent,
Collaborate
With Other
Organisations
And Wider
Community
Strategy, Management and
Governance
Organisation and Structure
Data Infrastructure and Data
Landscape Operations
Data And Resource Asset
Management
Smart Data Technology
Planning
Interaction
Derivation
Smart Data Standards
Contribution and Development
January 18, 2017 46

Competency Areas And Their Skill Levels
• Each competency area can be at a different level
January 18, 2017 47

Strategy, Management and Governance
Capability – Key Skills
• Concerned with the having and being able to effectively use
underlying strategic capabilities
• Concerned with the ability of your organisation to develop a
coherent smart data concept and design an effective strategy and
path to implementation
• Ability to design management and organisation structures
• Ability to design governance structures and processes
• Ability to design communication and organisation change processes
• Ability to manage the delivery of the strategy within the
organisations, articulate the vision, manage objections
• Ability to identify and exploit business opportunities
• Ability to recognise changes to existing products and services and
new products and services that can be enabled
January 18, 2017 48

Strategy, Management and Governance -
Characteristics
• Develop an initial smart-data
high-level description and
articulate the substance and
benefits of this vision to the
objectives, management and
business functions of your
organisation
• Allocate an initial budget for
smart data related strategy,
analysis and planning activities
• Determine how similar
organisations have initiated or
implemented smart data
initiatives and programmes
Improvement Actions And Events
• An initial smart-data high-level
vision has been defined that
targets operational improvement
• Your organisation has allocated
resources and budgets to
prototypes and test
implementations
• There is management recognition
of the importance of and support
for these initiatives within your
organisation
January 18, 2017 49

Establishment Of Base Structures and Processes For
Deciding On And Progressing Initiatives
Characteristics
• The initial smart-data high-level vision
has been extended to include business
units and functions
• A leader or sponsor for the smart data
initiative has been agreed
• Priorities have been assessed to allow
the implementation be structured
accordingly
• Designated contacts in business
functions have been identified
• Your organisation has started to
centralise smart data knowledge and
experience
standardise smart data related
processes
• The initial smart data high-level vision and strategy has been
created and accepted by the management of your
organisation
• The initial smart data high-level vision and strategy integrates
an individual business unit and function initiatives and
experiences
• The smart data strategy includes all the core elements
• The smart data strategy has security, privacy integration and
interoperability included from the start
• The initial smart data high-level vision and strategy has been
understood and accepted by the organisation
• Your organisation has agreed an investment programme that
is linked to the smart data high-level vision and strategy
• Your organisation has allocated budgets to implement specific
initiatives within the context of the smart data high-level
vision and strategy
• Your organisation has started to fund agreed smart data
prototypes to determine their viability
• The smart data prototypes are aligned with the smart data
high-level vision and strategy
• The smart data prototypes has been selected to achieve
defined goals in the context of the overall the smart data high-
level vision and strategy
January 18, 2017 50

Strategy, Management and Governance - Extension
And Linkage Of Completed Base Structures And Delivery
Of Results and Performance Improvements
Characteristics
• The individual business unit and
function smart data vision and
strategy components are joined
up to create an organisation wide
design
• Cross-functional smart data
processes have been defined that
link individual business unit and
function processes
achieve benefits from the
implementation and operation of
smart data initiatives
• The funding for smart data initiatives has been defined and accepted and the
expected benefits have been quantified
• Your organisation’s overall business strategy includes the achievement of the
specific smart data strategy
• Your organisation has defined and agreed a governance structure that includes
decisions or new or changes to existing organisation structures, roles, processes
and selected systems and applications
• Your organisation accepts that the defined governance structure will be used to
enable management to guide and lead the smart data implementation
programme
• The operation of the governance structure and associated processes are
frequently assessed to determine the effectiveness and appropriate changes are
reviewed and agreed
• Your organisation has appointed individuals, who have been given the required
permission, in business units or functions with responsibility for progressing smart
data initiatives in the context of the overall smart data strategy
• Business unit or function management have approved the overall smart data
strategy and their role in its delivery
• The involvement of appropriate external parties (data providers, data users) in
the delivery of the overall smart data strategy has been agreed and these parties
have agreed to be involved
• Data infrastructure and data operations have been updated to reflect the needs
of an integrated, automated full-functional smart data solution
• The data infrastructure is being used to deliver savings and innovations
• The data infrastructure is being used interact with external parties (data
providers, data users)
• Your organisation management is willing to invest further in data initiatives to
develop and use data assets to assist in the design and development of new
products and services and innovations
• Your organisation is actively looking for ways to use its smart data infrastructure
January 18, 2017 51

Embedding, Operationalising And Measuring
Usage And Results
Characteristics
• Data infrastructure and data operations
have been updated to reflect the needs
of an integrated, automated full-
functional smart data solution
• The data infrastructure is being used to
deliver savings and innovations
• The data infrastructure is being used
interact with external parties (data
providers, data users)
• Your organisation management is willing
to invest further in data initiatives to
develop and use data assets to assist in
the design and development of new
products and services and innovations
• Your organisation is actively looking for
ways to use its smart data infrastructure
• The smart data strategy and data infrastructure is fully
integrated into your organisation’s business strategy
• Your organisation continually invests appropriately in
smart data infrastructure and initiatives
• Your organisation continually evaluates new smart
data technologies and engages in pilot
implementations regularly
• Your organisation has a fully developed and
operational framework for smart data benefits
realisation
• Your organisation has a fully developed and
operational smart data governance framework
• Smart data is a central capability of all parts of your
organisation
• Your organisation uses smart data at the earliest stage
of any initiative or engagement
• Your organisation’s smart data strategy is constantly
updated to reflect new opportunities and capabilities
January 18, 2017 52

Innovate, Lead, Invent, Collaborate With Other
Organisations And Wider Community
Characteristics
• Your organisation pervasively and
extensively uses smart data to
guide and direct the operations of
the business and the
development of new products,
services and partnerships
• Your organisation contributes to
the development of smart data
research and standards
• Your organisation uses its smart data capabilities to
actively and continually identify new opportunities for
innovation, change, greater operational efficiencies
and new products, services and partnerships
• Your organisation’s business strategy is both based on
past insights derived from smart data and is
structured to incorporate smart data into future
actions
• Management have committed to continue to fund
existing smart data infrastructure and to grow and
expand it
• Smart data investment and funding continues to be
justified on generating a return for the business
through cost savings or new revenue sources
• Your organisation is able to identify new business
opportunities and partnerships based on the use of
and the insights gained from smart data
• Your organisation is able to optimise its business
model based on the use of and the insights gained
from smart data
January 18, 2017 53

Organisation and Structure Capability –
Key Skills
• Concerned with the defining and implementing the structures and abilities that your
organisation needs to deliver and operate a smart data programme and smart data
initiatives and to derive the greatest benefits from them
• Concerned with moving your organisation from siloed and vertical structures that are not
integrated to horizontal, integrated structures and processes
• Concerned with integrating smart data into your organisation’s decision making and moving
to an evidence-based approach
• Concerned with the ability of your organisation to recognise the need for change and then
define and realise those changes needed
• Concerned with communications structures and their operation to articulate the need for,
the benefits of and the progress of a smart data programme and smart data initiatives
• Concerned with defining and delivering an appropriate training programme at all levels to
define and then provide and develop the skills required
• Concerned with managing smart data knowledge
• Concerned with defining and implementing cross-functional structures and processes to
allow organisation wide design, development, implementation, use of and success of a
smart data programme and smart data initiatives
• Concerned with incentivising, promoting and recognising work and achievements on smart
data programme and smart data initiatives
January 18, 2017 54

Organisation and Structure -
Characteristics
• Your organisation realises and
accepts that there is a need to
develop a systematic and
organised approach to smart data
and to modernise existing data
capabilities
• The organisation takes the first
steps to start building the
required skills, resources,
experience and capabilities,
supported by commitment and
resources
• You have recognised and agreed the
need to create a smart data
competency and associated function
• Your management and leadership
team have given a commitment to
implement a smart data
implementation, management and
operations function and have
allocated an appropriate budget,
resources and timescale
• Your organisation has started on a
programme of activities to notify its
employees of the smart data
initiative and to extend the
knowledge and understanding of
employees in both smart data in
general and the planned actions in
particular
January 18, 2017 55

Organisation and Structure - Establishment Of Base
Structures and Processes For Deciding On And
Progressing Initiatives
Characteristics
• Work has started with those
business areas involved in the agreed
scope of the smart data programme
• The organisation changes required to
implement and operate a smart data
programme have been understood,
agreed and the changes are being
implemented
• The smart data programme team has
started engaging with the
operational business functions that
will be involved in the
implementation, operation and use
of smart data infrastructures
• The long-term view and idea of smart
data is starting to change the way data is
collected, managed and processed
• Smart data operational processes have
been defined
• Smart data applications and
implementations involve people from
the affected business functions.
• Training and instruction on smart data
implementation, operation and use has
been complied and is readily accessible
to be taken by personnel
• Processes for recognising the
performance and delivery of personnel
directly involved in smart data
implementation, operation and use
initiatives are defined and are active
January 18, 2017 56

Organisation and Structure - Extension And Linkage Of
Completed Base Structures And Delivery Of Results and
Performance Improvements
Characteristics
• Smart data implementation,
operation and use is beginning to
be embedded in standard
activities of operational business
functions. The activities of these
business functions has changes to
take account of this
• Operational business functions are changing to take
account of the long-term view of smart data
implementation, management and operations
• Your organisation has developed a framework for
measuring smart data implementation, management
and operations. The measurement framework is
operational
• Your organisation recognises achievements in smart
data implementation, management and operations in
the areas of successful initiatives by teams and
individuals, implementation of appropriate team
structures and business function performance
improvement due to use of smart data
• The management of your organisation that is assigned
the task of achieving smart data implementation,
management and operations articulates and performs
the activity coherently
• Your organisation is looking at smart data
implementation, management and operations cross-
functional views, processes, structures and linkages
that sit on top of operational processes
• Your organisation has developed or acquired and
given training that relates to using smart data
effectively
January 18, 2017 57

Organisation and Structure - Embedding,
Operationalising And Measuring Usage And
Results
Characteristics
• Your organisation has changed its
operational structures to
implement, operate and use
smart data and accomplish the
envisioned smart data strategy
• The collection and management
of smart data is embedded in the
your organisation
• The operational use of smart data
is embedded in the your
organisation
• The structures and processes of your
organisation are able to use smart data to
understand the operation of the organisation
and the internal and external interactions
• Your organisation has a complete view of the
operational smart data landscape. The business
functions of your organisation work together to
use smart data to improve operational
efficiency and effectiveness
• Your organisation is able to make decisions and
take actions based on the insights derived from
smart data.
• Your organisation has structured itself in terms
of roles and processes to make decisions and
take actions based on smart data
• Smart data insights are automated to reduce
the manual effort and delays associated with
analysis
• Smart data-based decision-making is immediate
and devolved to appropriate levels to allow for
faster action within your organisation
January 18, 2017 58

Organisation and Structure - Innovate, Lead,
Invent, Collaborate With Other Organisations
And Wider Community
Characteristics
• Your organisation is devoting
resources to data-related
standards and concepts research
and development
• You are developing data
innovations
• You are working with organisations to
develop data-related standards
• You are sharing data-related approaches
and insights with the wider community
• Your organisation easily and quickly
accepts new data initiatives and
collaborations
• Your organisation willingly pursues ideas
for new data-related business
opportunities
• Your organisation has adopted a
structure that fosters, recognises and
compensates data-related innovation
among personnel
• Data-related innovation in your
organisation is pervasive and reaches all
levels
January 18, 2017 59

Operations Capability – Key Skills
• Ability to implement and operate secure, reliable, available,
resilient, efficient, performing smart data infrastructure across
the entire landscape from data intake, data processing, data
analysis, reporting and presentation, data storage and data
administration, management and governance
• Ability to implement and operate of service management
processes to manage the smart data infrastructure and its
operation and use
• Ability to manage flexibility and scalability of the smart data
infrastructure
• Ability to optimise and automate the operation of the smart
data infrastructure
• Ability to manage cost of the acquisition and operation of the
smart data infrastructure
January 18, 2017 60

Operations - Foundational Skill Level
Characteristics
• Your organisation is looking at the
operations management of a
smart data infrastructure as part
of an overall smart data strategy
• Your organisation has created and approved some business
cases for investment in initial smart data infrastructure as part
of an overall smart data strategy and a larger and more
integrated smart data infrastructure
• Your organisation may not have a centralised smart data
business case approval process
• Your organisation is evaluating smart data infrastructure
equipment and options across elements of the technology
spectrum
• Your organisation is conducting some research and
development into smart data technologies
• Your organisation has developed and is using a structured
approach to performing smart data technology evaluations
• Your organisation has implemented some initial smart data-
related technologies and systems in order to trial and evaluate
options
• Your organisation is evaluating optimisation and automation
options in order to embed these characteristics into any smart
data technology
• Your organisation considers integration and interoperation as
part of any smart data technology evaluations
• Your organisation embeds security into any smart data
technology evaluations
January 18, 2017 61

Data Infrastructure and Data Landscape Operations -
Characteristics
implement integrated smart data
technologies, connecting previous
implementations
introduce automation into smart
data infrastructure
• Your organisation has introduced
service management processes into
smart data infrastructure
• Your organisation introduces
monitoring of the operation and use
of the smart data infrastructure
• Your organisation uses the
monitoring data collected the
improve the performance of and in
the planning of the smart data
infrastructure
January 18, 2017 62

Extension And Linkage Of Completed Base Structures
And Delivery Of Results and Performance Improvements
Characteristics
• Your organisation has extended
monitoring and control of the
operation and use of the smart
data infrastructure within the
context of greater integration and
connection of the previous
individual implementations
• Your organisation is obtaining and
using information on the
performance and use of the smart
data infrastructure to optimise its
performance and use
• The performance and usage data is
being used to improve automated
operations, availability and usability
• The performance data is being used
to integrate elements of the existing
smart data infrastructure into the
long-term target infrastructure
• Your organisation is making planning
and investment decisions based on
smart data infrastructure operations
data collected and analysed
January 18, 2017 63

Operations - Embedding, Operationalising And
Measuring Usage And Results
Characteristics
• Smart data infrastructure is being
integrated and optimised across
the entire landscape from data
intake, data processing, data
analysis, reporting and
presentation, data storage and
data administration, management
and governance
• Smart data infrastructure is being integrated
and optimised across the entire landscape from
data intake, data processing, data analysis,
reporting and presentation, data storage and
data administration, management and
governance
• Real time data is available and being used on
the operation and use of the smart data
infrastructure
• Smart data infrastructure planning and service
management is being performed proactively
using real time data
• The information being collected on the smart
data infrastructure is readily available to all the
relevant people in your organisation
• Actions are automated based on the
information being collected on the operation
and use of the smart data infrastructure
January 18, 2017 64

Characteristics
• Your organisation has complete
visibility of the operation and use of
the smart data infrastructure
• Your organisation has real-time
control of the smart data
infrastructure
• The smart data infrastructure is
completely reliable, available and
secure across the entire landscape
from data intake, data processing,
data analysis, reporting and
presentation, data storage and data
administration, management and
governance
• Incident determination and resolution
within the smart data infrastructure is as
automated as possible
• The smart data infrastructure is
designed to react to changes in demand
and usage across the entire landscape
from data intake, data processing, data
analysis, reporting and presentation,
data storage and data administration,
management and governance
• The health and status of the smart data
infrastructure is fully visible across the
entire landscape
• Real time provisioning decisions are
made in response to smart data
infrastructure status information
January 18, 2017 65

Data And Resource Asset Management
• Ability to optimise operations, data assets – soft data infrastructure such as data itself and data
sources, data about data and data about data usage, performance and operations, especially
external and third-party data sources - rather than the physical data infrastructure covered in the
Data Infrastructure and Data Landscape competency and resource and people allocation and use
across the entire data landscape from data intake, data processing, data analysis, reporting and
presentation, data storage and data administration, management and governance
• Ability to optimise organisation structures to improve data operations
• Ability to implement and operate capacity management to forecast resource requirements
accurately and quickly
• Ability to understand and react effectively and quickly to resource forecasts and requirements
• Ability to implement and operate the organisation structure and processes
• Ability to drive pro-active and reactive maintenance and infrastructure upgrades and changes
• Ability to install and configure new and reconfigure existing data
• Ability to allocate resources effectively and efficiently to ensure the security, resilience,
availability and reliability of organisations structures and resources across the data landscape
• Ability to move from reactive to proactive resource management
January 18, 2017 66

Data And Resource Asset Management -
Characteristics
• Your organisation is investigating
options and alternatives to
improve data assets and resource
and people management across
the data landscape
• Your organisation is developing a
comprehensive strategy for
resource and people
management
• Resource improvement initiatives
and targets has been defined and
incorporated into business cases
• Options for improving resource
management are being analysed
and plans developed
• Tools and facilities to assist with
effective and efficient resource
management across the data
landscape are being assessed
January 18, 2017 67

Data And Resource Asset Management - Establishment
Of Base Structures and Processes For Deciding On And
Progressing Initiatives
Characteristics
• Your organisation is investing in
implementing a data assets,
people and resource
management
• Your organisation is enhancing
and expanding its data assets,
people and resource
management strategy
• Your organisation is
implementing changes to data
assets, people and resource
management to achieve the long-
term strategy
• Your organisation is developing
an approach to data asset
management across the data
landscape
implementing views of data
assets to enable business
functions see the status of data
assets
an approach to the management
and optimisation of people
resources involved across the
data landscape
January 18, 2017 68

Data And Resource Asset Management - Extension And
Linkage Of Completed Base Structures And Delivery Of
Results and Performance Improvements
Characteristics
• Your organisation is starting to
join data assets, data
Infrastructure and people
resources to create an integrated
view of all aspects of data to
enable your organisation start to
derive tangible results and value
• Your organisation is using this
developing integrated view to
optimise operations to achieve
savings and efficiencies
• Your organisation has started to have an integrated
view of data assets, operations and resources for
some sets of assets, infrastructure and resources
• Your organisations is beginning to optimise its
interventions in and scheduled work on data assets
based on information on status, event and alert
information rather than unoptimised scheduled
interventions
• The optimised interventions are integrated with
resource management based on factors such as
required skills
• Your organisation is starting to identify and minimise
unnecessary scheduled work and use of resources
• Your organisation has linked processes and tools to
automate the notification, scheduling and
management of resource allocation with data status
information
• Your organisation has incorporated or is considering
the incorporation of ability, knowledge and
experience into any automation of management of
resource allocation
• Your organisation has a database of data assets that is
used to track them and to store associated metadata
and usage, operations and performance data
January 18, 2017 69

Usage And Results
Characteristics
• Your organisation has a complete
integrated view of data assets,
operations and resources for
some sets of assets,
infrastructure and resources
• Your organisation’s resource
management procedures and
optimised based on factors such
as skills required for interventions
and actions
• Your organisations manages the
integration of data assets across the
entire data landscape
• Your organisation’s asset contains
historical and lifecycle information as
well as current data about data
• Your organisation has implemented
and operates processes to manage
data asset lifecycles
and operates processes to
proactively address data asset issues
based on status and need
January 18, 2017 70

Characteristics
• Your organisation has a complete view of data
assets and their status that is dynamically
updated in real-time
• Your organisation has a complete view of data
resources, their activities and their status that is
dynamically updated in real-time
• Your organisation have implemented and
operates procedures to operate, administer and
manage data assets and resource allocation
using this complete and real-time view
• Your organisation has implemented and
operates procedures for identifying appropriate
external data suppliers with whom to share
data assets and which data assets to share
• Your organisation has implemented appropriate
data asset sharing with relevant external data
suppliers``
• Your organisation optimally uses
and manages data assets across
the entire data landscape and
across the data asset lifecycle
• Your organisation shares data
assets with external data
suppliers
January 18, 2017 71

Implementation Capability – Key Skills
• Ability to plan for and develop effective data technology strategy across the technology lifecycle, data landscape and data
asset lifecycle
• Ability to link the data strategy to the business strategy and to influence the business strategy by the capabilities and potential
defined in the data strategy
• Ability to implement and deliver on the data technology strategy
• Ability to address all aspects of data technology strategy that encompass identification, assessment, planning, evaluation,
acquisition, integration, testing, implementation, operation and service management and lifecycle management
• Ability to address all components of data technology strategy that include security, flexibility, responsiveness, availability,
reliability, usability, operability, maintainability, performance and affordability
• Ability to ensure that any strategy incorporates the identification, implementation and operation of the required
organisational change
• Ability to ensure that any strategy incorporates the required data communications and integration infrastructure
• Ability to ensure that any strategy incorporates the identification, implementation and operation of the required resources
and their management
• Ability to ensure that any strategy incorporates the identification, implementation and operation of the required processes
and controls
• Ability to ensure that any strategy includes and adheres to any applicable standards
• Ability to ensure that any strategy includes the definition of the required organisation changes to ensure its effective
implementation and operation
• Ability to ensure that any strategy includes the definition of the required training and education and to define a programme to
achieve this
• Ability to ensure that any strategy includes security awareness
• Ability to ensure that any strategy incorporates the achievement of defined business benefits and returns
• Ability to ensure that any strategy incorporates the external data suppliers
• Ability to ensure that any strategy incorporates the delivery of data-based value to external interacting parties
• Ability to update the data strategy as appropriate in response to feedback, experience and lessons learned, internal and
external business changes and new technology possibilities
January 18, 2017 72

Implementation - Foundational Skill Level
Characteristics
• Your organisation is exploring the
development of a data strategy
along all its dimensions
• Your organisation is linking the data strategy to
the overall enterprise IT architecture
• Your organisation is developing an
understanding of how the data strategy can
deliver on the operation and quality attributes
of security, flexibility, responsiveness,
availability, reliability, usability, operability,
maintainability, performance and affordability
• Your organisation is developing an approach to
a phased implementation of the data strategy
• Your organisation is putting in place processes
to achieve the organisational changes needed
to implement the strategy
• The data strategy attempts to quantify the
benefits and improvements that can be derived
from the implementation and operation of the
data strategy
• Your organisation have developed an approach
to evaluate technologies appropriate to the
implementation of the data strategy
January 18, 2017 73

Smart Data Technology Planning and Implementation -
Characteristics
• Your organisation has defined a
data strategy and an associated
investment programme
implement data technology in
specific business functions in the
context of the overall data
strategy and the associated
investment programme
• The specific implementations that have been selected are
being performed within the context of the data strategy
and an associated investment
• Your organisation has developed an investment plan from
the strategy’s investment programme
• Your organisation’s enterprise IT architecture has been
update to take account of the data strategy
• Your organisation has developed sets of standards to
achieve the implementation of the data strategy
• The standards take account of wider industry standards
and developments
• The evaluation process for data technologies is applied
consistently across all business units
• Your organisation has started to implement the required
communications and integration infrastructure
• Your organisation has started data technology pilots and
proofs of concept to validate the data strategy
• Your organisation is committed to embedding security,
resilience and availability into the data strategy and data
technology pilots and proofs of concept
• Your organisation embeds security awareness education
and training into any data technology pilots and proofs of
concept
January 18, 2017 74

Characteristics
implementing the data
technology strategy and
integrating previous pilots and
proofs of concept into the overall
target framework
• Your organisation is applying
common standards and
approaches to these
implementations
• Your organisation seeks to use
commonly available tools and
systems in these implementations
• Technologies, systems and processes related to
the smart data technology are aligned with and
comply with your organisation’s enterprise
architecture
• Your organisation has a technology roadmap for
the implementation of smart data technologies
• Specific implementations occur with the context of
this roadmap
• The smart data technology implementations are
delivering improvements in performance both in
business functions and across the entire business
• Your organisation is evaluating opportunities for
organisation-wide technology implementations
• Your organisation implements technology
solutions to collect data from internal and external
data sources
• Your organisation is developing an architecture for
organisation-wide data collection from internal
and external data sources including identification
of data sources and definition of the required data
communications infrastructure
January 18, 2017 75

Embedding, Operationalising And Measuring Usage And
Results
Characteristics
• The internal and external smart data
technology infrastructure across the
data entire technology landscape
from data collection, data intake,
data processing, data analysis,
reporting and presentation, data
storage and data administration,
management and governance is
integrated and connected
• The smart data technology
infrastructure is secure and complies
with privacy standards and
requirements
• The smart data technology
infrastructure delivers the required
performance
• Internally and externally data collection technology is
operating and data is being captured and processed
successfully to actualise the smart data technology
infrastructure
• Data is available to the designated internal and external target
users
• Linking the operation and use of smart data technology
infrastructure to your organisation’s overall enterprise
architecture ensures that execution is enhanced
• Individual business function smart data technology
operational processes are optimised and integrated across
your organisation
• The smart data technology infrastructure incorporates the
monitoring of activity and event and alert management across
the landscape to monitor the health of the infrastructure
• Your organisation has processes in place and operating for
event and alert management.
• Your organisation uses data collected on smart data
technology infrastructure to manage capacity and resources
and generate and action forecasts
• Your organisation has appropriate tools and processes to
report on analyse data collected on smart data technology
infrastructure to manage capacity and resources and generate
and action forecasts
• Your organisation uses data collected on smart data
technology infrastructure and insight derived from analyses of
this data to update the technology strategy
January 18, 2017 76

Characteristics
• Your organisation identifies the need
for new smart data technology
infrastructure and works with
industry to develop new
technologies
• Your organisation participates in the
development of standards in the
area of smart data technology
infrastructure
• Your organisation is innovative in the
development, application and use of
smart data technology infrastructure
• Your organisation demonstrates
leadership in the area of smart data
technology infrastructure
• Your organisation pioneers the
use of automation and intelligent
approaches and technologies to
the operation and management
of smart data technology
infrastructure
• Your organisation works to
develop and apply industry-wide
security standards to protect
smart data technology
infrastructure
January 18, 2017 77

Interaction Capability – Key Skills
• Ability to design, develop and implement a strategy for external party data interactions
• Ability to ensure that external party data interactions are common across all channels and platforms
• Ability to design and implement organisation structures and processes to operate external party data interactions
• Ability to define technology requirements to operate external party data interactions that integrates with your organisation’s
enterprise architecture
• Ability to prioritise data interactions and external parties for implementation to maximise returns and benefits
• Ability to develop and manage an investment and funding plan to implement the strategy for external party data interactions
• Ability to enable, drive and encourage external party data interactions and participation
• Ability to monitor the status of external party data interactions, to identify and respond to problems and outages
• Ability to design and deliver useful and usable data to external parties that provide value to external parties
• Ability to deliver applications that enable external party data interactions
• Ability to enable data-based interactions with external parties
• Ability to use information on data interactions with external parties to deliver business benefits and improve organisation
performance
• Ability to ensure that data interactions with external parties are secure and private
• Ability to collect data from external sources on external parties
• Ability to integrate internal and external data on external parties from multiple sources to create a single view of external
parties
• Ability to extend organisation business processes to external parties
• Ability to collect data on data interactions with external parties to optimise functionality
January 18, 2017 78

Interaction - Foundational Skill Level
Characteristics
• Your organisation is developing a vision
and strategy for external party data
interactions
• Your organisation is developing a plan to
implement the strategy
• Your organisation is profiling the data
that is available to and can provide value
to external parties
• Your organisation is designing
organisational structures and processes
to implement and operate external
party data interactions
technology plan for external party data
interactions
• Your organisation is developing an
investment and funding plan for external
• You are researching the available
technology options for external party
data interactions
• Your organisation is surveying and
understanding the data interaction
requirements and needs of external
parties and communicating plans
with key external parties
• Your organisation is benchmarking
its data interaction plans for external
parties with other similar
organisations
• Your organisation is embedding
privacy and security into plans and
designs for external party data
interactions
January 18, 2017 79

External Party Involvement and Interaction -
Characteristics
implement pilot and proof of
concept external party data
interactions systems and
processes within the context of
the overall strategy
• Your organisation is deploying
technology solutions to enable and
support external party data
interactions
solutions to collect data on the
operation, usage, activity and
performance of external party data
interactions
• Your organisation is analysing data
on the operation, usage, activity and
performance of external party data
interactions to understand how to
direct investment decisions
• Your organisation is analysing the
options to enable additional external
January 18, 2017 80

External Party Involvement and Interaction - Extension
Characteristics
• Your organisation is joining-up
the previously implemented
individual pilot and proof of
concept external party data
interactions systems and
processes
implementing an overarching
delivery and access framework to
allow individual implementations
be connected
• Your organisation is enabling two-
way interactions with external
parties
• Your organisation is optimising external
party data interactions based on analysis
of operation, usage, activity and
performance data
• Your organisation is achieving insights into
the needs of external parties
• Your organisation is able to classify
external parties based on patterns of
operation, use and activity
• Your organisation is able to identify and
respond to changes in patterns of external
• Your organisation is able to monitor the
status of external party data interactions,
to identify and respond to problems and
outages
• Your organisation is able to ensure that
external party data interactions are
common across all channels and platforms
January 18, 2017 81

Usage And Results
Characteristics
• Your organisation has an
integrated system for all external
party data interactions systems
and processes
• Your organisation has developed
new business processes and
models for external party data
interactions to deliver new
products and services
• Your organisation receives and
actions feedback from external
• Your organisation supports
external parties in the
interactions
• Your organisation has automated
operational, service management
and support processes associated
with external party data
interactions
January 18, 2017 82

Characteristics
• Your organisation develops industry-
wide innovations for external party
data interactions
• Your organisation provides
leadership in the development of
industry-wide standards for privacy
and security
industry-wide standards for external
leadership in the identification of
new technologies and solutions for
external party data interactions
• External parties can view the data being
collected from them and can control and
interact with this data
• You collaborate on data extensively with
external parties
• Collection of data from external parties
is resilient and reliable and issues are
automatically identified and resolved
• The required infrastructure to support
external party interactions is fully
implemented and operational
• You are contributing to and providing
technology standards for data
collaboration
• You are contributing to the development
of security and privacy standards for
data collaboration
January 18, 2017 83

Smart Data Value Addition And Derivation
• Ability to understand how smart data integration across entire landscape from
data intake, data processing, data analysis, reporting and presentation, data
storage and data administration, management and governance contributes to
the overall organisation’s value chain
• Ability to identify external interacting parties the associated data value chains
of which should be prioritised for optimisation
• Ability to understand the organisation’s data value chain and to identify value-
adding and non-value-adding primary and supporting activities across both
physical and virtual value chains and across all external interacting parties
• Ability to redefine and optimise data value chains
• Ability to integrate real-time data into the organisation’s data value chain
• Ability to develop and implement a smart data value-adding strategy
• Ability to design and develop processes that support smart data value-adding
operational framework
• Ability to automate the organisation’s data value chain primary and supporting
activities
• Ability to manage investment in data value chain activities
January 18, 2017 84

Derivation - Foundational Skill Level
Characteristics
• Your organisation is beginning to
understand how smart data
integration can assist in the
organisation’s value chain
operation and optimisation
strategy for utilising smart data to
enhance the organisation’s value
chain
• Your organisation has identified the
data integration requirements to
ensure the smart data value chain is
being defined
• Your organisation is planning to
implement data value chain
integration initiatives
• Your organisation has identified the
relevant data sources that are
involved in primary and supporting
activities across both physical and
virtual value chains
• Your organisation is embedding
security and privacy across primary
and supporting activities across both
physical and virtual value chains
January 18, 2017 85

Smart Data Value Addition And Derivation -
Characteristics
• Your organisation is making
investments in smart data
integration and data value chains
pilots and proofs of concept
data acquisition technologies as
part of data value chains
• Your organisation is redefining
and optimising data value chains
January 18, 2017 86

Smart Data Value Addition And Derivation - Extension
Characteristics
• Your organisation has integrated
the smart data integration and
data value chains pilots and
proofs of concept
implementations into a more
connected operational
framework
• Your organisation is changing the
data value chains to optimise
operation and remove non-value
adding activities
new models for data value chains
• Your organisation is integrating
real-time data into the
organisation’s data value chains
for specific external interacting
parties
• Your organisation is monitoring
the operation of data value chains
and has developed processes to
take action in the event of
problems
January 18, 2017 87

Usage And Results
Characteristics
and dynamic view of data flows
across optimised data value chains
and has processes in place to react
to feedback and to take appropriate
action
• Your organisation has fully optimised
data value chains
• Your organisation has fully
integrated real-time data into the
organisation’s data value chain
developed and implemented a smart
data value-adding strategy
• Your organisation has fully designed
and developed processes that
support smart data value-adding
operational framework
• Your organisation has partially
automated the organisation’s data
value chain primary and supporting
activities
• Your organisation has integrated
data value chains with external
interacting parties
view of the operation of data value
chains
January 18, 2017 88

Characteristics
• Your organisation contributes to
the design of data value chain
standards
• Your organisation works with
other similar organisations to
implement industry-wide data
value chains
automated the organisation’s
data value chain primary and
supporting activities
• Your organisation has a defined
and operational approach to
allocating and managing
resources to address and resolve
issues with data value chain
processing
January 18, 2017 89

Development Capability – Key Skills
• Ability to contribute to the development of standards and reference architectures for optimised smart
data operations and use
• Ability to define standards for secure, reliable, available, resilient, efficient, performing smart data
infrastructure across the entire data landscape from data intake, data processing, data analysis,
reporting and presentation, data storage and data administration, management and governance
• Ability to contribute to the development of smart data privacy and security guidelines for smart data
• Ability to create sets of differentiated and segmented smart data standards for different external
interacting parties and types of customer and user
• Ability to assist with the development of successful reference implementation and operational models
for smart data value chains
• Ability to contribute to the design and technology solutions and associated standards across the entire
data landscape from data intake, data processing, data analysis, reporting and presentation, data
storage and data administration, management and governance
• Ability to work with external interacting party organisations and representation groups to develop
smart data standards
• Ability to benchmark your organisations smart data performance with other organisations both in your
industry sector and with companies that excel in areas of competence your organisation requires or
demonstrates
• Ability to define and agree a set of organisational targets and objectives for participation data
standards development
• Ability to create training standards for smart data including possible certifications
January 18, 2017 90

Development - Foundational Skill Level
Characteristics
• Your organisation is aware of the
need for data standards across all
aspects of the smart data
landscape
• Your organisation is starting to develop
an approach to contributing to the
development of smart data standards
investment plans for a programme of
work to contribute to the development
of smart data standards
• Your organisation is starting to promote
the need for industry-wide smart data
standards
• Your organisation is starting to share its
smart data vision with the wider
community including external
interacting parties, other organisations
and standard development entities
January 18, 2017 91

Smart Data Standards Contribution and Development -
Characteristics
• Your organisation is engaged with
similar organisations in the
development of smart data
standards and reference
architectures
• Your organisation has agreed an
investment plan for its
involvement in the development
of smart data standards and
reference architectures
• Your organisation is working with
external interacting party
organisations and representation
groups to develop smart data
standards
work with technology providers to
define the requirements of smart
data enabling technology
• Your organisation has started
participating in working groups for
smart data standards
• Your organisation is involving
selected customers in consultations
on data standards across the data
landscape
January 18, 2017 92

Characteristics
• Your organisation has formalised
its involvement with the
development of smart data
standards
the development of smart data
standards
• Your organisation is measuring your
participation in and contribution to smart
data standards development
• Your organisation has agreed a set of
targets and objectives for participation
data standards development
• Your organisation is contributing to the
creation of reference architectures
• Your organisation is benchmarking its
smart data performance against other
similar organisations
• Your organisation has create sets of
differentiated and segmented smart data
standards for different external interacting
parties and types of customer and user
• Your organisation welcomes the
participation by customers in the
development of smart data standards
January 18, 2017 93

Development - Embedding, Operationalising
And Measuring Usage And Results
Characteristics
• Your organisation is regularly
contributing to smart data standards
development
• Your organisation is regularly
contributing to the creation of smart
data reference architectures
technology providers in the design
and technology solutions and
associated standards across the
entire data landscape from data
intake, data processing, data
analysis, reporting and presentation,
data storage and data
administration, management and
governance
• Your organisation has established or
have assisted with the establishment
of smart data standards groups and
regularly meets with external
interacting parties, other
organisations and standard
development entities
• Your organisation regularly publishes
details on its participation in smart
data standards development and
groups
• Your organisation regularly publishes
papers on data standards
development
January 18, 2017 94

Characteristics
• Your organisation is recognised as
a leader in smart data standards
development
• Your organisation is contributing
to the design and technology
solutions and associated
standards across the entire data
landscape from data intake, data
processing, data analysis,
reporting and presentation, data
storage and data administration,
management and governance
• Your organisation has fully aligned its
internal data standards with the
external smart data standards
development
• Your organisation has developed a
portfolio of reference smart data
implementations that it has
published
external parties to implement a
secure, integrated and resilient
smart data framework
• Your organisation has developed a
set of best practices for smart data
implementations and operations
that it has published
January 18, 2017 95

• No all organisations need to have the same level of skills in
all competency areas
• Skills levels depend
January 18, 2017 96

Data
Administration,
Management and
Governance
Indicative Data Reference Architecture - Core And
Extended
January 18, 2017 97
Data Intake
Data Collection
Data Source
Management
Data Import
Data Processing
Data Quality/
Summary/ Filter/
Transformation
Data Aggregation
and Consolidation
Data Management,
Retention
Data Analysis
Data Modelling Use Case Triggering
Analysis and
Reporting
Management and
Administration
Data Storage
Data Storage
External Party Interaction Zones, Channels and Facilities
Platforms, Channels,
Data Sources
Security, Identity ,
Access and Profile
Management
Specific Applications
and Tools
Applications
Delivery and
Management Tools
and Frameworks
Operational and
Business Systems
Security, Privacy
and Compliance
Capacity Planning
and Management
Data Access
Physical Data Layer

Indicative Data Reference Architecture - Core And
Extended
• Each component consists of a one or more technology
modules
• Any data strategy has to be actualised by technology and
supported by processes and people
January 18, 2017 98

Additional Data Technology Layers
January 18, 2017 99
Business Processes
Data Strategy
Actionable Information and Business Value
Skills and Resources

Mapping Capability View To Technology View
• Strategy must
encompass this
mapping
• Capability and technology
views must map to each
other
January 18, 2017 100

Mapping Capability View To Technology View
• Layer the Smart Data capability framework onto the
organisation’s data strategy and its associated
technologies, processes and people to identify the most
suitable and beneficial strategy
January 18, 2017 101

More Information
Alan McSweeney
http://ie.linkedin.com/in/alanmcsweeney
January 18, 2017 102

Forget Big Data. It's All About Smart Data

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