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

Rates At 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 Competency Areas

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


Smart Data Technology

Planning and Implementation

External Party Involvement And

Interaction

Smart Data Value Addition And

Derivation

Smart Data Standards

Contribution And Development

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Smart Data Competency Areas 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


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


1. Management of data assets and personnel resources 2. Capacity planning 3. Fault and error detection and correction

January 18, 2017 29

Smart Data Competency Areas 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


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


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


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









1 2 3 4 5


January 18, 2017 41


What the skill level for the specific

competency area looks like


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

Smart Data Competency Areas And Skill Levels 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



Smart Data Technology Planning




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 - Foundational Skill Level

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

Strategy, Management and Governance - 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

• Your organisation has started to 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

• Your organisation has started to achieve benefits from the implementation and operation of smart data initiatives

Improvement Actions And Events • 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

Strategy, Management and Governance - 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

Strategy, Management and Governance - 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 - Foundational Skill Level

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

Data Infrastructure and Data Landscape 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

Data Infrastructure and Data Landscape 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 - Establishment Of Base Structures and Processes For Deciding On And Progressing Initiatives

Characteristics

• Your organisation has started to implement integrated smart data technologies, connecting previous implementations


• Your organisation has started to 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

Data Infrastructure and Data Landscape Operations - 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

Data Infrastructure and Data Landscape 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

Data Infrastructure and Data Landscape Operations - Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community

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 Capability – Key Skills

• 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 - Foundational Skill Level

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

• Your organisation is implementing views of data assets to enable business functions see the status of data assets

• Your organisation is developing 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

Data And Resource Asset Management - Embedding, Operationalising And Measuring 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

• Your organisation has implemented and operates processes to proactively address data asset issues based on status and need

January 18, 2017 70

Data And Resource Asset Management - Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community

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

Smart Data Technology Planning and 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

Smart Data Technology Planning and 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 - Establishment Of Base Structures and Processes For Deciding On And Progressing Initiatives

Characteristics

• Your organisation has defined a data strategy and an associated investment programme

• Your organisation has started to 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

Smart Data Technology Planning and Implementation - Extension And Linkage Of Completed Base Structures And Delivery Of Results and Performance Improvements

Characteristics

• Your organisation is 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

Smart Data Technology Planning and Implementation - 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

Smart Data Technology Planning and Implementation - Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community

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

External Party Involvement and 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

External Party Involvement and 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

• Your organisation is developing a technology plan for external party data interactions

• Your organisation is developing an investment and funding plan for external party data interactions


• 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 - Establishment Of Base Structures and Processes For Deciding On And Progressing Initiatives

Characteristics

• Your organisation has started to 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

• Your organisation has implemented 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 party data interactions

January 18, 2017 80

External Party Involvement and Interaction - Extension And Linkage Of Completed Base Structures And Delivery Of Results and Performance Improvements

Characteristics

• Your organisation is joining-up the previously implemented individual pilot and proof of concept external party data interactions systems and processes

• Your organisation is 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 party data interactions

• 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

External Party Involvement and Interaction - Embedding, Operationalising And Measuring 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 party data interactions


• 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

External Party Involvement and Interaction - Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community

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

• Your organisation provides leadership in the development of industry-wide standards for external party data interactions

• Your organisation provides 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 leadership in the development of 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 Capability – Key Skills

• 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

Smart Data Value Addition And 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

• Your organisation is developing a 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 - Establishment Of Base Structures and Processes For Deciding On And Progressing Initiatives

Characteristics

• Your organisation is making investments in smart data integration and data value chains pilots and proofs of concept


• Your organisation is investing in 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 And Linkage Of Completed Base Structures And Delivery Of Results and Performance Improvements

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


• Your organisation is developing 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

Smart Data Value Addition And Derivation - Embedding, Operationalising And Measuring Usage And Results

Characteristics

• Your organisation has a complete 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

• Your organisation has fully 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

• Your organisation has a complete view of the operation of data value chains

January 18, 2017 88

Smart Data Value Addition And Derivation - Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community

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


• Your organisation has fully 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

Smart Data Standards Contribution and 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

Smart Data Standards Contribution and 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

• Your organisation is developing 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 - Establishment Of Base Structures and Processes For Deciding On And Progressing Initiatives

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

• Your organisation has started to 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

Smart Data Standards Contribution and Development - Extension And Linkage Of Completed Base Structures And Delivery Of Results and Performance Improvements

Characteristics

• Your organisation has formalised its involvement with the development of smart data standards

• Your organisation is investing in 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

Smart Data Standards Contribution and 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

• Your organisation works with 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

Smart Data Standards Contribution and Development - Innovate, Lead, Invent, Collaborate With Other Organisations And Wider Community

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

• Your organisation works with 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

Smart Data Competency Areas And Skill Levels

• 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


January 18, 2017 102
