jeanette bosch & magan naidoo - data foundations presentation at the chief data officer forum,...

A short "OUR"story

Of Nearly EverythingData

Not by Bill Bryson

Copyright © 2016 Dimension Data

Our world of Data is exploding with Digital Transformation technologies and platforms generating data.


Pillars: Data Governance, Data Architecture, Data Management.

The big challenge is to bring the data pillars together to ensure synergy and drive strategy.

The Goal: To align the Vision / Strategy, with Architecture, and how you will Manage & Enable and Govern all things Data.

In the future, it will become even more important for the data expert community to connect the dots between strategy,

architecture, data management and data governance.


Business Divisions

Motor

Corporate

DirectAxis

MotoVantage

“Rest of Africa”

Rentworks

TFS

VW

Data Office

Our view of the Data Office

Information Office - CDO

Group CRO

FirstRand

Information / Data Governance

Information / Data Architecture

Information / Data Management

Program / Project - EPO

Data Management Practice

Shared Service Model / Grow Competency & Succession

PlanningWhenWho / What / How of Data

Capabilities (domains)Architect What / HowIndependent Governance of the What / How

Program Management

Project Management

Prioritization Process (incl. group projects)

Data Project Roadmaps

Administration and reporting

Change Management

Benefit Tracking in conjunction with Business

Cost tracking

Expectation Management

Business Value Management

IM & IG Report Services

Enterprise Data Capabilities (Domains):Data Development and Integration BI and Data WarehouseRef & Master Data ManagementData Quality ManagementMetadata Management Records, Document and Content Management Data Operations ManagementData Protection / Privacy / SecurityData Performance

Additional*:Enterprise Credit Data ModelInformation ClassificationDictionary Taxonomy

Information Level:StrategiesLandscapesArchitecturesFrameworksData and Information Management FrameworkMethod / ApproachesData InnovationFuture State InnovationStandards / Guidelines to support FSR PolicyStandards / Guidelines for EDMStandards / Guidelines to support Additional* Data ActivitiesData Level:Data ModellingData ArchitectureData AnalyticsBusiness Process ModelsAdditional:Key data sources identified and managedData Flow ownership

Principles, policy and standards

Ownership defined and allocated

Governance structures

Key data sources identified and managed

Material data elements defined

Governance around Data flows

Data Controls rolling up into the Information Governance Controls

Process:Data Management Practice Process

Data Services / Data Monetization

Data Management Roles and Responsibility Definition

Shared Services Model

Skills DevelopmentData Management Competency Framework

Succession planning

Data Culture Development

Promote Information Management Culture

Information Management and Governance Reporting Framework and Report ServicesTechnology Enablement – IT


Vision/Strategy

The data strategy should link back to the following strategies; business strategy,

IT strategy and digital strategy. Governance, Risk and Compliance should

be represented, as well as the economy of data related strategic goals.

The industry trend is to setup a Data Office with a Data Office Strategy under the leadership

of a CDO - to support business strategies.

Executive buy-inSponsorshipLine of sight on strategiesTop-down / Bottom-upRoles & ResponsibilitiesBusiness Value Definition

Principles


Architecture

The architecture should speak to the strategic objectives the company wants to achieve. The architecture should ensure that the economy of data, the governance and regulatory aspects are addressed with the same level of importance. Architect for Data Management and Business Value.

Capability Model - Unlock Business Value & Data Management

Architect for Regulatory and Governance

Architect for Business ValueAlign to Strategy

Architect with Future Trends in mind (future proof)Advisory & Guidance

Principles


Data Management

Data Management relates to the actions being enabled through the

architecture layer.

The output and activities of Data Management should link back to

business value (the economy of data) or a governance / compliance benefit

that will be achieved.

Data Management FrameworkData Driven CultureData Capability RoadmapPeople - grow passion and knowledgeProcess - built in governance controlsTechnology - fit for purposeData Management for Governance

Principles


Data QualityKPIs – applicable to all personnel that influence data

Linking quality to business impact – cost, complexity, operational, service delivery, reputational impact, legislative

Define quality dimensions, metrics and gateways

Process and mechanism for reporting on quality

Data policy clearly defining rules of the game

People – management control, training & guidance

Technology – automation of rules enforcement and workflow approvals

Data Processes

Organizational collaboration

KPI's definedLink Quality to business impact

Define Quality DimensionsProcess & Mechanisms for reporting

Principles


Data Governance

Data Governance consists of 3 types of activities.

Guidance upfront during strategy definition and design.

Assistance during enablement and setup.

Controls to ensure that during the lifecycle we have implemented consistently.

OwnershipGovernance CouncilPolicies and StandardsData StewardshipData MaturityReporting and AnalyticsData Architecture

Principles


Community of PracticeTo bring the pillars (Data Governance, Data Architecture, Data Management) together in a community of practice or a formal office where one can guide and drive alignment between the discipline areas.

This is a journey to bring the previous silo type thinking into a hive-mind type thinking culture.

Your vision and strategic focus will guide the community of practice or the data office.

Operating ModelEngagement Model

Service ModelCosting Model

Partnership ModelStrong Program and Project ManagementGovernance Models

Business & Regulatory Value Realisation

Principles


Sun Hot

Earth Mild

Mars Cold

Jupiter Freezing

Data ThermometerOn a scale from Hot as the Sun to Jupiter Freezing, please reflect on the current state of your Data Environment.

Do you have clearly defined ownership?

What is your Data Maturity level within your Organization?

How would you rate your data quality?

Do you have a formal data governance practice in place?

How would you rate your data investment?

Thank

You

jeanette bosch & magan naidoo - data foundations presentation at the chief data officer forum,...

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