Is Your Agency Data Challenged?

Kick start your data governance initiatives with DLT Solutions

July 2015

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• Federated data organizations in public sector face more challenges today than ever before. As discovered via research performed by North Highland Consulting, these are the top issues you are most likely experiencing: – Knowing what data is available to support programs and other

business functions – Data is more difficult to access– Without insight into the lineage of data, it is risky to use as the

basis for critical decisions – Analyzing data and extracting insights to influence outcomes is

difficult at best

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• The solution to solving these challenges lies in creating a holistic enterprise data governance program and enforcing the program with a full-featured enterprise data management platform.

• Kreig Fields, Principle, Public Sector Data and Analytics, from North Highland Consulting and Rob Karel, Vice President, Product Strategy and Product Marketing, MDM from Informatica will walk through a pragmatic, “How To” approach, full of useful information on how you can improve your agency’s data governance initiatives.

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• Learn how to kick start your data governance initiatives and how an enterprise data management platform can help you:– Innovate and expose hidden opportunities– Break down data access barriers and ensure data is trusted – Provide actionable information at the speed of business

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Data Governance for Govt.Kreig FieldsPrincipal, Public Sector Data & AnalyticsNorth Highland

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Agenda

1. Why data governance for public sector?

2. Establishing a data governance organization

3. Building a data governance solution

4. Do’s and don’ts

5. Open questions

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Why data governance for public sector?

Data governance enables cohesive, consistent and reliable data across all of these data perspectives

• Federated governance approach in public sector leads to fragmented data perspectives

HQ

District 1

District 2

District 3

District 4

District 5

District 6

AcquisitionACQ ACQ ACQ ACQ ACQ ACQ

Proj…Proj Proj Proj Proj Proj Proj

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Common gaps in enterprise data

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Challenging but not impossible

• Federal Government has defined a governance approach for aligning data and applications across the federal government

› Uses Federal Enterprise Architecture (FEA)

Link to Federal Enterprise Architecture information

› The DoD uses Department of Defense

Architecture Framework (DoDAF)

Link to DoDAF information

Proper data governance and tools are essential to managing these issues!

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Data Governance

• Decision-making and oversight

• Uses a Committee to make decisions

and to provide strategic direction

Data Stewardship

• Formally making someone accountable

for data integrity

• Manages internal data subject area and it’s impact to the business

• Coordinates with colleagues and recommends operational changes needed to improve data governance

Data Management

• Day to day execution of the Governance rules

• Responsible for the day to day data management activities

• Receives direction and guidance from data steward

Establishing a data governance organization

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Systems Model

Projects ModelBiz Function Model

Subject Area Model

Biz Process Model

Sample Data Governance/Stewardship Models

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Building a data governance solution

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Start by assessing where you are.

DataQuality

DataIntegration

DataStrategy andArchitecture

MasterData

Management

MetadataManagement

Analytics

Securityand

Privacy

DashboardsScorecardsReporting

Projects, interviews, and surveys

• Do not let perfection stand in the way of progress

Public Sector

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• Address data reliability and consistency issues

• Improve business visibility and decision-making

• Streamline time/effort required to share information

• Increase the organization’s understanding of the business in order to promote transparency and efficiency

• Drive increased accuracy, timeliness and the precision with which teams can discuss and collaborate on business issues and opportunities

• Communicate and coordinate activities such that rework and duplicative calculations, analysis, and reporting are either eliminated or recognized as necessary.

• Facilitate purposeful and coordinated ad hoc analysis

• Shift focus from data entry applications, to exploiting the value of information for our business and customers.

Data Governance: Do’s

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• Introduce cumbersome and unwieldy processes

• Create redundant processes

• Focus on just the technology, but on how business can achieve the maximum benefits of technology.

Data Governance: Don’ts

Thank You

Accelerating and Enabling a Sustainable Data Governance Program in Government

Rob Karel, Informatica VP Product Strategy and Marketing, Information Quality Solutions

Agencies Face Data Challenges

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Valuable information exists, but trapped in legacy

systems or not digitized

New sources and huge volumes with up to 80%

unstructured

Long lifespan of data, due to retention regulations, adds storage stress…

…But short life of usable data due to data degradation

No data map to classify types and importance of data

Data governance, including data policies, needed

Data stewardship and master data management non-existent

Proliferation of duplicate and

uncleansed data

With Many Unanswered Questions

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What is the quality of existing and new data? How do we define quality anyway? Do we capture data appropriately?

How much data must we store, and in what format? How long must we keep the data?

Who owns the data? How do we secure and address privacy of personal data? Where’s this information coming from? Should I trust it?

Who needs what data, and why? How do we balance real-time vs. right-time data delivery?

Does data change frequently?

And that’s just the tip of the iceberg

Data Governance is a Business Function

Data governance should be managed as a business function, no different

than Finance or Human Resources

Data Governance Maturity Stages

Fragmented Holistic

IT-d

rive

nB

usi

nes

s-d

rive

n

0: Unaware• No activity

1: Initial• Ad hoc

2: Repeatable• Pilot

3: Defined• Project

4: Managed• Program

5: Optimized• Function

Escalating Return on Data Investments

Fragmented Holistic

IT-d

rive

nB

usi

nes

s-d

rive

n

IT efficiencyandcompliance

Cost control, business efficiencies & risk reduction

Greater efficiency,compliance and support mission-critical objectives

Innovation, automation, economy of scale and agility

Data Governance Maturity Benchmarks (as of 7/15/2015)

Public sector maturity below x-industry

average

Data Governance is not – and should Never have been – About the Data…

…the vision mustbe to improve the business processes, decisions and interactions trusted, secure data enables!

The Ten Facets of Data Governance

People Vision and Business Case Tools andArchitecture

DependentProcesses

MeasurementOrg

AlignmentChange

ManagementPolicies

DefinedProcesses

ProgramManagement

Data Governance Roles and Responsibilities

Steering Committee

Business and IT Stewards

Data Governance Leader/Driver

Executive Sponsor(s)

• Facilitation• Communication• Measurement• Escalation• Business case

Drive X-functional:• Prioritization• Resource allocation• Approvals• Broader funding• Enforce collaboration

• Vision• Evangelism• Funding• Remove barriers

• Analysis• Definition• Business/IT liaisons• Education• Ensure compliance• Mitigation

Flavors of Data Governance Measurement

Operational monitoring

Service Level Agreements (SLAs)

Program effectiveness

Business Value/ROI

Data Governance Leader, LOB and Data Stewards

Executive Sponsors and Steering Committee

Sample Key Performance Indicators

KPI Name KPI Type KPI Description

Level of DG program influence

Program effectiveness

# of lines of business, functional areas, system areas, project teams and other parts of org that have committed stewardship resources or sponsorship

DG interactions Program effectiveness

Capture all types of value-added internal interactions such as training, consulting and project implementation support

Issue resolution Program effectiveness

Categorize and track status of all issues that come in to the data governance function

External validation Program effectiveness

Industry awards, benchmarking against peers, thought leadership via speaking tours

Data quality metrics Operational Monitoring of data accuracy, completeness, integrity, uniqueness, consistency, standardization, and other baseline DQ metrics

Policy compliance Operational Audits ensuring compliance with privacy, security, retention and other regulatory policies. 

Recovery time SLA A contracted agreement with the business on how long before a data exception will be mitigated

Data latency SLA A contracted agreement with the business on how quickly a data update or insight will be delivered to a dependent process or decision-maker

Compliance Biz value Reducing penalties by ensuring regulatory compliance; reducing enterprise risk (e.g., contractual, legal, financial, brand)

Cost savings Biz value Lowering costs (e.g., business, labor, software, hardware)

Spend optimization Biz value Optimizing spending (e.g., procurement, supply chain, services, labor)

Efficiency improvements Biz value Improving operational efficiencies (e.g., employee, partner, contractor);.

Revenue growth Biz value Increasing top-line revenue growth;

Customer satisfaction Biz value Optimizing customer experience and satisfaction

Data Governance Process Stages

Discover• Data discovery• Data profiling• Data inventories• Process inventories• CRUD analysis• Capabilities assessment

Define• Business glossary creation• Data classifications• Data relationships• Reference data• Business rules• Data governance policies• Other dependent policies• Key Performance IndicatorsMeasure

and Monitor• Proactive monitoring• Operational dashboards

• Reactive operational DQ audits

• Dashboard monitoring/audits

• Data lineage analysis• Program performance• Business value/ROI

Apply• Automated rules• Manual rules• End to end workflows• Business/IT collaboration

Apply

DataGovernance

Apply

Measureand

MonitorDefine

Discover

IT Business

Collaborate

Informatica Platform Built to Support Holistic Data Governance

Apply

DataGovernance

Apply

Measureand

MonitorDefine

Discover

IT Business

Discover Define

Measure and Monitor

Apply

Collaborate

Business Process Management

Architectural Scope of Data Governance

Enterprise Data Warehouse

BI/Analytics

Performance Management

MobileShared Capabilities

• Metadata/lineage • Business glossary• BPM/Workflow• Connectivity• Services• Collaboration• Monitoring• Policy management• Stewardship• Discovery• Security• Canonical Model

Cloud

Social

HadoopBig Data

Enterprise Integration

DQ, ProfilingCEP andBusiness

Rules

MDM/ReferenceData Mgmt

Business, Data and Process Modeling

Information Security/

ILM

DataVirtualization

Legacy

Web

Enterprise apps

On premises (machine) Big Data

3rd party/Market data

Identify candidate business opportunities

1. What are the top business imperatives as defined by your most senior leadership?

2. What organizational business processes, decisions and stakeholder (e.g., citizen, partner, employee) interactions are most important in support of these top imperatives?

3. What data and applications are used to support those processes, decisions and interactions?

Data

Scope thousands of “relevant” data items to dozens or hundreds of “critical”

Use Discovery Processes to prioritize roadmap

4. What upstream people, systems, and processes create, capture, and update that data?

5. What is the business end user’s level of confidence in the security and trustworthiness of that data?

Repeat process and reassess priorities ongoing (quarterly or bi-annually at minimum)

Data

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4.00

5.00

6.00

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Business Opportunity Name

High <--- Investment & Effort ---> Low

Bu

sin

es

s V

alu

e

Consider Prioritize

ExperimentIgnore

# Business Opportunity Name

1 Reduce eDiscovery risk

2 Improve customer satisfaction scores

3 Implement shared services /COE for data management

4 Improve financial reporting

5 Secure sensitive data

6 Optimize supply chain

7 Reduce costs and inefficiencies through modernization of enterprise applications

8 Reduce waste, fraud & abuse

9 Reduce costs through data Center Consolidation

10 Introduce new service channels e.g. mobile

Consider Standardizing Process For Business Opportunity Prioritization

Free Tools Available on GovernYourData.com

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Contact Us

DLT Solutions | Infrastructure Performance Management• Visit us on our website:

– http://www.dlt.com/brands/informatica

• Reach out to us via email:– ipm@dlt.com

• Find us on social media:

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Learn More

• For more information, click below to download the full on-demand webinar:

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