Data Governance - Turning Data Into Insight - Ken Jacquier

7/27/2019 Data Governance - Turning Data Into Insight - Ken Jacquier

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© 2013 International Business Machines Corporation

Minnesota Digi tal Governm ent Summ it

Data Governance –

Turning Data into Ins ight

July 31, 2013



2© 2013 International Business Machines Corporation

Data Governance – Turning Data into Insight

While we know that the velocity, variety and volumeof data continues to increase, do we really knowhow to handle it and what to do with it? This sessionwill look at implementing enterprise datagovernance including a look at the structure of datagovernance as well as some of the technologies -that can help answer questions we never thought to

ask and provide proactive solutions to problems wenever before thought could be solved.




Sustainable success turning structured data into insights has

required a focused Information Governance program

Maintaining and improving Data Quali ty is

funded as cr i t ica l cont inuous improvement

co re to innovat ion and leveraging

investments fo r greatest value

People Process Technology




Information Governance Structure to support

continuous improvement

DefineService or Program

Opportunity

ObtainExecutive

Sponsorship

ConductMaturity

Assessment

BuildRoadmap

EstablishOrganization

Blueprint

BuildBusinessGlossary

UnderstandData

CreateMetadata

Repository

DefineMetrics

Govern

LifecycleManagement

Govern

Security &Privacy

Govern Analytics

MeasureResults

= Mandatory

= Optional

Govern

Master DataManagement

Govern DataQuality




Barriers to sustaining Information Governance:Where do we recommend you get started?

DefineService/Program

Opportunity

ObtainExecutive

Sponsorship

BuildRoadmap

EstablishState’s

OrganizationBlueprint

DefineMetrics

MeasureResults

= Mandatory

= Optional




Define business problem

Information Governance Programs sustain value byfocusing on specific challenges

Need for better customer-centricity

Failed audit

Data breach

Risk due to poor quality or lack of trust of information

High expenditure managing and storing information

Inconsistent view of informationdepending on the system

This can be one problem aligned to a sponsor with funding

This can be a group of government problems with

documented business value where Data Quality is a critical enabler to success.

Current trend is to make Information Governance and Data Quality a core segment of an approved andfunded project; this is often a particular, measureable functionality such as data profiling.

Once the Information Governance program builds momentum with quick wins, it is important to make

the program a yearly line item in funding cycle This is the ultimate validation that the State

understands that information is an asset and must be managed as program and not a project.




Questions from Legislature

How many children under 15 also have children utilizing our services? How many people over 100 years of age receive benefits?

How many indigenous people receive income support payments?

Data Profiling by Business Intelligence department

Several one-year old children also had children

Number of people over 100 years of age exceeded the number of peoplefrom the national census

The percentage of indigenous people receiving income supportpayments was significantly lower than the average population

Outcomes

Focus on Date of Birth and Race as critical data elements People creating the situation (front office) were not the people

consuming the data (Business Intelligence)

Example of State Information Problem: Social Services Agency




Step 12: Securi ty and Privacy at Child Welfare Agency (Case Stud y)

The department received a complaint from a relative who cared for a family member’schild.

On numerous occasions she requested that her home address, telephone number andother details about the child remain private. The complainant was concerned about thechild’s parents’ criminal history, violence and drug use.

The complainant’s address details were included in documentation and sent to the

child’s parents by the department. As a result, the complainant moved house becauseof safety concerns. She complained to the department which provided her with somefinancial assistance as a result of the move.

The complainant requested that her new address be recorded as ‘withheld’ by thedepartment. However, the department failed to comply with this request.

The department subsequently sent documentation to the child’s parents which includedthe complainant’s new address details as well details concerning the child. Thecomplainant requested compensation to cover the cost of insurance and securitymeasures for her home, as well as increased rental costs.

The complainant’s payout was then reassessed and she was provided with a higher level of compensation.




Obtain Executive Sponsorship

Create virtual teams and a vision for Data Stewardship

Obtain support from senior management (front and back office)

Identify an owner for Information Governance

Are you ready for this to be a Chief Data Officer ?

Federal Reserve Board- Chief data officer since May 2013

9

Obtain execut ive sponso rship for Information Gov ernance




Sample Information Governance Metrics – Provid ers with in a Healthcare Syst em

Organization Business Drivers KPI

NetworkManagement

MedicalInformatics

Ensureappropriatephysiciancoverage for members (e.g.,50% of memberswith chronic

diseases need tobe situated near a Medical Home)

Conductappropriateprovider analytics

Fraud analytics

Poor MedicaidData

PCMH – Collectdata from 30Sites (50% of members need tobe near PCMH)

% of physicians with inaccurate ZIP_CODE

% of physicians with null state license number,Medicare number, Medicaid number, DEA number

% of providers with incorrect address, phone number and email address (change in office manager)

% of providers with the correct information regardingqualified services they can provide

% of providers with missing Primary Care Physician(PCP) data related to Pay for Performance

Number of provider duplicates

% of providers with missing attributes that are using for matching (e.g., Date of Birth)

Number of providers who have been sanctioned but

now show up in a new group as a new provider (fraudanalytics)

% of physicians incorrectly mapped to the wrongphysician group

“We update physician credentials every three years.”

“The Medical Informatics team relies on accurate physician

data but the responsibility for keeping that data up-to-datefalls on the Network Management team.”

“We have a number of dead physicians in our network.”




Build a roadmap-sample roadmap based on initiatives




Balancing Information Strategywith just diving in and doing the hard work

Dead people in the system

Appropriate provider analytics - Medicare

Citizens with missing attributes such as date of birth

Current address of citizen- People move!!!

Speed to address state’s leadership teams queries




Information Governance Structure to support

continuous improvement

DefineService or Program

Opportunity

ObtainExecutive

Sponsorship

ConductMaturity

Assessment

BuildRoadmap

EstablishOrganization

Blueprint

BuildBusinessGlossary

UnderstandData

CreateMetadata

Repository

DefineMetrics

Govern

LifecycleManagement

Govern

Security &Privacy

Govern Analytics

MeasureResults

= Mandatory

= Optional

Govern


Govern DataQuality




Sustainable success turning structured data into insights has

required a focused Information Governance program

Info rmat ion pro cesses are managed as an

enab ler o f Strategic Ini t iat ives sim ilar to

Supply Chain p rocesses

People Process Technology




Information is not just back office IT databases but a SUPPLY CHAIN

Analyze

Integrate

Manage

ExternalInformationSources

Cubes

Streams

Big DataMaster

Data

Content

DataStructured &Unstructured

Streaming

Information

Quality

Security &Privacy

Lifecycle

Warehouse

Standards

Transactional& Collaborative Applications

Content

Information

Governance

ODS

Data Model

IBM Big Data Platform

SystemsManagement

ApplicationDevelopment

Visualization& Discovery

Accelerators

HadoopSystem

StreamComputing

DataWarehouse

Information Integration & Governance

Business Analytics Applications




Realizing new opportunities- Requires harnessing non-traditional data sources…

Transactional &

Application Data

Machine Data Social Data

Volume

• Structured

• Unstructured

• Throughput

Velocity

• Semi-structured

• Ingestion

Variety

• Highly unstructured

• Veracity

Publications

and Research

Variety

• Highly unstructured

• Volume




Comprehensive Vision for Integration & Governance

Internal App Data

DataWarehouse

TraditionalSources

Structured

Repeatable

Linear

Transaction Data

ERP data

Mainframe Data

OLTP System

Data

HadoopStreams

NewSources

Unstructured

Exploratory

Iterative

Web Logs

Social Data

Text & Images

Sensor Data

RFID

DataWarehouse

HadoopStreams

TraditionalSources

NewSources

InformationIntegration &Governance

17

D t E l ti d I f ti G




Find, visualize and

understand all big data to

improve business

knowledge

Shorter cycles to

sustainable InformationGovernance

• Greater efficiencies in

business processes

• Develop new business

models with resultingincreased market

presence and revenue

CM, RM, DM RDBMS Feeds Web 2.0 Email Web CRM, ERP File Systems

Connector Framework

App Builder

BigInsights

Integration & Governance

UI / User

Streams

Data Exploration and Information Governance-

Understanding your structured and unstructured data

WarehouseData Explorer

Eff i i d I t i I t t i I f t i L i f l




Current

Production

Historical

Retrieve

Retrieved

Universal Access to Application Data

Application Application XML ODBC / JDBC

Eff ic iency and Innovat ion- Investments in your Information L i fecycle

prov ide cost savings to support an imp roved Inform ation Supp ly Chain

Archives

Reporting

Data

Historical

DataReference

Data

Archive

Optim

Mashup

Archiving is an intelligent process for moving inactive or infrequentlyaccessed data that still has value , while providing the ability to search and

retrieve the data




Information Integration and Governance

Understand, Improve, and Act upon Insights from all your Data

Understand Improve Act

• Discover / profile data

• Determine usagepolicies

• Filter unnecessary databefore integrating

• Derive entity context

• Improve data quality

• Master data• Secure and protect

sensitive data• Manage data lifecycle

• Integrate data

• Information as a service• Define policies to share

and act upon insights

Understand databefore analyzing it

Trust and protectwith appropriate

governance levels

Integrate and act oninsights appropriately




Your Information Governance journey must expand to include

structured and unstructured data

Information IsUnderstood

Information isCorrect

Information is Current Information isSecure

Information isHolistic

Information is Shared




Foundational

• What happened?

• When and where?

• How much?

Advanced, Predictive

• What will happen?

• What will be the impact?

• Dashboards

• Clinical data repositories

• Departmental data marts

Data integration

Data warehouse

• Basic reporting

• Spreadsheets

Transaction

reporting

• Enterprise analytics

• Evidence-based medicine

• Outcomes analytics

Decision support

analytics

• Personalized services & care

• Engaged citizens

• Population behavior

Predictive

analytics

Cognitive

• What are potential scenarios?

• What is the best course?

• How can we pre-empt andmitigate the crisis?

22

The Journey to Turn Data into Insights-




Q & A


http://slidepdf.com/reader/full/data-governance-turning-data-into-insight-ken-jacquier 24/43© 2013 International Business Machines Corporation

THANK YOU




APPENDIX




INNOVATION

See speaker notes

Establishing a solid integrated unified IM platform




BI /Reporting

Exploration /Visualization

Functional App

Industry App

Predictive Analytics

Content Analytics

Analytic Applications

IBM Big Data Platform

Systems

Management

Application

Development

Visualization

& Discovery

Accelerators

Information Integration & Governance

HadoopSystem

StreamComputing

DataWarehouse

Volume, Variety

InfoSphere BigIns ights

QUERYABLE ARCHIVE

UNSTRUCTURED DATA

VelocityInfoSphere Streams

REAL-TIME

STREAMING ANALYTICS

VisibilityInfoSph ere Data Explo rer

DATA DISCOVERY

VolumeDW Appl iances

STRUCTURED DATA

ANALSIS

VeracityIBM InfoSphere

MATCHING, SECURING

DATA SETS

Identifying Patients-at-risk, Cost of Care, Govtmandatd metrics, Next

Best Action……

AcceleratorsData Models, Social andMachine Data

Establishing a solid, integrated, unified IM platform



28© 2013 International Business Machines Corporation28

Sample Master Data Governance Sco recard

Data Governance Metrics Goal Oct

2011

Sept

2011

Aug

2011

July

2011

June

2011

May2011

(Baseline)

1.Percentage of customer duplicates 5% 9% 10% 11% 12% 13% 14%

2.Percentage of non-validated emailaddresses

3% 4% 5% 7% 7% 8% 14%

3.Percentage of non-validated phone numbers 12% 12% 14%

15%

18%

21%

23%

4.Percentage of incorrect SSNs 8% 10% 10%

11% 11% 12%

15%

5.Percentage of non-validated mailing address 2% 6% 8% 12%

15%

18%

22%

Establish the Data

Governance baselineEstablish the critical data elements

with the Data Governance Council

Establish the Data Governance

acceptable threshold or goal with the

Data Governance Council

Report monthly progress to the Data Governance

Council. The Data Governance Lead should circulate

these metrics to the data stewards to monitor

ongoing performance.




Government L eaders Movin g to A ddress These Chal lenges

Optimized veteran claims

adjudication, single view of vet

Greatly enhance veterans care US Veterans

Administrat ion

Automated content extraction, entityresolution and analysis from seized

assets

Child Predator Investigation Western National

Law Enforcement

Connect the dots, predict and

prevent threatsProtect The Nation Department o f

Homeland Securi ty

Robust automated enterprise

financial reportingGreatly enhance budget

planning & Execution

US Missi le

Defense

Advanced citizen and benefits

analyticsGreatly enhance citizen service,

and improved outcomes US Medicare

Shared citizen data across multipledepartments, geographies

Greatly enhanced citizenservice, and improved Western European Gov’t Social




Social Services Smarter Service imperatives

“How can I ensure that limited

resources are going to thosewho qualify?”

• Provide analytics to improveeligibility determination and on-goingcase management

“How can I achieve better

outcomes by optimizing the

programs offered?”

• Gain insight into the impact of various programs and the mix of programs that are driving the greatestsuccess

“How can I make it easier for

our clients to interact with our

Agency?”

“How can I better job

detecting and deterring

fraudulent activities”

• Know who’s who and whoknows who

• Identify individuals sharinghouseholds

• Identify clients who do notmeet current eligibility rules.

“What tools can I use today to

help caseworkers prioritize and

manage workload”

• Provide a consolidated view of information about the client and family

• Provide alerts to focus the knowledgeworker on key activities that must becompleted.

• Provide multi-channel accessto client/program information• Have a common identifier torecognize the clients across allthe programs




Smarter Soc ial Services Delivery

Gain a HolisticView of Client &

Family

Improve Efficiency

ThroughStreamlined Case

Management

Reduce Fraud, Abuse and Errors

Measure, Monitor

and AnalyzePrograms

Performance and

Client Outcomes

Provides Social Services agencies with a means to improve effectivenesswhile at the same time reducing fraud and waste. The solution:-- Provides a holistic view of client and family-- Streamlines case management-- Reduces fraud, abuse, and errors-- Measures, monitors and analyzes program performance

Solution Definition

Aligns to Key Citizen Needs and Improves Agency Efficiency




Tax Agency Compliance Imperatives

“How do I simplify and enhance

the taxpayer experience?”

• Intelligent access to relevant taxcode, forms and “account “ status.

• Single view of taxpayer across allchannels and touchpoints

• Straightforward taxpayer service

“How do I reduce underpaymentand fraud?”

• Enhanced taxpayer guidancethrough statistical analysis

• Enhance identity and householdinganalysis

• Better information sharing acrossthe federal ecosystem (e.g, SSA)

“How do I optimize

collection & compliance”

• Business performancemanagement & executive

dashbaoaring

How do I improve my Audit efficiencyand effectiveness

• Predictive analytics to identify anomalousbehavior

• Identity resolution to identify who is who,and how knows who

• Base management for more efficientaudit adjudication




Clark County Family Services Increases Visibility, Productivity andCompliance

CCFS used IBM Business Analytics software to streamline case management andreporting practices, which increased visibility and productivity while improving its abilityto justify funding of targeted case management activities

“ In light of a fast -growing state populat ion and strugg l ing economic cl imate, we were able to not o nly boo st our qual i ty of serv ice, but also generate abou t $4 mi l l ion in new revenue. The IBM solut ion, wi th i ts abi l i ty to help ident i fy bot t lenecks and impro ve business proc esses, was inst rum ental in these successes – so m uch so that other coun ty depar tments are now implement ing the solution and mirroring our BI infrastructure.”

Eboni Washing ton, QA/QI Superv isor,

Fami ly Serv ices Department , Clark Coun ty




Audit Information Logging

and Reporting

Classification and Metadata(C&M)

Data Architecture

Data Quality Management

(DQM)

Data Risk Management

(DRM) and Compliance

Information Lifecycle

Management (ILM)

Information Security and

Privacy

Organizational Structures

and Awareness

Policy

Stewardship

Value Creation

Initial Repeatable Defined Managed Optimizing

Assess current state Determine future staterequired capabilities Develop roadmaps

Inform ation Governance for Government Agency

Priority




© 2013 IBM Corporation

Organizations rated their decision making as 7 or

higher on a scale of 1 to 10.

4 out of 5Organizations are improvingat 3 times the rate of

competitors.

3X Organizations show high or

very high levels of trust77%

Source: The Big Data Imperative: Why Information Governance Must Be Addressed Now, Aberdeen Group, Dec 2012

There is a Golden Opportunity – If We Govern Information




Information Integration and Governance Platform

Information Integration and Governance

Metadata, Business Glossary and Policy Management and Entity Analytics

Privacy &Security

DataLifecycle

Management

InformationIntegration


DataQuality

• Extract, Transform,Load

• Replicate• Federate

• Standardize

• Validate

• Verify• Enrich

• Match

• Master multipledomains

• Registry or transaction hub

• Collaborativelyauthor

• Govern master data

• Database Archiving

• Test data

management

• Activity monitoring

• Masking

• Encryption• Redaction

• Automated data discovery

• Enterprise metadata repository• Business terminology defined in business glossary

• Define, share and execute information governance policies

• Information Governance project blueprints

• Incremental context accumulation




Make decisions onuntrusted information1 in 3

60%

Don’t have necessaryinformation1 in 2

Time spent on project tounderstand information40%

Have more data than theycan use

60%

More Data, Less ConfidenceIncreasing Volume, Variety, and Velocity makes it harder to establish veracity




3838

To ensure the econom ic health, welfare and secu r i ty of th eir

citizens, smart governments are working to…

STRENGTHEN SECURITY AND PUBLIC SAFETY

Enabling defense and law enforcement organizationsto achieve situational awareness, increased speed of command and combat superiority.

MANAGE RESOURCESEFFECTIVELYLeveraging businessintelligence and planning toimprove insight and elevate

performance with visibility

and control.

IMPROVE CITIZEN ANDBUSINESS SERVICES

Connecting people to programs based on

individual needs—

achieving sustainableoutcomes while reducing

operational costs and maximizing taxpayer value.

ENSURE A SUSTAINABLEENVIRONMENT

Deploying environmentally responsible operations,

from energy efficiency and conservation to

transportationmanagement and the

pursuit of renewable resources.

GOVERNMENT




Puerto Rico Treasury Dept. (Hacienda)

Challenge

Solution

• Data intake was increasing 300% annually

• Storage Costs were getting out of control

• Application performance was beingdegraded by the processing the increasingamounts of data

IBM Optim Data Growth Solut ion

• Reduce Costs associated with Data Growth

• Improve performance of overworked productionapplications

• Store data in an immutable format for audit anddiscovery purposes

Saved $2 Million in storage and CPU costs bymoving data off of the primary processingenvironment

Allowed the Treasury Dept. to continuallyarchive data to deal with the 300% annual

increasesReduced the batch processing windows for

payroll and financial reporting, allowing criticaldeadlines to be met.

Benefits




Georgia Dept of Labor

Challenge

Solution

• Secure data associated with UnemploymentInsurance benefits in test/developmentenvironments

• Reduce the amount of storage required for testing

• Improve time to launch of applicationimprovements

IBM Optim Data Privacy Solut ion

IBM Optim Test Data Management Solution

• De-identify/mask data in non-productionenvironments

• Improve time-to-market for new/upgradedapplications

• Reduce storage costs in test/developmentenvironments

Risk of sensitive data loss from non-productiondata breach has been mitigated

Storage investments can be deferred due toreduction in space required to store test data.

Reduction in time/costs to fix errors found in

the development cycle.

Benefits

http://www.dol.state.ga.us/




Challenges

Criminal investigations were inaccurate and inefficientdue to information being spread across boroughs

Manually leverage existing investments in criminal investigations

Difficulty analyzing and synthesizing information

Inability to get information to the right people

Comprehensive Threat Prediction & Solution

IBM InfoSphere Entity Analytic Solutions, Global NameRecognition , Information Server

IBM Crime Information Warehouse

SPSS Predictive Analytics and Cognos Dashboarding

Benefits

Real time “Connect the Dots” investigative capability

Straightforward and intuitive visualization and link analysis

Sophisticated predictive analytics supports resource optimization

Crime analysts are able to spend time on proactive crime analysisrather then data manipulation

New York Police Department RTTC

Alameda County Social Services closes service gaps through better




“This is a tool that will tell us

where things really are and how

they are doing, every day.”

— Don Edwards, assistant

agency director,

Alameda County Social Services

y g p guse of information

Gaining a deeper insight into case and program status

The Need:

Faced with new regulations requiring better welfare case outcomes, AlamedaCounty Social Services needed to gain a better understanding of case status andprogram performance. It needed to give its caseworkers direct access toinformation about their own cases, at the individual case level, and needed faster and better reporting.

The Solution:

Alameda County engaged IBM to develop an information system that combinesentity analytics with business intelligence to give a comprehensive view of individual cases. Known as the Social Services Integrated Reporting System(SSIRS), this data warehouse allows the county to not only track benefitrecipients, but also recognize and understand the complex relationships betweenclients and programs.

What Makes it Smarter:

A near real-time view of cases gives workers deeper insight, enabling serviceflexibility, avoiding regulatory sanctions and saving money by reducing fraud andwaste – such as payment to individuals who are no longer eligible for assistance.

Enables direct savings of over US$11 million through waste reduction.

Generates reports in minutes instead of weeks or months – allowingcaseworkers to apply their expertise by trying “what if” scenarios.

http://www.alamedasocialservices.org/public/index.cfm



Information Integration & Governance Must Scale, Handle Complexityand be Adaptive

Scale to Handle the DataExplosion

• Integration performance andscalability

• Lifecycle management toretire data

• Automation and intelligence

Understand Data DespiteComplexity

• Rapidly understand data

• Business-drivengovernance

• Automatically derive context

Provide Agility for Faster Deployments

• Act with confidence oninsights

• Adaptive and alwaysavailable - capabilities

embedded in consuming app

Sources Consumers

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