GovLoop training analytics

Analytics to Outcomes:

Leveraging Predictive and Prescriptive

Analytics

September 8, 2011

Brought to you by:

https://www-950.ibm.com/events/wwe/grp/grp004.nsf/v16_enrollall?openform&seminar=ZC9PJZES&locale=en_US

Today’s Speakers

Steve ResslerPresident and FounderGovLoop

Christer JohnsonIBM Global Business Services, PartnerAdvanced Analytics Services Leader, N. America

Shaun BarryIBM Global Business Services, Associate PartnerGlobal Leader for Fraud Management Solutions

Housekeeping

o Twitter Hash Tag: #gltrain

o At any time during the next hour, if you would like to submit a question, just look for the "Ask a question" console. The presenters will field your questions at the end.

o If you have any technical difficulties during the Webinar, click on the Help button located below the slide window and you’ll receive technical assistance.

o And finally, after this session is complete, we will be e-mailing you a link to the archived version of this Webinar, so you can view it again or share it with a colleague and a GovLoop training certificate.

IBM Advanced Analytics Software

4

Analytics to Outcomes:

Leveraging Predictive and Prescriptive Analytics

September 8, 2011

Christer Johnson

IBM Global Business Services, Partner

Advanced Analytics Services Leader, N. America

Shaun Barry

IBM Global Business Services, Associate Partner

Global Leader for Fraud Management Solutions

IBM Advanced Analytics & Optimization

5

Captured

Detected

Inferred

What types of questions do we try to solve with Advanced Analytics?

Use Structured Data &

Unstructured Data

Descriptive

Analytics

Prescriptive

Analytics

Predictive

Analytics

Simplified to be

consumable and

accessible to everyone,

optimized for their

specific purpose, at the

point of impact, to

deliver better decisions

and actions through:

What

trends will

continue?

Forecasting

How can we

achieve the best

outcome and

address variability?

Stochastic

Optimization

What

happened?

What

exactly is

the

problem?

How many,

how often,

where?

What

actions are

needed?

What could

happen if?

Simulation

How can we

achieve the best

outcome?

Optimization

What will

happen

next if?

Predictive

Modelling

Analytics Sophistication

• Numeric

• Text

• Image

• Audio

• Video

http://www.spss.com/


6

Three Areas of Benefit for Analytics Solutions

Data Infrastructure ProductivityTake-out cost and improve efficiency

Analytics Simplification / BAO Foundation

Government EfficiencyImprove control, bottomline and stop losses

Finance / Risk / Fraud Analytics

Supply Chain / Operational Analytics

Government Responsiveness Better service citizens needs

Human CapitalAnalytics

Citizen ServiceAnalytics


7











8

Veterans Administration (VA)

Agent Orange Fast Track Claims Processing System

Background

Second largest federal agency

supporting our nation’s veterans

500,000 staff, and 15,000 paper

claims processors

58 Regional Office processing

centers

Solution

Fast Track is comprised of:

–An external website which both Veterans and

Medical Providers access to support information

or evidence to a claim.

–An internal VA FileNet system where users can

process these disability claims.

–An IBM scanning facility in Rocket Center, WV

where hardcopies can be digitized and included

with the Veteran‟s claim and supporting

evidence.

Benefits and Results

System up and running in 120 days

34,000 claims (150,000 documents)

processed through the Fast Track system

Reduced the VA end-to-end claim processing

time without decreasing the quality and

consistency of the program via Fast Track

electronic claims

Veterans have 24x7 online access to the

status of their claims and now have a much

less complex application process

Challenges

VA has a large disability benefits paper claims

backlog that continues to grow, even with 15,000

people manually processing.

Needed a way to quickly process Agent Orange

related claims

“…we have to get beyond just sort of the brute-force

approach to this and … get better business

processes, automation in place.” -General Eric

Shinseki, VA Secretary 5/14/10


99

Current State: “I have an offer – let me find a customer to sell to”

They don’t really know me -Customers are offered products that may feel irrelevant and disconnected vs. solutions

Mass Market

Mass Affluent

Small Business

“You do not know me & ask me multiple times about the same thing.”

“I use Large US Bank for convenience but primarily use another bank. “

“The Bank doesn’t understand me, my industry or my business. “

The Bank’s associates can’t address all of my business needs

Offer

Offer

Offer

Direct Mail

BC

Agent, IVR

Online, Email

ATM

Mobile, SMS

Chat

Relevance?Awareness?

Value?Understanding?

Clarity?

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

Offer

DEPOSITS

INVESTMEN

TS

MORTGAGE

CARD

Cu

sto

me

r N

ee

ds

& S

egm

en

t St

rate

gie

s

Mas

s M

arke

t |

M

ass

Aff

luen

t |

Sm

all B

usi

nes

sA Large US Bank

http://images.google.com/imgres?imgurl=http://www.faqs.org/photo-dict/photofiles/list/436/808envelope.jpg&imgrefurl=http://www.faqs.org/photo-dict/phrase/436/envelope.html&usg=__pz26vaK0QcU3xv3xLOli3eJXMos=&h=490&w=700&sz=22&hl=en&start=23&um=1&tbnid=TBisPhNZPRHPbM:&tbnh=98&tbnw=140&prev=/images?q=envelope&ndsp=18&hl=en&sa=N&start=18&um=1


1010

Direct Mail

BC

Agent, IVR

Online, Email

ATM

Mobile, SMS

Chat

Brilliant!

Target Vision: “I have a customer – what do they need most?”

“The bank knows me and values my relationship“

“They seem to know what I need and when I need it.”

“The bank isn’t always selling something.”

“They always get me to the right place and never fail to follow up.”

“There is real value to me in getting all my needs met by one bank.”

CIM

Governance,

Prioritization

&

Optimization

Customer Analytics

Integrated Data

DEPOSITS

INVESTMENTS

MORTGAGE

CARD

Cu

sto

me

r N

ee

ds

& S

egm

en

t St

rate

gie

s

Mas

s M

arke

t |

M

ass

Aff

luen

t |

Sm

all B

usi

nes

s

Customer

Experience &

Treatment

Strategies

A Large US Bank

http://images.google.com/imgres?imgurl=http://www.faqs.org/photo-dict/photofiles/list/436/808envelope.jpg&imgrefurl=http://www.faqs.org/photo-dict/phrase/436/envelope.html&usg=__pz26vaK0QcU3xv3xLOli3eJXMos=&h=490&w=700&sz=22&hl=en&start=23&um=1&tbnid=TBisPhNZPRHPbM:&tbnh=98&tbnw=140&prev=/images?q=envelope&ndsp=18&hl=en&sa=N&start=18&um=1


11











Real-Time Pattern Recognition of Streaming Data in a Neo-Natal Unit (Toronto Hospital)


13

Transforming Education – Gwinnett County Public Schools

Client Gwinnett County Public Schools (GCPS)

Industry Education

Challenge Education delivery has traditionally been „brick and mortar‟ classrooms and

instruction by textbook. Typically student challenges are identified after they

occur. GCPS‟ vision is to identify student challenges and opportunities for

improvement before they occur – applying the appropriate interventions or

enrichment to enhance learning for each student.

Solution For a pilot student population, IBM developed a model to identify factors that

potentially predict a student‟s success in Algebra. These predictors were used to

determine „at-risk‟ student groups, and thus assist educators in determining the

remediation and/or instructional guidance for different student populations.

Benefits The results of the analytical model convinced GCPS to expand the scope to

ensure integration of predictive analytics into the future teaching and learning

model for the school system. In addition, with the integration of appropriate

instructional content, GCPS has embarked on a path toward differentiated and

focused student instruction based on student needs – potentially before the

needs are identified. The goal is to enhance student learning and ultimately

improve student achievement.


14

North Carolina Medicaid – Fraud and Overpayment Detection

Client State of North Carolina

Industry Government

Challenge The current business process and technology used to fight fraud,

waste, and abuse in Medicaid is ineffective – producing only around

$25 million annually in recoupment letters. This leakage, combined

with a significant state budget deficit, motivated the state to

aggressively pursue cost takeout projects.

Solution The state implemented a comprehensive fraud analytics solution,

based on IBM technologies. The IBM solution examines claims for

suspicious patterns of behavior, and it identifies organized criminal

rings and collusive behaviors.

Benefits $75 million in recoupment letters issued in first 12 months


15

An example of how this analysis works

SCHEME – Services Not Rendered


16


SCHEME – Pop-up Provider/Storefront Scheme


17


SCHEME – Doctor Shopping


18

IBM‟s fraud analytics solutions. Our solution applies

business rules and predictive models to categorize and score

returns nightly and identifies the „next best case‟ for audit

selection. In addition, a separate web based portal provides

screening and resolution of cases.

Solution

Benefits

Challenge New York wanted to enhance current audit case selection

methods for detection of audit issues at the time a return is

processed. Specific audit programs include Earned Income

Credit, Dependent Child Care Credit, Itemized Deductions,

Wage/Withholding, and Identity Theft.

$1.6 billion increase in refund denials

Increased screener and auditor productivity

“Honest” taxpayers have refunds quickly processed with less

hassle

Lessons

Learned

Real-time analytics are complex but provide great benefit

Benefits can be gained without substantial increase in staff

Don‟t believe the “we‟re already doing that” argument

Having an aggressive Business Champion is essential

State of New York – Income Tax Refund Fraud


19

Aetna – Medical Cost Trend Analysis

Client Aetna

Industry Healthcare

Challenge With the goal to better manage medical cost, Aetna wanted to enhance

its capability to identify and diagnose changes or patterns in cost

trends in a more automated and timely basis.

Solution For a pilot set of data, IBM built a multiplicative regression model that

can simultaneously evaluate the impact that all possible factors have

on changes to overall medical costs.

Used optimization to determine the best fit regression model.

Benefits While only in pilot, the results of the model were enough to convince

Aetna to expand the scope of the model and pursue a path towards

implementing the model as part of their ongoing cost trending analysis

http://www.aetna.com/


20


$ Cost Impact

of Factor 1 =

$60

$ Cost

Impact of

Factor 2 =

$30

Let‟s say that:

2008 Cost = $100 and 2009 Cost = $180



21


Let‟s say that: 2008 Cost = $100 and 2009 Cost = $180

Factor 2 Individual Cost

Impact = $30

Total Cost Impact of Factor 1 & Factor 2

Combined

Cost Impact

$10

Factor 1

remaining impact,

with Factor 2

removed

$50

Factor 2

remaining

impact, with

Factor 1

removed

$20

Factor 1 Individual Cost

Impact = $60



22

Network Modelling and Optimization at USPS

Developed optimization and simulation models

(NIA) used to design future network structure

Developing a transportation optimization and

planning system (TOPS) to improve utilization

and reduce costs of the USPS‟s transportation

network

Benefits to the Client

– Estimated operational savings of 10- 20 percent

– Better understanding of excess capacity

• Node Optimization

• Route Plans & Schedules

• Routing Decision Rules

• Dispatch & Routing Execution (SAMS)

• Track & Trace Visibility (SASS)

(NIA)

Strategic

Tactical (TOPS)

Operational

Statistics Economics

Optimization

Simulation

Discrete-Event

Data Mining / Data Analysis

Estimating actual mail flows

Cost / Benefit Analysis

Econometrics

Micro Economics

Operations

Research


23

USPS Highway Corridor Analytical Program

Client U.S. Postal Service (USPS)

Challenge Needed to identify quick-hit savings for the plant to plant transportation

for a region of the country by increasing utilization on each truck.

Solution Built an optimization model using ILOG CPLEX to evaluate

transportation between approximately 20 sorting centers. HCAP was

designed as a transportation optimizer to identify opportunities to

consolidate USPS highway transportation in order to save costs.

Complex data mining and predictive analytics were required to

estimate mail volume flows.

Benefits Within the first year of implementation, USPS realized transportation

cost savings that resulted in a 400% return on investment.


24







Citizen SerivceAnalytics




25

Number of Recipients:

Total benefits:

Administrative costs:

12.4 Million

$105 Billion

$5 Billion

Background – U.S. Social Security Administration (SSA)


26

Initial

Application Reconsideration Hearing AppealsFederal

District Court

Level 1 Level 3 Level 4 Level 5Level 2

Up to 5 years

738,000

cases in

backlog

97 days to 17 months

Historically - Lengthy Disability Approval Process


27

All

Applications

Scoring

Model:

Is Applicant

Clearly

Disabled?

QDD Unit

Decision and

benefits in 11

days

Not Clearly

Disabled

Normal

Adjudication

and

application

levels

Decision: 97

days on

average, up

to 5 years

• Request additional

medical records

• Request medical

examination

Quick Disability Determination (QDD) – an new process

• SSA conceived of a new

process

• Create a centralized

team for expedited

review of cases

• Automatically send

workload to this group

Clearly

Disabled


28

The Specific Algorithms Used for QDD

Two were needed:

Robust Risk Minimizer

(RRM)

Misspelled Vocabulary

Correction (MVC)

• Analysis tool that “reads” the

text from the allegations field

and numeric data found on

the application

• Computes the probability of

being a QUICK DECISION

• Example of a Probabilistic

Classifier

• Essentially a spell checker

• Ensures the RRM does not

use the two or more different

spellings of the same

impairment as if they were

totally different impairments


29

Social Security Administration – Disability Benefits

Has reduced the cycle time to process 10% of applications for disability from:

97 days to 20 days

Has used predictive

modeling to save

$2 billion in disability

benefit renewal costs

since 2000.


30

Federal Housing Administration – Insurance Pricing

Client FHA

Industry Government Agency: Mortgage Finance

Challenge To accommodate the growing baby boomer population and changes in

the housing market, Federal Housing Administration (FHA) re-analyzed

the reverse mortgage (HECM) design and pricing structure to better

align insurance prices to the current conditions.

Solution IBM developed a simulation model for mortgage loan performance of

various premium structures. Then, IBM integrated the simulation with

an optimization algorithm to determine the optimal pricing structure.

IBM also leveraged grid-computing technology to boost computation

power and complete the re-pricing effort in a timely manner

Benefits FHA used the model to determine an array of insurance pricing and

risk management options to lower front-end insurance cost for the

borrowers, increasing the program‟s attractiveness to new enrollees. It

also strengthened the financial soundness of the program, allowing

HECM to maintain as a risk-neutral program in the volatile market

environment.


3131

Age +Income +

Geography

Best Buy Case Study: Segmentation Approach

Preferred Product

CategoriesPreferred Channel

Participation in Loyalty

ProgramUse of In-

House Credit Card

Use of Service Programs

Return / Exchange Behavior

Breadth of Categories Shopped

Length of Time as

Customer

Recency + Frequency +

Value

Response to Media

Time until Repurchase

in Key Categories

Annual Spend Level

Annual Transactions

Econometric: Real-estate &

Unemployment

• Start with 30-40 modeled variables – “Feature Vectors” – The customers response to the firm‟s value proposition

• Each feature vector is like a gene strand, which describes a facet, or set of customer behavior traits

Most segmentation approaches only

focus here


32

A Major Health Insurer: Customer Analytics

Industry Healthcare

Challenge With the changing in healthcare environment, the Payer is transforming

its traditional group-based engagement approach to a more consumer-

centric engagement approach.

Solution Leveraging predictive and customer analytics, IBM developed several

analytical models to extract key consumer insights for every customer,

including health insurance status, channel preferences, education needs.

Benefits Data-driven approach played a critical role in new customer engagement

strategy and enabled a more personalized and relevant consumer

engagement experience. Specifically:

– Insights into prospects‟ health insurance status enable a more targeted and

effective acquisition approach

– Insights into consumer‟s channel preference enable Payer to engage prospect

and members in the most effective channel for different messaging context

– Insights into members‟ education needs enable Payer to help member to

understand plan value and promote wellness, building trust and loyalty.


33

How to get started

Pick your spot

Roll it out over time

Prove the value

Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute of Business Value study. Copyright ©

Massachusetts Institute of Technology 2010.

Biggest and highest value opportunity

Start with questions Embed insights

Add capabilities Information agenda


34

Next Steps

Join the IBM GovLoop User Group Today:

Analytics to Outcomes

For those in the Washington D.C. area on September 15th join us for a complementary

analytics event:

Time: 7:30 a.m.-9:30 a.m.

Venue: Ronald Reagan Building ~ The Rotunda, 8th Floor (North Tower)

1300 Pennsylvania Avenue, NW, Washington, DC

To Register:

"Tough Choices, Hard Numbers: How Does Your Agency Cut Costs Without Losing Effectiveness?"

http://www.govloop.com/group/analyticstooutcomes

http://www.govexec.com/executiveevent/

http://www.govexec.com/executiveevent/

Audience Q&A

Today’s Speakers

Steve ResslerPresident and FounderGovLoop

Christer JohnsonIBM Global Business Services, PartnerAdvanced Analytics Services Leader, N. America

Shaun BarryIBM Global Business Services, Associate PartnerGlobal Leader for Fraud Management Solutions

Thank You!