rapa 2004 oct_six_sigma_in_insurance

Six Sigma in the Insurance Industry

Kevin DarterGE Insurance SolutionsUS A&H

New Orleans October 18, 2004

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June 7, 2004

What is Six Sigma?

• What is six sigma?• Customers• Defects• Data & Analysis• Six sigma leadership• Q&A/Discussion

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June 7, 2004

• Measure of Quality

• Process For Continuous Improvement

• Enabler for Culture Change

What is Six Sigma?

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June 7, 2004

A Measure of Quality

6 Sigma 6 Sigma Lingo Lingo Unit : Each Measurement Unit : Each Measurement

(Claim Booking, Policy, (Claim Booking, Policy, Check)Check)Defect : Measurement out Defect : Measurement out of Specof SpecDefect Opportunities per Defect Opportunities per Unit : 1Unit : 1

Quality expressed as Quality expressed as DPMODPMO

( Defects per Million ( Defects per Million Opportunities)Opportunities)

UpperSpecification

Limit

Lower Specification

Limit

Spec StandardSigma DPMO %Width Deviation Level In Spec 100 25 2 308,500 69.1

66

100 17 3 66,800 93.3 100 12 4 6,200 99.4 100 10 5 233 99.98 100 8 6 3 99.9997

UpperSpecification

Limit

Lower Specification

Limit

22

What is Six Sigma?

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June 7, 2004

Process Capability needs to be Better than you think ! ActivityActivity Defects @ 99% Defects @ 99% Defects @ Defects @

99.9997%99.9997% ( 3.8 Sigma ) ( 3.8 Sigma ) ( 6 Sigma ( 6 Sigma

)) Mail 20,000 lost articles 7 lost articles Delivery of mail per hour of mail per hour Drinking Unsafe drinking water Unsafe drinking water Water for 15 mins per day for 2 mins per year Hospital 5000 incorrect 2 incorrect Surgery procedures per week procedures per week Air 2 abnormal landings 1 abnormal landing Travel at most airports each day every 5 yearsSometimes 99% is just not good enough

What is Six Sigma?

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June 7, 2004

Process For Continuous Improvement Process For Continuous Improvement

What is Six Sigma?

•6 Sigma provides a process based approachto continuous improvement.

•It is independent of the measurement involved

•can be used to improve any business process

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Enabler for Cultural Change

What is Six Sigma?

•To be successful, 6 Sigma requires a radical change in the way an organization works.

•Business Leadership and 6 Sigma can together transform a company

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June 7, 2004

Fundamentally Different Approach

Enabler for Change

Before6 Sigma:

1) Inspect the product2) List the symptoms perceived as being the cause of the problem3) Initiate action to mitigate / eliminate the symptoms

1) Inspect the product2) List the symptoms perceived as being the cause of the problem3) Initiate action to mitigate / eliminate the symptoms

With6 Sigma :

1) Measure the process output & analyze the data2) Discover quantitative relationships between the output & in-process variables3) Develop & implement control plan

1) Measure the process output & analyze the data2) Discover quantitative relationships between the output & in-process variables3) Develop & implement control plan

Tough to achieve long-term sustainable improvement

Sustainable via In-process Control - no Product Inspection

What is Six Sigma?

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June 7, 2004

Customers


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June 7, 2004

Positively impact customers with Six Sigma by improving our processes, products, and

services

Customers

Completely Satisfying Customer Needs Profitably

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June 7, 2004

The FocusThe focus for 6s quality is characterized by a continuous and thorough understanding of our customer. We need to ensure our customers feel and see the benefits of 6s quality

CustomerWhat does my customer

need from our process?

How is our process

performance from the customer

perspective?

How does my customer

measure my process?

How would my customer like for our process to perform?

What can we do better?

How does my customer view my process?

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June 7, 2004

IdentifyCustomers

Voice Of TheCustomer (VOC)

Determine CTQs

A Process To Identify Customers And Understand Their CTQs

List customers

Define customer segments

Narrow list

Organize all customer data

Translate VOC to specific needs

Define CTQs for needs

Prioritize CTQs

Contain problem if necessary

Review existing VOC data

Decide what to collect/ select VOC tools

Collect data

Steps To Determining CTQs

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June 7, 2004

Quality Starts with the Customer

What are CTQs

•Fast Renewal Quotes •Renewal quote in customer’s hands within eight working hours

•Accurate Invoices •Customer data on invoice matches current coverage document, field by field

CTQs are specific and measurable requirements taken directly from our customers — Not what we think our

customers want or need

Customer Needs(What they say)

CTQs(What they mean)

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June 7, 2004


Improve our products, processes and services from our customers’ standpoint - drives metrics

Provide a common language regarding customer requirements throughout the company

Create a differentiation in the marketplace

Why CTQs are important

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June 7, 2004

How we use them

CTQs are gathered directly from customers:

- Customer meetings- Surveys- Scorecards, dashboards

CTQs are the input of every cockpit and drive the performance of those cockpit metrics

CTQs are at the front end of every Six Sigma project

CTQs are concise, clearly defined, and easily understandable


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June 7, 2004

Customers Project ExampleNew Customers

Setup

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June 7, 2004

Business Case / Business Y: Big Y – Find to Issue. Priorities – Customer Relationships, Electronic Data Capture

Problem Statement: Critical Illness does not have a customer set up process - leading to lack of confidence in our ability to effectively manage our strategic customer relationships based on agreed-to processes. As we target significant growth in this business, we need a process to effectively manage our customer relationships and obtain marketing data about these customers. We need a cohesive customer set up strategy that facilitates data sharing among functions….reducing the amount of time that is spent fighting fires due to lack of coordination.

Goal Statement: Establish a Customer Set up Process that optimizes how we work with our clients. 1. Reduce Future Customer Pain … Enhance Client Experience. 2. Ensure Client & ERC Both Understand Data Needs Through Relationship and all parties have the required data to monitor the account effectively. 3. Ensure all functional areas and parties understand the intent of treaty and the relationship

Project Scope:

Start: when customer (cedent) indicates acceptance of a quote. Stop: once a document of understanding has been presented and acknowledged by customer (cedent)Includes: GLH A&H U.S. Critical Illness, Process and documentation for customer set up, Definition of customer set up elements as they relate to the treaty, A “service agreement” between the customer and GE ERC, Changes to existing agreementsExcludes: Establishing a Customer Database / CRM system, Consistency of reserving, financial reporting, etc. , Actual execution of the treaty, Other A&H businesses

Project Team:• Project Leader…Champion…Sponsor… Mentor…Team Members

Stakeholder(s):• External Customers – Critical Illness Customers and Prospects• Internal Customers – All Functions impacted by customer set up process• Shareholders - US A&H senior management

Project CTQs

-Level 1: Creation of Service Agreement / Communication Plan for Relationship

-Level 2: Accurate, Timely and Complete

-Level 3: Data in Service Agreement = Agreed to Terms and Relationship Parameters, 100% of ‘Fields’ in Service Agreement are Complete, Services Agreement is Signed Prior to First Sale/Deal, Communication Plan is Developed Prior to First Sale/Deal, 100% of Communication Plan has been completed

CDFSS Define Summary

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June 7, 2004

VOC Collection Forms and Examples

•Survey to identified stakeholders – 16 completed surveys representing Sales & Marketing, Underwriting, Claims, Legal, Product Managers and IT.

•One-on-One Functional Interviews

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June 7, 2004

COPIS

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June 7, 2004

CTQ Drill Down Tree

Level 2: Accurate

New Customer Set Up Process

Level 1 CTQ: Creation of Service Agreement

Level 1 CTQ: Communication Plan for Relationship

Level 2: Timely Level 2: Timely Level 2: Complete

Level 2: Complete

Level 3: Data in Service Agreement = Agreed to Terms and Relationship Parameters and is in line with Treaty data

Level 3: 100% of ‘Fields’ in Service Agreement are Complete

Level 3: Services Agreement is Signed Prior to First Sale/Deal

Level 3: Communication Plan is Developed Prior to First Sale/Deal

Level 3: 100% of Communication Plan has been completed

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June 7, 2004

QFD Process and Results New Customer Setup Project

Product Requirement

Customer Expectation

Import

ance

Pro

cess f

or

treaty

agre

em

ent

Clie

nt

agre

em

ent

to t

reaty

and p

rocess

Custo

mer

ow

ner

assig

nm

ent

pro

cess

Tota

l

Receive all expected data 5 H 45Service agreement signed prior to first sale/deal5 H H 90Communication plan completed 5 H L 50Communication plan developed prior to first sale/deal5 H L 50An owner identified for each customer 4 H 36Data collection process needs to be established – including timeliness5 H H 90Overall reporting process communicated - monthly reports, timing, what is included, completeness5 H H 90Operational definitions around reporting process4 H M 48

Total 261 202 36

QFD Controls

View Total View Results

Create Next House

Sort QFD

CTQ Flowback X

CTQ Flowdown YClear

High

Low

Medium

Partition QFD

6-Piece Pareto

View Zero Importance Items

0 50 100 150 200 250 300

Process for treaty agreement

Client agreement to treaty andprocess

Customer owner assignmentprocess

New Customer Setup Project Pareto

3 main product requirements will satisfy all customer expectations

All 3 requirements will be met by the new process solution

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June 7, 2004

Defects


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June 7, 2004

A defect is any event that does not meet the specification of a CTQ

My quote was two days late!

This policy is missing my endorsement!

This deal is three points below our pricing target!

This quote will not be bound!

We Feel CTQ Problems Every Day!!

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June 7, 2004

Do You Understand Your Processes?

Are your processes mapped?Do your processes have performance metrics?Do you know your current performance levels?

If you don’t, how do you know what defects your Quality projects are eliminating?

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June 7, 2004

What is a Defect?

It is NOT DONE.

It is DONE WRONG.

It is DONE LATE!

Recognizing a defect is the first step toward improvement

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June 7, 2004

Questions for Leaders

Six Sigma is all about eliminating defects

Are my projects clustered around dramatically reducing my critical process defects?

Have I begun to focus my resources on these projects?

Will my customers really feel the improvements from my Quality efforts?

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June 7, 2004

"A problem well stated is a problem half solved.“

Charles F. Kettering

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June 7, 2004

Data & Analysis


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June 7, 2004

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June 7, 2004

Analysis Project ExampleCDT Loading

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June 7, 2004Accurate, Timely Data LoadAccurate, Timely Data Load

Problem Statement:

Project Team:

Define Summary

Goal Statement:

Customer:

Project Scope:

Business Case / Business Y:

CTQs:

Project Timeline: Start Date End Date Actual Date Define 01-MAY-01 01-MAY-01 01-MAY-01

Measure 01-MAY-01 12-MAY-01 29-MAY-01

Analyze 12-MAY-01 22-MAY-01 14-JUN-01

Improve 22-MAY-01 20-JUN-01 10-AUG-01

Control 20-JUN-01 30-JUN-01 15-AUG-01

Project Leader: Tami Moran

Champion: Bob Buckner

Sponsor: Tami Moran

Mentor: Kevin Darter

Team Members: Karen Santi, Beth Brink, Chip Thomas

US CDT Loading

Reduce total elapsed time to process a CDT file to 24 hours

Scope is limited to the process loading, and repairing errors in cession data for mapped companies. The process starts with the file load process for CDT and ends when the transactions/cessions are available in the production database.

Baseline data indicates it takes a median of 96 elapsed hours to load a transaction file. At current staffing levels and process capacity, the backlog for the 66 CDT customers currently mapped would never be eliminated.

• Actuary: Accurate, complete data on key clients monthly

• Admin: CDT Data loaded within 24 hours of receipt of media

• Claims: Access to cession level information on claims & retro

• Pricing: Access to development & mortality data by company

• Actuary: Experience Analysis & Reserving

• Admin: Customer fulfillment and billing & collections

• Claims: Claim payment and retrocession collection

• Pricing: New business pricing and analysis

Productivity: CDT data has a potential fiscal benefit of $5MM annually, this benefit cannot be realized until the data supplied by clients can be loaded for analysis. Loading data enables all subsequent cession level analysis.

Scope: Load CDT File

ReceiveFile

Extract from Media

ScrubFile

Load toStaging

Resolve Errors

Verify Premium

Load to Production

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June 7, 2004Good Reliability in Measurement…Highly Variable ProcessGood Reliability in Measurement…Highly Variable Process

Measure Summary Project Y & Performance Specifications: Data Collection Highlights:

Data Display: Process Metrics:

MSA Results

US CDT LoadingUnit: In-force or Transaction data file for a

Legal Entity (ERC Co #)

Opportunity: In-force or Transaction data file for a Legal Entity (ERC Co #)

Defect: Total Load time >24 hours

Perf Spec: Time elapsed from start of load data to the time it is completely loaded into production--24 hours

• Collected data on 100% of CDT files loaded from January to May (n=170 total population).

• Baseline Period Jan through March

• Manual Collection using Access (X’s & Y’s)

• Automated Collection of Y’s using DB2

• Passed one-way ANOVA Gage R&R (sample data) with less than 5% variation attributed to measurement

65050035020050

95% Confidence Interval for Mu

9585756555453525

95% Confidence Interval for Median

Variable: TAT_Hrs_Tota

28.000

101.166

55.853

Maximum3rd QuartileMedian1st QuartileMinimum

NKurtosisSkewnessVarianceStDevMean

P-Value:A-Squared:

48.494

125.286

89.747

724.000 79.500 44.000 23.000 1.000

17017.35743.9135112529.1111.934 72.800

0.00021.933


95% Confidence Interval for Sigma


Anderson-Darling Normality Test

Descriptive Statistics

Right Skewed distribution- use median for central tendency

Data is not Normal

Variable N Mean Median TrMean StDev SE MeanTAT_Hrs_ 170 72.80 44.00 53.77 111.93 8.58

Variable Minimum Maximum Q1 Q3TAT_Hrs_ 1.00 724.00 23.00 79.50

Large StandardDeviation--High variation

Date SPAN Mdn DPMO (Hours)

Baseline Performance 06/JUN/01 263 96 670,588 1.0

Target Performance 30/MAY/01 24 12 67,000 3.0

Current Performance 15/AUG/01 60 16 222,222 2.3

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June 7, 2004

“Staging Load Failures” is the Focus of Improvement Efforts. Client Group and Admin

System Results Show that Successive Loads Get Faster and Have Fewer Errors.

•Central Tendency Test:

Mood Mdn: p=0.489

•Variation Test: HOV: p=0.003

•Group analysis more meaningful than company # because client sends single file

•As we get more experience loading a company’s files, we get more consistent (i.e., Kemper vs. 1st Penn))

Total TAT

Staging Load Failure

Analyze Summary

US CDT Loading

Admin System

Fix Records Issue

# Records Loaded

# Error Records

Grouped for Processing

Client Group


Mood Mdn: p=0.165


•No significant differences between grouped and not grouped company files


Mood Mdn: p=0.000


•If a file fails in the initial load, both the central tendency and the spread are higher


Mood Mdn: p=0.449


•greatest spread is TAI 1.09. Only used by 1st Penn…could be the Co or the system.


Mood Mdn: p=0.003


•Correlation:to Total TAT r = 0.30to Stage Load r=0.21to Migrate r = 0.03

•Team expected a strong relationship b/w # records and times.

•Other factors have a stronger influence on TAT

•Other X’s Considered but no Significant Findings:

•ERC Company•Manual Vs. Automatic Data Load•Client Company Number

•Correlation:to Total TAT r=0.10to Fix r=0.14

•Team expected a strong relationship b/w # errors and time to fix.

•Other factors have a stronger influence on TAT

•Regression:Total Records & Total ErrorsR-Sq(adj) = 8.2%

•Overall not a valuable predictor of Total TAT.

• Correlation b/w order processed and Load time r= (0.31) Slightly better predictor than # records.

•Correlation:Total TAT & Load TAT r = 0.78Total TAT & Fix TAT r= 0.41Total TAT & Migrate r= 0.47

•Load Time more predictive of overall TAT than Fix…Focus improvements there.

Wait time is 92% of TAT

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June 7, 2004

Appendix - Measure

What causes CDT file load totake more time?

Methods Materials

Machines EnvironmentPeople

Primary Cause

Auto ScriptLoad Fails

File loaded to wrongERC CompanyManual Load

Files in Hartford

Do Not HaveMetrics on Load

Auto Script doesnot Pick up File

Auto ScriptLoad Fails

Data map is wrong

Chg to programcreate error

Source Layout is wrong

Server Down

File Manuallyloaded

Change in source file

Script altered with no change in source

Maps are re-typed by programmersUse wrong Maps (multiple copies)

Revert toprevious

code

Code changeimplemented

too early

High # errors in SourceFile cause reload of file

File loadedmultiple times

Source File format Changes

Client added treaty codes

Error in data map

Client data error prone (Admin system)

Can't Move Fileto Ops Tbls

Linked to otherco not ready to

move

No response fromescalation of issue

No backup for Gail Hartford file moves are slow

Move files acrossWAN

Mail Cartridges to OP

Hartford does not havecartridge reader

Fewer Resources on CDT

CDT Volume

Other Responsibilities

Linked company file is readmultiple times (PHL-Kemper)

Autoscript set to read multiple times

Reloading and didnot delete old data

Auto load script failure readingsame data multiple times

No edit preventingmultiple load of same

co/fmonth

Look at Load Failures as Possible XLook at Load Failures as Possible X

Process Analysis--Load to Staging Root Causes

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June 7, 2004

Appendix - AnalyzeData Analysis Plan--Descriptive

Histogram

Boxplot

Scatter Diagram

• Distribution of Total Y (10 hr Bins)• Distribution by Company• Distribution by Admin System• Distribution by ERC Company (Location)• Distribution by File Type (Inforce or Transaction)

• # Records by Total Cycle Time (Stratify by Company)• # Records by Load to Stage Time (Stratify by Company)• # Records by Load to Production (Stratify by Company)• # Errors by Total Cycle Time• # Errors by Fix Time (Stratify by Company)

• Total TAT by Client Co.• Total TAT by ERC Co (Location)• Total TAT by Admin System• Total TAT by Load Errors

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June 7, 2004

Appendix - AnalyzeData Analysis Plan--Continuous X’s

Y = Time to Load File to Production

y = Load to Stg. y = Fix y = Load to Prod.

# Records

# Errors

Continuous X’s

Continuous Y’s

Ho: rxy= 0Test:correlation, regressionStrat: Company, Grouped

Ho: rxy= 0Test:correlation, regressionStrat: Company, Grouped

# Records

# Errors

Ho: rxy= 0Test:correlationStrat: Company, Grouped

Ho: rxy= 0Test:correlationStrat:Company, Grouped

Ho: rxy= 0Test:correlationStrat: Company, Grouped

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June 7, 2004

Appendix - AnalyzeData Analysis Plan--Discrete X’s

Y = Time to Load File to Production

y = Load to Stg. y = Fix y = Load to Prod.

Client Co.

Grouped

ERC Co

Discrete X’s

Mapping Error

Reload File

Matrix Chg.

Admin System

Continuous Y’s

Ho: x1= x2 = x3 ...Test:ANOVAStrat:

Ho: x1= x2

Test: MoodsStrat:

Ho: s1= s2

Test:HOVStrat:

Ho: x1= x2

Test: MoodsStrat:

Ho: s1= s2

Test:HOVStrat:

Ho: x1= x2

Test: MoodsStrat:

Ho: s1= s2

Test:HOVStrat:

Ho: x1= x2

Test: MoodsStrat:

Ho: s1= s2

Test:HOVStrat:

Ho: x1= x2

Test: MoodsStrat:

Ho: s1= s2

Test:HOVStrat:

Ho: x1= x2

Test: MoodsStrat:

Ho: s1= s2

Test:HOVStrat:

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June 7, 2004

Appendix - Measure

P-Value: 0.000A-Squared: 14.753


N: 155StDev: 85.2736Average: 63.3548

7006005004003002001000

.999.99.95

.80

.50

.20

.05

.01.001

Pro

babi

lity

TAT_Hr_Syste

Normal Probability Plot

Descriptive Data: Project Y

65050035020050


9585756555453525


Variable: TAT_Hrs_Tota

28.000

101.166

55.853

Maximum3rd QuartileMedian1st QuartileMinimum

NKurtosisSkewnessVarianceStDevMean

P-Value:A-Squared:

48.494

125.286

89.747

724.000 79.500 44.000 23.000 1.000

17017.35743.9135112529.1111.934 72.800

0.00021.933


95% Confidence Interval for Sigma



Descriptive Statistics

Variable N Mean Median TrMean StDevTAT_Hrs_ 170 72.80 44.00 53.77 111.93

Variable SE Mean Minimum Maximum Q1 Q3TAT_Hrs_ 8.58 1.00 724.00 23.00 79.50

Highly Variable, Non-Normal Process - Opportunity for Significant ImprovementHighly Variable, Non-Normal Process - Opportunity for Significant Improvement

Data does not fit normal curve

model

Mean & Median very different,

indicating skewed distribution

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June 7, 2004

Appendix - AnalyzeVital X : # Records

5000004000003000002000001000000

700

600

500

400

300

200

100

0

Total Records

TAT_

Hrs

_Tot

al

5000004000003000002000001000000

30000

20000

10000

0

Total Records

TAT_

Min

_Load

Slightly Positive Correlation

r=.30Not as strong as expected

Question: Does the number of records affect the total time to process a file?

5000004000003000002000001000000

40000

30000

20000

10000

0

Total Records

TA

T_M

in_M

igra

te

No pattern. # of Records is not

Driving Migration Timer= (.03)

Lack of Correlation between # Records and Load Time is CompellingLack of Correlation between # Records and Load Time is Compelling

Slightly Positive Correlation

r=.21Not as strongas expected

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June 7, 2004

Appendix - AnalyzeDistribution of TAT

Eliminating Load Failures Greatest Opportunity for ImprovementEliminating Load Failures Greatest Opportunity for Improvement

3%

1%

4%

92% Load to StgFix ErrorsLoad to ProdOther

Median Time By Activity • Processing time only 8% of Total TAT

• Excessive Delays and Wait time attributable to Load Failures Make Up Majority of Elapsed Time

• Eliminating Load Failures Addresses 92% of TAT

Other category includes time not actively processing a file (Nights, Weekends, Delays due to re-programming, waiting for review of premium, etc)

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June 7, 2004

"Don't ever take a fence down until you know the reason why it was put up.“

Gilbert Keith Chesterton

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June 7, 2004

Six Sigma Leadership


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June 7, 2004

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June 7, 2004

1995 1996 1997 1998 1999 2000 1995 1996 1997 1998 1999 2000 2001…2001…20042004

Timeline

Evolution at GE

1995 PRODUCTIVITY1995 PRODUCTIVITY

1997 PRODUCT DESIGN1997 PRODUCT DESIGN

1998 @ THE CUSTOMER1998 @ THE CUSTOMER

1999 FULFILLMENT1999 FULFILLMENT

2000 DIGITIZATION2000 DIGITIZATION

Six Sigma Evolution

2002 5 KEY CUSTOMER2002 5 KEY CUSTOMERCTQsCTQs

2004 2004 KEY BUSINESSKEY BUSINESSPROCESSESPROCESSES

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June 7, 2004

Key Success Factors: Leadership

Successful Six Sigma LeadersMust Have Credibility

Leadership Skills

Experience in Industry

Six Sigma Experience

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June 7, 2004

Key Success Factors: The Right Team

• Hire the Best People for Six Sigma

• Make it a Leadership Development Program

• Apply Six Sigma in All Areas

“The next CEO of GE will be a former black belt or

master black belt”- Jeff Immelt, GE Chairman and CEO

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June 7, 2004

Key Success Factors: Commitment

• Commit for the Long-Term

• Expect Many Generations

• Refocus as Necessary

Six Sigma Success Will Not Come

Overnight

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June 7, 2004

Share Your Successes

• Sharing Successes With the Business = Buy-in

• Avoid “Yeah, But That Won’t Work for us” Mentality

• Business Must Apply What You Learn

• Benchmark From Others: Go Outside Your Industry to Find the Best

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June 7, 2004

“You must be the change you wish to see in the world.“

Mohandas K. Gandhi

rapa 2004 oct_six_sigma_in_insurance

Business

sigma mail

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