1. Six Sigma in the Insurance Industry
Kevin Darter
GE Insurance Solutions
US A&H
New Orleans
October 18, 2004

2. 2 /
GE /
June 7, 2004
What is Six Sigma?
• What is six sigma?
• Customers
• Defects
• Data & Analysis
• Six sigma leadership
• Q&A/Discussion

3. 3 /
GE /
June 7, 2004
• Me asure o f Quality
• Pro ce ss Fo r Co ntinuo us Im pro ve m e nt
• Enable r fo r Culture Chang e
What is Six Sigma?

4. 4 /
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June 7, 2004
A Measureof Quality
6SigmaLingo6SigmaLingo
Unit : EachMeasurementUnit : EachMeasurement
(ClaimBooking, Policy, Check)(ClaimBooking, Policy, Check)
Defect : Measurement out of SpecDefect : Measurement out of Spec
Defect Opportunities perUnit : 1Defect Opportunities perUnit : 1
Qualityexpressedas DPMOQualityexpressedas DPMO
(Defects perMillionOpportunities)(Defects perMillionOpportunities)
Upper
Specification
Limit
Lower
Specification
Limit
Spec Standard Sigma DPMO %
Width Deviation Level In
Spec
100 25 2 308,500 69.1
66σσ
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
Upper
Specification
Limit
Lower
Specification
Limit
22σσ
What is Six Sigma?

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June 7, 2004
Process Capabilityneeds tobeBetterthanyouthink!
ActivityActivity Defects @99%Defects @99% Defects @99.9997%Defects @99.9997%
( 3.8 Sigma )( 3.8 Sigma ) ( 6 Sigma )( 6 Sigma )
Mail 20,000 lost articles 7 lost articles
Delivery of mail perhour of mail perhour
Drinking Unsafe drinking water Unsafe drinking water
Water for15 mins perday for2 mins peryear
Hospital 5000 incorrect 2 incorrect
Surgery procedures perweek procedures perweek
Air 2 abnormal landings 1 abnormal landing
Travel at most airports each day every 5 years
Sometimes 99% is just not goodenough
What is Six Sigma?

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June 7, 2004
Process ForContinuous ImprovementProcess ForContinuous Improvement
What is Six Sigma?
• 6 Sigma provides a process based approach
to continuous improvement.
• It is independent of the measurement involved
• can be used to improve any business process

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June 7, 2004
EnablerforCultural 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
FundamentallyDifferent Approach
EnablerforChange
Before
6 Sigma:
1) Inspect the product
2) List the symptoms perceived as being
the cause of the problem
3) Initiate action to mitigate /eliminate the symptoms
With
6 Sigma :
1) Measure the process output & analyze the data
2) Discoverquantitative relationships between
the output & in-process variables
3) 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
• What is six sigma?
• Customers
• Defects
• Data & Analysis
• Six sigma leadership
• Q&A/Discussion

10. 10 /
GE /
June 7, 2004

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June 7, 2004
Positively impact customers with Six
Sigma by improving ourprocesses,
products, and services
Customers
Completely Satisfying Customer Needs Profitably

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June 7, 2004
The Focus
The focus for6s quality is characterized by a continuous and thorough
understanding of ourcustomer. We need to ensure ourcustomers feel and see the
benefits of 6s quality
CustomerWhat does my
customerneed
fromourprocess?
How is our
process
performancefrom
thecustomer
perspective?
How does my
customermeasure
myprocess?
How wouldmy
customerlikefor
ourprocess to
perform?
What canwe
do better?
How does my
customerview my
process?

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June 7, 2004
Identify
Customers
Voice Of The
Customer (VOC)
Determine
CTQs
A Process To Identify Customers And Understand TheirCTQs
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 CustomerWhat areCTQs
• 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 arespecific andmeasurablerequirements takendirectlyfromour
customers — Not what wethinkourcustomers want orneed
CustomerNeeds
(What they say)
CTQs
(What they mean)

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June 7, 2004
Quality Starts with the Customer
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
WhyCTQs areimportant

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June 7, 2004
How weusethem
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
Quality Starts with the Customer

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June 7, 2004
Customers Project Example
New 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 agreements
Excludes: 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
CTQDrill 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
QFDProcess and Results
New Customer Setup Project
Product Requirement
Customer Expectation
Importance
Processfortreatyagreement
Clientagreementtotreatyandprocess
Customerownerassignmentprocess
Total
Receive all expected data 5 H 45
Service agreement signed prior to first sale/deal5 H H 90
Communication plan completed 5 H L 50
Communication plan developed prior to first sale/deal5 H L 50
An owner identified for each customer 4 H 36
Data collection process needs to be established – including timeliness5 H H 90
Overall reporting process communicated - monthly reports, timing, what is included, completeness5 H H 90
Operational 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 Y
Clear
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 and
process
Customer owner assignment
process
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
• What is six sigma?
• Customers
• Defects
• Data & Analysis
• Six sigma leadership
• Q&A/Discussion

24. 24 /
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June 7, 2004

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

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June 7, 2004

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June 7, 2004
Analysis Project Example
CDT Loading

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June 7, 2004
Accurate, 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
DateDefine 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 CDTFile
Receive
File
Extract
from Media
Scrub
File
Load to
Staging
Resolve
Errors
Verify
Premium
Load to
Production

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June 7, 2004
Good 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 Loading
Unit: 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
Maximum
3rd Quartile
Median
1st Quartile
Minimum
N
Kurtosis
Skewness
Variance
StDev
Mean
P-Value:
A-Squared:
48.494
125.286
89.747
724.000
79.500
44.000
23.000
1.000
170
17.3574
3.91351
12529.1
111.934
72.800
0.000
21.933
95% Confidence Interval for Median
95% Confidence Interval for Sigma
95% Confidence Interval for Mu
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 Mean
TAT_Hrs_ 170 72.80 44.00 53.77 111.93 8.58
Variable Minimum Maximum Q1 Q3
TAT_Hrs_ 1.00 724.00 23.00 79.50
Large Standard
Deviation--High variation
Date SPAN Mdn DPMO σ
(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 SummaryUS CDT Loading
Admin
System
Fix Records
Issue
# Records
Loaded
# Error
Records
Grouped for
Processing
Client
Group
• Central Tendency Test:
Mood Mdn: p=0.165
• Variation Test:
HOV: p=0.369
• No significant
differences between
grouped and not
grouped company files
• Central Tendency Test:
Mood Mdn: p=0.000
• Variation Test:
HOV: p=0.0000
• If a file fails in the initial
load, both the central
tendency and the spread
are higher
• Central Tendency Test:
Mood Mdn: p=0.449
• Variation Test:
HOV: p=0.001
• greatest spread is TAI
1.09. Only used by 1st
Penn…could be the Co
or the system.
• Central Tendency Test:
Mood Mdn: p=0.003
• Variation Test:
HOV: p=0.000
• Correlation:
to Total TAT r = 0.30
to Stage Load r=0.21
to 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=0.10
to 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
Errors
R-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 = 0.78
Total TAT & Fix TAT r= 0.41
Total 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 to
take more time?
Methods Materials
Machines EnvironmentPeople
Primary Cause
Auto Script
Load Fails
File loaded to wrong
ERC CompanyManual Load
Files in Hartford
Do Not Have
Metrics on Load
Auto Script does
not Pick up File
Auto Script
Load Fails
Data map is wrong
Chg to program
create error
Source Layout is wrong
Server Down
File Manually
loaded
Change in source file
Script altered with no change in source
Maps are re-typed by programmers
Use wrong Maps (multiple copies)
Revert to
previous
code
Code change
implemented
too early
High # errors in Source
File cause reload of file
File loaded
multiple times
Source File format Changes
Client added treaty codes
Error in data map
Client data error prone (Admin system)
Can't Move File
to Ops Tbls
Linked to other
co not ready to
move
No response from
escalation of issue
No backup for Gail Hartford file moves are slow
Move files across
WAN
Mail Cartridges to OP
Hartford does not have
cartridge reader
Fewer Resources on CDT
CDT Volume
Other Responsibilities
Linked company file is read
multiple times (PHL-Kemper)
Autoscript set to read multiple times
Reloading and did
not delete old data
Auto load script failure reading
same data multiple times
No edit preventing
multiple 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= 0
Test:correlation, regression
Strat: Company, Grouped
Ho: rxy= 0
Test:correlation, regression
Strat: Company, Grouped
# Records
# Errors
Ho: rxy= 0
Test:correlation
Strat: Company, Grouped
Ho: rxy= 0
Test:correlation
Strat:Company, Grouped
Ho: rxy= 0
Test:correlation
Strat: 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:ANOVA
Strat:
Ho: x1= x2
Test: Moods
Strat:
Ho: s1= s2
Test:HOV
Strat:
Ho: x1= x2
Test: Moods
Strat:
Ho: s1= s2
Test:HOV
Strat:
Ho: x1= x2
Test: Moods
Strat:
Ho: s1= s2
Test:HOV
Strat:
Ho: x1= x2
Test: Moods
Strat:
Ho: s1= s2
Test:HOV
Strat:
Ho: x1= x2
Test: Moods
Strat:
Ho: s1= s2
Test:HOV
Strat:
Ho: x1= x2
Test: Moods
Strat:
Ho: s1= s2
Test:HOV
Strat:

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June 7, 2004
Appendix - Measure
P-Value: 0.000
A-Squared: 14.753
Anderson-Darling Normality Test
N: 155
StDev: 85.2736
Average: 63.3548
7006005004003002001000
.999
.99
.95
.80
.50
.20
.05
.01
.001
Probability
TAT_Hr_Syste
Normal Probability Plot
Descriptive Data: Project Y
65050035020050
95% Confidence Interval for Mu
9585756555453525
95% Confidence Interval for Median
Variable: TAT_Hrs_Tota
28.000
101.166
55.853
Maximum
3rd Quartile
Median
1st Quartile
Minimum
N
Kurtosis
Skewness
Variance
StDev
Mean
P-Value:
A-Squared:
48.494
125.286
89.747
724.000
79.500
44.000
23.000
1.000
170
17.3574
3.91351
12529.1
111.934
72.800
0.000
21.933
95% Confidence Interval for Median
95% Confidence Interval for Sigma
95% Confidence Interval for Mu
Anderson-Darling Normality Test
Descriptive Statistics
Variable N Mean Median TrMean StDev
TAT_Hrs_ 170 72.80 44.00 53.77 111.93
Variable SE Mean Minimum Maximum Q1 Q3
TAT_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_Total
5000004000003000002000001000000
30000
20000
10000
0
Total Records
TAT_Min_Load
Slightly Positive
Correlation
r=.30
Not 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
TAT_Min_Migrate
No pattern.
# of Records is not
Driving Migration Time
r= (.03)
Lack of Correlation between # Records and Load Time is CompellingLack of Correlation between # Records and Load Time is Compelling
Slightly Positive
Correlation
r=.21
Not as strong
as 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 Stg
Fix Errors
Load to Prod
Other
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
• What is six sigma?
• Customers
• Defects
• Data & Analysis
• Six sigma leadership
• Q&A/Discussion

45. 45 /
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June 7, 2004

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June 7, 2004
1995 1996 1997 1998 1999 2000 2001…1995 1996 1997 1998 1999 2000 2001…20042004Timelin
e
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 CUSTOMER
CTQsCTQs
20042004 KEY BUSINESSKEY BUSINESS
PROCESSESPROCESSES

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June 7, 2004
Key Success Factors: Leadership
Successful Six Sigma Leaders
Must 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

50. 50 /
GE /
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

51. 51 /
GE /
June 7, 2004
“You must be the change you wish to
see in the world.“
Mohandas K. Gandhi

52. Q&A