Transcript
Six Sigma in the Insurance Industry
Kevin DarterGE Insurance SolutionsUS A&H
New Orleans October 18, 2004
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What is Six Sigma?
• What is six sigma?• Customers• Defects• Data & Analysis• Six sigma leadership• Q&A/Discussion
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• Measure of Quality
• Process For Continuous Improvement
• Enabler for Culture Change
What is Six Sigma?
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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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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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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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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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Customers
• What is six sigma?• Customers• Defects• Data & Analysis• Six sigma leadership• Q&A/Discussion
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Positively impact customers with Six Sigma by improving our processes, products, and
services
Customers
Completely Satisfying Customer Needs Profitably
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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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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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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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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
Why CTQs are important
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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
Quality Starts with the Customer
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Customers Project ExampleNew Customers
Setup
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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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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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COPIS
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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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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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Defects
• What is six sigma?• Customers• Defects• Data & Analysis• Six sigma leadership• Q&A/Discussion
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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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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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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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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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"A problem well stated is a problem half solved.“
Charles F. Kettering
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Data & Analysis
• What is six sigma?• Customers• Defects• Data & Analysis• Six sigma leadership• Q&A/Discussion
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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 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 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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“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
•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 = 0.30to 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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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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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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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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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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Appendix - Measure
P-Value: 0.000A-Squared: 14.753
Anderson-Darling Normality Test
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
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 Median
95% Confidence Interval for Sigma
95% Confidence Interval for Mu
Anderson-Darling Normality Test
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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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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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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"Don't ever take a fence down until you know the reason why it was put up.“
Gilbert Keith Chesterton
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Six Sigma Leadership
• What is six sigma?• Customers• Defects• Data & Analysis• Six sigma leadership• Q&A/Discussion
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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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Key Success Factors: Leadership
Successful Six Sigma LeadersMust Have Credibility
Leadership Skills
Experience in Industry
Six Sigma Experience
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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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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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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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“You must be the change you wish to see in the world.“
Mohandas K. Gandhi
Q&A
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