© 2001 Six Sigma Academy
Six Sigma…Key ConceptsSix Sigma…Key Concepts
John Krupar
© 2002 Six Sigma Academy
Cost ReductionCost ReductionOperational ExcellenceOperational Excellence
Client SatisfactionClient SatisfactionGrowthGrowth
ProcessCapability
VARIABILITYVARIABILITY
FMEA CTQ
Multivariate Statistics
Mistake Proofing
Reliability
SPC
Process Mapping
DOE
C&E Matrix
Problem Solving
SystemsThinking
WASTEWASTE
Visual Controls
Linkages & Flow
Testing forValue
Value Stream Mapping
5S
Takt
Standardize
UnpredictableDemand
Balanced Work
JIT
GROWTHGROWTH
Supplier Capability QFD
Design From Ground Up
Predictive Modeling
ProductDevelopment
TRIZ
The Breakthrough Strategy®The Breakthrough Strategy®
© 2002 Six Sigma Academy
Cost ReductionCost ReductionOperational ExcellenceOperational Excellence
Client SatisfactionClient SatisfactionGrowthGrowth
ProcessCapability
DMAICDMAIC
FMEA CTQ
Multivariate Statistics
Mistake Proofing
Reliability
SPC
Process Mapping
DOE
C&E Matrix
Problem Solving
SystemsThinking
LEANLEAN
Visual Controls
Linkages & Flow
Testing forValue
Value Stream Mapping
5S
Takt
Standardize
UnpredictableDemand
Balanced Work
JIT
DFSSDFSS
Supplier Capability QFD
Design From Ground Up
Predictive Modeling
ProductDevelopment
TRIZ
The Breakthrough Strategy®The Breakthrough Strategy®
Solve Difficult Business Problems for the Last Time… Solve Difficult Business Problems for the Last Time…
Using the Appropriate ToolsUsing the Appropriate Tools
Solve Difficult Business Problems for the Last Time… Solve Difficult Business Problems for the Last Time…
Using the Appropriate ToolsUsing the Appropriate Tools
© 2002 Six Sigma Academy
BreakthroughStrategy
Characterization
Optimization
Phase 1:Measure
Phase 2:Analyze
Phase 3:Improve
Phase 4:Control
determination of improvement opportunities
Process Characterization is concernedwith the identification and benchmarkingof key process characteristics, and the
and goals.
Process Optimizationis aimed at identifying,improving and controlling the keyprocess variables which exertundesirable influence over the keyprocess characteristics.
Phase 0:Define
Phase 0:Define
•Define the problem and agree on the objective. Define the metrics.
•Map Process. Validate measurement systems. Collect relevant data and begin basic analysis
•Identify the few key factors which are directly influencing the problem.
•Determine optimum values for the few key factors which resolve the problem.
•Determine long term control measures which will ensure that improvements are sustained.
The Breakthrough Strategy®The Breakthrough Strategy®
© 2002 Six Sigma Academy
Key Concepts - Define & MeasureKey Concepts - Define & Measure
Understanding Customer Needs
Six Sigma Starts & Ends with the CustomerSix Sigma Starts & Ends with the CustomerSix Sigma Starts & Ends with the CustomerSix Sigma Starts & Ends with the Customer
© 2002 Six Sigma Academy
Val
ue
Performance
Satisfiers
Satisfier – Non-Smoking Room Available
Linear
Linear -- $10 Discount
Delighters
Delighter – Bellman greets by name, Correct Pillow, Shelled pistachio’s
Voice of the CustomerVoice of the Customer
Kano Analysis…One of Many ToolsKano Analysis…One of Many ToolsKano Analysis…One of Many ToolsKano Analysis…One of Many Tools
© 2002 Six Sigma Academy
Problem Statement
Baseline Performance and EntitlementMeasurement Systems Validation
Process Mapping
Practical Problem:
750,000 calls out of the 4,000,000 received at the call center are not resolved during the initial conversation with the client. These calls require the call center operator to make a return call to the client to answer their request. During a recent client survey, 20% of the clients stated that they were calling regarding an unresolved issue from a previous call.
The Problem Statement is written understanding of the practical problem Process Mapping gives a visual representation of the “Actual Process”
Short Term and Long Term Capability provide us a look at what is possible aswell as what our customers are experiencing from our process
Measurement Systems Analysis ensures that all Parties have the sameOperational Definition of the Problem
Client Iniates Call
Call Center Operator
Answers Call
Validate Customer ID
Number
Client Describes Question
Client Sent to Branch for New
Account Generation
Data Available to
Resolve
Operator Answers Question
Supervisor or Lead available
Yes
No
Research Area Answer
Call
No
Yes
Place Client on Call Back List
No Yes
AutomatedVoice
Response
Auto-Transferverify
Balance
Auto-TransferverifyLast 5
Transactions
Balance Verification
Operator Assisted
Verify Transaction
Current Client
Non-Client
1 2 3
70
80
90
100
Appraiser
Pe
rce
nt
Within Appraiser
1 2 3
50
60
70
80
90
100
Appraiser
Pe
rce
nt
Appraiser v s Standard
Assessment AgreementDate of study: March 21, 2001Reported by: Joe LynchName of product: Call Center - ResolutionMisc:
[ , ] 95.0% CI
Percent
Actual (LT)
Potential (ST)
3210
Process Performance
USLLSL
Actual (LT)
Potential (ST)
1,000,000
100,000
10,000
1000
100
10
1
200010000
Potential (ST)Actual (LT)
Sigma
PPM
(Z.Bench)
Process Benchmarks
1851.60
0.80
212889
2.90
Process Demographics
0
2.5
Opportunity:
Nominal:
Lower Spec:
Upper Spec:
Units:
Characteristic:
Process:
Department:
Project:
Reported by:
Date:
Report 1: Executive Summary
Call Center Case Study – Measure PhaseCall Center Case Study – Measure Phase
Illustr
ative E
xample
© 2002 Six Sigma Academy
Key Concepts - AnalyzeKey Concepts - Analyze
Entitlement
Variation
© 2002 Six Sigma Academy
EntitlementEntitlement
The focus should be to shift the overall performance to the Entitlement level. This drives dramatic short-term improvements in cost and quality with minimal investment in technology.
Only after the Entitlement level is achieved should an investment be made to redesign / reengineer the systems or infrastructure.
The optimum level that a process currently performs is the Entitlement.
This can be replicated once the variables are truly understood.
Output Variation
Days 1 5.5 11 18 38
MeanEntitlement
Performance Shift
Delivery of client Orders
Upper Specification Limit
Avoid Capital Investment Until Entitlement is ReachedAvoid Capital Investment Until Entitlement is ReachedAvoid Capital Investment Until Entitlement is ReachedAvoid Capital Investment Until Entitlement is Reached
© 2002 Six Sigma Academy
VariationVariation
Average vs. Variation
• Average tells little about client experience
• In example 1, the average number of days it takes to deliver our product is 40 days. However, this process has a high variation, with 50% of the orders filled between 40-80 days
• In example 2, the average number of days it takes to deliver our product is also 40 days. However, in this process, there is very little variation and the order is filled in no more than 50 days
• To drive dramatic improvements in performance, the variance in a process must first be minimized
Days 10 40 80
Output Variation
Mean
Example #1
Example #2
Product Delivery Process
.Businesses do not Excel Managing ‘Averages’. Businesses (and Customers)Businesses do not Excel Managing ‘Averages’. Businesses (and Customers)
Are Negatively Impacted by Extremes in the Variation of the ProcessAre Negatively Impacted by Extremes in the Variation of the Process
Businesses do not Excel Managing ‘Averages’. Businesses (and Customers)Businesses do not Excel Managing ‘Averages’. Businesses (and Customers)
Are Negatively Impacted by Extremes in the Variation of the ProcessAre Negatively Impacted by Extremes in the Variation of the Process
© 2002 Six Sigma Academy
Data Collection Plan
Hypothesis Testing
Multi-Vari Analysis
A Multi-Vari begins with a specific data sampling plan The Multi-Vari provides a graphical representation of the data
The Vital Few Variables are those X’s that are supported by the data and deserve further analysis
Hypothesis Tests are statistical tests that attempt to prove statistically ifthe averages and standard deviations of groups are the same or different
Statistical Problem:Data was collected from each of 16 operators, three times a day, over three days from each of the three call centers. The graphical representation identified 4 of the operators as having a lower mean and a very low standard deviation for resolution of client calls. This phenomenon was evident only in the morning.
Vital Few Variables
321
321321321
3.2
2.2
1.2
time of day
min
utes
to
r
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Multi-Vari Chart for minutes to r by operator - time of dayday
operator
1.20.70.2
95% Confidence Intervals for Sigmas
P-Value : 0.000
Test Statistic: 8.066
Levene's Test
P-Value : 0.000
Test Statistic: 120.764
Bartlett's Test
Factor Levels
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
Minutes to Resolve Based on the Multi-Vari Analysis and confirmed by the Hypothesis Testing, Operator and time of day was statistically significant. The X’s identified in our process exploration that are potentially impacted by this interaction are:
x1 Technical Support Availabilityx2 Bandwidth Availabilityx3 Market Volumesx4 Client Performance
Call Center Case Study – Analyze PhaseCall Center Case Study – Analyze Phase
Illustr
ative E
xample
© 2002 Six Sigma Academy
Key Concepts - ImproveKey Concepts - Improve
WasteTransfer Function(Re)Design “To Be” State
© 2002 Six Sigma Academy
Waste EliminationWaste Elimination
Lean (Waste Elimination) can be summarized in five principles*:
Principle 1 - Precisely specify the value of a specific process
Principle 2 - Identify the value stream for each process
Principle 3 - Allow value to flow without interruptions
Principle 4 - Let the customer pull value from the process
Principle 5 - Continuously pursue perfection
* Womack, J. P. and D. T. Jones, 1996, Lean Thinking, Simon & Schuster
© 2002 Six Sigma Academy
Pareto of Effects
Statistical SolutionMain Effects Plot
Interaction Plots
A Design of Experiments is the only true Cause and Effect tool to understandwhat impact each of the vital few variables has on the output
The final output of a Design of Experiment is a Mathematical Transfer Functiondescribing Y=f(x).
Main Effects Plots identify those variables whose impact is directly tiedto the output in question.
1.81.61.41.21.00.80.60.40.20.0
A
B
AB
C
ABCD
ABC
BD
AD
ACD
ABD
BCD
BC
AC
D
CD
Pareto Chart of the Effects(response is Time of, Alpha = .10)
A: TechnicaB: BandwidtC: Market VD: Client P 1
4
7711
3.5
2.5
1.5
0.5
Bandw idth
Technical Su
Mea
n
Interaction Plot (data means) for Time of Reso
Interaction Plots identify those variables that their result depends on the settingof another variable.
Client ProfiMarket VolumBandwidthTechnical Su
21217141
2.4
2.0
1.6
1.2
0.8
Tim
e o
f R
es
o
Main Effects Plot (data means) for Time of Reso
Conclusions: From the mathematical model, it is obvious that when bandwidth and Technical Support are available, many of our operators are ableto resolve the clients questions during the first call.
Call Center Case Study – Improve PhaseCall Center Case Study – Improve Phase
Illustr
ative E
xample
© 2002 Six Sigma Academy
Key Concepts - ControlKey Concepts - Control
Measure … Forever
Control …. The Key Differentiator of Six SigmaControl …. The Key Differentiator of Six SigmaControl …. The Key Differentiator of Six SigmaControl …. The Key Differentiator of Six Sigma
© 2002 Six Sigma Academy
Aspects of ControlAspects of Control
AMOUNT OF CONTROL
Ver
bal I
nstr
uctio
ns
Writ
ten
Inst
ruct
ions
Vis
ual M
anag
emen
t
Sta
tistic
al P
roce
ss C
ontr
ol
Pok
a -
Yok
e(M
ista
ke P
roof
ing)
Des
ign
for
Six
Sig
ma
Amount of Effort of Process Owner
Aut
omat
ion
Desired Direction of Control
Systemic Change
© 2002 Six Sigma Academy
“Someone, who with their team, solves a difficult business problem…
Definition of a Black BeltDefinition of a Black Belt
…for the last time.”
© 2002 Six Sigma Academy
Practical Solution
Financial ResultsFinal Capability
Control Continuum
The Control Phase focuses on implementing the practical solution
Driving the solution to a region of greater control assures the process ownerthat the solution is simpler than the problem… and the solution is mistake proof
Each 6 Sigma project is individually audited to ensure that it has a positiveimpact on the business, the client, and employee satisfaction.
AMOUNT OF CONTROL
Ver
ba
l Ins
tru
ctio
ns
Writ
ten
Ins
tru
ctio
ns
Vis
ual P
roce
ss
Sta
tis
tica
l P
roc
es
s C
ntr
l
Pok
a -
Yo
ke(M
ista
ke P
roo
fing
)
Des
ign
for
Six
Sig
ma
Amount of Effort Expended by the Process
1. Bandwidth Availability:A legacy tool, which requires a significant amount of bandwidth is used by a few of the operators. This tool could only be practically employed during the morning hours of the CC East and CC South,when users logged on to the system were at a minimum. This legacy tool was thought to be obsolete, but when IT was informed that operators still had a need for the screen, they reconfigured it to use just a fraction of the bandwidth. This allowed all operators to have the screen added to available on-line help.
2. Technical Resource Availability:When the “better operators” were monitored, it was shown that they were able to quickly answer their clients questions when a couple of supervisors in Cashiering were available by phone. These resources were generally only available during the early morning hours. When we spoke with these supervisors, we determined that they were reviewing information from a level of a help screen not authorized to the call center operators. A risk assessment was completed and it was determined that all call center operators should have this access.
Actual (LT)
Potential (ST)
210
Process Performance
USLLSL
Actual (LT)
Potential (ST)
1,000,000
100,000
10,000
1000
100
10
1
200010000
Potential (ST)Actual (LT)
Sigma
PPM
(Z.Bench)
Process Benchmarks
77.9617
2.47
6818.44
3.78
Process Demographics
0
2.5
Opportunity:
Nominal:
Lower Spec:
Upper Spec:
Units:
Characteristic:
Process:
Department:
Project:
Reported by:
Date:
Report 1: Executive Summary
The final capability is the statistical proof that the process is now improved
Defect Rate Reduction: 97%DPMO Reduction 205,000Sigma Level Improvement 0.88Cost Savings
$2.75M
Summary
Call Center Case Study – Control PhaseCall Center Case Study – Control Phase
Illustr
ative E
xample
© 2002 Six Sigma Academy
A Critical “Unintended” ConsequenceA Critical “Unintended” Consequence
Leadership
Development
© 2002 Six Sigma Academy
How Is Six Sigma Different From How Is Six Sigma Different From Other Change Initiatives?Other Change Initiatives?
IT IS NOT:
Just a “quality” program
IT IS:
Focused on strategic business priorities
Fact-based decision making
Focused on minimizing waste and variation
Dedicated resources with clear accountability
Narrowly scoped projects that are measured, statistically validated, controlled, and sustained
Quantified project benefits
Demonstrated track record of success across industries
An Enabler for Cultural Transformation
• Common Language
• Common Methodology
• Common Metrics
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