sixsigmaintroduction yb ver2.0
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8/11/2019 SixsigmaIntroduction YB Ver2.0
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Yellow Belt Course
Six Sigma Training
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Eighty-f ive percent of the reasons or fa i lure to m eet cus tomer expectat ions are
related to deficiencies in systems and process rather than the employee. The
ro le of management is to change the process rather than badger ing indiv idu als to
do better.- W. Edwards Deming
Six Sigma
If we cant express what we know in
the form of numbers, we really dontknow much about it. If we dont know
much about it, we cant control it. If we
cant control it, we are at the mercy of
chance.-Mikel J. Harry
Six Sigma will bring GE to a whole new
level of q ual i ty in a fract ion of the t ime i twou ld have taken to cl imb the learning
curve on our own.
Jack Welch
Six Sigma is a Rigorous Method for Measuring, Improving &Controlling Our Process Performance
http://images.google.co.in/imgres?imgurl=http://www.mikeljharry.com/images/bio_picture.jpg&imgrefurl=http://www.mikeljharry.com/bio.php&h=200&w=175&sz=8&hl=en&start=6&tbnid=XeO7I4NdoWnH9M:&tbnh=104&tbnw=91&prev=/images%3Fq%3Dmikel%2Bj%2Bharry%26svnum%3D10%26hl%3Den%26lr%3Dhttp://images.google.co.in/imgres?imgurl=http://www.fullerton.edu/ccws/images/jack-welch_portrait.jpg&imgrefurl=http://www.fullerton.edu/ccws/profiles/index.htm&h=269&w=225&sz=6&hl=en&start=1&tbnid=bV32nVGWv-N2tM:&tbnh=113&tbnw=95&prev=/images%3Fq%3Djack%2Bwelch%26svnum%3D10%26hl%3Den%26lr%3D%26sa%3DN -
8/11/2019 SixsigmaIntroduction YB Ver2.0
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1998
GE reports a revenueof $ 17 bn and
Savings of 70% fromSix Sigma
1988-89
Adopted by GEhaving contemporaryrevenue of $1 bn
1985-94
Motorola saves USD2.00 bn. in bottom-
line
1988
Motorola winsBaldridge Award
1981
Introduced byMotorola in response
to Japanesecompetition
Landmarks
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Companies Implementing Six Sigma
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8/11/2019 SixsigmaIntroduction YB Ver2.0
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5
Companies Implementing Six Sigma (Cont..)
http://rds.yahoo.com/_ylt=A9iby4IIPa9FTFMAWs2JzbkF;_ylu=X3oDMTBjcXBoZjEwBHBvcwMzBHNlYwNzcg--/SIG=1g6rd53kq/EXP=1169198728/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253Dpepsi%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=178%26h=153%26imgurl=brandautopsy.typepad.com%252Fphotos%252Fexamination_room%252Fpepsi.jpg%26rurl=http%253A%252F%252Fbrandautopsy.typepad.com%252Fphotos%252Fexamination_room%252Fpepsi.html%26size=7.5kB%26name=pepsi.jpg%26p=pepsi%26type=jpeg%26no=3%26tt=249,682%26oid=b480120160bddf20%26ei=UTF-8http://rds.yahoo.com/_ylt=A9iby4HxPK9FFxYBcs6JzbkF;_ylu=X3oDMTBjdmNoOTVjBHBvcwMyBHNlYwNzcg--/SIG=1fdgq3gbn/EXP=1169198705/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253Dcoca%252Bcola%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=400%26h=129%26imgurl=www.procomac.it%252Fimages%252Fcoca%252520cola.jpg%26rurl=http%253A%252F%252Fwww.procomac.it%252FNEWS_2004%252Fnews106.htm%26size=70.7kB%26name=coca%2Bcola.jpg%26p=coca%2Bcola%26type=jpeg%26no=2%26tt=397,100%26oid=68119c7f563f5014%26ei=UTF-8http://rds.yahoo.com/_ylt=A9ibyGXUPK9FfmsArhqJzbkF;_ylu=X3oDMTBjZmpxdmw3BHBvcwM3BHNlYwNzcg--/SIG=1fpb4iicu/EXP=1169198676/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253Dreliance%252Blogo%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=100%26h=83%26imgurl=www.foodinternational.net%252FPortals%252F0%252FReliance%252520logo.jpg%26rurl=http%253A%252F%252Fwww.foodinternational.net%252F%26size=2.8kB%26name=Reliance%2Blogo.jpg%26p=reliance%2Blogo%26type=jpeg%26no=7%26tt=519%26oid=ad0564ea147d656a%26ei=UTF-8http://rds.yahoo.com/_ylt=A9iby4CoPK9FugsBbhCJzbkF;_ylu=X3oDMTBjMHZkMjZyBHBvcwMxBHNlYwNzcg--/SIG=1gt0btvjf/EXP=1169198632/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253Dlogo%252Bkingfisher%252Bairlines%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=185%26h=165%26imgurl=www.tourorissa.com%252Fkingfisher%252520airlines%252520logo.JPG%26rurl=http%253A%252F%252Fwww.tourorissa.com%252Ftimings.htm%26size=6.4kB%26name=kingfisher%2Bairlines%2Blogo.JPG%26p=logo%2Bkingfisher%2Bairlines%26type=jpeg%26no=1%26tt=9%26oid=4b9890b96f97e27a%26ei=UTF-8http://rds.yahoo.com/_ylt=A9ibyGVlPK9FAWMALoaJzbkF;_ylu=X3oDMTBjMHZkMjZyBHBvcwMxBHNlYwNzcg--/SIG=1flhvc7jn/EXP=1169198565/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253Djet%252Bairways%252Blogo%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=170%26h=113%26imgurl=www.showhouseindia.com%252Fimages%252Fjet_logo.jpg%26rurl=http%253A%252F%252Fwww.showhouseindia.com%252Fjet_airways.htm%26size=3.8kB%26name=jet_logo.jpg%26p=jet%2Bairways%2Blogo%26type=jpeg%26no=1%26tt=64%26oid=540d1ebb7747e72a%26ei=UTF-8http://rds.yahoo.com/_ylt=A9iby6E6PK9F98sAaiaJzbkF;_ylu=X3oDMTBjMHZkMjZyBHBvcwMxBHNlYwNzcg--/SIG=1g5uhd02a/EXP=1169198522/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253DHP%252Blogo%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=866%26h=719%26imgurl=etudiant.epita.fr%252F%257Ebde%252Flogos%252FLogos%252Fhp_logo.jpg%26rurl=http%253A%252F%252Fetudiant.epita.fr%252F%257Ebde%252Flogos%252FLogos%253FM%253DA%26size=44.4kB%26name=hp_logo.jpg%26p=HP%2Blogo%26type=jpeg%26no=1%26tt=95,047%26oid=d10bf816c450edac%26ei=UTF-8http://rds.yahoo.com/_ylt=A9iby4UlPK9F7.EA4FiJzbkF;_ylu=X3oDMTBjMHZkMjZyBHBvcwMxBHNlYwNzcg--/SIG=1ek2hlfhd/EXP=1169198501/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253DHCL%252Blogo%2526ei%253DUTF-8%2526fr%253Dslv8-%2526vm%253Dr%2526x%253Dwrt%26w=80%26h=50%26imgurl=www.itnewsonline.com%252Fimages%252Flogo%252FHCL-logo.jpg%26rurl=http%253A%252F%252Fwww.itnewsonline.com%252F%26size=1.3kB%26name=HCL-logo.jpg%26p=HCL%2Blogo%26type=jpeg%26no=1%26tt=478%26oid=236e08a69f05f75a%26ei=UTF-8http://rds.yahoo.com/_ylt=A9ibyGVwOa9FxmEApOuJzbkF;_ylu=X3oDMTBjMHZkMjZyBHBvcwMxBHNlYwNzcg--/SIG=1ke30r7jh/EXP=1169197808/**http%3A//images.search.yahoo.com/search/images/view%3Fback=http%253A%252F%252Fimages.search.yahoo.com%252Fsearch%252Fimages%253Fp%253Dvisteon%2526ei%253DUTF-8%2526fr%253Dyfp-t-391%2526fp_ip%253DIN%2526vm%253Dr%2526x%253Dwrt%26w=160%26h=90%26imgurl=www.firmenverzeichnis.de%252Fverzeichnis%252Fimages%252Ffirmen%252Fthumbs%252FVisteon-Logo-Neu-220x90.jpg%26rurl=http%253A%252F%252Fwww.firmenverzeichnis.de%252Fverzeichnis%252Fproduct_info.php%253Fproducts_id%253D94%2526osCsid%253D859cc86986d52a6109148568671d8009%26size=8.7kB%26name=Visteon-Logo-Neu-220x90.jpg%26p=visteon%26type=jpeg%26no=1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6-Sigma is a Methodology to significantly improve
customer satisfactionand shareholder value by
reducing variabilityin every aspect of our business.
6-Sigma is not something else that you do i t is
what you do.
Passion + Execution = Fast and Lasting Results
What is Six Sigma ?
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7
A philosophy which mandates operational excellence
A business strategy
A set of tools designed to reduce variation in processesand operations
A statistical measure of a process capability - 3.4defects per million opportunity - 99.99966 % Probabilityof passing Non defective products to Customer
World class quality
.... A challenge, but others have
achieved.
What is Six Sigma ?
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8
What is Six Sigma ?
Metric
Goal
Locomotive
Way of LifeCulture
Benchmark
6
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9
Addresses Size
Enhances Execution Quality
Tightly clubbed in with the customer
Helps benchmark against the global best
Objective, Data based measurable, drives cont. improvement
Established yet allows innovation and adaptability
Why Six Sigma ?
Credible Methodology Culture Change
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If your process does not include Continuous Improvement and yourcompetitors does, you cannot stay in business
Suppose a competitor systematically improves productivity at arelatively modest annual rate of 7%, year over year, while yourproductivity remains static. After only 3 years, the productivity
differential is (1.07)3= 1.21, a 21% advantage
Changing market reality:
Old Paradigm: Cost + Profit = Selling Price
New Paradigm : Selling Price - Cost = Profit
6-Sigma process produce only 3.4 DPMO or 99.9997% error-free.
Typical Software Processes operate between 2.3 & 3.0 sigma
The Best Software Processes operate at 4 to 5 sigma
Why Six Sigma (contd)?
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Why Six Sigma?
StrategyDiscipline
What wasmissing --
Six Sigma!
Philosophy &Vision
Quality Vision
existed for years
(ISO, Zero defects)
Tools &Techniques
Many tools existed for
years
(statistics,DOE...)
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Six SigmaPeople Power + Process Power
Management DisciplineFocused on improvement areas
Breakthrough Strategy
Constant Process Improvement to achieve customer delight
Driven by data on customer relevant metrics
Focus on sustenance vs. quick fix
3.4 Defects Per Million Opportunities (99.99966% Yield)
Customers view towards out contribution
Our perspective
Our process
Customers process
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Six SigmaStatistical objectives
CenterProcess
ReduceSpread
Target
USLLSL
Reduce Variat ion & Center ProcessCustomers feel the
variat ion m ore than the mean
Proces s Off Target
Target
USLLSL
Excess ive Variat ion
Target
USLLSL
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Goal of Six Sigma
To reduce Variation
To reduce defects
To improve yield
To enhance Customer Satisfaction
To improve the Bottomline
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Six Sigma in practical terms
99.99966% Good (6 Sigma)
20,000 lost e- mails per hour
Unsafe drinking water for almost15 minutes each day
5,000 incorrect surgical operationsper week
Two short or long landings at mostmajor airports each day
200,000 wrong drug prescriptionseach year
No electricity for almost sevenhours each month
Seven e-mails lost per hour
One unsafe minute every sevenmonths
1.7 incorrect operations per week
One short or long landing everyfive years
68 wrong prescriptions per year
One hour without electricity every
34 years
98.930%Good (3.8 Sigma)
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Improvement mechanism
Logic and intuitionQuick fixes-Kaizen
Low hanging fruits
Simple QC tools
Bulk of fruitsProcess characterization
and optimization(DMAIC)
ProcessEntitlementSweet fruits
DFSS
Increase of sigma rating requires an exponential decrease in defect reduction
2s
4s
3s
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Six Sigma methodology identifies processes that are off-target,and/or have a high degree of variation, and corrects the process
Off-Target Variation
On-Target
CenterProcess
ReduceSpread
XX
XXXX
X
XX
X
X
XX
X
X
X
X X
X
X
XXX
X
Six Sigma Problem Solving Objective
XX
XXXX
X
XX
X
X
X
X
X
X
X
XX
X
X
XX
X X
X
XX
X
XX
XX
X
X
X
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A specification is a customer-defined tolerance for the output unit characteristics
Specifications can be one sided or two sided
Specifications form the basis of any defect measurement exercise
Specification example: Resolution of P1 tickets with 2 hours
USL: Upper Specification Limit for Y,
anything above this is a defect.
LSL: Lower Specification Limit for Y,anything below this is a defect.
Target: Ideally the middle point of USL & LSL.
LSL Target USL
Six Sigma Problem Solving Objective
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High
Probability
of Failure
66807Defects
Per Million
Opportunities
Much Lower
Probabilityof Failure
3.4Defects
Per Million
Opportunities
6 2s
1
6 2s
Mean / TargetLower
Specification Limit
Upper
Specification Limit
Higher this
number,
Lower thechance of
producing adefect
Higher these
numbers,
Lower thechance of
producing adefect
1
3 1s 3 1s
Six Sigma Problem Solving Objective
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6-Sigma as a Goal
-20 -10 0 10 20
Consider below performance on On time delivery
Target 0 days
Mean 0.70 days
On Target !!!! Good Performance ??
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6-Sigma as a Goal
-20 -10 0 10 20
What customer sees!!
Customer always looks at , mean is meaninglessvariance
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A Scientific Management Tool & Philosophy, One Of Its Kind
Six Sigma - Approach
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Six Sigma - Approach
To get results should we focus on Y or X?
Y
Dependent variable
Output of the process
Effect
Symptom
It is monitored
X1, X2, .., Xn
Independent variable
Input to the process
Cause
Problem
It is controlled
Y = f(X)
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Defects per millionopportunities
2 308,537
3 66,807
4 6,210
5 233
6 3.4
6-Sigma as a Goal
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As long as there is a process that produces an output whether it isa manufactured product, data, an invoice, etc... we can apply the
Six Sigma Breakthrough Strategy. For these processes to performto a customer standard they require correct inputs!!!
6 Sigma
Methods
MFG..
DESIGN
SERVICE
PURCH.
MAINT.
ADMIN.
QA
Marketing
Which Business Function Needs It?
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Executive Leadership (Part-Time)
Project Champion (Part-Time)
Black Belt (Ful l -Time Qual i ty Champio ns )
Green Belt (Part-Time)
Master Black Belt (Full-Time)
Deployment Structure
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What isimportant
How arewe doing
What iswrong
Whatneeds tobe done
How do weguarantee
performance
MMeasure
Performance
AAnalyze
Opportunity
IImprove
Performance
CControl
Performance
DDefine
Opportunities
MMeasure
AAnalyze
DDesign
VVerify
DDefine
For Existing Processes (DMAIC)
For new Design & new Processes (DMADV/DFSS )
Six Sigma Methodology
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DMAIC
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DMAIC Methodology
Customer-driven,
consistent,
metri cs focused,
resul ts oriented
Definethe opportunity
Measurethecurrent performance
Controland adjustnew processes
ImplementProcessefficiency Analyzethe
current processes
Project Charter/Stakeholder Analysis VOC/CTQ Measurable business objectives Linkage to business strategy Process Maps
CTQ Specification Pareto Analysis Sigma Calculation
Root Cause-Effect
Diagram Scatter Diagrams Benchmarking Value-addedAnalyses
Brainstorming Storyboarding Cost/Benefit Pilot Testing Control Chart Process/ProjectManagement Chart
Sigma Calculation
Control Chart Histogram Storyboard Sigma Calculation
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Define Phase - Flow
Project Charter
Problem Statement:
Goal:
Business Case:
Scope:
Cost Benefit Projection:
Milestones:
Develop charter to include project
description, baseline measures,
business results, team members,and schedule. Use Benchmarkingas appropriate to establish some
of the initial targets.
VOC
Key Issue
CTQ
Delighters
More Is Better
Must Be
Gather / displaydata verifying
customer needs
and requirements
VOC
OutputsProcess
SIPOCSUPPL
IERS
CUSTO
ME
RS
Inputs
Complete high-level as isprocess map and analyze
yield to identify the processstep with the highest impact
Business Case
Explain why it isimportant to work
on this project
Yield: 60%
Yield: 90%
Yield: 45%
Yield: 98%
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Define Roadmap
Define Measure Analyze Improve Control
CharterDetermine
CTQsMap
Process
1)The Team2) Business Case3) Problemstatement
4) Project Goals5) Scope6) Milestones
1)Identify customers2)Gather VOC data3)Organize VOCdata
4)Translate needs toCTQs5) Establish ProjectY
1) Process Definitions.2) Connecting theSupplier/ Customer toYour Process.
3) SIPOC
Deliverables
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Project Charter
A team charter is a written document and works as an agreement
between Sponsor and the team about what is expected from the
project
WHY?Clarifies what is expected of the team.
Keeps the team focused.
Keeps the team aligned withorganizational priorities.
Transfers the project from theSponsor(s) to the project team.
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Project Charter
Project Importance (Business Case):It was observed duringService Delivery Review for XYZ customer that there is a increasing
trend in P1 tickets volume. P1 tickets have bigger impact onCustomer infrastructure and hence the P1 SLAs are very stringent.Huge volume of P1 tickets increases the cost of delivery.
Metrics
Cost ofOperations
Current/Baseline
$50000 per annum
Goal
$40000p.a.
Problem Description (Quantified) :Average volume of P1 tickets
during Jan-Feb-Mar 08 was found to be 60% of overall ticket
volumes. Such volume of P1 tickets is extremely high and there is a
risk SLA slippage which causes Customer dissatisfaction.
P1 SLA 80% >95%
Project Goal / Objective:Reduce P1 tickets volume to 20% # of P1Tickets
Average 600 per
month
Avg
200 per
month
Projected Business Benefits:
Productivity gain
Improved SLA
Customer Satisfaction
# FTEs
P1 SLA
C-Sat Rating
4
80%
3
Redn of
1 FTE
>95%
4
Project Risk/Dependencies :Need help from Customer IT Team onpolicy redefinitions
Project Scope: BoundariesIn Scope: Only tickets generated from EMEA Region would betargeted for improvement
Out of Scope: Tickets generated from other regions
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A Business Case:
Asks Why should we do the project?
Lists the benefits like
Reduction of Rework cost
Increase in Customer Satisfaction
Decrease in costs
Reduction in Manpower
Reduction in cycle-time
Increased business opportunities
Example:
CTQCycle time of loans processing
Reduction in cycle time of loan processing will increase in the number of loans processed which
will beat the competitors hence acquiring more customers leading to increased market share. This
will result in higher business revenues for the bank.
Going Forward
D
E
F
I
N
E
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Problem Statement
Should address only the CTQ
Should be short, clear & crisp
Should address
Since when is the problem seen
What is the problem
How much is the problem
Example:
CTQCycle time of Loans processing
From Jan-04 to Apr-04 (Since When), the cycle time for loan processing has increased
(What) from 4 days to 9 days (How Much)
Going Forward
D
E
F
I
N
E
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Problem Statement
D
E
F
I
N
E
Good Example:
In the last 3 months, 12% of our customers are late, by over 45 days in
paying their bills. This represents 20% of our outstanding receivables &
negatively affects our operating cash flow.
Poor Example:
Our customers are angry with us and thus delay paying their bills.
What
When
MagnitudeConsequence
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Well defined project
Has a clearly defined problem statement
Is clearly linked to customer CTQs
Is relevant to the business and will havepositive impact
Has a clearly defined and measurabledefect
Is manageable in scope
Resources identified
Problem Statement:
Goal:
Business Case:
Scope:
Cost Benefit Projection:
Milestones:
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CTQ (Critical To Quality)
A CTQ is a
Product or Service
characteristic
that satisfies a
Customer Requirement
OR
Process Requirement
Business CTQ
Customer CTQ
Internal CTQ
Project CTQ
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All repetitive activities can be represented as a process
All processes have measurable characteristics
All measurable characteristics are represented as a frequency
distribution
The most common frequency distribution is a Normal distribution
Concept of a Process
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Define your customer
Six Sigma begins with the customer
Customers find it easier to define what they do not want
Customer CTQs are defined by customers
Sources of customer CTQs
Survey results
Service reviews
Meetings
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Voice Of TheCustomer (VOC)
DetermineCTQs
A Process To Ident i fy Customers And Understand Their CTQs
List
customers Define
customer
segments
Narrow list
Organize all customer data
Translate VOC to specific
needs Define CTQs for
specific needs
Prioritize CTQs
Contain problem if necessary
Review existing
VOC data
Decide what to
collect/ select VOC
tools
Collect data
IdentifyCustomers
Steps to determine CTQs
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Define your customer
INTERNAL INTERMEDIATE FINAL
Business
Management
Employees
Department
Suppliers
Partners
Channel
End customers
Shareholders
Regulators
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Define your customer
What does my
custom er need
f rom our
process?
How wou ld my
custom er like
for our process
to perform?
How is ourprocess
performance
from the
cus tomer
perspect ive?
How does my
customer
measure my
process? How does my
custom er view
my process?
What can we
do bet ter?
Customer Centricity
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Define your customer
Revenues and profitscome from
Customers,not products.
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What to collect?
Customer satisfaction with
what you provide today
What the customer wants based on his/her
true need (regardless of what your process
is capable of producing)
Whatsimportant
to you?
How Am I
Doing?
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Review existing VOC data
Avoid duplication of effort for both you and the customer
Customer
Project Team 1
Project Team 2
Project Team 3
Surveys
Personal Visits
Questionnaires
Interviews
Phone Calls
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Common tools for gathering VOC data
Method Description Advantages Disadvantages
Interviews Information obtained from customerseither by telephone or in person.
Detailedinformation
Follow up
Expensive Talent of the
interviewer
Surveys(Mostcommon tool
used inBPDO)
A set of written questions that is sent toselected customers to obtain informationthat can be formatted into data
Objective data Easy to
interpret
Poor responserate
Different answers
based on type ofquestions
Focus groups A collection of customers who answerquestions from a facilitator
Follow-upquestionsObserving non-verbal behaviors
ExpensiveSkill of the facilitator
Observing
the Customer
Seeing the customer using your product
or service
Unfiltered
information
No follow up
Complaints Information obtained whilesomeone complains about asituation
Opportunity tomake amends
Few peoplecomplain
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Define your customer
Translating VOC into CTQsSome ExamplesCustomer Need
1. Rapid delivery
2. Liberal returns policy
3. Friendly customer service athotel
CTQs
1. Orders delivered within 3 workingdays of purchase order receipt
2. Any returned item retailing for lesthan $1000 accepted with noquestions and with full cashrefund
3. Greet guest within 20 secs ofentry into lobby;address allguests with Mr. or Ms & last nameetc
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Define your customer
From High-Level To Specif ic Needs
High-Level
Need
(VOC)
Service/QualityIssue
Specific
NeedsStatement
Output
Characteristic
The Needs Statement Leads to Defining the 4 elements of the CTQ
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VOC -> CTQ Translation Matrix
D
E
F
I
N
E
IndexDefine Phase
Voice
ofCustomer(V
OC)
Tool
VOC Table
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VOC -> CTQ Translation Matrix
IndexDefine Phase
Voice of the
customer
ID Who Voice What When Where Why How
1
Registered
Users
Convenience of
Bill Payment athome
Avoid the trouble
of physical Billpayment
As per
billingcycle
At
respectivepayment
counter
Not
enoughtime
Online
Payment
Application to be
run on standard
browsers
Application to be
run on IE or NS
From any
location
which has
internet
Java
Electricity,
water, telephone
At fixed
frequency
As per
billingcycle
Secure txn.
Using credit
cards
To avoid
the misuse
of credit
cards
Digital
certificate
Voice of Customer Table
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Return to charter
After you have identified your CTQs, refer back to thecharter and revise as necessary
Does your CTQ relate to the problem?
Do you need to rewrite or revise any of the sections?
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VOC -> CTQ Translation Matrix
D
E
F
I
N
E
Voice of the
Customer
Key Issue Need Statement CTQ Output
Characteristic
Poor resolution
Of incidents
Resolution time is
Not as per
customer
requirement,
quality of
resolution is bad
Reduce turn-around-
Time of incidents,
Good quality of
resolution
Improve MTTR from
6.5 hours to 3 hours,
Reduce re-opening of
Incidents from 20% to
0%
IndexDefine Phase
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Select Project YCTQ/Project Y matrix
IndexDefine Phase
ExampleProcess: Ordering Pizza
Primary output (product or service):Delivery of Pizza
Strong relationshipStrong indication of the extent to which requirement is met
Moderate relationship
Weak relationship
Potential Project Y Measures
CTQ Output Characteristic Timefromorderto
delivery
#
of
co
mplaints
ab
outwrong
or
der
Customer
fe
edbackscore
Te
mpofPizza
at
timeof
de
livery
On time delivery of Pizza
Pizza as per the order
Pizza that is hot
CPR #
Customer PriorityRank Number
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CTQ Drill Down Tree
Cycle time for recruitment
Needidentification
time
Time foradvertisement
Interviewprocess
time
Joiningtime
Shortlistingtime
Interviewtime
CTQ ToolsDrill Down Tree
IndexDefine Phase
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Customers & Suppliers
D
E
F
I
N
E
IndexDefine Phase
Mysuppliers
suppliers
processes
Mysuppliersprocesse
s
Mycustomerscustomers
processes
Mycustomers
processesMy
processes
Inputs from
suppl iers
Outputs to
cus tomers
Chain of customers and suppliers
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SIPOC Diagram Example
Receive ticketCheck whether
it belongs to
our Queue
If yes, Ack the
ticket and
assign it to FTE
Resolve the
ticket
Closure in the
Ticketing Tool
NSSVendors
Tickets thrua Tool (P1/P2/P3/P4 andL1/ L2 /L3)Incident,Problem,Change ticket
Supplier Input
Incident resolution
Ticket closure
XYZ
Output Customer
Incident Resolution
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SIPOCQuestions to be asked
Purpose Why does this process exist?
What is the purpose of this process?
What is the outcome?
Outputs What product does this process make?
What are the outputs of this process?
At what point does this process end?
Customers Who uses the products from this
process?
Who are the customers of this
process?
Inputs/Suppliers Where does the information
or material you work on comefrom? Who are yoursuppliers?
What do they supply? Where do they affect the
process flow? What effect do they have onthe process and on theoutcome?
Process steps
What happens to each input? What conversion activities
take place?
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SIPOC Diagram Example
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Process mapping
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Process Mapping - Example
Request
Vendor foroutstanding
payments
Send goodsto HP
Send invoicesto HP
Mail Room atSingapore
Send documentsafter
scanning
Receive invoice for processing
1
Upload
TIVPTeam atBangalore
Query management
InformationSystems
SAP 2
Last updated on 05thNovember 2003
Daily Daily Daily processing
8
7 & 8
Vendors
Check the
scanned invoices for
Invalid PO#, legal
requirementsand
clarity of invoices
Request
for rescan /Return To Vendor
(RTV)
Business
Unclear or
incompleteinformation
on invoices
Respond to
queries
Complete
information
received
Enter the i nvoice information
received for processing
Invoice Processing
Daily processing
Clear Block
docs
InvoicesReady
for Payment
Invoices with Price
/ Qty variance
blocked for paymentInvoices with
correct
information
is processed
Perform QC and
validate data
captured
Capture information of theGoods Receipt (GRs)
5
4
6
Payments TeamBangalore
7
Data processed
for payments
Payments
Per schedule
9
10
11
6SAP E-mail
Decision /
Inspection
Manual
process step
Output of the
process
Data in
electronic form
Document in Fax , printout
or in a paper form
SAP
Detailsprovided
in nextlevel
3
Rescan / RTV
RTV
Rescan invoices
4 Futuresoft / M ALA
Respond to
queries
Unclear or
incompleteinformation
on invoices
11 SAP
Perform QC andvalidate data
captured 9
System processesthe data captured
Outstanding
Payments?
Yes
Write -off
Process
No
TIVP Invoice Managem ent
Start point of
process
Receive good s Invoice Recd?
Yes
No
2
7
8
Currently tracked
Currently not tracked
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Measure Phase - Flow
P
InputMeasures
ProcessMeasures
OutputMeasures
Measures
Measures
Develop measuresbased on CTQs
and SIPOC map
I1
I2
I3
I4
O1 O2 O3 O4
Funneling
Determine the criticalfew measures
Alignment toBIG Y
Gage R&R
Validate yourmeasurement system
Col# 1 2 3 4 5 6
Inspector A BSample # 1st Trial 2nd Trial Diff 1st Trial 2nd Trial Diff
1 2.0 1.0 1.0 1.5 1.5 0.02 2.0 3.0 1.0 2.5 2.5 0.03 1.5 1.0 0.5 2.0 1.5 0.54 3.0 3.0 0.0 2.0 2.5 0.55 2.0 1.5 0.5 1.5 0.5 1.0
Totals 10.5 9.5 3.0 9.5 8.5 2.0
Averages 2.1 1.9 0.6 1.9 1.7 0.4
Sum 4.0 Sum 3.6
XA 2.0 XB 1.8RA
RB
Display the data in graphic
form to show current
variation and other patterns
Process Capability
Calculate current processcapability and sigma
LSL
USL
Cp
=
0.4
= 2.7
Data Display
0
1000
-1000
10 20 30
UCL
X
LCL
D B F A C E Other
Data Collection Plan
Operational Definition and Procedures
Data Collection Plan
What quest ions do you want to answer?
Data
What Measure type/Data type
Howmeasured
Relatedconditions
Samplingnotes
How/where
How will you ensureconsistency and stability?
What is your plan forstarting data collection?
How will the data be displayed?
Develop a datacollection plan
Wh ?
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Why measure?
Measurement allows Teams to Establish baseline process performance
Isolate sources of variation
Identify areas where improvements can be made
We dont know what we dont know.
If we cant express what we know in the form of numbers,
we really dont know much about it.
If we dont know much about it, we cant control it.
If we cant control it, we are at the mercy of chance.
Wh t t ?
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What to measure?
M MeasureE Everything
T That
R ResultsI In
C Customer
S Satisfaction
M Ph Fl
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Measure Phase - Flow
Input
measuresProcessmeasuresOutputmeasures
Define Measure ImproveAnalyse Control
DataCollectionMeasures
6Sigma &
ProcessCapabilityVariation
4 step datacollectionprocess
Graphicaldisplay ofdata
Calculateprocess
sigma
M Ph Fl
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Measure Phase - Flow
Serial No. Activity Typically used Tools
1 Performance Standards Performance Standards
2 Data Collection Plan Data Collection Plan
3 Data Collection Normality CheckGraphical Summary
Run Charts
4 MSAGage R & R
5 Base lining the Current
processCapability Analysis
D t C ll ti Wh ?
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Data CollectionWhy?
M
E
AS
U
R
E
What is Data ?
Data is a numerical expression of an activity.
Conclus ions based on facts and data are necessary
for any improvement.
-K . Ish ikawa
If you are not able to express a phenomenon in
num bers, you do not know abou t i t adequately.
-Lo rd K elvin
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Data CollectionWhy?
M
E
AS
U
R
E
Binary Orderedcategories
Count
Classifiedinto one of
two categories
Rankingsor ratings
Counteddiscretely
Measuredon a
continuum
or scale
Tossing a Coin Customersatisfaction
rating ofContact center
service
Number oferrors in anapplication
Time toprocess anapplication
Description
Example
Discrete/ Attribute
Continuous/Variable
DataTypes
Unorderedcategories
No rankings
Types ofproducts
Time
C ti / Di t D t
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Continuous v/s Discrete Data
M
E
AS
U
R
E
IndexMeasure Phase
E l f C ti & Di t D t
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Examples of Continuous & Discrete Data
M
E
AS
U
R
E
IndexMeasure Phase
Attribute Data
Categories
Yes/No
Go/No Go
Pass/Fail
Good/Defective
Variable Data Continuous Data
Decimal places showabsolute distance between
numbers
Time Finance Charges Length
Width
Characteristics Continuous & Discrete Data
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Characteristics Continuous & Discrete Data
M
E
AS
U
R
E
IndexMeasure Phase
Continuous Data Discrete Data
More Powerful & Sensitive Insensitive
Yields more insight into the process Show if the process is good / bad
Requires Small Sample size Requires large sample size
Use Continuous Data whenever possible
Continuous
Data type practice
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Data type practice
M
E
AS
U
R
E
IndexMeasure Phase
1. The number of suitcases lost by an airline.
2. The height of corn plants.
3. The number of ears of corn produced.
4. The number of green M&M's in a bag.
5. The time it takes for a car battery to die.
6. The production of tomatoes by weight.
7. Lateness of a delivery
8. Defective slabs
9. Overdue accounts
10. Equipment breakdowns
11. Amount of steel melted
12. Cycle time of production
13. Errors on reports
14. % On time payment of invoices
Continuous Data Characteristics
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Continuous Data Characteristics
M
E
AS
U
R
E
IndexMeasure Phase
Usually illustrated in tables & histograms / frequency polygons
A histogram or frequency distribution shows the number of data points in a
data set that fall
into each of the frequency classes
A frequency polygon is constructed by connecting the mid-points of each of the
vertical bar
in the Histogram
90 95 100 115 120 125 130
Continuous Data Characteristics
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M
E
AS
U
R
E
IndexMeasure Phase
Location / Central Tendency
It is a measure of the center point of any data set
Spread / Dispersion
It is a measure of the spread of any data set around its center
Shape It is a measure of symmetry of any data set around its center
Continuous Data Characteristics
Continuous Data Characteristics
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M
E
A
S
U
R
E
IndexMeasure Phase
Mean: Mean is the arithmetic average of all data points in a data set
Mode
Mode is the most frequently occurring data point in a data set (Garment/ Shoes
inventory/ mfg would be based on most common sizes sold rather than mean of
sizes)
Median
Median is the middle data point of a data set arranged in an ascending /
descending order (Management institutes announcing placement packages use
median than average)
Y1 + Y2 + Y3 + . + Yn
nWhere n = number of data pointsY =
Odd number of data points Even number of data points
Average
Continuous Data Characteristics
Continuous Data Characteristics
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M
E
A
S
U
R
E
IndexMeasure PhaseAverage
Continuous Data Characteristics
Range
Range is the difference between the maximum & minimum data point
Variance / Standard Deviation
Variance & standard deviation measure how individual data points are
spread around mean
( Y1 - Y )2 + ( Y2Y )
2 + . + ( YnY )2
( n1 )Variance = s2 =
Standard Deviation = s = s2
Importance of spread
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M
E
A
S
U
R
E
IndexMeasure PhaseAverage
Importance of spread
Mean of Curve A is more representative of its data set as compared to Curves
B & C
Spread outside the specifications may result in defects; this information is not
provided by mean
From a process perspective, individual customers are subject to different
behaviors
of the process
A
B
C
Normal (Gaussian) Distribution
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M
E
A
S
U
R
E
IndexMeasure PhaseAverage
Normal (Gaussian) Distribution
Its a Probability Distribution, illustrated as N ( , )
Simply put, a probability distribution is a theoreticalfrequency distribution
Higher frequency of values around the mean & lesser & lesser at values away frommean
Continuous & symmetrical
Tails asymptotic to X-axis
Bell shaped
Total area under the Normal curve = 1
100 110 120 130908070
Figure 3.01
1 unitof
standarddeviation
+-
Normal DistributionwithMean =100
Standard Deviation = 10
Origin: German Army
Normal Distribution Property
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M
E
A
S
U
R
E
IndexMeasure PhaseAverage
Normal Distribution Property
Figure 3.02
+-
- 1 + 1
95.46%- 2 + 2
68.26%
- 3 + 3
99.73%+ 4
99.9937%
- 599.99943%
+ 5
- 6 + 699.999998%
- 4
Concept of Z value
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M
E
A
S
U
R
E
IndexMeasure PhaseAverage
Concept of Z value
To standardize different measurement units; such as, inches, meters, grams; a
standard Z variable is used.
Where Y = Value of the data point we are concerned with
= Mean of the data points
= Standard Deviation of the data points
Z = Number of standard deviations between Y & the mean()
Z value is unique for each probability within the normal distribution
It helps in finding probabilities of data points anywhere within the distribution
It is dimensionless
Z =
Y -
Example
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IndexMeasure PhaseAverage
Example
Its found that time taken for resolution of customer complaints follow a
normal distribution with mean of 250 hours and standard deviation of 23hrs. What is the probability that a complaint resolution will take more than
300 hrs?
250 300
Z =300 - 250
23= 2.17
Z
The complete picture
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IndexMeasure PhaseAverage
The complete picture
On CenterLarge Spread
LSL USLT
On CenterSmall Spread
LSL USLTLSL USLT
Off CenterSmall Spread
Off CenterLarge Spread
LSL USLT
Which type of data is preferable?
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IndexMeasure PhaseAverage
Which type of data is preferable?
Continuous data helps you to understand process variation
Sample size required is less
Discrete data does not allow to understand the process variation. It does not tell you how bad is bad
You need larger samples with Discrete data
Normality Test
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Normality Test
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Data is normal as p-value > 0.05
Effort Based Defect Density
Percent
0.070.060.050.040.030.020.010.00-0.01-0.02
99
95
90
80
70
60
50
40
30
20
10
5
1
Mean
0.188
0.02714
StDev 0.01890
N 7
AD 0.450
P-Value
Probability Plot of Effort Based Defect DensityNormal
IndexMeasure Phase
Graphical Summary
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Graphical Summary
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Data is normal as p-value > 0.05
Skewness is somewhat close to 0 indicating symmetric data
A negative value of Kurtosis indicates a distribution flatter than normal
0.060.050.040.030.020.01
Median
Mean
0.050.040.030.020.01
A nderson-Darling Normality Test
V ariance 0.000357
Skewness 0.778909
Kurtosis -0.087360
N 7
Minimum 0.010000
A -Squared
1st Q uartile 0.010000
M edian 0.030000
3rd Q uartile 0.040000
Maximum 0.060000
95% C onfidence Interval for Mean
0.009665
0.45
0.044621
95% C onfidence Interval for Median
0.010000 0.045333
95% C onfidence Interval for StDev
0.012178 0.041615
P-V alue 0.188
M ean 0.027143
S tDev 0.018898
95 % Confidence Intervals
Summary for Effort Based Defect Density
IndexMeasure Phase
Count the Occurrence of letter I in the Paragraph
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A country preacher was walking the back-road near a church. He became
thirsty so decided to stop at a little cottage and ask for something to drink. The
lady of the house invited him in and in addition to something to drink, she
served him a bowl of soup by the fire. There was a small pig running around the
kitchen. The pig was constantly running up to the visitor and giving him a great
deal of attention. The visiting pastor commented that he had never seen a pig
this friendly. The housewife replied: "Ah, he's not that friendly. Actually, that's his
bowl you're using!"
Count the Occurrence of letter I in the Paragraph
Plan for data collection
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Ensure DataConsistencyAnd Stability
EstablishData CollectionGoals
DevelopOperationalDefinitions
Clarify purpose of
data collection
Identify what data to
collect
Test and validate
measurement systems
Write and pilot
operational definitions
Develop and pilot data
collection forms and
procedures
Establish a sampling
plan
Collect DataAnd MonitorConsistency
Train data collectors
Pilot process and
make adjustments
Collect data
Monitor data
accuracy and
consistency
1 432
Plan for data collection
What is Operational Definition?
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What is Operational Definition?
A definition that gives communicable meaning to a concept by specifying
how the concept is measured and applied within a particular set ofcircumstances.
-Deming
To remove ambiguityEveryone has a consistent understanding
To provide a clear way to measure the characteristic
Identifies what to measure
Identifies how to measure it
Makes sure that no matter who does the measuring, the results are consistent
Always measure one scale lower than your customer measures
Sampling
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Sampling
Sampling is the process of:
Collecting only a portion of the data that isavailable or could be available, and drawingconclusions about the total population(statistical inference)
Examples :
Blood TestA few dropsof blood is tested to drawconclusion Cosmetic: Asmall sample is applied totest the reaction
Wine tasting
Buy Fruits/Vegetables
Audits:Based on the few process/entity auditedeffectiveness of QMS is implied
Inspection:A few units are checked and the entire lshipped
Election result:Based on the response of few peoplresults are forecasted
Sampling
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Sampling
Random Sampling:
Each unit (X) has an equal probability ofbeing selected in a sample
Population Picking 2 Tickets during the shift for
checking SLA compliance
Picking 30 calls to calculate average
TAT
Systematic Random Sampling
Sampleevery nth Unit
Process
Check every 10thTicket during each
shift for checking Response SLA
compliance
Subgroup Sampling
The population is divided in to subgroups
Process Select 5 tickets resolved by each of
team members during the shift
Stratified Random Sampling
Randomly samplewithin a stratified category or group
Population Select 5 tickets responded by team
member
Measurement System Analysis
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Measurement System Analysis
Quantitative evaluation of the tools and
process used in data collection
Conducted to ensure the informationcollected is a true representation of the
process.
Types of Measurement System Analysis
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yp y y
Operational Definitions Walking the Process
Gage R&R
Variable Data Attribute Data
Gage R & R
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g
Repeatability is the variation
in measurementsobtained with
one measuring instrument when
used several timesby a measurer
while measuring the identical
characteristicon the same part.
Measurement System Analysis
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y y
Gage R&R - Repeatability
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g p y
The term repeatability refers to:
The inherent variability of the measuring system
Variation that occurs when repeated measurements are
made of the same item under absolutely identical
conditions
Same operator
Same setup
Same units
Same environmental conditions
Gage R&R - Reproducibility
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g p y
Reproducibility is the variation in the averageof the
measurements made by different measurersusing
the same measuring instrumentwhen measuring the
identical characteristics on the same item.
Gage R&R - Reproducibility
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g p y
The term reproducibility refers to:
The variation that results when different conditions are
used to make the measurements Different operators
Different setups
Different units
Different environmental conditions
Different measurement systems
Sources of Variation
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Observed Process Variation
ActualProcessVariation
MeasurementVariation
Short-termProcessVariation
Long-termProcessVariation
Variationwithin aSample
Variationdue to
Operators
Variationdue toGage
RepeatabilityAccuracy
Reproducibility
Stability Linearity
Gage R&R - Example
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g p
W
A
B C
Operator 1
Operator 2
Operator3
Values across rowsContribute to
Repeatability
Values across columnsContribute to Reproducibility
Task :Establish Gage R&R for
Measurement of Width of Box
# Measurers :3 # of Samples :3 Gage : VernierCalipers
Gage R & R
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IndexMeasure Phase
Percent
Part-to-PartReprodRepeatGage R&R
100
50
0
% Contribution
% Study Var
SampleRange
0.010
0.005
0.000
_R=0.00467
UCL=0.00987
LCL=0
Operato r 1 Operato r 2 Operato r 3
SampleMean
10.5700
10.5675
10.5650
__X=10.566844
UCL=10.569536
LCL=10.564153
Operato r 1 Operato r 2 Operato r 3
Box Id
CBA
10.5700
10.5675
10.5650
Operator Id
Operator 3Operator 2Operator 1
10.5700
10.5675
10.5650
Box Id
Average
CBA
10.568
10.567
10.566
Operator Id
Operator 1
Operator 2
Operator 3
Gage name: Vernier C alipers
Date of study: 01-02-2005
Components of Variation
R Chart by Operator Id
Xbar Chart by Operator Id
Width (in mm) by Box Id
Width (in mm) by Operator Id
Operator Id * Box Id Interaction
Gage R&R (ANOVA) for Width (in mm)
Process SigmaCommon metric
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IndexMeasure Phase
Which Process Is Performing Best?
Response to a P1 ticket
Billing
Vendor Payment
Customer Survey
11 +/- 5 minutes (Average speed of response)
98 +/-1% (Accuracy)
33 +/- 2 Days (Average delay)
82% (Rated 4 or 5 on Responsiveness)
Process Y Performance
Process SigmaCommon metric
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IndexMeasure Phase
Z = # standard deviation units
between the specification limit and
the mean
ZUSL=
ZLSL=
Process Capability:A measure in Standard Deviation Units (Z) of how far the process meanis from the performance standard.
How far (in standard deviation units) is the mean from the specification (Lines A+B)
s
+1 +2 +3-1-2-3
LowerSpecLimit
6-sigma : the closest
specification is at least 6
standard deviation units (Zs)
away from the mean
Smaller the variation in the process,higher the sigma value
+1 +2 +3-1-2-3
X - LSLs
USL - Xs
s
+4 +5 +6-4-5-6X X
UpperSpecLimit
LowerSpecLimit
UpperSpecLimit
Capability Analysis
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IndexMeasure Phase
Check for NormalityData is considered Normal
only when
P-Value > 0.05
Z Benchis automatically calculated
Analyze Phase - Flow
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Define Measure ImproveAnalyse Control
Quantify the
opportunity
Identify
possiblecauses
Data stratification
Process mapanalysis
Cause and effectdiagrams
Determine thefinancial benefits
Narrow toroot causes
Hypothesis testing
Regressionanalysis
Run Chart
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Example of a Run Chart
Median
A graphical tool to monitor Project Y
Use to develop a preliminary understanding of the variation in a process
Variation Over a Period of Time
Run Chart
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1. Collect 20 or more data values over time
2. Plot the data in time order
3. Pencil in the median line
4. Check for signals of special cause
Slow to detect special causes
Wont detect: Shifts of short duration
Increases In variation
Advantages: Disadvantages:
How to make a Run Chart ?
Can be used for almost any datacollected over time
Easy to plot
No calculations are necessary
Easy to interpret
Provide a baseline for key measures
Run ChartSpecial cause patterns
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Cycle 14 or more consecutivepoints up and down
Find out what wasdifferent about the processaroundthe time the cycle
occurred
Shifts 8 or more points in a row onthe same side of the medianindicate a shift in a keyelement of the process.
Find out what wasdifferent about theprocess around thetime that the shiftoccurred.
Customercomplaintsincrease due tochange in policy
Trends 7 or more points in a rowcontinuously increasing orcontinuously decreasing
indicate a trend.
Find out what wasdifferent about theprocess around the
time that the trendstarted.
Market growth ordecline
A sequence of 7 ormore points having thesame value.
Find out ifmeasurement deviceis stuck.
Poor resolution.
Cycle timemeasured tonearest day
SameValue
Pattern Plot Conclude Action Example
Fluctuations instaffing due toholidays
5 Why Analysis
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1. Whydo we pay invoices some invoices late ?
Because we receive them late from vendors
2. Why do we receive them late ?
Because vendors send invoices in batches
3. Why do vendors send invoices in batches ?
Because individual invoices are not available during shipment
4. Why individual invoices are not available ?
Because invoices are not printed for each transaction
5. Why invoices are not printed for each transaction ?
Because Shipping Dept does not have a printer and no resource to collect individual invoices if printedindividually. Hence printed in bunches.
Use after verifying an Xwith data
Ask why five times toidentify deeper causes
Use process data toanswer each WHY
question
Pareto Analysis
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IndexAnalyze Phase
Incidents
Percent
Servers
Count 380324279263219210210161705
Percent
2587
18 14 10 10 9 8 8 4 3 2
1915
2 2 2 1 1 1 5
Cum % 18 32
1473
42 52 61 69 77 81 83 86 88 89
1393
91 92 94 95100
128211281078567
Othe
r
ONN
N-US
PX1-MS
PPROD
1
ONNN
-SRV
UPDAT
E
ONNN
-SMP
RODQ
A
ONN
N-EV
ALPO
WER
EDGE
ONN
N-US
PX1-
SMPROD
2
ONNN
-SODIU
M
ONN
N-US
PX1-
SMPROD
4
ONNN
-AZ0
1-DDC
M
ONNN
-AZ0
1-LEG
AL-01
ONNN
-NBM
EDIA
ONN
N-AZ
01-PMI
S
ONNN
-USP
X1-SCM
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