SixsigmaIntroduction YB Ver2.0

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


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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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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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6/135

6

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 ?


7/135

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 ?


8/135

8

What is Six Sigma ?

Metric

Goal

Locomotive

Way of LifeCulture

Benchmark

6


9/135

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


10/13510

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)?


11/13511

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...)


12/13512

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


13/13513

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


14/13514

Goal of Six Sigma

To reduce Variation

To reduce defects

To improve yield

To enhance Customer Satisfaction

To improve the Bottomline


15/13515

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)


16/13516

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


17/13517

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


18/13518

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



19/13519

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



20/13520

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 ??


21/13521

6-Sigma as a Goal

-20 -10 0 10 20

What customer sees!!

Customer always looks at , mean is meaninglessvariance


22/13522

A Scientific Management Tool & Philosophy, One Of Its Kind

Six Sigma - Approach


23/13523

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)


24/13524

Defects per millionopportunities

2 308,537

3 66,807

4 6,210

5 233

6 3.4

6-Sigma as a Goal


25/13525

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?


26/13526

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


27/13527

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


28/13528

DMAIC


29/135

29

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


30/135

30

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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INTERNAL INTERMEDIATE FINAL

Business

Management

Employees

Department

Suppliers

Partners

Channel

End customers

Shareholders

Regulators


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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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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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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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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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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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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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58

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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Input

measuresProcessmeasuresOutputmeasures

Define Measure ImproveAnalyse Control

DataCollectionMeasures

6Sigma &

ProcessCapabilityVariation

4 step datacollectionprocess

Graphicaldisplay ofdata

Calculateprocess

sigma

M Ph Fl


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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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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



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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




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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




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M

E

A

S

U

R

E

IndexMeasure PhaseAverage


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


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


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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80

M

E

A

S

U

R

E


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


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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82

M

E

A

S

U

R

E


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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M

E

A

S

U

R

E


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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M

E

A

S

U

R

E


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

M

E

A

S

U

R

E

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

M

E

A

S

U

R

E

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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M

E

A

S

U

R

E

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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M

E

A

S

U

R

E

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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M

E

A

S

U

R

E

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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M

E

A

S

U

R

E

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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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.



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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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Y

Z

E

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

Documents

SixsigmaIntroduction YB Ver2.0