ref_phase2__lean_six_sigma_green_beltv11institute_07072023191233.pdf

lss

1. ©2019 Grant Thornton India LLP. All rights reserved.
Part 2
Lean Six Sigma Green Belt
training programme

2. Lean Six Sigma Green Belt training
programme
–
Part 2Analyzephase
2

3. Lean Six Sigma Green Belt training
programme
–
Part 2
Analyze Phase Roadmap
01
Review the
process map
Brainstorm and
RCA
Apply Lean
Principles
Validate the
assumptions with
Hypothesis
Validate the
Parameters using
Correlation
02 03 04 05
3

4. Lean Six Sigma Green Belt training
programme
–
Part 2
Learning outcomes
At the end of the ANALYZE phase, you will be able to:
Identifying the
Root causes
Applying the
Lean
Principles
Prioritizing
using Pareto
Validate
causes using
Hypothesis
Find the
correlation and
use regression
equation
4

5. Lean Six Sigma Green Belt training
programme
–
Part 2
Root Cause Analysis
What Are The Vital Few Process Inputs And Variables (X’s)
That Affect CTQ Performance Or Output Measures (Y’s) ?
Process Variables (Xs)
Process
Input
Variables
(Xs)
Outputs
(Ys)
5

6. Lean Six Sigma Green Belt training
programme
–
Part 2
Root Cause Analysis
Why do a root cause analysis?
•Use the process data to understand the problem and identify the vital few
root causes in order to reduce variation that the customer experiences.
•Eliminate actions based on intuition and preconceived ideas.
•Recalibrate project scope.
•Establish performance goals for the process.
•Allows teams to develop sustainable process improvements that will lead to
long-term benefits.
•Determine potential benefit of project.
6

7. Lean Six Sigma Green Belt training
programme
–
Part 2
Process Door
Analysis –Lean
Principles
7

8. Lean Six Sigma Green Belt training
programme
–
Part 2
The pioneer of Lean
8
1909 1928
The Ford Model T was an American car built between 1908 and 1928 by the Ford Motor Company of Detroit, Michigan.
It is one of the most important cars in history because it was one of the first cars to be sold for very little money,
making it easy for people to travel from place to place.
Henry Ford’s revolutionary advancements in assembly-line automobile manufacturing made the Model T the first car to
be affordable for a majority of Americans.

9. Lean Six Sigma Green Belt training
programme
–
Part 2
Lean origin
9
1908
Before: cars were built at one spot and the
workers moved from car to car.
After: Ford implemented a moving line and
kept the workers stationary
First Notions of Flow

10. Lean Six Sigma Green Belt training
programme
–
Part 2
Origin of Lean
10
Three men were especially prominent in creating the Toyota Production System (TPS) Lean Enterprise:
Sakichi Toyoda
Sakichi Toyoda was the inventor of Automatic Looms who founded the Toyota Group
Kiichiro Toyoda
Kichiiro Toyoda was the son of Sakichi Toyoda. He travelled to USA to study the Ford Motors operation
system and adapted that to Toyota Production
Taiichi Ohno
Taiichi Ohno rose to become the Executive Vice President of Toyota. He was inspired by the operations
of Walmart and created the Pull System

11. Lean Six Sigma Green Belt training
programme
–
Part 2
What is Lean?
11
“All we are doing is looking at a timeline from the moment the
customer gives us an order to the point when we collect the
cash.And we are reducing that timeline by removing the
non value added steps”
Taiichi Ohno, Toyota Production System 1978
It is all about
waste elimination and flow creation!

12. Lean Six Sigma Green Belt training
programme
–
Part 2
Lean History
12
1900-1940 1940 -1980
1990
WomackHouse of Toyota
“Flow”
1930
1902
“Built in
Quality”
Sakichi
Toyoda
1978
Toyota Production
System
Toyota Motor
Company Ltd
“Improved
Flow”

13. Lean Six Sigma Green Belt training
programme
–
Part 2
Lean pillars –House of Toyota
13
CustomerDemand Leveling
Heijunka
TPS
ToyotaProductionSystem
•Single Piece flow
•Pull production
•Takt time production
•Level
•Loading
•Sequencing
•Stability or Standardized
work KAIZEN
•Built in Quality
•Autonomation
•Stopping at abnormalities

14. Lean Six Sigma Green Belt training
programme
–
Part 2
3M –3 Enemies (Losses)
14
3M
MURA Unevenness
MURI Overburden
MUDA Waste

15. Lean Six Sigma Green Belt training
programme
–
Part 2
Waste: Muda (無駄)
15
Muda Type 2 includes non-value added activities in the
processes, but these activities are unnecessary for the
customer. As a result, Muda Type 2 should be
eliminated.
Muda Type 2
Muda Type 1 includes non-value-added activities in the
processes that are necessary for the end customer.
For example, inspection and safety testing does not
directly add value to the final product; however, they
are necessary activities to ensure a safe product for
customers.
Muda Type 1
Muda means wastefulness, uselessness and futility, which is contradicting value-addition. Value-
added work is a process that adds value to the product or service that the customer is willing to pay
for. There are two types of Muda, Type 1 and Type 2.

16. Lean Six Sigma Green Belt training
programme
–
Part 2
The 8 Classical Wastes
16
•Waste not defined, not easy to see
•Reactive improvement
•Can’t discern sources of waste
•Problems repeat
•Waste is “tangible”
•Identify many small opportunities
•Leads to large overall change
•Continuous improvement
Waste
Defects
Over
Production
Overproce
ssing
Waiting
Motion
Inventory
TransportSkills
Types
of
wastes
WO
O
D
ST
I
M

17. Lean Six Sigma Green Belt training
programme
–
Part 2
Transportation
17
•Poor Ergonomics
•Safety Hazards
•Increased Lead time
Effects:
•Reverse Flow
•Zig-Zag process layout
•Multi-level shop floors
•Non availability of proper MHE
Some Causes:
Movement of information or materials that does not add value. This could be within or outside the
work area.

18. Lean Six Sigma Green Belt training
programme
–
Part 2
Inventory
18
•Huge capital investment
•More space required
Effects:
•Bulk purchases
•Huge variety of items (no commonization)
•Improper line balancing
Some Causes:
A company's merchandise, raw materials, and finished and unfinished products which have not yet
been sold but stored in different stages. Having more than the minimum stocks necessary for the
process.

19. Lean Six Sigma Green Belt training
programme
–
Part 2
Motion
19
•Poor Ergonomics
•Very Low productivity(silent killer)
Effects:
•Zig-Zag process layout
•Non-availability of proper tools
•Work station not fit ergonomically
Some Causes:
Operators / persons making movements that are straining or unnecessary, such as looking for parts,
tools, documents etc.

20. Lean Six Sigma Green Belt training
programme
–
Part 2
Waiting
20
•Process delays
•Productivity loss
Effects:
•No line balancing
•Communication gaps
•Lack of Andon systems
Some Causes:
Operators / persons standing idle as machine cycles or equipment failed or required parts have not
arrived yet..

21. Lean Six Sigma Green Belt training
programme
–
Part 2
Over Production
21
•Erosion in
Profitability
•Increase in
Inventory
Effects:
•High setup
change times
•Fluctuating
demands
•Improper line
balancing
•Inconsistency in
raw material
supplies
Some Causes:
Operators / persons standing idle as machine cycles or equipment failed or required parts have not
arrived yet..

22. Lean Six Sigma Green Belt training
programme
–
Part 2
Over Processing
22
•Erosion in
Profitability
•Increased process
time
Effects:
•Lack of
awareness or
skills
•Process not
studies
•Improper tools
Some Causes:
Providing or creating MORE than the customer specification requirement.

23. Lean Six Sigma Green Belt training
programme
–
Part 2
Defects
23
•Increase in
production cost
•Results in rework
•Results in
shortage
•Increased scrap
Effects:
•Lack of skills
•Machine failures
•Quality errors
Some Causes:
Producing the output not conforming to the specifications of the product.

24. Lean Six Sigma Green Belt training
programme
–
Part 2
8 kinds of waste (muda)
24
T = Transport
I =
Inventory
M =
Motion
W =
Waiting
O =
Over-production
O =
Over-engineering
D = Defects
S =
Skills
…are all linked with each other and reinforcing each other.
To remove waste,
we should recognize waste.
Acronym:TIMWOODS

25. Lean Six Sigma Green Belt training
programme
–
Part 2
Waste Examples
25
WasteType Definition Example
Transportation
Unnecessary movementofitemsresulting inwasted
effortsandcost.
ConveyorBeltsfortransportingrawmaterialfrom
warehousetoplant
Inventory
Pileupofsemiprocessedorfinishedgoodsthatblock
workingcapitalandholdupcashflow.
LoanApplicationspieduponthemanagerstablefor
approval.
Motion
Unnecessary movement of people to perform an
activity.
Pharmacistmovingaroundthewholeshopinorderto fetch
medicinesfromvarious drawers
Waiting Waiting for the next process step. WaitingforyourturntomeetthedoctoratOPDin hospital
Over-Processing Toomuchprocessingofinformation.
Fivetosixreviews/signaturesonPurchaseOrders
beforesendingtoSupplierandyetwrongmaterialgets
delivered.
Over-Production Producingmorethanthe requirement.
Producinggoodsformaintainingmachineutilization
inspiteofnocustomerneedororder.Over productionwill
alwaysleadtoinventorybuildup.
Defects Anyprocessoractivitythatresultsinrework.
Cardoorsrejectedinpaintshopduetodentsorsurface
unevenness.
Skills
Overutilizationorunderutilizationofskills. Engineerbeingusedasoperatorforoperatingmachine.

26. Lean Six Sigma Green Belt training
programme
–
Part 2
Waste: Mura (斑)
26
Mura means unevenness, non-uniformity, and irregularity. Mura is the
reason for the existence of any of the seven wastes. In other words,
Mura drives and leads to Muda.
For example, in a manufacturing line, products need to pass through
several workstations during the assembly process. When the capacity
of one station is greater than the other stations, you will see an
accumulation of waste in the form of overproduction, waiting, etc. The
goal of a Lean production system is to level out the workload so that
there is no unevenness or waste accumulation.
Mura can be avoided through the Just-In-Time ‘Kanban’ systems and
other pull-based strategies that limits overproduction and excess
inventory. The key concept of a Just-In-Time system is delivering and
producing the right part,
at the right amount, and at the right time.

27. Lean Six Sigma Green Belt training
programme
–
Part 2
Waste: Muri (無理)
27
•Muri means overburden, beyond one’s power, excessiveness,
impossible or unreasonableness. Muri can result from Mura and in
some cases be caused by excessive removal of Muda (waste) from
the process.
•Muri also exists when machines or operators are utilized for more
than 100% capability to complete a task or in an unsustainable way.
Muri over a period of time can result in employee absenteeism,
illness, and breakdowns of machines.
•Standardize work can help avoid Muri by designing the work
processes to evenly distribute the workload and not overburden any
employee or equipment.

28. Lean Six Sigma Green Belt training
programme
–
Part 2
Principles of Lean Thinking
28
1. Identify
Value
2. Map
The Value
stream
5. Perfection
Seek perfection
4. Pull
Establish Pull
3. Flow
Create flow
The Lean Enterprise Institute (LEI), founded by James P.
Womack and Daniel T. Jones in 1997, introduced the five
key lean principles: value, value stream, flow, pull, and
perfection.

29. Lean Six Sigma Green Belt training
programme
–
Part 2
Principle 1 –Identify Value
29
What is value?
Who defines value?
According to Womack and Jones –Value is expressed in terms of a specific product or service (or both) which meets
customers’ need at a specific price at a specific time.
The key question to be asked here is –What is the timeline? What is the price point? What are the other requirements
that must be met?
Account opening takes 3 to 4 days
Introduction of instant account opening
with online documentation
Providing value to the customers is the only reason for the existence of our business.

30. Lean Six Sigma Green Belt training
programme
–
Part 2
Principle 2 –Map the value stream
30
According to Womack and Jones –Mapping the value stream is a step in taking a specific product or service (from
scratch) to its final recipient i.e. the end customer.
What is a Value Stream?
•Value stream map is a sequence of steps taken to create product / service to the end customer
•Value stream mapping identifies the Value Added (VA) / Non-Value Added (NVA) / Value Enablers (VE) steps in a
process and quantifies time spent on each step
•Eliminate the NVA’s that contribute to the highest time to the process.
Supplier Value Stream Supplier
Sub Process / Activities
Start Finish

31. Lean Six Sigma Green Belt training
programme
–
Part 2
Principle 3 –Create Flow
31
What is a Flow?
It is a movement of the product or service from the supplier to the end customer
Womack and Jones advises –“make the value creating steps occur in tight sequence, such that the product or
service flow smoothly towards the end customer.”
•The rationale behind flow is that the product or service flow smoothly in the value chain without interruptions
•Waiting time and hand-offs are eliminated from the process flow
Customer walks in the
bank for account opening
Customer walks in the
bank for account opening
Customer walks in the
bank for account opening
Customer documentation rework,
applications are waited at the branch
before sending it across to the main
processing center

32. Lean Six Sigma Green Belt training
programme
–
Part 2
Principle 4 –Establish Pull
32
Pull is the movement of product or service from the supplier to the customer
only when the customer needs it.
•Making or processing the product only when there is a customer demand
•Create a “Just in Time” manufacturing or delivery
•Reduced storage, stockpile, inventory
Customer places an
order online
Order Processing Customer receipt of order
Customer Pull’s from the
value stream

33. Lean Six Sigma Green Belt training
programme
–
Part 2
Principle 5 –Seek Perfection
Perfection or Continual Improvement is a never ending
journey towards delivering world class product or service to
your end user or customer.
•Mistake proof the process
•Include process improvement as part of the organization
culture
•Continuously keep fine tuning the process
•Restart from 1 to 4
33

34. Lean Six Sigma Green Belt training
programme
–
Part 2
What is a value stream?
34
•A value stream is all the activities required to bring a service/product
from a customer request to fulfillment/completion.
•All the activities involved in creating value for thecustomer
•The process starts with raw material or information and ends with the
endcustomer.
•The process involves functions both internal and external to thefirm.
•Activities can be described as value added (VA) or non-value
added(NVA)
•Value stream mapping (VSM) is a method of creating a picture which
shows the flow of information, material, activities and people through
a process from end to end.
•It uses a standard set of symbols and metrics and enables the
identification of value (through the eyes of the customer) and the
identification of
•It can then be used to identify opportunities for improvement.
•Value Stream Maps can be used to understand the current process
and can also be used to design the future state process.

35. Lean Six Sigma Green Belt training
programme
–
Part 2
What value stream mapping can show….
35
•Material flow/movement.
•Information flow.
•People movement.
•Tools and equipment movement.
•Inventory levels.
•Value added time versus lead time.
•Level of rework at each step.
•Waste.
•Systems.
•Activities.

36. Lean Six Sigma Green Belt training
programme
–
Part 2
What does VSM look like?
36
Middle Office
Allocation of Breaks
(flown into the system)
Post settlement team
1 Min
Manual Proposed
Matching
Reconciliation
Identify the reason for
Breaks and resolve the
same
Vol: 75
CT ~15 min (for one
Investigation)
FTE: 17
Investigation
15 min
Collateral relating to
mortgage is registered
Charge based on
jurisdiction
Action/Amendment
10 mins
Match off in Internal
system and provide
comms to client
Matching
1 Min
700 breaks
Internal: 500
breaks
300+300 CP
breaks
Internal:
50+50 CP
breaks
Matching Logic for
proposed matching of
Internals to be revisited
No auto
population using
query
Create SOP for
handling Breaks
Have standard e-
mail template
RSU responsibility
being done by the team
in Chennai
Auto Allocation of Mails
using macros and rules
in outlook
Approximately Daily volume
Post Setts: 2,000 Breaks
Internals: 600 Breaks
FTE: ~4FTE
Post Settlement Confirmed
Trade ~ 2,000 daily transactions
1 Min
Vol: 60
CT ~1 min (for one
proposed match)
FTE: 15
Vol: 30
CT ~1 min (for one break
allocation)
FTE: 5
Vol: 90
CT ~10 min (for one request)
FTE: 10
Vol: 105
CT ~1 min (for one request)
FTE: 19
C/T = 28 mins
Lead time = 23,640 mins
Value Add % = 0.12%
Client
The diagram below shows an example value stream map. The example is taken from the investment bank and shows the
flow of a trade through IB operations where there is a requirement for manual intervention to settle.
IRD –Post Settlement/Internals –VSM

37. Lean Six Sigma Green Belt training
programme
–
Part 2
Why use a value stream map?
37
Suppliers
•Provides an overview of the end to end value stream.
•Links information and material flows.
•Enables the visualization of waste within the system.
•Enables clear targeting of waste elimination.
•Acts as a good communication tool for operations.
•Provides a framework for improvement discussions.
•Enables discussion as to how an operation functions and how it should function.
•Prevents operations from focusing on large improvement opportunities that have little impact.
01 Processes02 Customers03
Value Stream

38. Lean Six Sigma Green Belt training
programme
–
Part 2
Value Stream Mapping -Symbols
38
Customer
Supplier
Processing Box
•C/T:12s
•C/O: 15min
•1Worker
ProcessBox
Worker /Operator
PushArrow
Transport
FinishedGoods
Withdrawal
Digital InformationFlow
Manual InformationFlow
Document
IdeaProblem
ManualObservation
Database

39. Lean Six Sigma Green Belt training
programme
–
Part 2
VSM Step by Step Guide
39
Lead
Time Ladder
Material Flow
Information Flow

40. Lean Six Sigma Green Belt training
programme
–
Part 2
VSM Step by Step Guide
40

41. Lean Six Sigma Green Belt training
programme
–
Part 2
Calculate metrics
41
Timeline
•A timeline shown below the process map helps to illustrate value added versus non value added time.
Value added
Total value
added time =
Lead time =
Non value added
•Dividing the value added time by the total time gives an indication of waste levels (Efficiency of
process/Value added ratio –VAR).
•A similar process can be used to capture other information e.g. inventory levels and distance travelled.

42. Lean Six Sigma Green Belt training
programme
–
Part 2
Waste analysis
42
All other meaningless,
non essential activities i.e. eight
waste categories. Aim is to
Eliminate.
Any activity that physically changes
the material or information being
worked on and increases its value.
Aim is to Maximise.
Waste (Non Value Added) Value Added
Any work carried out, which is
necessary under current conditions
but does not increase value
e.g.Compliance. Aim is to
Minimise.
Necessary (Non Value Add)
We can divide work into three categories:

43. Lean Six Sigma Green Belt training
programme
–
Part 2
Review the Process Map
43

44. Lean Six Sigma Green Belt training
programme
–
Part 2
Exercise –Analyze the process map
44
Basedontheapproach for
ProcessAnalysis explainedin
previous slide
Overutilizationorunderutilizationoftalent. Engineerbeingusedasoperatorforoperatingmachine.

45. Lean Six Sigma Green Belt training
programme
–
Part 2
Terms you should know
45
1
Inventory
Build up of work between steps in the process that prevents seamless flow to the customer.
Lead time
The time taken for the development and delivery of a product or service to a client from the time
the request was made.
Necessary non value add
A step that does not directly impact the customer but it’s important in terms of compliance and
legal guidelines. E.g. compliance guidelines; regulatory guidelines to be adopted.
Non value add step (NVA)
Meaningless/non essential activities that do not add value to the customer i.e. eight waste
categories.
Cycle Time (C/T)
The time an operator/analyst takes to complete a step in the process.01
02
03
04
05

46. Lean Six Sigma Green Belt training
programme
–
Part 2
Terms you should know
46
Pull
A flow mechanism where products or services are pulled through the value stream once
they are required to be worked on next.
Push
A flow mechanism where products or services are pushed through the value stream
once complete.
Queue Time
The waiting time or the idle time between steps, its also known as Lag time.
Value Add (VA)
The steps which physically changes the material or information being worked on and
increases itsvalue
Process Map
A term used to describe a portrayal of the operation, systems, people and process with
supporting documentation accompanying each process step.
06
07
08
09
10

47. Lean Six Sigma Green Belt training
programme
–
Part 2
Points to Remember
47
•Start with the customer –information flow
•Identify the product or service that is being worked on
•Determine your process steps from cradle to grave
•Identify the time it takes to perform the task without delays
(starting or within the process) or interruptions within the total
cycle time
•Identify and quantify the time it takes to perform the task including
delays and interruptions–lead time (LT = CT + delays)
•Investigate the causes of the waste between processes –what
are the barriers to flow?
•Calculate total processing time (cycle time) versus total lead
time(throughput/turnaround)

48. Lean Six Sigma Green Belt training
programme
–
Part 2
Data Door
Analysis –Six
Sigma Principles
48

49. Lean Six Sigma Green Belt training
programme
–
Part 2
Brainstorming
49
Alex Osborn
The word brainstorming was originally introduced byAlex F.Osbornin 1953 through his book Applied
Imagination: Principles and Procedures of Creative Thinking.
Osborn suggested that the participants in the group should have varying amounts of experience in the task
that was at hand, however, he discouraged mixing participants from various levels in the company’s
hierarchy within a brainstorming group. Other specifics that Osborn suggested were that participants had to
be adequately informed in advance about the problem that would be tackled during the brainstorming session
so that the creative focus would be on the specific problem.

50. Lean Six Sigma Green Belt training
programme
–
Part 2
Taking to next level
50
•Statutory Norms
•Global Policies
•Acts of God
•Environmental Issues
Stated as “LACK OF…..”
Provide ones that are feasible with
regards to cost and ease of
procurement. This will lead to buy
in from the workforce and help in
implementation phase
Three Categories
•Events –Validated through
Pareto and Why? Why? Why?
Analysis
•Theories –Validated through
Hypothesis Testing. P<0.05
validates root cause
•Parameters –Validated through
Regression Analysis. Fit
Regression Model
Direct Improvement Causes Likely Root CausesNon-Controllable Causes
Brainstorming + Affinity
List of Potential Causes

51. Lean Six Sigma Green Belt training
programme
–
Part 2
Cause and Effect diagram
51
Y
(Effect)
Measurement Methods Machinery
Mother Nature People Materials
A visual tool used by an improvement team to brainstorm and logically organize possible causes for a
specific problem or effect.
Potential High
Level Causes (Xs)
•Summarize potential high-level causes.
•Provide visual display of potential causes.
•Stimulate the identification of deeper potential causes.

52. Lean Six Sigma Green Belt training
programme
–
Part 2
Cause and Effect Diagram
52
People Machinery
Measurement Methods
Why is there a
delay in
processing?
Brainstorm the “major” cause categories and connect to the centerline of the Cause & Effect diagram.

53. Lean Six Sigma Green Belt training
programme
–
Part 2
Example of Fish Bone Diagram
53Delayed or
Incorrect
Payments
Staff Procedures
Management
Customer
Location
Equipment
Poor Location
Bad weather can
Delay Post Bags
Parking for
B5+ only
Noisy
environment
Poor Facilities
Premises cramped
Poor toilets
Small staff room
Office too hot &
stuffy
No Co-operation
Between
departments
Temperature
Not even in
office
Picking & choosing work
Workload
stress
Poor staff
knowledge
Incorrect filing
Incorrect inputs
By staff
No sort code
prep
Lack of Resource
Staffing problems
Too much workload
Short or no
lunches
Difficult for staff to
get time off
Understaffed team
Low staff morale
Never leave on
time
Blamed for lost
payments
Nanny state
Lack of Training
Staff thrown in at the
deepend
Lack of big picture
awareness
Staff are clicky
Inconsistencies
No clear cut off for bringing payments over at the
end of the day
Poor CMR management
Referrals not actioned
Unclear Procedure documents
Difficulty understanding cut off
times
Too much jargon
Unclear Guidelines
Procedures not trained
Unnecessary
procedures cause delays
More training required for
new staff
Lack of training means
payments go back more
than once
Communication
Poor communication
Not enough feedback
Ops perceived as poor relations
Poor Planning
No Management
forecasting
No capacity planning
Too much expected of
staff from Management
Low morale due to
Mismanagement of staff
Poor Team Management
Not accessible
Lack of incentives
No time to lead the team
Staff not praised
Customer Education
Bulk payments
Illegible details from
customer letter
Customers too
demanding
Lack of information
provided
Unaware of cut off times
Or pricing
RM’s hard to get hold of
for the customer
Favours for local corporates
Don’t keep KYC up to date
Persistent IT failure
Intermittent software
failures
Systems unstable
Eclipse unrealiable
AFTS goes slow at times
Customer System down
time
Screen quality
AFTS screen too small
Can’t always read account
amount on screen

54. Lean Six Sigma Green Belt training
programme
–
Part 2
Sorting the Possible Causes
54
These are causes that the team
unanimously conclude are beyond
the control of the present process
boundaries or outside the physical
location of the process execution.
These are causes that are actually
solutions that can be implemented
directly and need no further
analysis. They are usually stated
as lack of resources, equipment,
tools or training.
Lack of Solution OR Direct
Improvements
These causes are the causes that
have passed the above two filters
and need further analysis.
Likely and Controllable CausesNon-Controllable Causes

55. Lean Six Sigma Green Belt training
programme
–
Part 2
Why-Why analysis
55
•The immediate next step after the segregation is to attack the likely and controllable causes and ask at least 3 –5
why’s?….. for each cause. This is called root cause drill down.
•Only after we have asked why 3 -5 times to each of the likely causes, we will be able to arrive at the possible root
cause, also known as KPIV.

56. Lean Six Sigma Green Belt training
programme
–
Part 2
A Monumental Mystery
56
Problem:
The Jefferson Monument in
Washington DC was falling
apart/ deteriorating.
1. Why?:
Because of usage of Harsh Chemicals to clean the monument.
2. Why?
Harsh chemicals were used to clean bird droppings
3. Why?
Birds Feasted on spiders on the monument
4. Why?
Spiders Feasted on Midgets/ Gnats on monuments
5. Why?
Midgets/ Gnats were attracted to the lights at dusk.
Root Cause: Timing of
the dusk lights.

57. Lean Six Sigma Green Belt training
programme
–
Part 2
Pareto Analysis
57
What is a Pareto Diagram?
•A Pareto chart is a bar chart that graphically ranks defects from largest to smallest, which can help prioritize quality
problems and focus improvement efforts on areas where the largest gains can be made.
•Pareto analysis was conceptualized by an Italian economist –Vilfredo Pareto.
•In his endeavor, Pareto tried to prove that distribution of wealth and income in societies is not random, but there is a
consistent pattern.
•In his study –Principle of Unequal Distribution, he proved that 80% of wealth in Italy is controlled by 20% of elite.
•The concept was formulated in six sigma by Dr Joseph Juran.
•Juranextended this principle of 80-20 to quality control stating that most defects in a production are a result of small
percentage of the cause of the defects –which he described as “vital few from trivial many”.
•Therefore, Pareto analysis is based on the principle that 80% of problems find their roots in 20% causes.
•In other words, it is a diagram that shows 20% of the inputs (X’s) cause 80% of the problems with dependent
process outputs (Ys).

58. Lean Six Sigma Green Belt training
programme
–
Part 2
Pareto Analysis
58
Minitab path:
Refer the data: “Clothing Defect”.
•Click on Stat → Quality Tools → Pareto
Chart.
•In Defects or attribute data in, enter
Defect.
•In Frequencies in, enter Count.
•Select Combine remaining defects into
one category after this percent, and enter
95.
•Click OK.

59. Lean Six Sigma Green Belt training
programme
–
Part 2
Pareto Analysis
59
In the above graph, 45.2% of the defects are missing buttons and 23.3% are stitching errors. The cumulative
percentage for missing buttons and stitching errors is 68.5%. Thus, the largest improvement to the entire clothing
process might be achieved by solving the missing button and stitching problems.

60. Lean Six Sigma Green Belt training
programme
–
Part 2
Tackling the other causes
60
•The non-controllable causes need to be factored into the improved
process so that they do not affect the Process Capability.
•The team should launch initiatives to implement actions for the lack
of solutions or direct improvements. This can happen in parallel as
the project progresses.

61. Lean Six Sigma Green Belt training
programme
–
Part 2
Hypothesis
Testing
61

62. Lean Six Sigma Green Belt training
programme
–
Part 2
Hypothesis Testing
62
•Hypothesis testing is a statistical test used to determine if the
hypothesis that was assumed for the sample of data is true for the
entire population or not.
•Hypothesis testing is a method for testing a claim or hypothesis
about a parameter in a population, using data measured in a
sample.
Examples:
•Hypothesis testing is a statistical test used to determine if the
hypothesis that was assumed for the sample of data is true for the
entire population or not.
•Hypothesis testing is a method for testing a claim or hypothesis
about a parameter in a population, using data measured in a
sample.

63. Lean Six Sigma Green Belt training
programme
–
Part 2
Why Hypothesis Testing?
63
•There are certain times when a graph or computed statistics
cannot tell us whether a difference between two processes is
statistically significant or not. In these scenarios, the decision could
be unexpected or uncertain. Therefore, a statistical hypothesis test
is performed to determine whether there is a difference.
•We use hypothesis test In the Analyze Phase to verify the potential
vital few inputs or causes to confirm which are the true or actual
vital few inputs or causes.
•To evaluate and quantify the improvement, we use hypothesis
testing in the improve phase.
•In the control phase, hypothesis test is used to verify that the
implementation is producing the expected outcomes.

64. Lean Six Sigma Green Belt training
programme
–
Part 2
Hypothesis Testing Steps
64
•State the hypothesis (Null & Alternative)
•Set the criteria for a decision (Level of significance “α” )
•Select the appropriate hypothesis test
•Calculate the test statistic
•Make decision (Fail to reject Null or Reject Null)

65. Lean Six Sigma Green Belt training
programme
–
Part 2
Types of Hypothesis
65
•There is a significant difference between the two or
more groups that were selected for the test.
•The term “Alternative hypothesis" refers to a claim
that completely contradicts a null hypothesis by
asserting that the true value of a population
parameter is greater, less, or not equal to the value
given in the null hypothesis.
•Alternate hypothesis is the purpose of the study.
What we are trying to prove.
Example:
•The call resolution time for Team A is not equal or
more than or less than Team B for the same
process.
•Which can be represented as H1: µ1 ≠ µ2 or µ1 >
µ2 or µ1 < µ2
Alternative hypothesis (H1 / Ha):
•Null is the hypothesis which is tested.
•There is NO significant difference between the two
or more groups that were selected for the study
•Null Hypothesis is considered as the Status Quo.
Meaning, there is no change between sample
statistics and population parameter.
Example:
•The call resolution time for Team A is same as
Team B for the same process.
•Which can be represented as H0: µ1 = µ2
Null hypothesis (H0):

66. Lean Six Sigma Green Belt training
programme
–
Part 2
Significance Level (“α”)
66
•The decision to reject or retain the null hypothesis is
called significance.
•The threshold value or criteria by which one can
reject or fail to reject the null hypothesis is known as
the level of significance.
•In other words, the risk of rejecting the null hypothesis
when it is true.
Significance Level (“α”)

67. Lean Six Sigma Green Belt training
programme
–
Part 2
Determining Significance Level (“α”)
67
•Most used Confidence level is 95% or we can say
that in decimals it is 0.95.
•Confidence level states that at what level of
confidence you want your hypothesis or
assumption to be true.
•Level of significance (α) = 1 –confidence level =
1 -0.95 = 0.05 or 5%
•For critical processes we use confidence level at
99% (Ex: Aviation Industry, Pharmaceutical etc.)
•In those cases, Level of significance (α) = 1 -
0.99 = 0.01 or 1%

68. Lean Six Sigma Green Belt training
programme
–
Part 2
Risk of Hypothesis
68
Null Hypothesis is…… False True
Rejected Correct Decision (True Positive)
Fail to Reject Correct Decision ( True negative)
Now as we know that there are some %age of risks (Ex: 10%, 5%, 1%) involved while taking the decision so let
us know about what are those risks.
Null Hypothesis is…… False True
Rejected
Type I Error, False Positive,
Alpha “α” Error and Producer risk.
Fail to Reject
Type II Error, False Negative,
Beta “β” Error and Consumer’s risk.

69. Lean Six Sigma Green Belt training
programme
–
Part 2
Risk of Hypothesis
69
Null Hypothesis is…… False True
Rejected
Means, I will be treated for Malaria,
and I am infected. Which is true
positive.
Fail to reject (accepted)
Means, I will be not treated for
Malaria, and I am not infected. Which
is true negative.
Example:
Let's consider a hypothetical example, I am having fever and I am assuming that I am malaria positive.
So here,
Ho = I am not Malaria positive, and
Ha = I am Malaria positive

70. Lean Six Sigma Green Belt training
programme
–
Part 2
Risk of Hypothesis
70
Null Hypothesis is…… False True
Rejected
•Means, I will be treated for
malaria when I am not infected.
Which is false positive.
•Alpha “α” Error
•Type I Error
Fail to reject (accepted)
•Means, I will not be treated for
malaria while I am infected. Which
is false negative.
•Beta “β” Error
•Type II Error

71. Lean Six Sigma Green Belt training
programme
–
Part 2
Type I Error (“α” Error)
71
Example:
Let's consider another example,
•An automotive company had set a limit of 2% defective for the auto components it receives from one of its vendor.
•A sample of 1000 parts taken for inspection out of 5000 lot. Out of which, 30 parts found defective means 3%
defective which is greater than the acceptable limit of 2%.
•The shipment was rejected by the customer.
•A 100% inspection was done by vendor, and they found that only 55 parts were defective in that lot. Which means
only 1.1% defective.
•In this scenario, 1.1 percent of the parts were defective as compared to an acceptable level of 2%, hence rejecting
the shipment was an error.
•If we convert this scenario into hypothesis language, we can say that the null hypothesis is rejected but, the lot was
well within acceptable limit.
•In this case we have committed Type I error or “α” error. This is also known as producer’s risk because the
manufacturer or the producer is affected

72. Lean Six Sigma Green Belt training
programme
–
Part 2
Type II Error (“β” Error)
72
Example:
In the same example,
•A sample of 1000 parts taken for inspection out of 5000 lot. Out of which, only 11 parts found defective means 1.1%
defective which is less than the acceptable limit of 2%.
•The shipment was accepted.
•But while using the components it was found that there were 130 defective parts in the lot. Which means 2.6%
defective.
•In this scenario, 2.6% of the parts were defective as compared to an acceptable level of 2%, hence accepting the
shipment was an error.
•If we convert this scenario into hypothesis language, we can say that we failed to reject the null hypothesis while,
the lot was not within acceptable limit.
•In this case we have committed Type II error or “β” error. This is also known as consumer’s risk. Because here the
consumer is affected

73. Lean Six Sigma Green Belt training
programme
–
Part 2
How to select hypothesis!!!
73
Comparing
With 1 set of data to a specific
standard (1:Standard)
With 1 set of data with
another set of data (1:1)
With More than 2 or
multiple sets of data
For Mean
(Continuous Data)
•1 sample Z-test (More than 30
samples)
•1 sample t-test (</= to 30
samples)
•2 sample t-test
(Independent groups)
•Paired t (Dependent
groups)
•One-way Annova
For Proportion(%)
(Discrete Data)
•For Proportion(%) (Discrete
Data)
•2 proportion test
•Chi-Square Test for
association

74. Lean Six Sigma Green Belt training
programme
–
Part 2
Path for Hypothesis tests in Minitab (Reference)
74
Type of Test (Mean) Path
1-Sample Z Stat > Basic Statistics > 1-Sample Z…
1-Sample t Stat > Basic Statistics > 1-Sample t…
2-Sample t Stat > Basic Statistics > 2-Sample t…
Paired t Stat > Basic Statistics > Paired t…
One-Way Anova Stat > ANOVA > One-Way…
Type of Test (Proportion) Path
1 Proportion Stat > Basic Statistics > 1 Proportion…
2 Proportion Stat > Basic Statistics > 2 Proportion…
Chi-Square Test for Association Stat > Tables > Chi-Square Test for Association…

75. Lean Six Sigma Green Belt training
programme
–
Part 2
Path for Hypothesis tests in Minitab
75
1-Sample Z
1-Sample t
2 Proportions
2-Sample t
1 Proportion
Paired t

76. Lean Six Sigma Green Belt training
programme
–
Part 2
One-WayANOVA
Path for Hypothesis tests in Minitab
76

77. Lean Six Sigma Green Belt training
programme
–
Part 2
Path for Hypothesis tests in Minitab
77
Chi-Square Test for Association

78. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Sample Z test
78
When to use:
When the population
standard deviation is
known, sample size is
more than 30, 1-
sample z test is
performed to compare
the sample mean to the
population mean.
Assumption:
•Data should be
continuous
•Should be following
a normal distribution
•Population Standard
deviation should be
known
Case Study
Example:
A team leader is
claiming that his team's
call resolution time is
less than that of the
company standard
which is currently at 33
minutes. To prove his
claim, his manager took
last 60 days data with a
population standard
deviation of 1.5
minutes. Help him to
prove whether the team
leader's claim.
Hypothesis:
Ho: µ = 33 (Avg. call
resolution time = 33
min.)
Ha: µ < 33 (Avg. call
resolution time < 33
min.)

79. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Sample Z test
79
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Basic Statistics > 1-Sample Z..)
•Step 3: Select the column from the work sheet
•Step 4: Enter the known SD and select the perform hypothesis test
and enter hypothesized mean
•Step 5: Go to options & select Confidence level & Alternative
hypothesis

80. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Sample Z test
80
Test Result
Inference
•Sample Mean = 32.152
•The 95% upper bound for mean is 32.471 means, in the
current context, the maximum mean value for the population
would be 32.471.
•As the hypothesized mean is more than the 95% upper
bound, we can say that the test is significant, and we can
reject the null hypothesis.
•P-Value is 0.000 < 0.05. Reject Null Hypothesis.
•The claim is valid
Note:
•Easy Remember Technique:
•“P” Low Null should go. (Reject Null)

81. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Sample T test
81
When to use:
When the population
standard deviation is
unknown, sample size
is less than 30, 1-
sample T test is
performed to compare
the sample mean to a
standard mean.
Assumption:
•Data should be
continuous
•Should be following
a normal distribution
Case Study
Example:
One of your competitor
claims to transport
products from point A to
point B in 4 business
days. But your logistics
team assumes that its
more than 4 business
days. They shared with
you the data from that
company's last 30
deliveries. check if your
logistic team is correct
or not?
Hypothesis:
Ho: µ = 4 (Avg.
transportation time = 4
business days)
Ha: µ > 4 (Avg.
transportation time > 4
business days)

82. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Sample T test
82
•Step 1:Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Basic Statistics > 1-Sample t..)
•Step 3: Select the column from the work sheet
•Step 4: Select the perform hypothesis test and enter hypothesized
mean or the standard value
•Step 5:Go to options & select Confidence level & Alternative
hypothesis

83. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Sample T test
83
Inference
•Sample Mean = 5.0833
•The 95% lower bound for mean is 4.9212 means, with the
current sample, the minimum mean value for the population
would be 4.9212.
•As the hypothesized mean is less than the 95% upper
bound, we can say that the test is significant, and we can
reject the null hypothesis.
•P-Value is 0.000 < 0.05. Reject Null Hypothesis.
•The claim of your logistic team is valid
Test Result

84. Lean Six Sigma Green Belt training
programme
–
Part 2
2 Sample T test
84
When to use:
2-sample t test is used
to compare the mean of
two independent
groups.
Assumption:
•Data should be
continuous
•Should be following
a normal distribution
•The samples should
be independent.
Case Study
Example:
A production manager
feels that there is a
difference between
Team A and team B in
assembling a specific
mechanical component.
Last 25 days data
collected. Check
whether he is correct or
not.
Hypothesis:
Ho: µ1 = µ2 (Mean of
team A Assy. time =
Mean of team B Assy.
time) (The difference
will become 0)
Ha: µ1 ≠ µ2 (Mean of
team A Assy. time ≠
Mean of team B Assy.
time) (The difference
will not be 0)

85. Lean Six Sigma Green Belt training
programme
–
Part 2
2 Sample T test
85
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Basic Statistics > 2-Sample t..)
•Step 3: Select the columns from the work sheet (Sample 1
& Sample 2)
•Step 4: Go to options & select Confidence level & Alternative
hypothesis

86. Lean Six Sigma Green Belt training
programme
–
Part 2
2 Sample T test
86
Inference
•The 95% upper & lower bound for the difference in
mean for Sample 1 and sample 2 is (-0.224 to 0.949)
•As the hypothesized difference is falling in the 95%
upper & lower bound difference range, we can say that
the test is not significant, and we can not reject the null
hypothesis.
•P-Value is 0.220 > 0.05. Fail to reject Null Hypothesis.
•We can say that there is no difference between Team A
and Team B
Test Result

87. Lean Six Sigma Green Belt training
programme
–
Part 2
Paired T test
87
When to use:
Paired t test is used to
compare the mean of
two dependent groups.
Assumption:
•Data should be
continuous
•Should be following
a normal distribution
•The samples should
be dependent
Case Study
Example:
Researchers have
developed an additive
to improve the mileage
of petrol cars. They
chose 15 cars and
measured their mileage
in the lab condition,
with and without
additive. Use
hypothesis test to
check whether the
additive is effective or
not?
Hypothesis:
Ho: µ1 = µ2 (Mileage of
cars without additive =
Mileage of cars with
additive) (The
difference will become
0)
Ha: µ1 < µ2 (Mileage of
cars without additive <
Mileage of cars with
additive) (The
difference will be less
than 0)

88. Lean Six Sigma Green Belt training
programme
–
Part 2
Paired T test
88
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Basic Statistics > Paired t..)
•Step 3: Select the columns from the work sheet (Sample 1 &
Sample 2)
•Step 4: Go to options & select Confidence level & Alternative
hypothesis

89. Lean Six Sigma Green Belt training
programme
–
Part 2
Paired T test
89
Inference
•The 95% upper bound for the difference in mean for
Sample 1 and sample 2 is -0.351.
•As the hypothesized difference is more than the 95%
upper bound difference, we can say that the test is
significant, and we can reject the null hypothesis.
•P-Value is 0.001 < 0.05. Reject Null Hypothesis.
•We can say that the mileage of cars without additive is
less than that of with additive.
Test Result

90. Lean Six Sigma Green Belt training
programme
–
Part 2
One-Way ANOVA
90
When to use:
ANOVA is used to
compare the mean of
more than 2
independent groups.
Assumption:
•Dependent
variableshould be
continuous
•Should be following
a normal distribution
•The samples should
be independent
Case Study
Example:
Three plants of ABC
Automotive Ltd. In
Noida, Bengaluru &
Chennai are producing
similar parts. The CEO
of the company wants
to identify if there is a
difference in throughput
time between the
plants.
Hypothesis:
Ho: µ1 = µ2 = µ3
(Mean throughput time
of Noida = Bengaluru =
Chennai) (All means
are equal)
Ha: µ1 ≠ µ2 = µ3 or µ1
= µ2 ≠ µ3 (Mean
throughput time of
Noida ≠ Bengaluru =
Chennai or Noida =
Bengaluru ≠ Chennai)
(At least one mean is
different or Not all
means are equal)

91. Lean Six Sigma Green Belt training
programme
–
Part 2
One-Way ANOVA
91
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > ANOVA > One-Way…)
•Step 3: Select the columns from the work sheet into responses (Type of confidence interval)
•Step 4: Go to options & select Confidence level & Alternative hypothesis
•Step 5: Go to Graphs select the interval plot

92. Lean Six Sigma Green Belt training
programme
–
Part 2
One-Way ANOVA
92
Inference
•P-Value is 0.263 > 0.05. Fail to reject null.
•In the Interval plot, overlap of means can be observed in the 95% CI.
•We can conclude that there is no significant difference in the means.
Test Result

93. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Proportion Test
93
When to use:
1 proportion test is used to
determine whether a population
proportion is significantly
different from a hypothesized
value.
Case Study Example:
A political party is thinking to
support an independent
candidate from a particular
constituency. But the party
decided to support only if more
than 55% of the constituency
support him. Your team collected
the data of 1640 people and
found that 870 have chosen to
vote him. Suggest the party to
take decision
Hypothesis:
Ho: p = 0.55 (Proportion of
people supporting = 55% or less)
Ha: p > 0.55 (Proportion of
people supporting > 55%)

94. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Proportion Test
94
•Step 1: Select the path (Stat > Basic Statistics > 1 Proportion)
•Step 2: Select the summarized data from drop down
•Step 3: Enter the data in the given area
•Step 4: Select the perform hypothesis test and enter
hypothesized proportion.
•Step 5: Go to options & select Confidence level & Alternative
hypothesis

95. Lean Six Sigma Green Belt training
programme
–
Part 2
1 Proportion Test
95
Inference
•Sample proportion = 0.53
•The 95% lower bound for p is 0.510217 means, with the
current sample, the minimum proportion for the
population would be 0.51 or 51%.
•As the 95% lower bound proportion is less than
hypothesized proportion, we can say that the test is not
significant, we failed to reject the null hypothesis.
•P-Value is 0.944 > 0.05. Fail to reject Null Hypothesis.
•Proportion of people supporting the candidate is equals
to 55% or less
Test Result

96. Lean Six Sigma Green Belt training
programme
–
Part 2
2 Proportion Test
96
When to use:
2 proportion test is used to
determine whether there is
significant difference between
proportion of two groups.
Case Study Example:
A manager wants to validate if
the defect percentage in night
shift is more than the day shift.
He collected data of the last 6
months.
Hypothesis:
Ho: p1 -p2 = 0 (Defect
proportion in night shift = Defect
proportion in day shift) (The
difference will become 0)
Ha: p1 -p2 > 0 (Defect
proportion in night shift > Defect
proportion in day shift) (The
difference will > 0)

97. Lean Six Sigma Green Belt training
programme
–
Part 2
2 Proportion Test
97
•Step 1: Select the path (Stat > Basic Statistics > 2 Proportion)
•Step 2: Select the summarized data from drop down
•Step 3: Enter the data in the given area (Sample 1 & Sample 2)
•Step 4: Select the perform hypothesis test and enter
hypothesized proportion.
•Step 5: Go to options & select Confidence level & Alternative
hypothesis

98. Lean Six Sigma Green Belt training
programme
–
Part 2
2 Proportion Test
98
Inference
•Normal approximation P-Value is 0.410 > 0.05. Fail to
reject Null Hypothesis.
•There is no difference in the defect percentage.
Test Result

99. Lean Six Sigma Green Belt training
programme
–
Part 2
Chi-Square Test
99
When to use:
The Chi-Square Test for
Association is used to determine
if there is any association
between two variables.
Case Study Example:
A medical billing company
operating in 6 different regions
across the US, wants to know if
there is a relation in region and
claim denial rate of medical bills.
They have collected last six
months data of different regions.
Verify whether there is an
association or not.
Hypothesis:
Ho: The variables are
independent there is no
association between the
variables
There is no association
between the region and claim
denial rate
Ha: The variables are not
independent. Association
between the variables exist.
There is association between
the region and the claim
denial rate exist

100. Lean Six Sigma Green Belt training
programme
–
Part 2
Chi-Square Test
100
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Tables > Chi-Square Test for Association..)
•Step 3: Select the column containing the data from the work sheet
•Step 4: Enter the labels for the table (optional)
•Step 5: Go to statistics check (tick) the Chi-square test box & in the counts
check both option

101. Lean Six Sigma Green Belt training
programme
–
Part 2
Chi-Square Test
101
Inference
•Pearson P-Value is 0.000 < 0.05. Reject Null Hypothesis.
•There is association between region and claim denial exists.
Test Result

102. Lean Six Sigma Green Belt training
programme
–
Part 2
Probability Value or “P” Value
102
Definition:
•There is a probability is that the samples were taken from the same population that was being analyzed.
Explanation:
•If a sample is taken from a population, the population's characteristics and the sample's statistics won't differ much,
and a high probability value (P-value) would suggest the same.
•A high P-value, like 0.55, indicates that there is 55% chance that the sample represents the population.
•When the P-value is low, for an example 0.01 means there is only a 1% likelihood that the sample represents the
population.
Sample 1
High probability
sample is drawn
from the population
Sample 2
Low probability sample is
drawn from the
population
Population

103. Lean Six Sigma Green Belt training
programme
–
Part 2
Probability Value or “P” Value
103
•We can see that the range of the 95 percent confidence
interval for the mean lies between 9.860 and 10.268. Now let’s
test the three hypothesized means to see how our P-value
changes.
•The P-value will be more than 0.05 if we test new means that
are inside the confidence interval i.e., from 9.860 to 10.268,
less than 0.05 if we test new means that are outside the
confidence interval, and exactly 0.05 if we test new means
those are exactly on the confidence interval i.e., for 9.860 &
10.268
Definition:
•The probability that the value which is being tested will fall within the specified confidence interval at a specified level
of confidence.
Explanation:
•For reference, have a look at the Average Handling Time summary in the graph below.

104. Lean Six Sigma Green Belt training
programme
–
Part 2
Applications of Hypothesis Testing –DMAIC Phases
104
Phase Purpose Intended outcome Preferred type of test
P value
expected
Measure To validate the improvement target
To prove statistical difference between current mean
median and target mean / median
•1 sample t for Normal
•1 sample sign for skewed
P < 0.05
Analyze
To validate Root Causes stated as
theories and to take decision on
whether or not to implement the
change
To prove that the observed difference between the
original data and the trial data is real and change will
significantly benefit the outcome of the process.
•2 sample t
•ANOVA
•2 Proportion
•Chi SQ
•Mann Whitney
•Moods Median
P < 0.05
Improve
To validate that improvement claimed
is real
To compare data on the "Y" before and after
improvement and prove that after improvement data
on "Y" is statistically and significantly different from
Measure Phase data on "Y"
•2 sample t
•2 Proportion
•Mann Whitney
P < 0.05
To validate whether the improvement
target has been achieved or not
To compare the post improvement data on the "Y" with
the Set Target and determine whether it has been
achieved. Even if the 2-sample test validates that the
process has improved, we need to know whether we
have actually achieved the target.
•1 sample t for Normal
•1 sample sign for Skewed
P > 0.05
Other than
Six Sigma
Any situation when it is required to
understand whether current
performance is meeting set target
To compare mean of current performace data against
a Target Performance and determine whetehre we are
meeting the target or not
•1 sample t for Normal
•1 sample sign for skewed
P > 0.05

105. Lean Six Sigma Green Belt training
programme
–
Part 2
Correlation Analysis
105
When to use:
•Correlation is a
statistical analysis
which determines the
association or
relationship between
two variables.
•When we have two
variables say X and
Y, to check whether
X is influencing Y or
not correlation
analysis is used.
Assumption for
correlation
analysis:
•Both variables must
be continuous
•Should be normally
distributed
Case Study
Example:
A car manufacturer
wants to know whether
there is a relationship
between weight of the
car & mileage
Hypothesis:
Ho: There is no
correlation between the
two variables.
Ha: There is correlation
between the two
variables exist.

106. Lean Six Sigma Green Belt training
programme
–
Part 2
Path for Correlation Analysis in Minitab
106
Correlation

107. Lean Six Sigma Green Belt training
programme
–
Part 2
Correlation Analysis
107
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Basic Statistics > Correlation...)
•Step 3: Select the columns from the work sheet to variables
•Step 4: Go to options & select Pearson correlation from dropdown
option then select Confidence level
•Step 5: Go to Graphs select correlation and p-value from dropdown

108. Lean Six Sigma Green Belt training
programme
–
Part 2
Correlation Analysis
108
CorrelationCoefficient(r)Guideline
±0.70to±1.00 StrongCorrelation
±0.50to±0.69 ModerateCorrelation
±0.2to±0.49 Low Correlation
±0.00to±0.19 Verylowornocorrelation
Test Result
Inference
•Pearson Correlation Coefficient r = -0.994 and p value = 0.000
•Means, There is a strong negative correlation between the two
variables exist.
•Mileage of car is inversely proportional to weight of the car.
Note: Remember correlation doesn’t imply causation always!!!

109. Lean Six Sigma Green Belt training
programme
–
Part 2
An Interesting Anecdote on Correlation Analysis
109

110. Lean Six Sigma Green Belt training
programme
–
Part 2
An Interesting Anecdote on Correlation Analysis
A complaint was received by the Pontiac Division of General Motors:
•‘This is the second time I have written to you, and I don’t blame you for not answering me, because I sounded crazy,
but it is a fact that we have a tradition in our family of ice cream for dessert after dinner each night, but the kind of
ice cream varies so, every night, after we’ve eaten, the whole family votes on which kind of ice cream we should
have, and I drive down to the store to get it. It’s also a fact that I recently purchased a new Pontiac and since then
my trips to the store have created a problem….
•You see, every time I buy a vanilla ice-cream when I start back from the store my car won’t start. If I get any other
kind of ice cream, the car starts just fine. I want you to know I’m serious about this question, no matter how silly it
sounds “What is there about a Pontiac that makes it not start when I get vanilla ice cream, and easy to start
whenever I get any other kind?” The Pontiac President was understandably skeptical about the letter but sent an
Engineer to check it out anyway.
•The latter was surprised to be greeted by a successful, obviously well-educated man in a fine neighborhood. He had
arranged to meet the man just after dinner time, so the two hopped into the car and drove to the ice cream store. It
was vanilla ice cream that night and, sure enough, after they came back to the car, it wouldn’t start. The Engineer
returned for three more nights. The first night, they got chocolate. The car started. The second night, he got
strawberry. The car started. The third night he ordered vanilla. The car failed to start.
110

111. Lean Six Sigma Green Belt training
programme
–
Part 2
An Interesting Anecdote on Correlation Analysis
•Now the engineer, being a logical man, refused to believe that this man’s car was allergic to vanilla ice cream. He
arranged, therefore, to continue his visits for as long as it took to solve the problem. And toward this end he began
to take notes: He jotted down all sorts of data: time of day, type of gas uses, time to drive back and forth etc.
•In a short time, he had a clue: the man took less time to buy vanilla than any other flavor. Why? The answer was in
the layout of the store. Vanilla, being the most popular flavor, was in a separate case at the front of the store for
quick pickup. All the other flavors were kept in the back of the store at a different counter where it took considerably
longer to check out the flavor.
•Now, the question for the Engineer was why the car wouldn’t start when it took less time. Eureka –Time was now
the problem –not the vanilla ice cream!!!! The engineer quickly came up with the answer:“vapor lock”. It was
happening every night; but the extra time taken to get the other flavors allowed the engine to cool down sufficiently
to start. When the man got vanilla, the engine was still too hot for the vapor lock to dissipate!!!
111

112. Lean Six Sigma Green Belt training
programme
–
Part 2
Regression Analysis
112
When to use:
•While correlation is used to
understand the direction,
shape and strength of a
relationship between 2
variables, regression analysis
creates a predictive equation
to quantify this relationship.
•Regression analysis explains
how to mathematically relate
an independent variable to a
dependent variable.
Case Study Example:
CEO of the company ABC wants
to predict revenue on the basis
of amount spent on
advertisement.
Hypothesis:
Ho: Amount spent on ad doesn’t
influence revenue ( X doesn’t
influence Y)
Ha: Amount spent on ad does
influence revenue ( X does
influence Y)

113. Lean Six Sigma Green Belt training
programme
–
Part 2
Regression Analysis
113
Were,
•Y = Output / Dependent Variable / Response
•X
1= Input / Independent Variable / Predictor
•β1= Slope
•β0= Constant / Intercept (Value of Y, when X = 0)
LinearRegressionModelbasedonmathematicalmodelofstraightline;
y =mx+c. EquationofLinearRegressionModelis:
Y=β
0+β
1*X
1

114. Lean Six Sigma Green Belt training
programme
–
Part 2
Regression Analysis -Coefficient of Determination –R2
114
•Value of R
2
is the square of coefficient of correlation (r)
•Value of R
2
varies between 0 and +1
•Value of R
2
will always be smaller than value of r for all values of r not equal to 1.
•Minitab reports three values; R
2
, R
2
ADJand R
2
PREDTo be on a conservative side, we need to consider value of
R
2
PRED to define the strength of regression model / equation.
•When value of R
2
PRED > 0.5, relation is strong, between 0.5 and 0.3, it is moderate and below 0.3, it is weak.

115. Lean Six Sigma Green Belt training
programme
–
Part 2
Regression Analysis -Selection of Regression Model / Equation
115
For a regression model / equation to be acceptable, all the following three conditions must be
satisfied.
•P value < 0.05 for the predictor “x”
•R
2
PRED > 0.5 or 50%
•Variation Inflation Factor –VIF < 5
•Once a regression model / equation is accepted, the corresponding cause represented by the “X” in the equation is
validated as a Root Cause.
•We can now go ahead and confidently achieve the following two outcomes:
−Predict value of Y based on value of X
−Condition the value of X to achieve a desired value of Y

116. Lean Six Sigma Green Belt training
programme
–
Part 2
Path for Regression Analysis in Minitab
116
FittedLinePlot…

117. Lean Six Sigma Green Belt training
programme
–
Part 2
Regression Analysis
117
•Step 1: Copy the data from excel to Minitab
•Step 2: Select the path (Stat > Basic Statistics >
Regression > Fitted Line Plot...)
•Step 3: Select the Response or Y and Predictor or X from
the work sheet

118. Lean Six Sigma Green Belt training
programme
–
Part 2
Regression Analysis
118
Inference
•Coefficient of determination R-Sq= 95.71% and p value = 0.000
•R-Sq= 95.71% Means, 95.71% of variability in revenue depends on
the amount spent on advertisements.
Test Result

119. Lean Six Sigma Green Belt training
programme
–
Part 2
Analyze Phase recap:
119
Cause Identification
•C&E Diagram
•5 Whys
•Pareto Analysis
Process Door Approach
•Lean Principles
Data Door Approach
•Hypothesis Testing
•Type I & Type II Errors
•Test for Means
•Test for Proportion
•Correlation & Regression

120. Lean Six Sigma Green Belt training
programme
–
Part 2Improve Phase
120

121. Lean Six Sigma Green Belt training
programme
–
Part 2
Improve Phase -Roadmap
121
01
Generate and
Select Solutions
Refine / Risk Proof
Solutions
Test Solutions Justify Solutions
02 03 04

122. Lean Six Sigma Green Belt training
programme
–
Part 2
Learning outcomes:
122
At the end of the Improve phase you will be able to
Shortlist the
appropriate
solution
Risk proof the
solution using
FMEA
Validate the
improvement
by testing the
solutions
Justify the
benefits of the
project to the
management

123. Lean Six Sigma Green Belt training
programme
–
Part 2
132
Generate and
Select Solutions
123

124. Lean Six Sigma Green Belt training
programme
–
Part 2
Unstructured brainstorming
In this form of brainstorming, ideas are generated
randomly and there is no need to pass. The solutions are
discussed freely and can be proposed at any time. This
type of brainstorming process is effective when the
representation of each of the diverse groups involved in
the discussion is large. However, the facilitator should be
careful that even in this randomized discussion with large
representations, ideas may not be captured completely.
Brainstorming Techniques
124
Structured brainstorming
This is a process in which the ideas are generated in a
systematic method by moving from one person to another
and obtaining an idea. The person who does not wish to
provide an idea, passes. The process is continued until
each participant passes and the facilitator determines no
fresh ideas are being generated. As with all forms of
brainstorming, the ideas are then taken up for discussion.
At the end discard any ideas that are similar and debate
on each idea to come up with the finalized list of possible
solutions.

125. Lean Six Sigma Green Belt training
programme
–
Part 2
Brainstorming Techniques
125
Structured brainstorming.
▪Smooth flow of ideas.
▪Everyone has an opportunity to express opinions.
▪Efficient process in terms of idea generation.
▪Less creative in approach.
Unstructured brainstorming.
▪Smooth.
▪Random flow of ideas.
▪All opinions may not be captured.
▪Lesser number of ideas generated.
▪Effective process for creative ideas.

126. Lean Six Sigma Green Belt training
programme
–
Part 2
Brainstorming Principles
126
Must be” for all brainstorming forms
Prevent biases
(group/function/subject)
Avoid large groups
(6 -10 optimum)
Focus on critical Xs
and CTQs
Create heterogeneous
groups
Allow free flow of ideas
Manage time
Scribe all details
Use voting techniques

127. Lean Six Sigma Green Belt training
programme
–
Part 2
Prioritizing solutions
127
Channeling Anti solution
Structured approach to brainstorm on
specific category of solutions available to
the team.
Structured approach to brainstorm on the
opposite of the objectives of the
discussion.

128. Lean Six Sigma Green Belt training
programme
–
Part 2
Prioritizing solutions
128
Analogy Brain writing
Brainstorm on ideas on related topic
to unblock the thought process.
Build on ideas written on a sheet of
paper randomly distributed amidst
the group.

129. Lean Six Sigma Green Belt training
programme
–
Part 2
Prioritizing solutions
129
Channeling: This form of brainstorming entails channeling of thoughts of the participants similar to the discussion in fishbone diagram.
The discussion revolves on specific stream/section of solution. E.g. while discussion on methods to improve the sales of soaps,
potential solutions can be channeled into: Improvements related to the packaging, fragrance, cutting of costs or distributionsystem for
the product.
Antisolution:Here the objective of the team is reversed to exactly the opposite of what is to be determined. E.g. In an effort to improve
the training programme, the team can debate about the ways in which the training programme can be worsened. The solutions are
opposite of what is determined during the discussion.
Analogy: Analogy form of brainstorming encompasses a discussion on a process/product that is similar to the one which is being
improved. E.g. Instead of discussing on ‘what are ways to improve the productivity of call center associates for an insurancecustomer
service call center, the team can discuss opinions on productivity of associates in the customer service call center for automobile
leasing’. Make associations at the end of the discussion.
Brain writing:Written ideas are exchanged in this process. Each person who receives a written idea tries to expand on it or adds a
totally new idea to it. The pieces of paper are rotated, and a collections of ideas or solutions are then debated and prioritized. This is
used when the team members are unknown to each other.

130. Lean Six Sigma Green Belt training
programme
–
Part 2
139
Select Solutions
130

131. Lean Six Sigma Green Belt training
programme
–
Part 2
Select Solutions
131
N/3 voting
Screening against ‘Must Be’
Criteria based matrix
•Ease of Use
•Inter site availability
•Preparation of
Charts
•Information Real
time
•Auto escalation of
unresolved issues
•Filters and regulated
access
Establish Criteria Assign
Wt.
Soln. 1Soln. 2# of
Votes
Total score:
Generate/update
list of solutions
Combine all similar
choices with
consensus
Allow members
to choose 1/3 of the
list as choices
Tally votes
for each
choice
Rationalize/justify/reject
solutions
Solutions for further discussions
Pay off matrix
Effort
Benefits
L H
H
Compliance, policies and
regulations
Customer CTQs
Business CTQs

132. Lean Six Sigma Green Belt training
programme
–
Part 2
Various approaches to selecting solutions
132
•Pay-off matrix: After the possible solutions are generated, they can be assigned to different quadrants of
the pay off matrix. The ideas which are low on benefits, are rejected. The discussion is then focused on the
high effort/high benefits, and these are rationalized for implementation. Some of the solutions in this
quadrant are so prohibitively expensive that they can be eliminated without further analysis. Caution needs
to be maintained when eliminating potential solutions from this quadrant.
•Screening against ‘Must be’ criteria: Company policies, local laws and social considerations are
extremely important before proceeding further on any solution. Finally, the extent to which the customer
CTQs of the project are satisfied is a key consideration for selection (use KANO model to evaluate expected
extent of satisfaction generated).
•N/3 voting: The key consideration in this form is that all rejected solutions should be justified
•Criteria matrix: Solutions scoring differently under each defined criteria.

133. Lean Six Sigma Green Belt training
programme
–
Part 2
Payoff Matrix
133
Effort
Benefits
L H
H
Solution for further Discussion
•Payoff Matrix is a simple tool to prioritize the improvements generated from the Improve phase of your Lean Six
Sigma project according to their benefits if implemented and the resources needed to implement.

134. Lean Six Sigma Green Belt training
programme
–
Part 2
Steps of Payoff Matrix
134
•Before we can prioritize the improvements, we must make a comprehensive list of the improvements. These
improvements must be actionable items that mitigate the root causes that you uncovered in the analyze
phase.Actionable items are problems that we can implement a tangible fix.
Effort
L H
H
4
1
7
3
2
5
6
5
5Benefits
Solutions Efforts
(High/Low)
Benefits
(High/Low)
Sol 1 H H
Sol 2 L H
Sol 3 L L
Sol 4 L H
Sol 5 H L
Sol 6 H L
Sol 7 H H

135. Lean Six Sigma Green Belt training
programme
–
Part 2
Steps of Payoff Matrix
135
•High Benefits and Low Effort: These are improvements that are easy to implement and have a
relatively high benefit. This is the quadrant that should be the priority when implementing Lean Six
Sigma project improvements
•Low Benefits and Low Effort: The improvements in this quadrant will individually have less effect but
cumulatively could have a large effect.
•High Benefits and High Effort: The improvements in this quadrant are costly in time and/or expense.
These improvements are where we must evaluate the risk of giving up the resources and the reward
gained.
•Low Benefits and High Effort: The improvements in this quadrant have little effect and are costly.
These improvements are either tabled or we can decide they are not worth pursuing.

136. Lean Six Sigma Green Belt training
programme
–
Part 2
N/3 Voting
136
Generate/update
list of solutions
Allow members
to choose 1/3 of the
list as choices
Tally votes
for each
choice
Rationalize/justify/reject
solutions
Combine all similar
choices
with consensus
What is N/3 voting?
It’s a Technique used to narrow down and prioritize
many ideas. N/3 Voting can be helpful in determining
which ideas to follow at the end of brainstorming
session.
Steps for N/3 Voting:
•Step 1: Assign Ideas to Groups on which members are going to vote.
•Step 2: Group votes. Each Group member may cast multiple votes. The number of votes a member may cast
is equal toone thirdof the number of available options (hence, N/3).
•Step 3: Tally the votes.
•Step 4: Repeat until you have a list, you’re comfortable with. The goal may not be to whittle the list down to a
single item. You can vote as many times as the situation demands.

137. Lean Six Sigma Green Belt training
programme
–
Part 2
Criteria Based Matrix (CBM)
137
Where to use CBM?
•More than a few criteria for solution selection.
•Solutions scoring differently under each criteria.
•The weight for each criteria differs.
How to use CBM?
•Identify criteria and assign weightage.
•The team members to give votes to each idea.
•The votes are then multiplied with the weights of the criteria
established for selection.
•The total scores obtained at the bottom of the solution are
used to select the same.

138. Lean Six Sigma Green Belt training
programme
–
Part 2
149
Solutions with
Lean Approach
138

139. Lean Six Sigma Green Belt training
programme
–
Part 2
Kaizen
139
•“Kai” means “change”.
•“Zen” means “good (for the better)”.
•Gradual, orderly, and continuous improvement.
•Ongoing improvement involving everyone.
What is a Kaizen?
•Kaizen is a Japanese word for the philosophy that defines management’s role in continuously
encouraging and implementing small improvements involving everyone.
•It is the process of continuous improvement in small increments that make the process more efficient,
effective, under control, and adaptable.
•It focuses on simplification by breaking down complex processes into their sub processes and then
improving them.

140. Lean Six Sigma Green Belt training
programme
–
Part 2
Kaizen-PDCA
140
PLAN
•Analyze current
problem and
condition.
•Establish change
objective.
•Create Processes to
achieve solution
ACT
•Standardize the
solution.
•Review and define next
issues.
DO
•Implement plan
•Test small changes
•Gather data on the
changes'
effectiveness.
CHECK
•Evaluate data
•Identify deviations
between outcomes and
planned objectives.

141. Lean Six Sigma Green Belt training
programme
–
Part 2
Why use Kaizen?
141
WhentouseKaizen?
•To solve problems (without already knowing the solution).
•To eliminate waste (Muda).
•Transportation, Inventory, Motion, Waiting, Over-production, Over-processing,
Defects.
•Create ownership and empowerment.
•Support lean thinking.
WhatisaKaizenBlitz?
•Total focus on a defined process to create radical improvement in a short period of time.
•Dramatic improvements in productivity, quality, delivery, lead-time, set-up time, space utilization, work in
process, workplace organization.

142. Lean Six Sigma Green Belt training
programme
–
Part 2
Kaizen Themes
142
KaizenThemes:
•Red Tagging (getting rid of clutter).
•Visual Control (instructions in the workplace).
•Better (any small improvement).
•Benchmark (adopt other industry service).
•Clarity (communication without confusion).
•Pit Stop (streamlining critical activity).
•Service Supreme (using our best experience as our standard).

143. Lean Six Sigma Green Belt training
programme
–
Part 2
Kaizen Advantages
143
KaizenAdvantages:
•Do Right Things (effectiveness).
•Do Things Right (efficiency).
•Do Things Better (improve).
•Do Away With Things (cut).
•Do Things Others Do Well (adapt).
•Do What No Other Is Doing (unbeatable).
•Do What Can’t Be Done (incredible).

144. Lean Six Sigma Green Belt training
programme
–
Part 2
Kaizen Cycle
144
Identify
Waste
Plan
counter
measure
Reality
Check
Make
changes
Verify
change
Measure
results
Make
this the
standard
Celebrat
e
Do it
again
Docume
nt
Kaizen
Cycle
Start

145. Lean Six Sigma Green Belt training
programme
–
Part 2
156
Kanban
145

146. Lean Six Sigma Green Belt training
programme
–
Part 2
•Kanban literally means “visual card,” “signboard,” or “billboard.”
•Toyota originally used Kanban cards to limit the amount of inventory tied up in “work in progress” on a
manufacturing floor.
•Not only is excess inventory waste, time spent producing it is time that could be expended elsewhere.
Kanban
146

147. Lean Six Sigma Green Belt training
programme
–
Part 2
•Kanban is a “pull” system that involves cascading or signaling production and delivery instructions from
downstream to upstream activities in which nothing is produced by the upstream supplier until the
downstream customer signals a need.
•All production is based on consumer demand, with nothing "pushed" downstream.
•Simply said, nothing is produced without a signal from the next station in the line.
•Kanban acts as the means of signaling used for material & information movement.
•Kanban is usually in a piece of paper in a vinyl envelope or container; outline marking on the floor.
Why Kanban?
147

148. Lean Six Sigma Green Belt training
programme
–
Part 2
•Production Kanban:authorizes production of goods.
•Withdrawal Kanban:authorizes movement of goods.
•Kanban square:a marked area designated to hold items.
•Signal Kanban:a triangular Kanban used to signal production at the previous workstation.
•Material Kanban:used to order material in advance of a process.
•Supplier Kanban:rotates between the factory and suppliers
Types of Kanban
148

149. Lean Six Sigma Green Belt training
programme
–
Part 2
160
5 S
149

150. Lean Six Sigma Green Belt training
programme
–
Part 2
5S
150
•To improve efficiency and productivity.
•To maintain safety and cleanliness.
•To maintain good control over the processes.
•To maintain the good product quality.
Why 5S?
A systematic approach to organize and standardize the
workplace. 5S was originally developed within the
Toyota Production.
What is 5S?

151. Lean Six Sigma Green Belt training
programme
–
Part 2
5S
151
•SEIRI
•SEITON
•SEISO
•SEIKETSU
•SHITSUKE
Sort / Segregate
Self Arrange
Spic and Span
Standardize
Self Discipline

152. Lean Six Sigma Green Belt training
programme
–
Part 2
Objectives of 5S
152
Promote Safety.01
Improve Workflow.02
Better Product Quality.03
Reduce Inventory Waste.04
Give People Control of Their Workplace.05

153. Lean Six Sigma Green Belt training
programme
–
Part 2
Step 1: Sort (Seiri)
153
•Ensuring each item in a workplace is in its proper place or identified as unnecessary and removed.
•Sort items by frequency of use.
•Get rid of unnecessary stuff.
Can tasks be simplified?
Do we label items, and dispose of waste
frequently?
While Sorting (Seiri) keep in mind:
•How often things are used.
•What is the life of the material.
•Cost of the material.
•Be sure to throw the things, otherwise you may
repent.
Consequences of not Sorting (Seiri):
•The wanted is hard to find when required.
•More space is demanded.
•Unwanted items cause misidentification.
•Misidentification causes errors in operation.
•Maintenance cost of the equipment increases.

154. Lean Six Sigma Green Belt training
programme
–
Part 2
Step 2: Set in Order (Seiton)
154
Identifying places to arrange the things and placing them in proper order for prompt usage.
“A place for everything and everything in its place.”
While arranging or setting things in order
(Seiton) keep in mind:
•The right location where the things will be used.
•FIFO (First in First out) arrangement.
•Labeling of the area and the equipment is very
important.
•Keep proper gaps between two things to avoid
confusion.
•Good SEITON includes use of labels signs, indications,
display, cautions.
•Use of labels signs, indications, display, cautions
highlights difference between normality and abnormality.
•Non -users of the equipment also become aware of its
use and precautions.
Consequences of not arranging things in
order (Seiton):
•Things are seldom available when needed.
•Items get lost.
•Items get mixed up.
•Visual control not possible.
•Failure to achieve targets.

155. Lean Six Sigma Green Belt training
programme
–
Part 2
Step 3: Shine (Seiso)
155
•Sweep your workplace thoroughly so that there is no dust/dirt/scrap anywhere.
•The area should say “ Who I’m” and its neatness should give you a natural welcome.
While arranging or setting things spic and
span (Seiso) keep in mind:
•Cleaning should be done regularly.
•Use the best cleaning agent.
•All the nooks and corners should be cleaned.
•Keep all the labels intact.
•All the labels should correct, visible and legible to all.
Consequences of not being spic and span
(Seiso):
•Performance of machines deteriorates.
•The quality / aesthetic quality deteriorates.
•Dirty place is unpleasant and hazardous to health.
•Sends uncaring and irresponsible message to the
team members and society at large.
•People working at dirty areas are generally found to
have low desire to excel and their motivation level is
low.

156. Lean Six Sigma Green Belt training
programme
–
Part 2
Step 4: Standardize (Seiketsu)
156
•Always aim at maintaining the standard level of cleanliness, hygiene and visual control.
•Keep all the 4 M’s ( Man., Machine, Material and Method) intact, a lapse in any one of them will
make you loose the rest of the three.
While standardizing (Seiketsu) keep in mind:
•The standards should be arrived at unanimously.
•Always keep the standards flexible to changes and improvements.
•Standards should be known to all and displayed.
Essence of standardizing (Seiketsu):
•It is the proof that 3-S (SEIRI, SEITON, SEISO) are being religiously carried out.
•It is the barometer which indicates the control level based on the 5-S of all the workers.
Consequences of not standardizing (Seiketsu):
•Dual standards yield multiple results.
•Multiple results lead to conflicts and confusions.
•Rework increases.
•Rework increases the basic cost of the finished product without any value addition.

157. Lean Six Sigma Green Belt training
programme
–
Part 2
Step 5: Sustain (Shitsuke)
157
•Train all team members on 4-S.
•Correct wrong practices on the spot.
•Punctuality is the backbone of 5S.
•Follow work instructions.
To ensure success:
•Rules will always be followed.
•Laid down targets will be achieved.
•Improvements will be promoted.
•The no. of defects will be reduced.
•The cost will not increase.
If you are disciplined. :

158. Lean Six Sigma Green Belt training
programme
–
Part 2
Advantages of 5S
158
•Provides basis for being a world-class competitor.
•Starts the foundation for a more systematic
approach to the workplace.
•Improves productivity and morale.
•Empowers employees.
•Increases profit.
How to plan for 5S?
•Assemble a 5S Lead team.
•Define the work area 5S boundaries (list them).
•Assign work group members to their 5S areas.
•Determine 5S targets, activities, and schedule.
•Review/finalize plans with work group and site
leadership
Advantages:

159. Lean Six Sigma Green Belt training
programme
–
Part 2
5S Implementation
159
Obtain existing standards for color-coding and signage.01
Decide on 5S color-coding and signage standards.02
Communicate, communicate, communicate! (e-mail, signs, one on one).03
Install 5S communication board.04
Set acceptable timetable for completion.05

160. Lean Six Sigma Green Belt training
programme
–
Part 2
Roles for 5S implementation
160
TOP MANAGEMENT
MIDDLE / LINE
MANAGEMENT
EMPLOYEES
•Play the role of mentor
•Initiate the 5S program
•Provide resources
•Appreciate the efforts
•Play the role of facilitator
•Take initiative in his area of work
•Train the people in 5S
•Give the feedback
•Participate actively.
•Give suggestions.
•Respect the opinion of others.
•Be a good team player, and
•Maintain discipline

161. Lean Six Sigma Green Belt training
programme
–
Part 2
Source:
Internet
Examples with 5S
161

162. Lean Six Sigma Green Belt training
programme
–
Part 2
Examples with 5S
162
Source: Internet

163. Lean Six Sigma Green Belt training
programme
–
Part 2
178
Poka-Yoke
163

164. Lean Six Sigma Green Belt training
programme
–
Part 2
Poka-Yoke
164
•Poka means “Mistake” or “Error” and Yoke means “Proofing” or “Avoid”.
•In other words, Poka-Yoke means Error Proofing or Mistake Proofing or Avoidance of Error.
•Poka-Yoke is a Japanese improvement strategy for mistake-proofing to prevent defects (or
nonconformities) from arising during production processes.
•The Poka-Yoke concept was created in the mid-1980s by Shigeo Shingo, a Japanese manufacturing
engineer.
•Mistake Proofing is a method for avoiding errors in a process.
•The simplest definition of ‘Mistake Proofing’ is that is a technique for eliminating errors by making it
impossible to make mistakes in the process.
•It is often considered the best approach to process control.
•Poka-Yoke device is any mechanism that either prevents a mistake from being made or makes the
mistake obvious at a glance.

165. Lean Six Sigma Green Belt training
programme
–
Part 2
Why Poka-Yoke?
165
•Error free designs or processes.
•Eliminate the possibility of setting the X’s beyond the limits.
•Warns operators before the X’s move to the outside limit so that the preventive
action can be taken.
•Can also be used in conjunction with the risk management or SPC.
•The opportunity for error needs to be minimized or eliminated.
Get it right during process design…!

166. Lean Six Sigma Green Belt training
programme
–
Part 2
Poka-Yoke -Examples
166
Source:
Internet

167. Lean Six Sigma Green Belt training
programme
–
Part 2
Poka-Yoke -Examples
167
Source:
Internet

168. Lean Six Sigma Green Belt training
programme
–
Part 2
Refine/Risk Proof
Solutions
168

169. Lean Six Sigma Green Belt training
programme
–
Part 2
Failure Mode & Effects Analysis (FMEA)
169
A team activity with the subject matter experts…!
A Failure Mode and Effects Analysis is a systemized
team activity intended to:
•recognize and evaluate potential failure and its
effects.
•identify actions which will reduce or eliminate the
chance of failure.
•document analysis findings.

170. Lean Six Sigma Green Belt training
programme
–
Part 2
FMEA
170
•FMEA is designed to prevent failures from occurring
or from getting to internal and external customers.
•FMEA is essential for situations where failures
might occur and the effects of those failures
occurring are potentially serious.
•FMEA can be used on all improvement projects.
•FMEA serves as an overall control document for
any given process.
When to use FMEA
•Identify the high priority failure modes and causes
of defects in an operational or transactional
process.
•Identify high priority input variables (Xs) that impact
important output variables (Ys).
•Evolve a consensus on the recommended
corrective actions and procedures to follow.
Objective of FMEA

171. Lean Six Sigma Green Belt training
programme
–
Part 2
FMEA Steps
171
1.FMEA is carried out on a new process/product or
redesigned process/product.
2.For each process step, list requirements for each
process step.
3.For each requirement, list the failure mode for each
requirement.
4.For each failure mode, list the effect of failure for each
failure mode.
5.For each effect of failure, estimate the severity.
6.For each failure mode, list causes.
7.For each cause of failure, estimate the likelihood of
occurrence.
8.For each cause of failure, list the current process
controls.
9.For each process control, estimate the detection.
10.For each cause of failure, calculate the Risk Priority
Number by multiplying the scores associated with
severity, occurrence and detection.
11.For high priority causes of failure and/or failure modes,
develop recommended actions.
12.For each recommended action, assign responsibility
and completion dates.
13.For each recommended action, implement the action
and note its effect.
14.For each implemented action, re-estimate the severity,
occurrence and detection rankings and recalculate the
RPN.

172. Lean Six Sigma Green Belt training
programme
–
Part 2
FMEA Worksheet
172
Process
Step
Potentia
l failure
mode
Potentia
l failure
effect
S
E
V
Potential
causes
O
C
C
Current control D
E
T
R
P
N
Action
Recommended
Resp. Action
taken
S
E
V
O
C
C
D
E
T
R
P
N
RPN =
Severity
X
Occurrence
X
Detection

173. Lean Six Sigma Green Belt training
programme
–
Part 2
FMEA –Example
173
Function/
Process
Potential
failure mode
Potential effect
of failure
S
E
V
Potential Causes of
failure
O
C
C
Current Process
Control
D
E
T
Critical
Charact
eristic
R
P
N
Recommend
ation
Resp.
Soap
Making
Misshapen
Soap
Mildly
displeased
customer 6
1.Soap Molds are old
2.Uncareful
workmanship.
3.Soap molds are not
regularly cleaned out
3
1.None.
2.Close Supervision.
3.None 1N 18
Too Small or
Too Big in
Size
Possible
Company
Losses
8
1.Uncareful
Workmanship.
2.No uniform Mold.
3
1. Close Supervision
3N 72
Provide a
Uniform Mold
Factory
Supervis
or.
Wrong
Fragrance
Dissatisfied,
Possibly irked
customer
10
1.No Standard
Measurement.
2.Low skill sets of
Worker.
3
1.None.
2. None,
2Y 60
1.Standardiz
e the Mixer
Procedure.
2.Hire and
expert in
mixing,
1.Produc
t
manger.
2. G.M.

174. Lean Six Sigma Green Belt training
programme
–
Part 2
Severity Scale
174
RPN = Severity x Occurrence x Detection
More the severity, higher is the rating
Low
High

175. Lean Six Sigma Green Belt training
programme
–
Part 2
Occurrence Scale
175
More often it occurs, higher is the rating
RPN = Severity x Occurrence x Detection
Low
High

176. Lean Six Sigma Green Belt training
programme
–
Part 2
Detection Scale
176
High
Low
Lower the ability to detect, higher is the rating
RPN = Severity x Occurrence x Detection

177. Lean Six Sigma Green Belt training
programme
–
Part 2
Risk Priority Number (RPN)
177
•The RPN number is calculated from the team’s estimates of Severity,
Occurrence and Detection.
•RPN = S x O x D.
•If you are using a 1 -10 scale for Severity, Occurrence and Detection,
the worst RPN = 1000 (10 x 10 x 10), while the best would be RPN = 1
(1 x 1 x 1).
•Use RPN numbers to prioritize failure modes and/or causes of failures
in order to work on the highest priority issues.

178. Lean Six Sigma Green Belt training
programme
–
Part 2
FMEA –Useful Tips
178
Suggestions for completion of the activity in time:
Similar to a process map, FMEA is also a
“live” document used throughout the
DMAIC journey.
01
Make it a “team effort.”02
Address concerns from a process
perspective and not business
contingency perspective.
04
Analyze existing processes to find and fix
problems.
05
Analyze new processes to avoid
problems before they happen.
03
Analyze existing processes to discover
the high priority (“key”) process input
variables.
06

179. Lean Six Sigma Green Belt training
programme
–
Part 2Test Solutions
179

180. Lean Six Sigma Green Belt training
programme
–
Part 2
Testing for solutions
180
•Small scale experimentation-piloting.
•Modeling-physical models.
•Simulation-computer models.
How to test solutions
•Confirm to potential solution.
•Obtain feedback and buy-in for proposal.
•Opportunity for refining solution.
Why test solutions

181. Lean Six Sigma Green Belt training
programme
–
Part 2
Ensure consistency & stabilityHow to collect?What to collect?
Testing Essentials
Create A data collection plan and Monitor Activities For data Consistency and stability.
Verify that the process has improved-process capability, hypothesis testing for evaluating statistical significance of the old
and the improved process.
Help ensure robust measurement plan for testing the solution.
Why collect data?
181

182. Lean Six Sigma Green Belt training
programme
–
Part 2Justify Solutions
182

183. Lean Six Sigma Green Belt training
programme
–
Part 2
Justify solution
183
Intangible benefits
Tangible benefits
•Savings
•Incremental revenue
•Interest cost and
income
•Cash flow
•Reduced workforce
Intangible benefits
•Customer retention
•Improved VOB/VOC
•Ease of work
•Better governance
Prepare net financial gains and supplement with intangible gains and
obtain business and finance leader approvals before proceeding.

184. Lean Six Sigma Green Belt training
programme
–
Part 2
Cost Benefit Analysis (C B A)
184
Hard Gains
Cost Heads Vendor In House Training
Trainer Cost 250,000 0
T and L 30,000 0
Q Team Support 4,444 11,111
Facilities 20,000 20,000
Equipment 1,000 1,000
Stationary and Manuals 15,000 10,000
GB Examination 50,000 2,222
Total Cost 370,444 44,333
Estimated annual cost
Cost with Vendor Cost with Quality Team
Per Training 370,444 44,333
12 Training per year 4,445,333 532,000
Cost of creating the training manual
Man Days Spent Average per day cost Total Cost incurred
30 2,222 66,667
Savings per year
3,846,667
Assumptions
1.Hypothetical Costs assumed
2.Recurring cost of upgrading the content is INR66,667
* All Figures in INR
Soft gains
Trainings customized to
the need of the employees
Calendar and duration of
the training according
to organizations need
Benefits of training
in-house
Vs.
Employing a
vendor

185. Lean Six Sigma Green Belt training
programme
–
Part 2
Inference from Improve Phase
185
•Shortlist the appropriate solution.
•Risk proof the solution using FMEA.
•Validate the improvement by testing the solutions.
•Justify the benefits of the project to the management.

186. Lean Six Sigma Green Belt training
programme
–
Part 2
Improve Phase Recap
186
Generate & Prioritize Idea
•Brain Storming
•Prioritizing solutions
Selecting Solutions
•Pay-off Matrix
•Screen against “Must be” Criteria
•N/3 Voting
•Criteria Matrix
•Nominal Group Technique (NGT)
Solutions with Lean Approach
•Kaizen
•Kanban
•5S
•Poka-Yoke
Refine / Risk proof solution
•FMEA
Testing Solutions (PILOT)
Justify Solutions
•Cost Benefit Analysis

187. Lean Six Sigma Green Belt training
programme
–
Part 2Control Phase
187

188. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Phase -Roadmap
01
Implementation
and Acceptance
Strategy
Introduction to
SPC
Response Plan
and
Documentation
02 03
188

189. Lean Six Sigma Green Belt training
programme
–
Part 2
Learning outcomes:
At the end of the Improve phase you will be able to
Document and
communicate
results.
Identify the
appropriate
KPIVs to be
measured
Identify the
appropriate
control chart
Transfer knowledge
and responsibility for
process control to
appropriate position(s)
189

190. Lean Six Sigma Green Belt training
programme
–
Part 2
Time
Process control
N o pr ocess contr ol
Improvements
Why control?
To hold the gains of the DMAIC project there by help ensuring that
the efforts of the project team are not written off.
190

191. Lean Six Sigma Green Belt training
programme
–
Part 2
Input measures
(Xs)
Output
measures
Monitoring points
Process measures
•At the barest minimum, measure CTQs.
•Strive to measure the critical Xsto provide chances to make corrections.
•Install the appropriate data collection plan.
•Audit appropriately.
•Early warning system prevent $$ impact (rework reduction).
What to control?
191

192. Lean Six Sigma Green Belt training
programme
–
Part 2
Implementation
and Acceptance
Strategy
192

193. Lean Six Sigma Green Belt training
programme
–
Part 2
Implementation
193
01
02
03
Objectives
Resources and time frame
Control plan
Elements of good implementation planning:
04
05
06
Influence strategy
Control plan
Documentation

194. Lean Six Sigma Green Belt training
programme
–
Part 2
Strategy control
194
Quality of solution Acceptance of solutionX
Effectiveness of implemented solution

195. Lean Six Sigma Green Belt training
programme
–
Part 2
Acceptance Strategy
195

196. Lean Six Sigma Green Belt training
programme
–
Part 2
Key Constituent map
196
Identify stake holders to be addressed first
Project Impact Profile
Aim
•To identify key stakeholders.
•Prioritize the Stakeholder to be
addressed

197. Lean Six Sigma Green Belt training
programme
–
Part 2
Implementing Solutions
197

198. Lean Six Sigma Green Belt training
programme
–
Part 2
217
Control plan
198

199. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Plan
199
Purpose
A Control Plan should check identified inputs (significant influencing variables), which determine the output
(dependent size). The process should be "on target" with a minimalvariance and should not be "over
adjusted".Necessary trainings must be given (e.g., on dealing with possible control cards and necessary
intervention in the process).
Whatquestionsshouldbeansweredbyacontrolplan?
•Who is responsible if the process is getting out of hand?
•What happens whenthe responsible personisn't there?
•How is ensured that the process stays on the set value/level?
•Arepreventive maintenance routines considered?
•How were necessary security measures considered?
•Are all important elements included inthe plan?
•Do reaction plans exist?

200. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Plan
200
The Control Plan helps assure quality is maintained in
a process in the event of employee turnover by
establishing a standard for quality inspection and
process monitoring.Control Plans are living
documents that should be periodically updated as the
measurement methods and controls are improved
throughout the life cycle of the product.
What is Control Plan
The Control Plan is a document that describes the
actions (measurements, inspections, quality checks or
monitoring of process parameters) required at each
phase of a process to assure the process outputs will
conform to pre-determined requirements.
In simpler terms, the Control Plan provides the
operator or inspector with the information required to
properly control the process and produce quality
parts or assemblies. It should also include
instructions regarding actions taken if a non-
conformance is detected.
TheControlPlandoesnotreplacedetailed
operatorinstructions.Insomecases,the
ControlPlanisusedinconjunctionwithan
inspectionsheetorchecklist.

201. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Plan
201
Why Develop a Control Plan
Developing and implementing Control Plan Methodology has several benefits.01
The use of Control Plans helps reduce or eliminate waste in a process. Businesses today must reduce
waste everywhere possible.
02
The Control Plan improves product quality by identifying the sources of variation in a process and
establishing controls to monitor them.
03
Control Plans focus on the product characteristics most important to the customer and the business. By
focusing on what is critical to quality during the process, you can reduce scrap, eliminate costly reworks
and prevent defective product from reaching the customer.
04
When scrap and reworks are reduced, throughput of the process is inherently improved. Manufacturing
efficiency is improved, and your company’s bottom line is impacted in a positive manner.
05

202. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Plan
202
How to Develop a Control Plan
The Control Plan should be developed by a Cross Functional Team (CFT) that understands the process
being controlled or improved.
01
By utilizing a CFT, you are likely to identify more opportunities for improvement of the process. The
Control Plan is more than just a form to fill out.
02
It is a plan developed by the team to control the process and ensure the process produces quality parts
that meet the customer requirements.
03

203. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Plan Template
203
Process Process
step
Input Output Process
specification
Cpk/PPM Measuremen
t Instrument
%R&R Sample size Control
Frequency
Control
Method
Re-Action
plan

204. Lean Six Sigma Green Belt training
programme
–
Part 2
Introduction to
SPC
204

205. Lean Six Sigma Green Belt training
programme
–
Part 2
Why control?
205
•Process control is essential to prevent the
loss of gains over a period.
•Detect the out-of-control state of
processes and determine the appropriate
actions.
•Control system incorporates risk
management, SPC, measurement and
audit plans, response plans,
documentation and ownership.

206. Lean Six Sigma Green Belt training
programme
–
Part 2
Statistical Process Control (SPC): An Overview
206
Control charts
•Statistical Process Control or SPC was
conceptualized by Walter A Shewhart to
determine if a business process (back then
manufacturing process) is in a state of
control.
•SPC primarily uses Control Charts.
•Control charts are also known as Shewhart
charts, or process behavior charts.

207. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Limits
20740302010Subgroup 0
6000
5000
4000
3000
2000
5/20/013/11/0112/31/0010/22/00Week
1
X=4198
3.0SL=5587
-3.0SL=2810
Upper Control Limit
Lower Control Limit
Common
Cause/Random Variation
Special Cause
Variation
Average
Time/Sequence Axis
Value/Measurement Axis
Select process, measures to be charted01
Establish data collection and
sampling plan
02
Calculate the statistics03
Plot control charts04

208. Lean Six Sigma Green Belt training
programme
–
Part 2
Special Cause vs. Common Cause Variation
208
HighLow
In Our Control
Common causes Special causes
Mistake 1
Tampering
(increases variation)
Focus on systematic
process change
Mistake 2
Under-reacting
(missed prevention)
Investigate special
causes for possible
quick-fixes
Common
causes
True variation type…
Special
causes

209. Lean Six Sigma Green Belt training
programme
–
Part 2
Statistical Process Control (SPC): Why and When Control Charts?
209
Control charts
•Control Charts monitor changes in the Xsand
detect changes that are due to special causes.
•Used when the Xscannot be mistake proofed
or need to be controlled for inherent variations.

210. Lean Six Sigma Green Belt training
programme
–
Part 2
Introduction to SPC
Types of Control Charts
210

211. Lean Six Sigma Green Belt training
programme
–
Part 2
Selecting Control Charts
211
Type of Data
Individual Measurements or
Subgroups?
Subgroup < 8
X –Bar R
chart
X -Bar S
chart
YesNo
I –MR Chart
VARIABLE /
CONTINUOUS
SubgroupsIndividual
DISCRETE / ATTRIBUTE
Defects or Defectives?
DefectsDefectives
Constant Sample Size?
np-chart P-chart C-chart U-chart
Constant Sample Size?
YesNo YesNo

212. Lean Six Sigma Green Belt training
programme
–
Part 2
Identifying Special Cause Variations
212
Test 1. Points beyond Control Limits:
Points beyond control limits are isolated high or low
points. 1 point more than 3s from center line.
Test 2. Points on one side of the center line:
9 points in a row on same side of center line.
Test 3. Trend:
Trends will continue up or down without a well-defined end.
Six points in a row, all increasing or all decreasing.

213. Lean Six Sigma Green Belt training
programme
–
Part 2
Identifying Special Cause Variations
213
Test 4. Variation pattern:
A cycle produces a pattern of up and down points, very much as
if the values of the points were time dependent. Fourteen points
in a row, alternating up and down.
Test 5. Points on same side:
Two out of three points more than 2s from the center line
(same side).
Test 6. Points on same side:
Four out of five points more than 1s from the center line
(same side).

214. Lean Six Sigma Green Belt training
programme
–
Part 2
Identifying Special Cause Variations
214
Test 7. Identifies a pattern of variation:
Fifteen points in a row within 1s of center line (either side).
Test 8. Mixture Pattern:
Eight points in a row more than 1s from center line (either
side).

215. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Charts –Variable / Continuous Data
215

216. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Charts –Attribute / Discrete Data
216

217. Lean Six Sigma Green Belt training
programme
–
Part 2
Benefits of Control Charts
217
Control Charts reduces defects by keeping processes centered01
Improves overall quality by reducing chances of quality deviations02
Aids in timely troubleshooting03
Serves as a communication tool for changes in CTQs04
Sustain improvements05

218. Lean Six Sigma Green Belt training
programme
–
Part 2
Inference from Control Phase
218
Develop and implement control plans01
Identify the appropriate KPIVs to be
measured
02
Identify the appropriate control chart03
Transfer knowledge and responsibility for
process control to appropriate position(s)
04

219. Lean Six Sigma Green Belt training
programme
–
Part 2
Project Closure
219
Essentials of project closure:
Document and communicate results.01
Recommend translation opportunities.02
Evaluate team success-results, process and relationships.03
Celebrate.04
Disband project team.05

220. Lean Six Sigma Green Belt training
programme
–
Part 2
Control Phase Recap
220
Control Plan01
Statistical Process Control (SPC) | Control Charts 02
Project Closure03

221. Lean Six Sigma Green Belt training
programme
–
Part 2
Scan and meet in office
www.grantthornton.in
For more information or for any queries, write to us at [email protected]
© 2022 Grant Thornton Bharat LLP. All rights reserved.
“Grant Thornton Bharat” means Grant Thornton Advisory Private Limited, the sole member firm of Grant Thornton International Limited (UK) in India, and those legal entities which are its related
parties as defined by the Companies Act, 2013, including Grant Thornton Bharat LLP.
Grant Thornton Bharat LLP, formerly Grant Thornton India LLP, is registered with limited liability with identity number AAA-7677and has its registered office at L-41 Connaught Circus,
New Delhi, 110001.
References to Grant Thornton are to Grant Thornton International Ltd. (Grant Thornton International) or its member firms. Grant Thornton International and the member firms are not a worldwide
partnership. Services are delivered independently by the member firms.
Contact us
221