Transcript HG067-2.8_Lean Six Sigma - Session 4

Lean Six Sigma Tools and Techniques
for Continuous Improvement
Session Four
(Best Practices Improvement Tools and Approaches)
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Session 4 Agenda
•
Understand SPC
•
Design and Implement the Data Gathering Plan
(Tollgate #5)
•
Complete Lean Turnaround (Module 2)
Simulation
•
Analyze Data, the Process and the Root
Cause(s)
•
Complete ‘Stat-a-Pult’ Measurement Simulation
VALUE STREAM MAP
WORKSHOP
CREATING THE
CURRENT STATE
What is a Value Stream?
• Definition: A sequence of
processes that are connected
by a common customer,
product, or service request.
What is Value Stream Mapping?
• Definition 1: The visual representation of
processes to meet customer demand.
• Definition 2: The process of identifying and
charting the flows of information,
processes, and physical goods across the
entire supply chain, from raw material
supplier to the possession of the customer.
• Definition 3: A basic planning tool for
identifying wastes, designing solutions,
and communicating lean concepts.
Why Value Stream Map?
• Visualize Current State material and
information flows
• Facilitate the identification and elimination
of waste from the Current State
• Prioritization of Lean Enterprise
continuous improvement activities
• Creates an action plan using Lean tools
and Kaizen implementation techniques
• Define a desired Future State
Where to Use VSM?
• Pre-Contract Processes
– Services Definition
– Services Costing
– Quotation Fulfillment
Process
• Operations
–
–
–
–
–
Order Processing
Purchasing
Production
Distribution
Inventory Control
• Service Delivery
Processes
– New Hire Application
– Employee Training
– Service Delivery
Scheduling
– Materials Procurement
– Quality Monitoring
Processes
Benefits of Value Stream Mapping
• Defines a Common Language that is icon based and
simple to understand by all employees.
• Creates a Visual Connection between materials &
information flows that impact company
performance from the customer viewpoint.
• Promotes a Common Mission among employees
along the entire Value Stream.
• Creates Employee Agreement on the “Current
State” of the organization.
• Illustrates to all employees How Value is Created for
the Customer.
• Improves the Employee Decision Making process
across departments, which is now based upon a
common view of activities critical to high company
performance.
Visualize the Value Stream
With Icons
Current State Map Objectives
• Establish a Company Wide Current State Value
Stream Map.
• Tie 4 Teams Value Streams
– Assess Total Lead Time
– Identify Where 8 Wastes Occur
– Identify “Negative Moments” Customer Viewpoint
– Identify Lean Tools to Apply during “Improve”
– Provide a Common Foundation for Developing the
Future State Map (Second Work Shop)
Current State Map Workshop
• Using Qi-Macros prepare a Current State Map for
each Team (Red, Blue , Yellow, Green)
– Identify Major Process Steps (From SIPOC)
– Indicate the Value Added Cycle Time for each
process.
– Indicate the Non-Value Added Time Wait Time &
Insert this either just before or just after each
Process Step.
– Use Icons where possible & to indicate where 8
Wastes occur.
– Indicate Where “Negative Moments” Occur &
source of Negative Moment.
Current State Map Highlighting
• Areas for Detailed Data Collection
• Areas for Kaizen
• Target Negative Moments for
Elimination
Future State Via Harry Potter
• Accio…Future State!!
• If you could wave a magic wand what
would you create as the Future
State?
• If your Customer Waved a magic
wand what would they create for
your Future State Company
Performance?
Lean Six SIGMA Tollgates
MEASURE
DEFINE
1
2
3
Develop LQS
4
Create
ANALYZE
IMPROVE
6
9
Analyze
Team Charter,
LQS Model
Measurement
The
& Masterplan
Scorecards
Data
5
Identify
Implement
Customer
Requirements
Project Data
CTQs
Collection Plans
Develop the
High-Level
SIPOC
7 Analyze
8
CONTROL
11
Determine
Generate
Lean
Solutions
Control Points
10
12
Select/
Implement
The
Test
The Lean
Process
Solutions
Analyze
The Root
Causes
Management
Response Plan
Measurement: Two Approaches
Get the Facts
Expert
Novice
•Create detailed customer
measures with targets
•No addressing customer
measures
•Operationally define the
customer requirements
•Missing and ambiguous
measures of customer
requirements
•Create a data collection plan
•No systematic plan to
collect data
•Understands sampling
techniques
• No understanding of
sampling
• Implement the data
collection plan
•No real data collection plan
• Understand basic statistical
process control
•No real understanding of
SPC
• Measure current process
efficiency
•No understanding of
measures of process
efficiency
Overview of Data Collection
Understand SPC
Create Data Collection Plan
Implement Plan
Why Lean Six Sigma? To Reduce Process Variation
Off-Target
Too Much Variation
Centered
On-Target
Center
Process
Reduce
Spread
The objective is to understand customer requirements and
reduce process variation and center the target
SPC Measurement Fundamentals
• Observe first, then Measure
• Know the difference between
discrete and continuous data
• Measure for a reason
• Have a Measurement Process
that is validated
Why Do We Measure?
• To obtain data to assess the performance of
processes against customer requirements
(CTQ’s)
• To identify variation (relative strengths and
weaknesses) in your processes
• To drive improvement--obtain information for
process management, improvement, or
design/redesign.
Key Measurement Challenges
• The ability to observe something in
order to measure it.
• To make customer requirements
clear, observable and measurable.
• The ability of understand the basics
of SPC
Operational Definition: Accuracy
Accuracy is the lack of difference between the observed
average value of measurements and the master value.
Average
value is too high
and to the right
My bathroom
scale is always 2
pounds over!
Master Value
(Truth)
A problem with accuracy is a problem with the
TRUTH
Operational Definition: Precision
Precision is an estimate of the overall variation in the
measurement system, including repeatability and
reproducibility.
I never know what
my bathroom
scale will tell me;
sometimes it is 5
pounds over, or
10 pounds under,
or 2 pounds under
or 7 pounds over!
Master Value
(Truth)
A problem with precision is a problem with CONSISTENCY
Types Of Data
•Statistical data is objective data used to determine
performance of processes and to test hypotheses.
Measurability is essential. The three types of data are:
• Attribute
• Variable
• Location
•More widely used are attribute data and variable data.
However, to use data properly, it is essential that you
know what type of data you are collecting and
analyzing.
Operational Definition: Attribute Data
• Attribute data is discrete in nature. This means that
the data is only in integers such as 4, 52, and 1159.
Count data, another term for attribute data, provide
answers to questions such as:
• How many
• What kind
• This data is absolute, meaning it belongs or it does not
belong to a defined group.
Assessing Attribute Processes
• With attribute data we are either classifying a unit as
good or bad or counting the number of flaws in a unit.
• A perfect measurement system would always call a good
unit good and a bad unit bad.
• It seems that attribute inspections require little
judgment: the correct answer is obvious - “the light is
on” or “the light is off”. In reality, they are often
extremely subjective - especially in the areas of
business processes and nondestructive testing.
Operational Definition: Variable Data
• Variable data is continuous. This means that the
data values can be any “real number” such as 2.076, 4.69, 84, and 101.3. Measured data (another term for
variable data) answers question such as:
• How long
• How high
• How much time
• How far
• There is usually a measuring device like a meter, ruler,
or gauge used to gather the data.
Operational Definition: Location Data
• Location data is neither attribute or
variable data. It simply answers the
question:
Where
3 Handouts
The Bell Shaped Curve
• Distributions with the stated three characteristics
can be graphically and mathematically
approximated by the a normal distribution, a bellshaped curve which looks as follows:
Low Score
Mean
Mode
Median
High Score
Not All Bell-Shaped Curves Look The Same
• Depending on the standard deviation the curve can
be flatter.
Same Number
of scores
Fewer around
the mean
s=10
Or it can be taller such as this:
Same Number
of scores
More around
the mean
s=5
Distribution Of Standard Distributions
For A Bell-Shaped Curve
Number Of Scores
X
More
-3 σ
-2 σ
-1 σ
+1 σ
Less
68.3%
95.44%
99.74%
Frequency Of Scores
+2 σ
+3 σ
Comparing Normally Distributed Scores
• A population of students took three tests with the
following scores:
I.Q. Test
Math Test
English Test
Mean
Standard Deviation
100
15
60
10
105
8
One student in the population received the following
scores:
I.Q. Test
Math Test
English Test
Scores
135
74
91
Using The Normal Distribution
To Compare Scores
The Standard Deviation allows us to set a Normally Distributed
scale at 3 standard deviations above and below the mean by
cumulatively adding 15 (IQsd) to 55. [100-(3*15)=55]
IQ Test Normal Distribution with 3 standard distribution from the mean plus and minus
I.Q
Mean
minus
3 s.d.
Mean
minus
2 s.d.
Mean
minus
1 s.d.
55
70
85
Mean
Mean
Plus 1
s.d.
Mean
Plus 2
s.d.
Mean
Plus 3
s.d.
100
115
130
145
We can not create a bell-shape curve because we do not have
individual scores. This analysis does not tell us if the
distribution is normal, it can only be assumed.
Comparing Test Scores
Here we added all three test scores and placed the
individuals scores in the distribution.
I.Q
Mean
minus
3 s.d.
Mean
minus
2 s.d.
Mean
minus
1 s.d.
Mean
Mean
minus
1 s.d.
55
70
85
100
115
Mean
Mean
minus minus
2 s.d. 135 3 s.d.
130
145
74
Math
Test
30
40
Englis
h Test
81
89
19
50
60
70
80
90
97
105
113
121
129
We can now see where our student placed relative to the other scores.
Overview of SPC Measurement Control Charts
Control charts, although similar to run charts,
provide additional information. They are used to
depict the expected range of values that may
occur within 3 standard deviation of the mean.
UCL
Zone A
Zone B
Zone C
Zone C
Zone B
LCL
Zone A
On Taking Action
• SPC is about when to
act and just as
importantly, when not
to act
• Knowing whether the
variation is ‘common’
cause or ‘special’
cause is critical
Process Stability
Prediction
Time
Process
• Stable process outputs form distributions that are
stable over time; that is, they are predictable.
Process Instability
?
Prediction
Process
Unstable process outputs will not be stable over
time = that is: they are not predictable.
SPC Goals
Time
In control
(Special causes eliminated)
Out of control
(Special causes present)
The Goals are to stabilize the
processes so that they have predictable
output performance.
Process Capability
In control and capable
Time
In control but not
capable
Lower
Specification Limit
Upper Specification
Limit
Processes that are in control (stable) are not
necessarily capable of meeting requirements,
our eventual primary objective.
Relationship of Variation to Stability
Stable
In control
Predictable
Common causes only
Time
Unstable
Out of control
Unpredictable
Special causes present
Time
Operational Definition: Run Chart
10
9
8
Number
of
Errors
7
6
5
4
3
2
1
0
1
5
10
15
Weeks
A run chart is a line graph that
shows data plotted over time
20
Operational Definition: Control Chart
Upper
control limit
Center line
Lower
control limit
Control chart: graphic display of
process variation over time;
used to distinguish between
common and special causes.
Common Causes of Variation
Special Causes of Variation
Key Uses of Control Charts
• Monitor process variation over time.
• Differentiate between sources of
variation.
• Assess results of changes
• Establish the basis for determining
process capability.
Rule 1: A lack of control is indicated whenever a
single point falls outside the control limits.
Rule 1 Illustrated:.
Unexpected point may indicate change
in process
Rule #2: Out of Control
Rule 2 Illustrated : A lack of control is indicated
whenever at least two out of three successive values
fall on the same side of, and more than two sigma
units away from the center line.
UCL
Zone A
Zone B
Zone C
Zone C
Zone B
LCL
Zone A
Rule 3: A lack of control is indicated whenever
four out of five successive values fall on the
same side of, and more than one sigma unit
away from, the center line.
UCL
Zone A
Zone B
Zone C
Zone C
Zone B
LCL
Zone A
Rule 4: A lack of control is indicated whenever
at least eight successive values fall on the
same side of the center line.
UCL
LCL
Rule 5: Potential Problem With Non-rational Samples
Rule 5 Illustrated:
Lack of Stratification
Inadequate Measurement Units
1
2
3
4
5
.140.143.137.134.135
.138.143.143.145.146
.139.133.147.148.149
.143.141.137.138.140
.142.142.145.135.136
.1470
.1450
.1378
.1430
.1432
.1398
.1400
.009
.008
.016
.006
.010
1
2
3
4
5
.14
.14
.14
.14
.14
.144
.143
.142
.1430
.1410
.1390
.141
.140
.139
.138
.1370
.1350
.137
.136
.020
.015
.010
.01
.005
.000
.00
.14
.14
.13
.14
.14
.14
.14
.15
.14
.14
.13
.14
.15
.14
.14
.14
.15
.15
.14
.14
.138
.142
.144
.140
.140
.01
.01
.02
.00
.00
Overview of Attribute Control Charts
Attribute control are similar in structure to
variables control charts, except that they
plot statistics from counted data.
UCL
Zone A
Zone B
Zone C
Zone C
Zone B
LCL
Zone A
Building Project Measures
• 30 minute exercise: Using your Process Maps
and Failpoints Matrix:
• Identify the potential for failure at each point
• Select one of the most critical failure points
• Identify what you are going to look at
• Identify what you are going to look for
• Identify how much data you will collect
• Identify why, what, where, when and how
you will collect the data
House of Lean Six Sigma
Continuous Improvement
Lean Enterprise
TPM
DMAIC
Lean Tools
Standardized Work
Facility Layout
Lean Scorecards
Data Analysis Tools
Pull/Kanban
Visual
POUS
5S System
Value
Stream
Mapping
Six Lean Tools
1.Process Simulations
2. Visual Workplace and Visual
Controls
3. Value Stream Mapping
4. Learning to See ‘Muda’ by
Standardizing Operations
5. POUS and Quality at the Source
6. Quick-and-Easy Kaizens
Why Process Simulation?
A process that is well defined, organized, orderly,
safe, efficient, and dependable results in:

Fewer accidents

Improved efficiency

Reduced searching time

Reduced contamination

Visual workplace control

Improved morale

A foundation for all other improvement
activities
Stat-a-Pult Exercise
• Review
Team Process
• Identify Quick & Easy Improvements
•Move to Future State Idealized Process
Components of Standardized Operation
Takt Time
Work
Sequence
Standard
Work
In-Process
Consistency + Predictability = Less Confusion
Lean Six SIGMA Tollgate #5
MEASURE
DEFINE
1
2
3
Develop LQS
4
Create
ANALYZE
IMPROVE
6
9
Analyze
Team Charter,
LQS Model
Measurement
The
& Masterplan
Scorecards
Data
5
Identify
Implement
Customer
Requirements
Project Data
CTQs
Collection Plans
Develop the
High-Level
SIPOC
7 Analyze
8
CONTROL
11
Determine
Generate
Lean
Solutions
Control Points
10
12
Select/
Implement
The
Test
The Lean
Process
Solutions
Analyze
The Root
Causes
Management
Response Plan
Objectives of Tollgate 5
•Create & Install the data collection plan using the
Data Collection tools
•Learn the Basic Steps to Creating your Data
Collection Plan
•Identify the various types of measures for your
Project– Input, Process, and Output
•Determine the Type of Data you will collect in
your project – Discrete and Continuous
•Determine targets and specifications for
your measures
•Develop Check Sheets to use in your Data
Collection Efforts
Efficiency and
Effectiveness
Efficiency – Internal Process measures that tell us how we
are doing such as cost and volume of resources and the
improvements made inside processes – lower cost, less
time, less staff
Effectiveness – Outcome measures of what your service
looks like to your customers and suppliers- have you met or
exceeded their expectations and customer satisfaction
ratings.
Data Collection Planning Tool
Measure
Type of
Measure
Type of
Data
Operational
Definition
Specification
Target
Data
Collecti
on
Form
Sampling
Determine the Type of Measures and Data
TYPES OF MEASURES
Input Measures
(Effectiveness)
Process Measures Output Measures
(Efficiency)
(Effectiveness)
Measures that
Measures Used
The Key Quality
Are internal to
To Determine
And Delivery
Your Process
How well
Requirements
•Cost
Customer
•Cycle Time
Needs and
Placed on Your
Supplier
•Value
Requirements are
•Labor
Met
How Many Measures to Collect?
•Two to Three Output measures
•One to Two Input Measures
•Seven to Ten Process Measures
Types Of Data
•There are two types of data
• Discrete – Yes/No
• Continuous – Ratings on a continuum e.g. height,
weight, temperature
Determine the Targets and Specifications
•Determining the Target – The target
measure is the customer’s ideal
performance of the product or
service
•Determining the Specification – A
specification is the least acceptable
measure of performance for the
product or service in the eyes of the
customer
Determine the Type of Data Collection
Forms Necessary to Collect the Data
•Discrete Data – Use a Defect
Checksheet
•Continuous Data – Use a Frequency
Distribution Checksheet
Check Sheet Operational Definition
•A Check Sheet is a simple data collection
tool used for collecting and recording the
known data of a product, process, or
service in an easy, structured and
consistent format.
•Check Sheets ensure each person
collecting data will record the data in the
same way using a common format
Determine Factors that Ensure Random
and Representative Samples
•Sampling
•Definition – Sampling is the process of
taking only a few products or services
from a larger pool of events.
•Most projects cannot look at the entire
population of events, therefore
sampling is used to save time and
money
Key Questions to Consider
1. What has been done to ensure the sample is a
representative sample?
• Definition of Representative Sample – Sample
has been divided into subpopulations (strata)
and samples are taken of each strata
2. What has been done to ensure the sample is taken
in a random manner?
• Definition of Random Sample – when any one
event has an equal likelihood of being taken
3. How large should the sample size be?
Lean Six SIGMA Tollgate #6
MEASURE
DEFINE
1
2
3
Develop LQS
4
Create
ANALYZE
IMPROVE
6
9
Analyze
Team Charter,
LQS Model
Measurement
The
& Masterplan
Scorecards
Data
5
Identify
Implement
Customer
Requirements
Project Data
CTQs
Collection Plans
Develop the
High-Level
SIPOC
7 Analyze
8
CONTROL
11
Determine
Generate
Lean
Solutions
Control Points
10
12
Select/
Implement
The
Test
The Lean
Process
Solutions
Analyze
The Root
Causes
Management
Response Plan
Overview of Data Analysis
Start With
The Data Collection
System
Analyze Waste &
Root Cause(s)
Analyze Processes
Analyze
The Data
Analyze Phase Approaches
Understand what is causing the waste, the
problems and their effects
Expert
Novice
•Analyze the data from
the data collection
measurement system
•Does not analyze the
data from the
measurement system
•Analyze the process
data and fail points
•Superficial analysis of
process steps
•Do root cause analysis •Jump to improvement
solution
•Test the hypotheses
•No testing
Why Do We Analyze?
• To use Data Analysis tools and
Process Analysis techniques to
identify and verify root causes of
waste and errors
• To identify and eliminate variation in
your processes
• To become ‘Defect Detectives.’
Analysis Challenges
• Moving too quickly from Measurement to
Improve without considering all the relevant
data
• Difficulty in developing and confirming the
best-case hypothesis
• Navigating through the iterative stages of
Exploring, Hypothesis and Verifying Causes
smoothly and productively
Fundamental Question of Analysis
“Is the variation (spread) of my measurement
system too large to study the current level of
process variation?”
Process Variability
(actual variability)
Measurement
Variability
+
Total Variability
(observed variability)
=
Must I stop and correct my measurement system before
proceeding on my improvement project ?
Discrete Data Analysis
• Variation in any process is the enemy of the
Six Sigma team
• It is easier to fight the enemy we can see
• Statistics provide numerical insight into the
inner workings and outside influences of a
process
• Pictures of data, however, allow us to gain
more insight than crunching numbers
• Statistical pictures of discrete data are
created with Pareto Diagrams
Continuous Data Analysis
• Continuous Data is collected using the
Frequency Distribution Checksheet and
analyzed using the Histogram
• Advantage is that it tells team much
more about magnitude of the problem
than Discrete data
• Tells the team about the 6 major factors
affecting the performance of the
process or the data collection system.
Continuous Data Analysis Histogram
• The chief purpose in graphing
data is to show the central
tendency and the spread of
variation
• The Histogram is used as a
graphical display of the number
of times that something occurs
in a set of observations
Data Problems
• Histogram data showing two or
more peaks is multi-modal
• Multiple major peaks is not
unusual, and usually means that
there is a factor(s) affecting the
system to cause it to behave
‘schizophrenically.’
Six Major Factors of Continuous Data
Analysis
The 6Ms
• Machines (and Software)
• Materials (used in data gathering)
• Methods (employed in data gathering)
• Mother Nature (Environment)
• Measurements (used )
• Manpower (People)
Continuous Data Analysis
When no one of the 6Ms are
having an undue influence on
the process or the data
collection, the continuous data
is always ‘bell shaped’–
With most of the measures in
the middle and the rest tailing
out in either direction.
Cause-And-Effect Diagram
• The Cause-And-Effect Diagram is used
to identify causes of variation in the
data collection and in the process, as
well as Root causes of waste and error
• It is one of the most useful all-around
Lean Six Sigma quality tool
• It is also known as the Fishbone in that
it presents a fish-like composite
picture of the system elements that
may be causing problems
Cause-And Effect Diagram
• The diagram consists of six
diagonal lines with boxes
representing the 6Ms
• Cause-And-Effect Analysis can
be carried out on multiple levels
• Up to five levels can be
constructed, roughly
corresponding to the 5 Whys
Lean Six SIGMA Tollgate #7
MEASURE
DEFINE
1
2
3
Develop LQS
4
Create
ANALYZE
IMPROVE
6
9
Analyze
Team Charter,
LQS Model
Measurement
The
& Masterplan
Scorecards
Data
5
Identify
Implement
Customer
Requirements
Project Data
CTQs
Collection Plans
Develop the
High-Level
SIPOC
7 Analyze
8
CONTROL
11
Determine
Generate
Lean
Solutions
Control Points
10
12
Select/
Implement
The
Test
The Lean
Process
Solutions
Analyze
The Root
Causes
Management
Response Plan
Analyzing a Process
DMAIC
Inputs
Process
Outputs
•Observations
•Measurements
•Data
All information gathered by a measurement system
is potentially, and usually, distorted by it.
With DMAIC, the goal is to assess whether the measurement
system consistently yields a true picture of the process
Process Analysis
• Six Sigma is all about reconciling
two voices: the Voice of the
Customer (VOC) and the Voice of
the Process (VOP)
• The effect that each has upon one
another is called capability
• Process ‘Failpoints’ and Process
Capability Measurement help us to
know where to focus attention.
Process Analysis Tools
• Process Maps and Failpoints
Matrix
• Histograms
• Fishbone Diagrams
• Capability Measures
Importance of Reducing Process
Variation
To increase a process
sigma level, you have to
decrease variation.
Less variation provides:
•Greater predictability in the process
•Less waste and rework, which lowers cost
•Products and services that perform better, more consistently
•Happier customers
Six Steps to Analyzing Your Process
1. Create a detailed process map from your
SIPOC Core Process map
2. Do a value added analysis to identify waste
3. Estimate the time for each process step
4. Complete a Process Failpoints Analysis
5. Complete a Moments of Truth Analysis
6. Calculate the Process Capability Index
Steps to Calculate Baseline Sigma Level
We analyze the process in order to calculate
baseline sigma levels as follows:
1. Identify the Unit of performance
2. Determine how a Defect can be created
3. Determine how many Opportunities exist
for a Defect to occur
4. Calculate the Baseline Sigma (Defects per
Million Opportunities <DPMO>)
5. Reference the Sigma Conversion Chart to
determine baseline Sigma performance
6. Determine if the process is capable.
Theme Of Lean Turnaround #2
•The major theme of Lean Turnaround
Module #2 centers around Problem
Identification and Establishing
Objectives:
•Identify the 4 major problem areas
•Establish the 6 most important turnaround
objectives
Project’s Baseline Sigma Performance
Sigma captures the amount of variation in the
processes as it compares to their customer
requirements.
Too much variation
Hard to produce output
within customer
requirements
Low sigma values (0-2)
Moderate variation
Most output meets
customer requirements
Middle sigma values (24.5)
Very little variation
Virtually all output
meets customer
requirements
High sigma values (4.56)
Calculate the Baseline Sigma (Defects
per Million Opportunities DPMO)
Example – Pizza Delivery
Unit – 520 Pizza Deliveries
Defect – 4 (Two late, one discourteous call,
one wrong topping)
Opportunities - 3
________Number of Defects___________ X 1,000,000
Number of opportunities x Number of Units
___4____
3 X 520
X
1,000,000 = 2,564 (DPMO)
Reference the Sigma Conversion Chart to
Determine Baseline Sigma Performance
2564 defects per million
opportunities (DPMO) = 4.3 Sigma
Percent Yield (%)
Defects per
Million
Opportunities
Sigma
99%
6,210
4.0
99.745%
2,550
4.3
99.977%
233
5.0
Six Lean Tools
1.Process Simulations
2.Visual Workplace and Visual
Controls
3. Learning to See ‘Muda’ by
Standardizing Operations
4. POUS and Quality at the Source
5. Value Stream Mapping
6. Quick-and-Easy Kaizens
Lean Six SIGMA Tollgate #8
MEASURE
DEFINE
1
2
3
Develop LQS
4
Create
ANALYZE
IMPROVE
6
9
Analyze
Team Charter,
LQS Model
Measurement
The
& Masterplan
Scorecards
Data
5
Identify
Implement
Customer
Requirements
Project Data
CTQs
Collection Plans
Develop the
High-Level
SIPOC
7
8
Analyze
CONTROL
11
Determine
Generate
Lean
Solutions
Control Points
10
12
Select/
Implement
The
Test
The Lean
Process
Solutions
Analyze
The Root
Cause(s)
Management
Response Plan
Objectivity in Problem Solving
• Decision Theory is based on choosing
among alternatives using quantifiable
measures
• When subjectivity becomes a factor,
the analysis techniques become invalid
due to personal preferences, which
negates prediction
• Root Cause Analysis provides the
inherent objectivity and avoids partial
or incomplete solutions.
Tollgate #8: Perform Root Cause Analysis
• The Root Cause is the most basic reason
causing an undesirable condition or problem
• If eliminated or corrected, it would have
prevented the problem from existing or
occurring
• Root Cause Analysis refers to the process of
identifying and eliminating those so-called
causal factors.
• It is about finding the real cause of the
problem and dealing with it rather than simply
continuing to deal with the symptoms.
Root Cause Analysis (RCA) Questions
RCA raises several questions:
• How does the team determine which situations
are candidates for root cause analysis?
• How does the team figure out what the root
cause is, and how much is related to waste vs.
variation?
• Does the removal of the cause require more
resource expenditure than it takes to continue
to deal with the symptom?
• Which Tools do we use?
Figuring Out What the Root Cause Is
• To find root causes there is one really
only one question that's relevant,
"What can we learn from this situation
that is waste related vs. variation
related?"
• Research has repeatedly proven that
unwanted situations within
organizations are about 95% related
to process problems and only 5%
related to personnel problems.
Is Removal Cost Effective?
• Once the root cause is determined then it has to be
determined whether it costs more to remove the root
cause or simply continue to treat the symptoms.
• This is often not an easy determination!
• Even though it may be relatively easy to estimate the
cost to remove the root cause of waste, it is generally
very difficult to assess the cost of treating the
symptom when it involves variation.
• This difficulty arises because the cost of the
symptom is generally wrapped up in some number of
customer and employee satisfaction factors, in
addition to the resource costs associated with just
treating the symptom.
Which Tools Do We Use?
Root Cause Analysis Tools fall into three
categories:
• Structured Tools such as Cause-and-Effect
(Fishbone) Diagram and Tree Diagram
• Unstructured Tools such as The 5 Whys
and the Relations Diagram
• Critical Thinking Tools such as Waste
(Muda) Analysis, Events/Causal Factors
Analysis, Change Analysis, and Barrier
Analysis
Step-By-Step Root Cause Analysis
Analyzing potential root causes
effectively is best accomplished by
following these key steps:
• Identify the potential cause(s)
• Determine the most likely cause(s)
• Identify the true root cause(s)
Chapter Six of Step-By-Step Problem
Solving explains how this process
works.
Major Factors Affecting Root Cause Analysis
The 6 Ms :
• Machines
• Materials
• Methods
• Mother Nature
• Measurement
• Manpower (People)