Transcript Process Management Training Materials v1.1

Basic Statistics
OSSS Process Management
Copyright OpenSourceSixSigma.com
What is Statistics?
Shilling - “Statistics is communicating information from
data.”
H.G. Wells - “Statistical thinking will one day be as
necessary for efficient citizenship as the ability to read
and write.”
Statistics is a tool to organize data into meaningful
information for understanding the past, to make
informed decisions and to predict the future.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Game Show Exercise
This exercise is based on the game show “Let’s Make a Deal”. The purpose of this exercise is to
analyze the classes decision making patterns and then relate those patterns to probability.
Read the following background for the exercise:
This exercise is based on an actual true set of events, in fact there was much controversy about the
exercise after it was published in Parade Magazine’s “Ask Marylyn” section.
The game show “Let’s Make a Deal” has done this very exercise with its guest hundreds of times. In the
game show, a person from the audience (you) is given an opportunity to win a valuable prize. To win
the prize, you must select from one of three doors. Behind each door is a prize. Only one of the doors
has a valuable prize behind it and only the game show host knows which door has the valuable prize.
The other two doors have booby prizes.
After you have made your selection of door 1, 2 or 3, the game show host will provide you with an
option to change your decision. To do so, the game show host will open one of the remaining two doors
and the door he opens will never have the valuable prize behind it. The host will now ask you if you
want to stay with your original selection or if you would like to switch your selection to the other
remaining unopened door.
Task 1: Decide if you would stay with your original selection or if you would switch your decision
to select the remaining unopened door. You will have just 10 seconds to decide (The TV show
was on-air and broadcast time is valuable time). Check the appropriate decision box below.
_____ Stay with my original selection
_____ Change my mind and switch to the remaining door.
Task 2: The instructor will poll the class and discuss the data.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Game Show Exercise
Discussion:
1.
2.
3.
4.
Should you change?
Does it matter?
If you change, will it improve your chance to win the car?
How would you analyze this situation using data to
determine the best choice?
OSSS Process Management
Copyright OpenSourceSixSigma.com
Analyzing the Possibilities
1
2
3
Change
Do Not
Change
I
1
2
III
2
WIN
WIN
LOSE
WIN
LOSE
3
II
1
LOSE
3
When intuition leads us down the wrong path,
the use of statistical tools and data can set us straight!
OSSS Process Management
Copyright OpenSourceSixSigma.com
Ask Marilyn – Parade Magazine Feb. 1991
“You are utterly incorrect about the game-show question, and I hope this
controversy will call some public attention to the serious national crisis in
mathematical education. If you can admit your error, you will have
contributed constructively toward the solution of a deplorable situation.
How many irate mathematicians are needed to get you to change your
mind?”
E. Ray Bobo, Ph.D.,
Georgetown University
“You are in error-and you have ignored good counsel-but Albert Einstein
earned a dearer place in the hearts of the people after he admitted his
errors.”
Frank Rose, Ph.D.,
University of Michigan
“Your logic is in error, and I am sure you will receive many letters on this
topic from high school and college students. Perhaps you should keep a
few addresses for help with future columns.”
W. Robert Smith, Ph.D.,
Georgia State University
OSSS Process Management
Copyright OpenSourceSixSigma.com
Ask Marilyn – Parade Magazine Feb. 1991
“Maybe women look at math problems differently than men.”
Don Edwards,
Sunriver, Or.
“You’re wrong, but look on the positive side. If all those Ph.D.’s were
wrong, the country would be in very serious trouble.”
Everett Harman, Ph.D.,
US. Army Research Institute
“You are indeed correct. My colleagues at work had a ball with this
problem, and I dare say that most of them - including me at first - thought
you were wrong!”
Seth Kaleon, Ph.D.,
Massachusetts
Institute of Technology
OSSS Process Management
Copyright OpenSourceSixSigma.com
Levels of Analysis
1. Using previous experience.
2. Collecting data and then
looking at the numbers.
A decision is made based on the similarity of a
previous event or occurrence.
Data is collected, looked at and “sized” based
on the apparent patters and a decision made.
3. Grouping data so as to form
charts and graphs.
Generally the data is put into an excel
spreadsheet, graphs are looked at and a
decision is made.
4. Using census data with
descriptive statistics.
Data is collected on 100% of the items under
review and statistics like average, minimum and
maximum are used to make decisions.
5. Using sample data with
descriptive statistics.
Data is collected on a subset of the items under
review and statistics like average, min and max
are used to make decisions.
6. Using sample data with
inferential statistics.
Data is collected on a subset of the items under
review and the analysis allows inferences about
larger populations with known risks.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Exercise - Usage of Data Exercise
The purpose of this exercise is estimate the amount of time your
company tends to use the various levels of analysis to make decisions
and to run the business. Be as honest as you can, we will put all of the
data from the class together and present it back to immediately upon the
completion of the exercise.
Read the following background for the exercise:
Most companies have not thought about the typical level of data
analysis they use. You and your colleagues in this class will form a
“sample” of the organizations you are a part of. This exercise will be
used to establish a reference that you can use to build from in your
organizational pursuit of improvement.
Task 1: Estimate to the best of your ability what percentage of the
time your company tends to use each level of analysis. Your total
should add up to 100%.
Task 2: The instructor will then collect each individuals estimates
and sum them together using an Excel spreadsheet tool to show
the results.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Exercise – Usage of Data
Levels of Analysis
% Use
1. We use previous experience
Instructions
1.
Estimate from your
personal experience the
percent of time your
organization uses these
various levels of data
analysis to either make
decisions or to manage
process performance
2.
Try to allocate among the
six levels to obtain a total
of 100%
3.
We will collect the data
from the class and make a
Histogram.
2. We collect data and then
look at the numbers
3. We group data so as to form
charts and graphs
4. We use census data with
descriptive statistics
5. We use sample data with
descriptive statistics
6. We use sample data with
inferential statistics
Total
OSSS Process Management
100%
Copyright OpenSourceSixSigma.com
Knowledge is in the Data
“When you can measure what you
are speaking about, and express it in
numbers, you know something about
it; but when you cannot express it in
numbers, your knowledge is of a
meager and unsatisfactory kind.”
Scottish
mathematician
and physicist who
contributed to
many branches of
physics
1824 – 1907
1. We use previous
experience
2. We collect data and then
look at the numbers
3. We group data so as to
form charts and graphs
4. We use census data with
descriptive statistics
5. We use sample data with
descriptive statistics
6. We use sample data with
inferential statistics
Success
As the level
of analysis
increases
so does
our
success
Extent of Knowledge
(Derived from observation and measurement)
OSSS Process Management
Copyright OpenSourceSixSigma.com
Types of Data
Attribute (Qualitative) Data
• Yes, no
• Go, no go
• Acceptable, unacceptable
• Pass, fail
Continuous (Quantitative) Data
•Discrete (count) Data - patients,
bottles of medicine, late deliveries,
system lock-ups
•Continuous Data - dimension,
volume, time (decimal subdivisions
are meaningful)
Parameter
Height
X
Weight
X
Fail
Length
Width
X
X
Quantity
Parameter
X
Measurement
Height
27.44 Pounds
Weight
16.02 Inches
Length
12.03 Inches
Width
9.75 Inches
Quantity
OSSS Process Management
Pass
12 Units
Copyright OpenSourceSixSigma.com
Understanding Variation
Each day you
target to arrive
at work at 8:00
AM, but do you
always arrive at
exactly 8:00
AM?
OSSS Process Management
Arrival Time
Arrival Day
Data
1
8:03
2
7:52
3
7:55
4
7:54
5
8:09
6
7:59
7
7:55
8
8:04
9
8:08
10
8:02
11
8:00
12
7:55
13
8:06
14
8:02
15
7:58
16
8:03
17
8:01
18
7:57
19
7:55
20
8:06
By measuring the
arrival times we
notice that the
times are not
exactly the same.
Copyright OpenSourceSixSigma.com
Visualizing Variation - Histogram
The Histogram represents the
behavior of the variable of interest for
every time it was measured
The Normal
Distribution
Frequency
(Number of Occurrences)
6
5
4
3
2
1
0
7:52
7:55
7:58
8:01
8:04 8:07 8:10
Data that was measured for arrival time to
work. Histograms can be for any variable
such as volumes in ml, errors per request,
time in hours, etc.
OSSS Process Management
The shape that forms for
many types of data we
deal with daily.
Copyright OpenSourceSixSigma.com
Variation and its Source
Each time you call a company for
customer service, you get a
different level of service and you
experience a different level of
satisfaction.
Each time you hit a golf ball it goes
a different direction and distance.
Some golfers are more accurate
than others, but no one is perfect.
Each time you provide a product
or a service to your customer, it
varies. If it varies too much, your
customer will not accept it.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Variation is Everywhere and Affects Everything
Color
You should always construct a
histogram when working with data,
either mentally or on paper
Weight
Time
Height
6
Length
5
Frequency
4
3
Width
Shape
2
1
Speed
Temperature
0
7:52
OSSS Process Management
7:55
7:58
8:01
8:04 8:07 8:10
Copyright OpenSourceSixSigma.com
Variation and its Source
Each time you call a company for
customer service, you get a
different level of service and you
experience a different level of
satisfaction.
Each time you hit a golf ball it goes
a different direction and distance.
Some golfers are more accurate
than others, but no one is perfect.
Each time you provide a product
or a service to your customer, it
varies. If it varies too much, your
customer will not accept it.
OSSS Process Management
SO WHY DOES
EVERY OUTPUT
VARY?
Because all inputs, the
X’s vary. Remember,
the output Y is a
function of the input X’s.
TIP: To control the
variation in an outcome
you are interested in,
you will have to control
the variation of the
inputs that affect it.
Copyright OpenSourceSixSigma.com
The X’s (Inputs)
X1
X2
X3
X4
Y = f(X)
The Y’s (Outputs)
Process:
“A Blending
Of Inputs to
Achieve
Some Desired
Output/Result”
Y1
Y2
Y3
X5
Critical X - Any input
variable that exerts an
undue influence on one
or more of the important
outputs of a process.
CTQ = Critical to
Quality - Any output
variable of a process
which exerts an undue
influence on the success
of the process or
customer needs.
Outputs that do not meet requirements create defects and generate
additional costs called “Cost of Poor Quality” or COPQ.
OSSS Process Management
Copyright OpenSourceSixSigma.com
The things you measure as an
indication of the success of the
process
Materials, People, Equipment, etc.
Six Sigma View of a Process
Variation – Signal – Noise – Error
Pictorial Representation of Y = f(X) +
e
“Function of”
Controllable
Inputs
Xs
Process Temperature
Information or Data
Time
Room Temperature
The Process:
The Blending
Of Inputs
Ys
e
Noise Inputs
Humidity
Process
Outputs
Things that we or
the customer want
People
Machines
Unknown Inputs
OSSS Process Management
Copyright OpenSourceSixSigma.com
Averages and Variation
PO Time Data
41 53 54 53
50 50 50 52
47 48 47 55
53 57 50 47
51 50 48 51
50 46 53 49
49 42 48 47
54 43 52 48
53 49 53 49
52 50 58 53
47 51 60 50
53 51 51 57
52 51 49 52
50 47 48 49
48 51 48 47
43 50 53 51
46 49 44 50
49 45 49 45
47 51 46 52
47 52 51 50
40
43
54
48
48
51
51
53
52
50
48
52
50
50
55
52
46
51
49
52
51
OSSS Process Management
45
50
55
60
time (seconds)
First three measurements for filling
out a purchase order form
40
45
50
55
60
time (seconds)
100 measurements of elapsed time for
filling out a purchase order form
Copyright OpenSourceSixSigma.com
Averages and Variation
PO Time Data
41 53 54 53
50 50 50 52
47 48 47 55
53 57 50 47
51 50 48 51
50 46 53 49
49 42 48 47
54 43 52 48
53 49 53 49
52 50 58 53
47 51 60 50
53 51 51 57
52 51 49 52
50 47 48 49
48 51 48 47
43 50 53 51
46 49 44 50
49 45 49 45
47 51 46 52
47 52 51 50
OSSS Process Management
40
43
54
48
48
51
51
53
52
50
48
52
50
50
55
52
46
51
49
52
51
45
50
55
60
time (seconds)
First three measurements for filling
out a purchase order form
40
45
50
55
60
time (seconds)
100 measurements of elapsed time for
filling out a purchase order form
Copyright OpenSourceSixSigma.com
Calculating the Average
PO
41
50
47
53
51
50
49
54
53
52
47
53
52
50
48
43
46
49
47
47
OSSS Process Management
Time Data
53 54 53
50 50 52
48 47 55
57 50 47
50 48 51
46 53 49
42 48 47
43 52 48
49 53 49
50 58 53
51 60 50
51 51 57
51 49 52
47 48 49
51 48 47
50 53 51
49 44 50
45 49 45
51 46 52
52 51 50
43
54
48
48
51
51
53
52
50
48
52
50
50
55
52
46
51
49
52
51
Mathematically, the process for
calculating the mean is written as:
xi
x
n
X (pronounced “x bar”) is the
symbol representing the calculated
average;
Xi represents each of the individual
measurement values;
The Greek letter  tells you to
sum (add) all the individual
measurements; and
n is the number of individual
measurements(100 in this
example) for your data set.
Copyright OpenSourceSixSigma.com
Calculating the Average
PO Time Data
41 53 54 53
50 50 50 52
47 48 47 55
53 57 50 47
51 50 48 51
50 46 53 49
49 42 48 47
54 43 52 48
53 49 53 49
52 50 58 53
47 51 60 50
53 51 51 57
52 51 49 52
50 47 48 49
48 51 48 47
43 50 53 51
46 49 44 50
49 45 49 45
47 51 46 52
47 52 51 50
43
54
48
48
51
51
53
52
50
48
52
50
50
55
52
46
51
49
52
51
Average
= 50
Seconds
40
45
50
55
60
time (seconds)
100 measurements of elapsed time for
filling out a purchase order form
OSSS Process Management
Copyright OpenSourceSixSigma.com
Variation and Average
15%
40
45
50
We would experience
the average 15 times
out of 100, or 15% of
the time.
55
60
We would experience
some other value 85
times out of 100, or
85% of the time.
time (seconds)
You and your customers rarely feel the average, most
often you feel the variation.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Variation and Average
Scenario 1
The average price
is $125,000
GREAT!!
25 homes are in
the neighborhood.
Scenario 2
+
5 Additional homes
valued at $400,000
each.
=
The average
price is now
$170,000
Same 25 homes are in
the neighborhood.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Variation and Average
Scenario 1
Scenario 2
XXXXX
X
XXX
XXXXX
XXXXXXX
XXXXX
XXX
X
$170,000
$125,000
$400,000
$350,000
$300,000
$250,000
$200,000
$150,000
$100,000
OSSS Process Management
Copyright OpenSourceSixSigma.com
Variation and Average
“The Rio Grande, on
average, is only 4 feet
deep. So let’s wade
across!” Well, the
variation is from 1 inch
to 20 feet! Could you
have a problem?
You will get paid, on
average, once every
two weeks. But
sometimes the check
is three weeks late.
Would this be a
problem?
OSSS Process Management
A salesperson arrives to
work on average at 8:00
AM. Some mornings he
is there as early as 7:30
and as late as 8:30.
Customers needing his
support sometimes get
him in the morning just
after 8:00, other times
they get his voicemail.
Some customers call the
competition!
Copyright OpenSourceSixSigma.com
Example - Averages and Variation
You tell your customers that your
delivery time is two days, on average.
You have just set a customer
expectation for a two day delivery.
Because of the variation in your delivery
process, 20 percent of the time packages
take more than two days to deliver. How
do you tell one out of five unhappy
customers that they are just a victim of
the averages?
OSSS Process Management
Copyright OpenSourceSixSigma.com
Common Statistical Metrics
Average (Mean, m, Xbar) - The arithmetic average of a set of values
•
•
Uses the quantitative value of each data point
Is strongly influenced by extreme values
Median (M) - The number that reflects the 50% mark of a set of values
•
•
Can be easily identified as the center number after all values are
sorted from high to low
Is not affected by extreme values
Mode - The value that appears most frequently
Range (R) - The spread of the data from lowest to highest, calculated by
subtracting the minimum value from the maximum value
Sigma - A value that measures the amount of variation in a population
For a Normal Distribution, the Mean, Median and Mode are the same.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Usage of Data Exercise
The purpose of this exercise is to demonstrate how easy it is to collect a
data set and turn it into a Histogram.
Read the following background for the exercise:
Not everyone is the same height, not even in this class. As a class we will
plot a Histogram on a flipchart for the distribution of everyone’s height in
this classroom. Data will be gathered from the class for the purpose
creating a histogram. Use the post-it notes supplied to record your height.
Task 1: Write your height in inches rounded to the nearest inch.
Task 2: Pass the note to the instructor.
Task 3: The instructor will have one of the students read the
values.
Task 4: The instructor will generate a Histogram of the data
Frequency
Y-Axis
X-Axis
58"
60"
62"
64"
66"
68"
70"
72"
74"
76"
147 cm 152 cm 157 cm 163 cm 168 cm 173 cm 178 cm 183 cm 188 cm 193 cm
Height
OSSS Process Management
Copyright OpenSourceSixSigma.com
Exercise – Developing a Histogram
Observations:
1. Is there variation in the data?
2. What is the Range (max value – min value)?
3. What is the average height (sum of all heights/number of
students)?
4. Does the data create a specific shape (which distribution)?
5. Is it symmetrical or is it skewed in one direction?
6. What is the Mode?
OSSS Process Management
Copyright OpenSourceSixSigma.com
Understanding Probability
1. Probability is the likelihood of an event
occurring in the future:
•
The weatherman predicts an 80% chance
of rain tomorrow
2. Probabilities come from facts (data) and
statistics:.
•
•
Wind direction, altitudes and velocity
Temperature, humidity, barometric pressure
3. Probabilities can be used to predict the outcome
of single events or combinations of events:
•
The probability it will rain (P1), that it will rain 2 or
more inches (P2) and that the temperature will be 73
degrees (P3)
OSSS Process Management
Copyright OpenSourceSixSigma.com
Understanding Probability
Other examples of probability:
1. I flip a coin and pick heads as my choice. What are
the chances of getting a head?
•
One in two, or 50%
2. I buy a lottery ticket. There is one winner and 1,000 tickets are sold.
What are my chances of winning?
•
One in one thousand or .001
3. Over a 6 month period of time you discover that consistently 20
percent of the products you have shipped to customers are
defective. Your best performance has been 18% defective and your
worst has been 22.5% defective. If you take no action to improve,
what is the probability that the next 2 months of shipments will
average between 15% and 25% defective?
•
Essentially 100%, more precisely it will be 99.99…..%
OSSS Process Management
Copyright OpenSourceSixSigma.com
Understanding Probability
The sum of all probabilities always equals 100%. This allows us
to more easily solve Statistical Problems because one side of the
equation is always known.
Certainty
+
Uncertainty = 100%
Known
+
Unknown
= 100%
Belief
+
Disbelief
= 100%
Risk
= 100%
Confidence +
Yield
+
Defect Rate = 100%
Remember - The sum of probability is always 100%
OSSS Process Management
Copyright OpenSourceSixSigma.com
Understanding the Die Probabilities
Questions:
1. What’s the probability of rolling a 1?
2. What’s the probability of rolling a 2?
3. What’s the probability of rolling a 6?
4. What’s the sum of the six probabilities of rolling a 1, a
2, a 3, a 4, a 5, a 6?
Remember - the sum of all possible
outcomes always equals 100%
OSSS Process Management
Copyright OpenSourceSixSigma.com
Understanding the Dice Probabilities
To understand the probabilities of all the combinations
in the roll of two dice, you simply have to construct a
matrix of all the combinations.
Value from Die 2
Value from Die 1
1
2
3
4
5
6
1
2
3
4
5
6
7
2
3
4
5
6
7
8
3
4
5
6
7
8
9
4
5
6
7
8
9
10
5
6
7
8
9
10
11
6
7
8
9
10
11
12
OSSS Process Management
Note: There are 36
possible outcomes for
the sum of the roll of two
dice with six numbers on
each dice.
Copyright OpenSourceSixSigma.com
Understanding the Dice Probabilities
What’s the probability of rolling an 8 with 2 dice?
Value from Die 2
Value from Die 1
1
2
3
4
5
6
1 2
3
4
5
6
7
2 3
4
5
6
7
8
+
3 4
5
6
4 5
6
7
5 6
7
6 7
8
OSSS Process Management
+
7
8
9
8
9
10
8
9
10
11
9
10
11
12
+
+
Using the matrix, we
see there are 5
combinations that add
up to a total of 8
Copyright OpenSourceSixSigma.com
Understanding the Dice Probabilities
What’s the probability of rolling an 8 with 2 dice?
Each combination is a 1/36 chance
multiplied by 5 combinations equals a
5/36 probability.
Value from Die 2
Value from Die 1
1
2
3
4
5
6
1
1/36
1/36
1/36 1/36
1/36 1/36
2
1/36
1/36
1/36 1/36
1/36 1/36
+
3
1/36
4
1/36
5
1/36
1/36
1/36 1/36
1/36 1/36
1/36 1/36
+ 1/36
_________________________________
1/36 1/36
1/36 1/36
1/36 1/36
1/36 1/36
+
6
1/36
1/36
OSSS Process Management
+ 1/36
+ 1/36
+
1/36
+ 1/36
1/36 1/36
+
1/36
1/36
5/36 = 0.138
or 13.8%
Copyright OpenSourceSixSigma.com
Understanding the Dice Probabilities
What’s the probability of rolling a 7 with 2 dice?
Value from Die 2
Value from Die 1
1
2
3
4
5
6
1 2
3
4
5
6
7
+
2 3
4
5
6
7
8
8
9
+
3 4
5
4 5
6
5 6
+
6 7
OSSS Process Management
6
+
7
+ 1/36
+ 1/36
+ 1/36
+ 1/36
7
8
9
10
7
8
9
10
11
8
9
10
11
12
+
1/36
+ 1/36
_________________________________
6/36 = 0.167
or 16.7%
Copyright OpenSourceSixSigma.com
Exercise – Meeting Customer Expectations
The purpose of this exercise is to demonstrate how a simple process will
generate data and to demonstrate what probability is.
Read the following background for the exercise:
This exercise involves the process of rolling two dice. Each die has six sides numbered 1
through 6. After rolling the dice a number of times, the output (Y) will be a range of
numbers between 2 and 12. This output is called the VOP (Voice of the Process).
The process has a customer who will only accept outcomes between 3 and 11. They will
not accept a 2 or a 12. This is called the VOC (Voice of the Customer). The lower limit of 3
is called the LSL (Lower Spec Limit) and the upper limit of 11 is called the USL (Upper
Spec Limit)
Task 1: Break into teams of two. One person will roll the dice 50 times while the other
records the data on the following page. The team members will switch jobs and repeat
the process.
Task 2: The data will be recorded directly into a histogram. Each time a number is
thrown, add an “X” in the appropriate numbered column.
Task 3: Calculate the percentage of times your process was unable to meet the
requirements of the customer.
Task 4: When everyone is finished, your team will report your data to the Instructor for
further evaluation by the class.
OSSS Process Management
Copyright OpenSourceSixSigma.com
Quantity of Times A Number is Thrown
Exercise – Meeting Customer Expectations?
30
29
28
27
26
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
1. Place an X into the column
representing the value of
each throw
2. Each person will toss the
dice 50 times for a total of
100 tosses for the team
1. Count the number of X’s
that appear in the 2 and 12
columns
2
3
4
5
6
7
8
9
10
11
12
2. Since you made 100
tosses, the combined
number is the percentage of
times you failed to meet the
VOC
Total Value of the Dice Throw
OSSS Process Management
Copyright OpenSourceSixSigma.com
Back to Meeting Our Customer’s Needs
1.
Value from Die 2
2.
3.
Remember, the customer required an outcome that totals 3, 4,
5, 6, 7, 8, 9, 10 or 11.
What is the probability of meeting customer expectations?
Is our process, the process of tossing two dice, capable of
meeting the VOC?
Value from Die 1
1
2
3
4
5
6
1 2
X
3
4
5
6
7
2 3
4
5
6
7
8
3 4
5
6
7
8
9
4 5
6
7
8
9
10
5 6
7
8
9
10
11
6 7
8
9
10
11
12
OSSS Process Management
X
34 / 36 = 0.944
Which is
94.4%
Or 5.6% Defects
The Process is Not
Capable!
Copyright OpenSourceSixSigma.com