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RMS Six Sigma Training
Credit to multiple data sources including Villanova University Black Belt and Green Belt Courses, Six Sigma Memory Jogger I and II, and Lean Six Sigma Pocket Toolbook.
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What is Six Sigma?
The Six Sigma methodologies are a business philosophy and initiative that enables world-class quality and continuous improvement to achieve the highest level of customer satisfaction. Metrics are established that align an Organizations’ strategic goals and values to that of their customer’s needs and expectations.
MeasureMeasure
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How Does it Work?
• Uses Data and Statistical Tools to Systematically Improve Processes and Sustain Results
• Process Metrics are Evaluated• Comparison of Average and Variation to Performance
Specifications or Targets• Methodology is a Project-Focused Approach
Consisting of Five Phases-DMAIC
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Who Uses Six Sigma?
Define Measure Analyze Improve Control
The following companies claim to have successfully implemented Six Sigma in some form or another:
• 3M
• Advanced Micro Devices
• Air Canada
• ALCAN
• Amazon.com
• Bank of America
• Boeing
• Caterpillar Inc.
• CIGNA
• Dell
• Delphi Corporation
• DHL
• Deutsche Telekom
• Dow Chemical Company
• DuPont
• Ecolab
• Ford Motor Company
• General Electric
• GlaxoSmithKline
• Heinz Co.
• Honeywell
• HSBC Group
• Ingram Micro
• LG Group
• Lockheed Martin
• Merrill Lynch
• Merck
• Motorola
• Nielsen Company
• Nortel Networks
• Northrop Grumman
• Penske Truck Leasing
• Quest Diagnostics
• Samsung Group
• Siemens AG
• Staples Inc.
• Target Corporation
• Teradyne
• The Hertz Corporation
• Toshiba
• United States
Armed Forces
• Vodafone
• Whirlpool
• Xerox
Source: Wikipedia
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Affinity Diagram
Comm Plan
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CTQ Tree
Data Collection
Kano Model
Pareto Chart
Run Chart
SIPOC
Tollgate
VOC
Control Charts
Frequency Plots
Check sheet
Flowchart
Histogram
Kano Model
Pareto Charts
Process Sigma
Run Chart
Loss Function
Tollgate Review
Brainstorming
Cause and Effect Diagram
Design of Experiments
Control Charts
Histogram
Hypothesis Test
Interrelationship Diagraph
Scatter chart
Tree Diagram
Tollgate Review
Gantt Chart
Brainstorming
Control Charts
FMEA
Histogram
Design of Experiments
Pareto Chart
PDCA
Prioritization Matrix
Process Sigma
Run Chart
Tollgate
Communication Plan
Control Charts
PDCA Cycle
Process Mgmt Chart
Run Chart
Six Sigma Storyboard
Pareto Chart
Prioritize Matrix
Affinity Chart
Pareto Chart
Activity Network
PDPCQFD
Tollgate Review
Control Charts
The Tools of Six Sigma
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Source: Villanova University Six Sigma Lectures
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DMAIC Overview
DMAIC – Tollgate Subdivisions by George EckesSource: Villanova University Six Sigma Lectures
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Project CharterID & validate customer needs and requirements
High level picture of the target processCreate a collection plan
Implement plan, compute baseline sigmaExamine data
Watch the processDetermine root cause
Generate solutionsSelect solutions
Implement solutionsPick the right control methodDocument the response planControl
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Analyze
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Team Roles within a Six Sigma Organization
Master Black Belt
Trains and coaches Black Belts and Green Belts. Functions more at the Six Sigma program level by developing key metrics and strategic direction. Acts as an organization's Six Sigma technologist and internal consultant
Black Belt Leads problem solving projects. Trains and coaches project teams
Green BeltAssists with data collection and analysis for Black Belt projects. Leads Green Belt projects or teams.
Yellow BeltParticipates as a project team member. Reviews process improvements that support the project.
White BeltCan work on local problem-solving teams that support overall projects, but may not be part of a Six Sigma team. Understands basic Six Sigma concepts from an awareness perspective.
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Executive Roles within a Six Sigma Organization
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Champions
Translate the company's vision, mission, goals and metrics to create an organizational deployment plan and identify individual projects. Identify resources and remove roadblocks.
ExecutivesProvide overall alignment by establishing the strategic focus of the Six Sigma program within the organization's culture and vision.
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Purpose
• Define Business Metrics
• Identify Projects for Process Improvement
• Identify Resources for Process Improvement
Tools
• SIPOC
• Understanding the Voice of the Customer• Kano• QFD
Key Outputs
• Project Charter• Project Team• Management
Commitment
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Projects and Process Improvements are based on Customer’s Needs and Requirements
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DefinitionNeeds Establishes the relationship between the company &
the customer
Requirements Characteristics that determine whether the customer is satisfied
Notes:• It is very important to
establish clear metrics and goals to validate satisfaction levels
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Projects begin with understanding
Projects end with meeting
Six Sigma and VOC
Source: Villanova University Six Sigma Lectures
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In order to improve upon a process, you must first understand the process.The SIPOC Method can help…
SIPOC is used to document a process at a high level and visually show the process
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Supplier Inputs Process Outputs Customer
News Newspaper / Internet
Select Dealership
Dealership Car Test Drive
Manufacturer Brochure Select Option Package
Car Chosen Purchaser
Customer Information / Offer
Negotiate Financing / Price
Purchaser’s Family
Finance Company
Credit Info Finance Contract
SIPOC Diagram
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Another SIPOC Example
Inputs Process Output CustomerSuppliers
Nurse
Doctor
Diagnosis
Admis
Discharge
Prescrip
Billing
Referral
Treatment
Hospital
Patient
Family
Insurance
Drugs
MedicalEquip
Patientrecords
911
Paramedic
Drug man
MedicalEquip man
Inputs Process Output CustomerSuppliers
Nurse
Doctor
Diagnosis
Admis
Discharge
Prescrip
Billing
Referral
Treatment
Hospital
Patient
Family
Insurance
Drugs
MedicalEquipmentSupplier
Patientrecords
911
Paramedic
PharmaceuticalSupplier
MedicalSupplier
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Take care of your customers’ expectations in sequence from expected to normal to exciting!
• Our customer’s basic servicing expectations
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Develop Affinity Heading Cards
• What do our customers want?
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Post the QFD where all the teams can refer to it often, to better understand why decisions are made!
Usage:
• Fully understand BPO customer needs at initiation of services
• Clearly prioritize key requirements (DSO, Aging Reduction, AHT)
• If possible, learn from competition
Source: Villanova University Six Sigma Lectures
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What is a Project Charter?
The project charter defines all interactions of the project and sets the stage for a successful completion.
A project charter is the first step in the Six Sigma methodology. It takes place in the Define step of DMAIC, and the charter can make or break a successful project. It can make it by specifying necessary resources and boundaries that will in turn ensure success; it can break it by reducing team focus, effectiveness and motivation.
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Usage:
• Provides written and agreed upon details for short term projects
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Project Title: Sales Analysis
Business Case:
(A broad definition of the issue as well as therationale for why this project should be a business priority.)
Sales at Company X has been growing annually, but it has experienced unusually low sales during July/Aug. Management is concerned about implications to their stock price.
Document Your Project Using a Project Charter
Source: Villanova University Six Sigma Lectures
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Project Title: Sales Analysis
Problem/Opportunity Statement:
1 or 2 sentences describing the symptoms, such as where is the problem, how big is the problem, or what is the impact.
Low July/Aug sales in the eastern region have declined 20%. Other regions have not seen a decline in sales.
Gap between desired state and current state
Source: Villanova University Six Sigma Lectures
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Problem/Opportunity Statement:Low July/Aug sales in the eastern region have declined 20%.
Goal Statement
Problem Statement and Goal statement are a matched pair. Measurable target for desired results and completion target date.
SMART – Simple, measurable, accurate, realistic, timely
Identify & eliminate the cause of low sales in the Eastern region by December 1 so that Eastern region sales rebound by 25% by the end of 1st quarter 2007.
Benchmark – George Eckes – 50% improvement
Usage:
• Use the “SMART” tip when writing goals for clear down and backlog reduction plans
Source: Villanova University Six Sigma Lectures
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Define Measure Analyze Improve Control
Project Title: Sales Analysis
Project Scope:
Where does the project start and stop? Where does the process start and stop? Identifyconstraints and assumptions.
The 7 member team will begin analysis of the Eastern sales process on September 1 and report their findings on November 1.Budget $25,000. Analyze process from 1st sales call to thru close of sale. Does notincludes all sales leads.
Usage:• Very important in the front end of initiating services with new customers• FTE Analysis• Scope Creep• Clearly defined for the customer
Source: Villanova University Six Sigma Lectures
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Purpose•Establish Baseline Performance•Identify Validate Measurements for Project Improvement
Tools•Descriptive Statistics•Central Tendency•Dispersion•Basic Statistical Process Control SPC•Process Flow Diagram
Key Outputs•Data Collection Plan•Performance Baseline-DPMO•Six Sigma Level•Current Process Flow Chart
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A Data Collection Plan will help organize and validate what is to be measured.
Data Collection Plan
What to M
easure
Type of measure
Type of Data
Operational D
efinition
Specification
Target
Data C
ollection Form
Sampling
Baseline Sigm
a
Data Collection Plan
What to M
easure
Type of measure
Type of Data
Operational D
efinition
Specification
Target
Data C
ollection Form
Sampling
Baseline Sigm
a
Source: Villanova University Six Sigma Lectures
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Usage:
• ACD Stats• Aging Reduction• AR Roll• DSO• Productivity
ExamplesQuality • Product or Service Features
• Attributes• Dimensions
• Scrap• Rework• Reliability
Cost • Labor• Material• Overhead• Repair Costs
Speed • Lead Times• Delivery Times• Turnaround Times• Setup Times• Cycle Times• Delays
What to Measure?
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Source: Villanova University Six Sigma Lectures
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Input Metrics Process Metrics Output Metrics
• Accuracy of Customer Order• Quality of Ingredients
• Cooking Time• Preparation Sequence
Taste Quality
• Time to Receive Order• Time to Gather Ingredients• Time to Prep Food
• # of Process Steps• Time to Cook Food• Wait Time between Steps
Door to Door lead time Speed
• # and $ of Ingredients • # of Process Steps $$$ Cost
What is Important to the Customer?Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Operational definitions are clear and precise instructions on how to take a particular measurement.
Connection:
• 8 hour day vs. 7.5 hour day
• Productivity Calculation:• Unique Touches by Account
• Touches per Week at Invoice Level
Source: http://www.isixsigma.com/index.php?option=com_k2&view=item&id=1265:&Itemid=49
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The customer’s ideal performanceThe customer’s least
acceptable product or service
VOC: Voice of the CustomerSource: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Usage:• Root Cause• Synergy Categories (Start-up / Promises)• Aging Results
Source: Villanova University Six Sigma Lectures
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Usage:
• Synergy Categories (Start-up / Promises)• Aging Results
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Usage:
• Calls per Hour• Actions per Hour• ACD Statistical Analysis (AHT, Abrate)
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Usage:• Visual Displays• Correlation Analysis• Tenure of Employees & Productivity Rate
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Usage:
• Production Rates• Collection Rates• ACD Statistics
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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= level of precision (margin of error) desired from the sample in the same units as the “s” measurement
Example:
• The standard deviation for collector production is +/- 4
calls per hour. Average is 10 calls per hour
• See page 80 for a simple definition of standard deviation
Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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What is Sigma?A Simple Definition
• Six Sigma is a statistical term that equates to 3.4 defects per one million opportunities.
• Today, most organizations operate at around three sigma, which translates into roughly 67,000 defects per million opportunities.
• This methodology eliminates defects from existing processes, products, and services, saving millions of dollars every year and increasing customer satisfaction.
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PerformanceLevel SIGMA DPMO
A+
A
B
6
5
4
3.4
233
6,210
C 3 66,811
D 2 308,770
F 1 697,672
Handbook – Appendix XII-3
Sigma Levels
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What is an Opportunity?
Opportunity is any area in a product or service where a defect couldbe produced. Opportunities are things which must go right to satisfy the customer.
• Exact name on credit card• Billing address of credit card• Credit card number• Expiration date• Product ID being ordered• Quantity
Six Sigma Term
• DPMO = Defects per Million Opportunities
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Example:
Formula
Defects
(# of Opportunities * Sample Size)
Source: Villanova University Six Sigma Lectures
Measure
DPMO =
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Simplify Sigma
±6smLSL USL1s 2s 3s 4s 5s 6s1s2s3s4s5s6s
As my sigma (standard deviation of my data set) gets smaller, I am able to ‘fit in’ more sigmas before I reach my customer specs.
The sigma value (or the standard deviation) gets smaller (3.2 to 1.6), but the sigma levels gets larger. We want the sigma level to increase.
Sigm
a Va
lue
/ S
tand
ard
Dev
iatio
n
Customer SpecificationUpper Limit
Customer SpecificationLower Limit
Average
Source: Villanova University Six Sigma Lectures
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What is Standard Deviation?A Simple Definition
• The statistical measure of spread and variability in a distribution of data. (Variability will always exist in a data set because not every individual is going to have the exact same value)
Examples:• Prices of Homes vary from House to House and Year to Year• Grades in a Class vary among Students• Household Income varies from Household to Household
• Standard Deviation represents the typical distance from any point in the data set to the center
Do Not Get Overwhelmed!Formula
S=
Source: Villanova University Six Sigma Lectures
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Standard Deviation - A Simple Example
S=2
2 2
64 8
X = Average = (4+8) / 2 = 6
Steps:1. Find the arithmetic mean (or average) of 4 and 8
(4+8) / 2 = 6
2. Find the deviation of each number from the mean4-6= -2 and 8-6 = 2
3. Square each of the deviations (amplifying larger deviations and making negative values positive)(-2) * (-2) = 42 * 2 = 4
4. Sum the obtained squares (as the 1st step to obtain an average)4+4 = 8
5. Divide the sum by the number of values, which here is 2 (giving an average)8 / 2 = 4
6. Take the non-negative square root of the quotient (converting squared units back to regular units) 4 = 2
Suppose we wished to find the standard deviation of the set of the numbers 4 and 8.
So, the standard deviation of the set = 2.
Mean
Source: Wikipedia
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Standard Deviation – Calls per HourJan Feb Mar Apr
Mary 21 18 23 20John 20 21 19 23Joe 19 22 21 N/ASandy 22 19 23 21Melissa 20 22 24 20Dave N/A N/A 21 22
NameMonth
Dat
aC
alcu
latio
n
X X X-X (X-X)Result Average Deviation Deviation Squared
21 21 0 020 21 1 119 21 2 422 21 -1 120 21 1 118 21 3 921 21 0 022 21 -1 119 21 2 422 21 -1 123 21 -2 419 21 2 421 21 0 023 21 -2 424 21 -3 921 21 0 020 21 1 123 21 -2 421 21 0 020 21 1 122 21 -1 1
441 50
1) Calculate the Average. This is done by dividing the Sample Size by the Number of Results. The calculation is 441/21=21. The average is 21. All information used to calculate the Average is located in the Data Table.
2) Calculate the Deviation for each Result. This done by subtracting each Result from the
Average. Examples of these calculations are 21-20 = 1 (1 is the deviation), 21-21=0 (0 is the deviation) etc. The Deviation for each Result is located in the Deviation Column on the Calculation Table.
3) Square each Deviation. The Squared Deviation for each Result is located in Deviation Squared
Column on the Calculation Table.
4) Total the Squared Deviation. In our example the total is 50. The Total Squared Deviation is located at the bottom of the in Deviation Squared Column on the Calculation Table.
5) Calculate the total sample size (N), and subtract 1. The calculation is 21-1=20. The information used to calculate N is located in the Data Table.
6) Calculate the Standard Deviation. This is done by dividing the Total Square Deviation by the
total Sample Size –1, and then taking the square root. The calculation in our example would be 50/20. The Standard Deviation is 1.58
7) Calculate Sigma Level. How many standard deviations can fit between the average and upper limit, and the average and lower limit? Take the average and subtract the lower limit. Take this value and divide by the standard deviation. The answer is how many sigma can fit between the lower limit and the average. Repeat the same step for the upper limit. In our example, the calculations are as follows:
21 - 11.5 (lower limit) / 1.58 = 6.012 (# of Std. Deviations between average & lower limit) 30.5 (upper limit) - 21/ 1.58 = 6.012 (# of Std. Deviations between average & upper limit)
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Standard Deviation – Calls per HourJan Feb Mar Apr
Mary 21 18 23 20John 20 21 19 23Joe 19 22 21 N/ASandy 22 19 23 21Melissa 20 22 24 20Dave N/A N/A 21 22
NameMonth
Dat
aC
alcu
latio
n
LSL USL
11.5 30.521
X X X-X (X-X)Result Average Deviation Deviation Squared
21 21 0 020 21 1 119 21 2 422 21 -1 120 21 1 118 21 3 921 21 0 022 21 -1 119 21 2 422 21 -1 123 21 -2 419 21 2 421 21 0 023 21 -2 424 21 -3 921 21 0 020 21 1 123 21 -2 421 21 0 020 21 1 122 21 -1 1
441 50
Sum of all Results 441
Number of Results 21
Average 21
Sample Size 20
Upper Limit 30.5
Lower Limit 11.5
Standard Deviation 1.58
Sigma Level 6 Sigma
2120 21 22
19 20 21 22 2319 20 21 22 23
18 19 20 21 22 23 24
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PerformanceLevel SIGMA DPMO
A+
A
B
6
5
4
3.4
233
6,210
C 3 66,811
D 2 308,770
F 1 697,672
Handbook – Appendix XII-3
Recap
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In order to apply Six Sigma, you must understand the impact of Variation…
What is Variation?
Simply stated, Variation is the degree to which something differs from a former state or value, from others of the same type, or froma standard.
Formal Definition:
Variation: Inevitable change in the output or result of a system (process) because all systems vary over time. Two major types of variations are (1) Common, which is inherent in a system, and (2) Special, which is caused by changes in the circumstances or environment.
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Connection:• Excessive tardiness• Personal Calls• Invoice Issues• System Issue• Misapplied Payments• Incorrect Terms
Source: Villanova University Six Sigma Lectures
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Connection:
Man=
Machine=
Material=
Method=
Measurement=
Mother Nature=
Source: Villanova University Six Sigma Lectures
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• Tells you how tightly data is clustered around a center point.
Usage:• Analyzing Average Calls per Hour• Analyzing Average Promises to Pay• Analyzing Synergy
Actions• RMS Salaries
Source: Villanova University Six Sigma Lectures
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Definitions
MeanSum total of all data values divided by
# of data points (the average)
MedianMiddle value when data is ascending
or descending (midpoint)
Mode Value occuring most frequently
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Source: Villanova University Six Sigma Lectures
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Eliminate highly skewed resultsSource: Villanova University Six Sigma Lectures
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Additional CommentsThe Mean:
• Is Sensitive to Extreme Observations/data
• Most Affected by Skewed Data
• Most Frequently Used
The Median:
• Is Most Effective When Data is Skewed
• Is Best if Data is “Messy”
• Not Affected as Much by Outliers
Source: Villanova University Six Sigma Lectures
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• Tells you how data is distributed around a center point
• Describes expected amount of variation (variability) in
normally distributed data.
= Population
= SampleExamples:• On average, what is the variability in calls per hour?• On average, what is the variability in Synergy actions per hour?
Source: Villanova University Six Sigma Lectures
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S =
Note: In most cases data used in process improvement is a sample (subset) taken from a population.
Source: Villanova University Six Sigma Lectures
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Recap
• Tells you how tightly data is clustered around a center point.
• Tells you how the data is distributed
around the center point.• Large Amount of Variation =
Large Spread Why is this important?
Connection:
Example: Calls per Hour• If tightly centered: - Effective training• If skewed: - Time of day? - Skill set of employees• Are the calls inbound or outbound?
Source: Villanova University Six Sigma Lectures
Cen
tral
Te
nden
cy MeanMedianMode
Spread(Standard Deviation)
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Flowchart Techniques - Overview• Prepare a Current State Map to Document the Current Process
• Identify all Decision Points to Ensure Path Leads to Final Outcome
• Strive for the Proper Level of Detail• Too Little-Flowchart Useless• Too Much-Bog Down the Process
• Tip: If mapping out process documentation, you can never have enough detail
• Use Supplemental Charts to Limit Size
• Keep the Flowchart Moving in One Direction-Top to Bottom / Left to Right
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Flowchart Techniques - Create a Process Map
Source: George, M.L., Rowlands, D., Price, M., & Maxey, J. (2005). The Lean Six Sigma Pocket Toolbook, 40 – 41, 43 – 44.
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Flowchart Techniques - Tips
Source: George, M.L., Rowlands, D., Price, M., & Maxey, J. (2005). The Lean Six Sigma Pocket Toolbook, 40 – 41, 43 – 44.
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Another Type of Process Map – Swim-lane Flowchart
Source: George, M.L., Rowlands, D., Price, M., & Maxey, J. (2005). The Lean Six Sigma Pocket Toolbook, 40 – 41, 43 – 44.
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Another Type of Process Map – Swim-lane Flowchart
Source: George, M.L., Rowlands, D., Price, M., & Maxey, J. (2005). The Lean Six Sigma Pocket Toolbook, 40 – 41, 43 – 44.
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Flowchart Techniques - Common Symbols
Manual Input
Decision Point
Document
File
Process
Manual Operation
Connector
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Purpose•Set Performance Objectives•Indentify Sources of Variation
Tools•Control Charts•Hypothesis Testing•Cause and Effect Diagrams•FMEA•Value Stream Mapping
Key Outputs
•Defined List of Potential Sources of Variation•Cost Benefit Analysis
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Define Measure Analyze Improve ControlAnalyze
Review
Source: Villanova University Six Sigma Lectures
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Strategies to Control Variation
Common Cause Special CauseReduce common cause variation by reducing the spread of the process.No one factor is unduly influencing the process. Numerous small factors.
Reduce special cause variation by identifying it and eliminating it – 6M’s – key source of special cause variation.
Common Cause Special CauseReduce common cause variation by reducing the spread of the process.No one factor is unduly influencing the process. Numerous small factors.
Reduce special cause variation by identifying it and eliminating it – 6M’s – key source of special cause variation.
Six Sigma team will analyze 6M’sIdentify the source of variation and eliminate it.
Six Sigma team will analyze 6M’sIdentify the source of variation and eliminate it.
Design of Experiments –Lecture 68-75 – Systematically test influence of various factors
Expected Variation Six Sigma team will analyze 6M’s, identify the source of the variation,
and eliminate it.
Strategies to Control Variation
Source: Villanova University Six Sigma Lectures
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Normal Curve
50%50%
Common Cause Bell CurveNormal Curve Normal DistributionGaussian Curve ChanceRandom variation Expected variation
Most commonly used distribution in Six Sigma
Source: Villanova University Six Sigma Lectures
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VARIATION - 6 M’s• Man• Machine• Material• Method• Measurement• Mother Nature
Bonus points – Money, Mgmt
Drivers of Special Cause Variation
Variation - 6M’s
Source: Villanova University Six Sigma Lectures
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Run Charts
1 91 71 51 31 197531
6
5
4
3
2
1
0
1 91 71 51 31 197531
6
5
4
3
2
1
0
Tools to Control Variation
Basic – preliminary analysis – least sensitive of SPC
Sketch a quick run chart before more complex analysis
Tools to Analyze Variation
Source: Villanova University Six Sigma Lectures
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Run Charts
1. Allows team to study data for trends or patterns2. No control limits are drawn – no points out of control3. Data collected in order of occurrence4. Collected over a specified time period
191715131197531
6
5
4
3
2
1
0
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6
5
4
3
2
1
0
X axis (time or sequence scale)
Y
axis
scale
Usage:
• Analyzing Calls/Actions per Hour against the average over time, in order to identify variation
X Axis (time or sequence scale)
Y A
xis
(res
ults
)
Source: Villanova University Six Sigma Lectures
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Run Chart with statisticallybased limits
Control Chart – Sophisticated
S ample
Sam
ple
Mea
n
191715131197531
602
601
600
599
598
__X= 600.072
UCL= 601.722
LCL= 598.422
1
X bar C ha r t of L eng th
S ample
Sam
ple
Mea
n
191715131197531
602
601
600
599
598
__X= 600.072
UCL= 601.722
LCL= 598.422
1
X bar C ha r t of L eng th
Upper and Lower Control limitsSource: Villanova University Six Sigma Lectures
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A Little History on Control Charts…
Walter Shewhart, 1891-1967
Shewhart Control Chart
Responsible for defining…
assignable cause variation
chance cause variation
Developed the control chart specifically to distinguish between the two.
Source: Villanova University Six Sigma Lectures
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Understanding Variation
Two types of Variation we are looking for in control charts
• Special Cause• Detrimental• Beneficial
• Common Cause
The goal is a stable and predictable process!
Connection:
• Provide an example of a special cause variation with a beneficial outcome.
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Out-of-Control
A process is considered to be “out of control” when any one or more of the following symptoms occur
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Source: Villanova University Six Sigma Lectures
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Control Chart – Objectives
1. Study variation and its source
2. Monitors process behavior
3. Identifies if operating as expected or if corrective action is needed
4. Changes are only made when a) pointson the control chart are outside acceptable ranges or b) freak patterns – otherwise leave alone
Sample
Sam
ple
Mea
n
191715131197531
602
601
600
599
598
__X= 600.072
UCL= 601.722
LCL= 598.4221
Xbar C hart of L ength
Source: Villanova University Six Sigma Lectures
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Analyzing Variation - A Demonstration
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Six Sigma Tools & Techniques
Analyze
Tool Hypothesis TestingProcess Overview Used to evaluate whether making a change to a process input (x) significantly changes the output (y) of a
process. Hypothesis testing assists in using sample data to make decisions about population parameters such as averages, standard deviations and proportions. Testing a hypothesis using statistical methods is equivalent to making an educated guess based on probabilities associated with being correct.
Process Steps 1.Define the problem or issue to be studied.2.Define the objective.3.State the null hypothesis, identified as Ho. A null hypothesis is a statement of no difference between the before and after states. (Similar to a defendant being not guilty in court. The goal of the test is to either reject or not reject Ho.4.State the alternative hypothesis, identified as Ha.5.Determine the practical difference.6.Establish the risk levels and the number of samples needed to obtain the desired risk levels.7.Collect the samples and conduct the test.8.Determine whether to reject or not reject the null hypothesis Ho.
Examples Analyzing the impact of training on associate performance. Null Hypothesis-Ho: Productivity levels did not significantly change after training program. Example of Impact of Teachers on Grade Average: Within a school district, students were randomly assigned to one of two Math teachers - Mrs. Smith and Mrs. Jones. After the assignment, Mrs. Smith had 30 students, and Mrs. Jones had 25 students. At the end of the year, each class took the same standardized test. Mrs. Smith's students had an average test score of 78, with a standard deviation of 10; and Mrs. Jones' students had an average test score of 85, with a standard deviation of 15.Test the hypothesis that Mrs. Smith and Mrs. Jones are equally effective teachers. Use a 0.10 level of significance. (Assume that student performance is approximately normal.)
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Six Sigma Tools & Techniques
Analyze
Tool Hypothesis TestingExamples Bon Air Elementary School has 300 students. The principal of the school thinks that the average IQ of
students at Bon Air is at least 110. To prove her point, she administers an IQ test to 20 randomly selected students. Among the sampled students, the average IQ is 108 with a standard deviation of 10. Based on these results, should the principal accept or reject her original hypothesis? Assume a significance level of 0.01.
An inventor has developed a new, energy-efficient lawn mower engine. He claims that the engine will run continuously for 5 hours (300 minutes) on a single gallon of regular gasoline. Suppose a simple random sample of 50 engines is tested. The engines run for an average of 295 minutes, with a standard deviation of 20 minutes. Test the null hypothesis that the mean run time is 300 minutes against the alternative hypothesis that the mean run time is not 300 minutes. Use a 0.05 level of significance. (Assume that run times for the population of engines are normally distributed.)
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0
-3 -2 -1 1 2 3
Critical region to reject the null
Our t test statistic must be > our t critical value in order to conclude that the difference in the means of the two sets of data is statistically significant.
The light yellow part is not enough evidence due to the small sample size.Cannot say two data set are different unless they pass the critical value.
Critical region to reject the null
t=X-m
s/ √√ nHypothesis Testing
Connection:
• Confidence on Conclusion• Analyze Risk Levels
Source: Villanova University Six Sigma Lectures
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Another Tool for Analyzing ProblemsAlso called The Fishbone Diagram or Ishikawa Diagram
Source: Wikipedia
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Sample Fishbone Diagram(Collections / Customer Service)
Inconsistent Measurements Lack of Training Material Lack of Documented Procedures
High Level of Noise on Floor
Lack of Training
Measurement Materials Methods
Environment Man Power Machines
Phone Outages
Not Including
Breaks & Lunch
OTManuals
Job Aides
Scripts
Warm Transfers
Lack of Contiguous Seats Employee Turnover
Time
System Downtime
Client_
____
___
SAP
RMS ____
____
_
Synergy
Low ProductionNot Making Production
Goals
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Determine the Root Cause (the 5 Whys)5 whys as part of lean manufacturing is a problem solving technique that allows you to get at the root cause of a problem fairly quickly. It was made popular as part of the Toyota Production System (1970’s.) Application of the strategy involves taking any problem and asking “Why - what caused this problem?”
By repeatedly asking the question "Why" (five is a good rule), you can peel away the layers of symptoms that can lead to the root cause of a problem. Very often the first reason for a problem will lead you to another question and then to another. Although this technique is called "5 Whys," you may find that you will need to ask the question fewer or more times than five before you find the issue related to a problem.
Benefits Of The 5 Whys.• It helps to quickly identify the root cause of a problem. • It helps determine the relationship between different root causes of a problem.• It can be learned quickly and doesn't require statistical analysis to be used.• Can be used with the Fishbone Diagram
When Is 5 Whys Most Useful?• When problems involve human factors or interactions.• In all types of business situations whether solving a lean manufacturing or for any other business problem.
Source: http://www.govcomm.harris.com/suppliers/become/Problem_Solving_Tools.pdf
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Example of a Five Whys Analysis… Here is our “Wheel” Life Example:
1. Why is our largest customer unhappy? Because our deliveries of bicycles have been late for the last month
2. Why have our bicycle deliveries been late for the last month? Because production has been behind schedule.
3. Why has production been behind schedule? Because there is a shortage of wheels.
4. Why are we having a shortage of wheels? Because incoming inspection has rejected a large number of wheels for not being round.
5. Why are we rejecting so many parts? Because purchasing switched to a cheaper wheel supplier that has inconsistent quality.
Source: http://www.govcomm.harris.com/suppliers/become/Problem_Solving_Tools.pdf
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Purpose•Prioritize the Vital Few Causes of Variation•Establish Relationships between Output and Input Variables
Tools•FMEA•Design of Experiments•Principles of Lean Manufacturing•Process Capability Analysis
Key Outputs•Proposed Process Settings•Impact of Proposed Solutions•Improved Processes and /or Products
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FMEA – A Simple Explanation
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FMEA is a disciplined approach used to identify possible failures of a product or service and then determine the frequency and impact of the failure.
• FMEA relies on team experience to put safeguards in place.
• FMEA is applicable to any system
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Six Sigma Tools & TechniquesTool FMEA-Failure Mode Effects Analysis
Process Overview
Methodical approach to examine proposed designs for potential points of failure. Uses a Risk Priority Number to Identify the critical focus areas.
o RPN= FOC x SEV x COD o FOC=Frequency of Occurrence, SEV=Severity, COD=Chance of Detection
Identifies the actions which could prevent failures.
Process Steps
1.List the key process steps in the first column.2.List the potential failure mode for each process step. (How could this process step fail?)3.List the effects of this failure mode.4.Rate how severe this effect is (SEV). (1 Not Severe, 10 Most Severe)5.Identify the causes of the failure mode/effect and rank how likely this cause will occur in the occurrence column (FOC).6.Identify the controls in place to detect the issue and rank its effectiveness in the detection column (COD).7.Calculate the RPN by multiplying FOC x SEV x COD. 8.Sort by RPN number to identify the most critical issues.9.Take action and access results.
Example The aerospace industry used the FMEA during the Apollo missions in the 1960 ’s. 1974-US Navy developed MIL-STD-1629 which is a document that outlines the standards and proper use of the FMEA process. A new toaster design team uses FMEA to identify flaws in the design. This highlights ways in which the handle can stick and cause the toast to catch fire. This is prevented by adding a specific thermostatic safety release to the design. A secretary uses FMEA to highlight the possible undesirable effects of a room booking system not working properly, and consequently includes checks to reduce the chance of key effects of overbooking and key staff not being able to find rooms.
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SeveritySeriousness of
impact
OccurrenceLikelihood will
occur
DetectionAbility to detect
10 Hazardous Very high >1/day Cannot detect
9 Illegal Every 3-4 days Spot checks
8 Unfit for use Once/week Samples
7 Dissatisfaction Once a month Inspected
6 Malfunction Once 3 months Mistake proof
5 Complaint Once 6 months SPC
4 Minor loss Once/year SPC+
3 Nuisance Once 1-3 years SPC++
2 Unnoticed Once 3-6 years All inspected
1 No effect Failure unlikely Certain detect
SeveritySeriousness of
impact
OccurrenceLikelihood will
occur
DetectionAbility to detect
10 Hazardous Very high >1/day Cannot detect
9 Illegal Every 3-4 days Spot checks
8 Unfit for use Once/week Samples
7 Dissatisfaction Once a month Inspected
6 Malfunction Once 3 months Mistake proof
5 Complaint Once 6 months SPC
4 Minor loss Once/year SPC+
3 Nuisance Once 1-3 years SPC++
2 Unnoticed Once 3-6 years All inspected
1 No effect Failure unlikely Certain detect
Which of the 3 columns is your priority?
Define Measure Analyze Improve Control
Risk Priority Number (RPN)
Source: Villanova University Six Sigma Lectures
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Self –Service Gas - FMEA
FindGas
PumpCreditCard
Select Gastype
Return Hose
InitializePump
1. Team familiar with the process2. Brainstorm failure modes or points (may be lengthy)
Tip – Look at desired outcome of each stepthen consider 6Ms to identify possible failures
6 Ms - list
Define Measure Analyze Improve Control
FMEA Example – Self Service Gas
Usage:
• Collection Process Potential Failure
Points• File Drop not Received/Processed• Attrition/Turnover• Hiring Issues• Letter Issues• Synergy Issues• Lack of Client System Access• Plan for Failures and take Preventative Measures• Client Start-Up and Giving ETA’s
Source: Villanova University Six Sigma Lectures
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FMEA (Failure Mode & Effects Analysis)
Responsible : Name Prepared by: NameOriginal Date: Date Revised Date: Date
Process Step/ Input
Potential Failure Mode
Potential Failure Effects Se
verit
y (S
EV)
Potential Causes Occ
uran
ce (F
OC)
Current Controls De
tecti
on (C
OD)
RPN Actions Recommended Resp. Actions Taken
Add Milk to Cake Mix
Wrong amount of Milk
Cake too Dry of too Soggy 5
Samll Marks on Measuring Cup 10 None 6 300
Use Large Print on Measuring Cups JW Replacing Measuring Cups
5Faded Marks on Measuring Cup 5
Visual Inspection 3 75
Replace Faded Measuring Cups JW
Replaced Cups and Retrained Inspectors
5 Milk Spilled 4 None 8 160 Train Bakers HH Not Yet Complete
Flour Still in Measuring Cup
Too Little Milk-Cake to Dry or too Soggy 5
Employee Careleness 5
Training (Appears to be Ineffective) 9 225
Create Standard Operating Procedure and Improve Training Program HH
Created Documented SOP's and Scheduled Refresher Training
Lumps in Cake 6Employee Careleness 2
Training (Appears to be Ineffective) 9 108
Create Standard Operating Procedure and Improve Training Program HH
Created Documented SOP's and Scheduled Refresher Training
A Simple Example-Baking a Cake
Notice that ther can be several failure modes per step and several effercts and causes per failure mode.
Risk Priority Number (RPN)= Severity X Occurrence X Detection
Plan for both preventative actions and contingent actions (how to limit damage if it happens)
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Strategies to Control Variation
Common Cause Special CauseReduce common cause variation by reducing the spread of the process.No one factor is unduly influencing the process. Numerous small factors.
Reduce special cause variation by identifying it and eliminating it – 6M’s – key source of special cause variation.
Common Cause Special CauseReduce common cause variation by reducing the spread of the process.No one factor is unduly influencing the process. Numerous small factors.
Reduce special cause variation by identifying it and eliminating it – 6M’s – key source of special cause variation.
Six Sigma team will analyze 6M’sIdentify the source of variation and eliminate it.
Six Sigma team will analyze 6M’sIdentify the source of variation and eliminate it.
Design of Experiments–Lecture 68-75 – Systematically test influence of various factorsSystematically test influence of various factors
Source: Villanova University Six Sigma Lectures
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Six Sigma Tools & TechniquesTool DOE-Design of Experiments
Process Overview
Manipulating factors at different levels to see their effect on a desired result. DOE investigates a list of potential factors whose variation might impact the process output. Enables the study of multiple factors simultaneously. These factors can be derived from a variety of sources including process maps, Fishbone Diagrams, brainstorming techniques and Cause and Effect Matrices. Factors are set at usually two levels (High and Low) and multiple tests are conducted to evaluate the output level based upon the factor changes. DOE is an expensive evaluation process but can be very effective.
Process Steps 1.Define Objective2.Gather Knowledge about Process3.Develop List of Variables4.Assign Levels to Variables5.Conduct Experiments6.Data Analysis and Conclusions
Example Testing the impact of call scripts on call outcome. Does Script A have more of an impact than script B? Health Care Examples: Investigating the causes for emergency room wait times and determining which treatments in the operating room yield the fastest patient recover times. Improve Yield by Investigating Factor A (Temperature) and Factor B (Pressure) Output=Popped Kernels / Factors: Coil Temperature, Pan Type, Cooking Time
oExamples of LevelsCoil Temperature: High / LowPan Type: Copper / Stainless SteelCooking Time: 4 Minutes/ 3 Minutes
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DOE – A Simple Example – Popcorn
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• Taguchi’s methods and DOE are tools that “make something happen,”
unlike many statistical methods that tell us “what happened.” They are PROACTIVE instead of REACTIVE.
• Meeting customer specifications is not enough – the benefit of continually reducing variation
• Xerox is the most advanced user of Taguchi’s methods
“Variation is the Enemy!”
Dr. Genichi Taguchi
1 • Popularized the concept of robust design in Japan – Robustness derives from consistency or lack of variation– Robustness is a function of product design
2 • Popularized quality loss function
3 • Popularized the signal-to-noise ratio – Noise factors are uncontrollable influences
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$ Loss
500 600 700
$ $
Target
Quality Loss
• Quality loss increases as the product or service stray from its target
• $ Loss any time a product or service varies from a defined target
• Loss to Society• Capital ($)• Natural Resources• Human Capital
Taguchi’s Loss Function
Source: Villanova University Six Sigma Lectures
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Define Measure Analyze Improve Control
Lean Overview• Lean is a systematic approach to identifying and eliminating waste through continuous improvement, flowing the product at the pull of the customer in pursuit of perfection.”
Source: National Institute of Standards and Technology NIST
• More value to the customer and the company, with less of everything
that negatively impacts profits
• The Lean Approach:• Identifies and eliminates waste• Reduces cost• Improves quality• Generates new profit• Improves delivery & customer satisfaction• Empowers employees to make improvements
Connection:• FTE Analysis• Increase Production (more with
less)• Quality Reviews (eliminate re-
work)
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Define Measure Analyze Improve Control
Lean Overview – Batch Processing vs. Continuous Flow
Batch ContinuousConsidered to be convenient for the company, but not for the customer
Each process makes or completes only the one piece that the next process
needs
Makes a company less agile/flexible in the marketplace
The batch size is one
More sensitive to variables (time sequencing, process routing, etc.)
Each item is passed immediately from one process step to the next without
any stagnation
Inventory = Possible Waste No inventory = No waste
Also known as “Just in Time”
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Process CapabilityDefinition: The Ability of the Process to Meet Customer Requirements
USLLSLVoice of the Customer
(Specifications)
Leeway Created
by Tighter Controls and Less Variation
Leeway Created
by Tighter Controls and Less Variation
Voice of the Process(Process Variation)
• Is Your Process Capable?• Use Process Capability Studies• The Ideal Situation is to
Have Some Leeway between Performance and Specification Limits (Customer Goals)
Actions
• Center the Process• Modify the Process• Purchase New Equipment• Use Problem Solving to Improve Capability• Revise Specification Limits• Inspect 100%
Connection:
• Tighten Your Processes to Perform Well within Goal Range and Decrease Variation in Performance
• Look at the 6M’s for Drivers of Variation
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Purpose•Ensure Solutions are Sustained•Document Case Studies and Lessons Learned
Tools•Mistake Proofing•5S Organization Approach•Documentation
Key Outputs
•Improved Processes (In Control)•Robust Products•Project Documentation•Opportunity to Transfer Lessons Learned
Define Measure Analyze Improve ControlControl
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• Poka Yoke is a Japanese term that translates into “Avoid Inadvertent Errors,” or “Mistake Proofing.”
• Poka Yoke is a technique that ensures that an operation cannot be performed incorrectly
• Poka Yoke makes mistakes obvious at a glance so that the error does not turn into a defect for the customer
Preventative Measures – Poka Yoke
Usage:• Benefits Wizard Vista Templates• Required Fields• Sign Offs• Audits
Control
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Future State Process Map• Don’t Wait Until Your Current State Process Map is Perfect
• Your Current State Process Map Will Never be Perfect
• You Want Your Future State Process Map to Produce Product or Services Based on the Rate of Sales (Takt Time)
• If You Build Faster, You Build Inventory
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Treatedpatient
Billings toIns Co.
Health Insurance Claim Processing
Receipt Verify Claim
Calculatepayment
Print &Mail check
Doctor
Hospital
Doctor
Hospital
2 min2 days
10 min2 days
1 min2 days
1 min6 days
14 min
6 days
14 min
InsuranceCompany Database
Source: Villanova University Six Sigma Lectures
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• 5 S - Method of creating a clean and orderly workplace that exposes waste and errors
• Elements of a 5S program– Sort – Straighten/Store (Set in order) – Shine– Standardize – Sustain/Self Discipline– Safety (+1)
Organize Your EnvironmentThe 5S Approach
Source: Villanova University Six Sigma Lectures
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• Do Not Rely on Associates to Remember Critical Processes
• Lack of Documentation puts you at Major Risk during Attrition
• Obtain Customer Sign-off where Possible
• Start with High Level Flow-Charts
• Use Screen Prints for Each Step
• Create a Wrap-up Sheet Showing all Steps • Job Aide / Quick Reference
• Schedule Process Review and Refresh Often
• Post on Intranet Site when Possible
Document Your Processes
Define Measure Analyze Improve ControlControl
147
Define Measure Analyze Improve Control
• Step 1 – Create Process Flow
• Step 2 – Document Each Step with Screen Prints
• Step 3 – Create Condensed Step by Step Reference Guide
Documentation
Control
148
• Always include a Table of Contents• Create sections in logical order and group by topic
1. Company Overview
2. Contacts• RMS & Client
3. Treatment Overview• Matrix• Rules
4. Letters• Samples• Process
5. Disputes / Research• Types• Codes• Process / SLA’s
6. Systems• Synergy Reference• Client System Reference
7. Common Forms / Samples
8. Glossary of Common Terms
Goal:
Goal:Your manual should be so good that it would be titled “Collections Process for Dummies.”
Documentation – Manual Tips
Do not skip steps or combine too many on one page.
Define Measure Analyze Improve ControlControl
149
Relevance of Change to Six Sigma?
• Six Sigma philosophy demands we look for opportunities to initiate change
• Responsible for managing change in a systematic way
• Make ‘change routine’
Define Measure Analyze Improve Control
Source: Villanova University Six Sigma Lectures
Measure
150
Change Management
DefineChange
Communicateand train
End ofold way
Duration of disruptionDue to change
Valley ofdespair Clim
b to new
producti
vity
This is normalPrepare for it!
Source: http://www.isixsigma.com/library/content/c020812a.asp
Define Measure Analyze Improve ControlMeasure
151
PlanChange
Communicateand train
End ofold way
Duration of disruptionDue to change
Valley ofdiscomfort
Climb to new productivity
Agile company
Change Management
Define Measure Analyze Improve Control
Source: http://www.isixsigma.com/library/content/c020812a.asp
Measure
152
8 Stage Process of Creating Change
1) Sense of Urgency2) Powerful Coalition3) Vision4) Communication5) Empower Action – training, coaching participation 6) Short term wins - metrics7) Momentum of change8) Anchor in culture - celebrate
Warm up or defrosting activitiesNecessary to real change
Define Measure Analyze Improve Control
Source: Leading Change by John Kotter, 1996
Measure
153
Raise Urgency for Change
1) Expose employees to competitive data
2) Expose employees to unsatisfied customers
3) Limit ‘Happy Talk’ from senior management -honest discussion of problems
4) Set targets so high can’t reach by doing business as usual
5) Hold people accountable for broader measures – no subunit goals
6) Bombard with ideas on opportunities in marketplace
Define Measure Analyze Improve Control
Source: Leading Change by John Kotter, 1996
Measure
154
• In 1962, Thomas Kuhn wrote The Structure of Scientific Revolution, and popularized the concept of "paradigm shift”
• Think of a Paradigm Shift as a change from one way of thinking to another.
• It just does not happen, but rather it is driven by agents of change.
Paradigm Shift
Define Measure Analyze Improve ControlMeasure
155
Negotiation• Change agent has to be skilled in negotiation – strive for
win-win
• Negotiation is a business decision-making process not a competition
(This is NOT desirable)
Do’s and Don’ts
Do not negotiate in a hurry, nor under pressure. Know what you want and what the other party wants. Prepare thoroughly and comprehensively – fact & figures. Listen, empathize and observe. Be optimistic and never give up.
Define Measure Analyze Improve Control
Source: Villanova University Six Sigma Lectures
Measure
156
Negotiation Techniques
“Going to the balcony” – Strategic Break
Mental position from where you can view the action up to a certain point, regain your composure and plan positive further action.
a) Brief pause or silenceb) Rewind – “Let me make sure I understand what you’re saying”c) Remove yourself – get a drink of water
Define Measure Analyze Improve Control
Source: Villanova University Six Sigma Lectures
Measure