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This document provides an overview of 6σ (Six Sigma). It defines competitive quality as product, process, or service uniformity around a target value and notes this requires continuous improvement. Six Sigma aims to reduce variability through statistical tools to prevent defects rather than detect them through inspection. The goal is defect-free products and processes. Case studies show companies implementing Six Sigma have achieved significant cost savings, quality improvements, and productivity gains.

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6σ Overview Greenbelt Training 1
Concept of Competitive Quality Historically, Quality has been defined as “ Meeting the Specifications” “ Fitness for Use” Today the most acceptable definition of Quality is “ Meeting the Customer’s Requirements” 2
Concept of Competitive Quality Will just meeting the requirements ensure future Market share ? NO ! 3
Concept of Competitive Quality The definition of Competitive Quality is : “ Product, Process or Service Uniformity around a Target Value” The most noticeable difference in this operational definition of Quality The most noticeable difference in this operational definition of Quality is that ititrequires is that requires CONTINUOUS IMPROVEMENT CONTINUOUS IMPROVEMENT 4
Uniformity Around A Target Value WHY CHANGE ? The reason is simple, to remain or become competitive and thereby The reason is simple, to remain or become competitive and thereby increase Profitability and Market Share increase Profitability and Market Share 6
The Impact of Added Inspection If the likelihood of detecting the defect is 70% and we have 10 consecutive inspectors with this level of capability, we would expect about 6 escaping 1,000,000 ppm defects out of every 1,000,000 defects produced. 6 ppm 3.4 ppm You can save your self by producing quality You can save your self by producing quality 7 not by Inspection not by Inspection
Sigma - The Standard Deviation 1 Sigma - 68% µ σ= Σ (X – X)2 2 Sigma - 95% 3 Sigma - 99.73 % n 1σ p(d) Upper Specification Limit (USL) Target Specification (T) T USL Lower Specification Limit (LSL) Mean of the distribution (m) Standard Deviation of the distribution (s) 3σ 8
What is Six Sigma A 3σ process because 3 standard deviations fit between target and spec Before Target Customer 3σ Specification 1σ 0.27% Defects up-to 6.6 % 2σ 3σ Customer Target Specification After 1σ 2σ 6σ ! 3σ No Defects! 4σ 5σ 6σ 9 Reducing Variability Is The Key To Six Sigma
Philosophy of Six Sigma Six Sigma focuses on : ♦ Continuous Improvement of Processes ♦Defect Prevention through the use of Statistical tools as opposed to Defect Detection through inspection. 10
The Many Facets of Six Sigma • Focus and commitment to quality • Six Sigma provides classical must be driven by top leadership problem solving tools enhanced • Leadership must be fully with a fundamental knowledge of engaged and accountable for statistics and variation 6σ success Leadership Tools Process Metrics • Focus is on statistical process • Goal is defect free products and capability and process variation processes analysis • Focus is on true capability • Products must be designed to be (rolled throughput yield) rather manufactured within process than end of line yield capability • All decisions must be data • Process capability must be driven quantified 11
How Good is Six Sigma 99% Good (3.8 Sigma) 99.99966% Good (6 Sigma) 20,000 lost articles of mail per hour Seven articles lost per hour Unsafe drinking water for almost One unsafe minute every seven months 15 minutes each day 5,000 incorrect surgical operations per 1.7 incorrect operations per week week Two short or long landings at most major One short or long landing every airports each day five years 200,000 wrong drug prescriptions each 68 wrong prescriptions per year year No electricity for almost seven One hour without electricity every 34 years hours each month 12
What does Six Sigma means to [Company Name]…… Top Line Growth - satisfied customers are repeat customers Bottom Line Growth - it costs less to do it right the first time 13
Industry Overview The Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) model consistently yields rapid, measurable, benefits Avery Dennison Results: Avery Dennison Results: AlliedSignal Results: AlliedSignal Results: • •Implemented 6s in March, 1998. Implemented 6s in March, 1998. • •Implemented 6 in 1994 for Operations. Implemented 6 in 1994 for Operations. • •52 completed projects 52 completed projects • •Initial 44months, 600 projects reduced Initial months, 600 projects reduced Forecast ‘99 savings == $18,500,000 Forecast ‘99 savings $18,500,000 defects by 68%. defects by 68%. Actual savings (through 2Q)=$5,800,000 • •Saved $175M at bottom line in ‘95; Actual savings (through 2Q)=$5,800,000 Saved $175M at bottom line in ‘95; $500M in ‘98 ! ! (not includingoverhead, $500M in ‘98 (not including overhead, • •130 projects planned or in progress 130 projects planned or in progress inventory, indirect charges, or avoidance. inventory, indirect charges, or avoidance. Annualized savings ==$35M Annualized savings $35M • •Over $2B in savings realized since 1992. Over $2B in savings realized since 1992. ‘99 impact ==$12.3M • •Fastest rate for implementing 6 yet! ‘99 impact $12.3M Fastest rate for implementing 6 yet! GE Results: Motorola Results: Motorola Results: GE Results: • •Implemented 6 program in 1987 when Implemented 6 program in 1987 when Implemented  efforts in late 1995. ••Implemented 66 efforts inlate 1995. was performing at  level. itit was performingat aa44 level. • • Targets savings over$10 BB duringnext Targets savings over $10 during next • •By 1992 it averaged a 5.21 level. few years by reducing its current COPQ By 1992 it averaged a 5.21 level. few years by reducing its current COPQ ($7B /yr.) to less than $1B annually by: ($7B /yr.) to less than $1B annually by: • •Sales productivity increased from - - Reducingscrap parts. Reducing scrap parts. Sales productivity increased from $68.9K to $110.1K per employee $68.9K to $110.1K per employee - - Reducingreworked parts. Reducing reworked parts. and savings due to US operations - - Rectifyingtransaction mistakes. Rectifying transaction mistakes. and savings due to US operations 14 improvements were over $2.2 Billion. improvements were over $2.2 Billion.
Cost Opportunity Cost of Failure (% Revenue) 40% If [Company Name] is a 3σ Company, Cost of 35% Failure is Estimated to be at Least 15% of Revenue 30% 25% 20% 15% 10% 5% Defects per Million 3.4 233 6210 66,807 308,537 691,462 Sigma 6 5 4 3 2 1 A $4.5 Million Cost Reduction Opportunity! 15
Six Sigma Saving in GE renc e only For Refe Six Sigma Cost and Benefits 2500 2000 2000 Cost Benefits 1500 1450 1500 Net $ Million 1050 1000 700 550 380 450 500 200 320 170 -30 0 1996 1997 1998 1999 -500 Mostly variable cost productivity and asset utilization Up front investment and staying power Up front investment and staying power Significant impact on the bottom line Significant impact on the bottom line 16
How much Cost Reduction is possible Traditional Quality Costs (Easily Identified) Inspection Warranty Scrap 1.5 % COQ Rework Rejects (tangible) Hidden Quality Costs Lost sales (Difficult to measure) Customer Sat Long cycle times Overtime 15 % COQ Field Modifications (intangible) Late delivery More Setups T&L Excess inventory Expediting costs Lost Opportunity Lengthy Installs Customer Productivity Loss Lost Customer Loyalty Engineering change orders Employee Morale, Productivity, Turnover . .. .. .Six Sigma Reveals hidden facts and capabilities Six Sigma Reveals hidden facts and capabilities 17
Six Sigma as a Goal Distribution Shifted ± 1.5s σ PPM 2 308,537 3 66,807 4 6,210 5 233 6 3.4 Process Defects Per Million Capability Opportunities 18
Harvesting the Fruit of Six Sigma Sweet Fruit Design for Manufacturability 5 5 s Wall Must Address Designs s Wall - - Must Address Designs Bulk of Fruit Process Characterization and Optimization ---------------------------------- 4 4 s Wall Must Improve Internally s Wall - - Must Improve Internally Low Hanging Fruit Seven Basic Tools ---------------------------------- 3 3 s Wall Demand improvement s Wall - - Demand improvement Ground Fruit Logic and Intuition The walls crumble faster when addressing process issues 19
Attacking the Problem Practical Practical Rejects for bad estimation of cost =20% average Rejects for bad estimation of cost =20% average Problem Problem • •Process characterization data set is non-normal. Process characterization data set is non-normal. Statistical Statistical • •After normalization: σST ==5.50 After normalization: σST 5.50 Problem Problem σLT ==2.36 σLT 2.36 • •DOE Results: DOE Results: Statistical Statistical - -Technology Technology - -52% 52% Solution - -Labour rate Labour rate - -24% 24% Solution - -Interaction - -19% Interaction 19% • •Install standard measurement system for each technology Install standard measurement system for each technology Practical Practical • •Reward &&recognition policy to retain experienced labours in order to Reward recognition policy to retain experienced labours in order to Solution Solution increase productivity increase productivity 20
The Focus of Six Sigma Y f(X) • Y • X1 . . . Xn • Dependent • Independent • Output • Input-Process • Effect • Cause • Symptom • Problem • Monitor • Control Would you control shooter or target to get the Gold Medal at Olympics 21
Controlling the Output Y = F (x) OUTPUT SIGNAL IN-PROCESS PARAMETERS RELATIONSHIP or EQUATION THAT EXPLAINS Y IN TERMS OF X Determined by Distance traveled Car speed, traveling time Determined by Money to Spend Income, Commitments, Credit Rating OUTPUT (Y) IS DETERMINED BY THE VALUES OF THE IN-PROCESS PARAMETERS (X’s) 22
Controlling the Output Y = F (x) OUTPUT SIGNAL IN-PROCESS PARAMETERS RELATIONSHIP or EQUATION THAT EXPLAINS Y IN TERMS OF X Determined by Distance traveled Car Speed traveling time Car speed, Amount of wear on brakes Selection of CDs available Amount of gas in the tank Time since last service Understanding theF Traveling time Number of passengers gives insight into the right (x)S Weather 23 Car inside temperature
Controlling the Output Y = F (x) UNDERSTANDING OF F OUTPUT SIGNAL, Y VERIFY UNDERSTANDING SELECT IMPORTANT (x)S OF F QUANTIFY WITH CORRELATION How we’ve been taught to search for F 24
Controlling the Output Y = F (x) POOR OR NO UNDERSTANDING OF F AIN OUTPUT SIGNAL, Y TRY AG BRAINSTORM (x)S NO CORRELATION Thousands of(x)s to choose from....... Without an understanding of F - it’s your opinion vs mine ! 25
Model Y = F (x) Capturing the measurement on a Customer unit basis Understanding our output Verify Correlation to find F as the Customer sees it Learning from variance in performance on Customer Y Unlocking the process keys that control Customer impact 26
What are these opportunities….. Cost of Quality SPAN Customer Satisfaction 27
Cost of Quality Defects/Million Sigma Level Cost of Quality Opportunities 2 308,000 Not Competitive 3 66,800 ($12b) 25 - 40% of Sales 6210 ($7b) 4 15 - 25% of Sales Industry Average 5 233 ($4.5b) 5 - 15% of Sales 3.4($0.3b) 6 <1% of Sales World Class 28
SPAN Order-to-Delivery Time vs Customer Want Date 40 Day Span 5% of orders are >25 days 5% of orders late to request are >15 days early to request -15 days 0 +25 days Early Late Customer Want Date 29 On Time
Difference between Mean & variance Average River Depth - 4ft Focus on Average can turn your business red Focus on Average can turn your business red 30
Outside In Thinking Delivery cycle time (days) Insight Through Variance Baseline Improved? What WE see 12 27 24 7 13 15 7 4 16 18 8 6 20 23 25 6 11.2 15.8 14 2 10 24 What customers feel 11 2 • Using mean-based thinking, we improve 30 6 average performance by 29%, and we 16 5 break out the champagne ... Mean 15.8 11.2 • But our customer only feels the variance Std Dev 7.0 9.0 and cancels the next order! Customers feel variance, not the mean Customers feel variance, not the mean 31
The Eye of the Beholder Customer’s How did [Company Name] influence my View A→ C Performance? Missing data during download Customer Process A B C [Company Name] Process How did I do against my [Company A→ B Obligations? Name]’s View Missing data during logical execution 32
Where in [Company Name]… ... Can Be Applied To Every Business Function Business Operations Development Training HR 6 Sigma IT CRT Methods Finance Quality Admin / Transport Projects 33
Why Now? Customers & Competitors are adopting elements of this business improvement process: – Customers: • HP • Intuit – Competitors: • Wipro Spectramind • EXL • Hughes Driven by Customer Excellence at Lowest Cost Driven by Customer Excellence at Lowest Cost 34
Table of Contents Six Sigma Overview Pre-Tea What is Six Sigma Overview of Scope Linkage to Vision Roles and Responsibilities as Leaders/ Sponsor Pre-Tea Criteria for Project Selection Pre-Tea Criteria for BB/GB Selection Post-Tea Introduction to Process Post- Tea 35
Implementation Strategy Train…. Apply….. Review….. Every Every Participant arrives Participant arrives to training with aa well to training with well defined project with defined project with measurable savings measurable savings opportunities! opportunities! Integrate training with metrics performance to maximize the bottom line impact. Integrate training with metrics performance to maximize the bottom line impact. 36
Six Sigma Program Structure Define Define Measure Measure Analyze Analyze Improve Improve Program Direction, Management Process Control Support, Control Owner and Marketing Leadership Black Belt Change Agents and Process Leaders Green Belt Organizational “Buy-in” Program is structured to build aaself-sustaining critical mass of Program is structured to build self-sustaining critical mass of process improvement competencies. process improvement competencies. 37
Champion / Functional Leader Role 1. Lead the Six Sigma efforts overall in their BU 2. Provide Strategic Direction for Six Sigma Project teams 3. Track the Project’s Progress, Offer rewards as appropriate 4. Help the Black Belt / Green Belt overcome roadblocks, including seeking collaboration 5. Help find resources for the team as Needed, Allocate resources when authorized 6. Keep Black Belt / Green Belt focused on desired results 7. When immovable objects block the road, Redirect Project / Team activities 8. Serve as the Team’s Champion from Top-To-Bottom of Entire Business 9. Ensure that Project Solutions are well implemented, Gains are sustained and on-going responsibility transfers to Process Owner 38
Six Sigma Roles • Champion/Sponsor/Functional Leader – The Champion Or Sponsor Is The Person(s) Who Is Accountable For And Sanctions A Six Sigma Project. The Champion Or Sponsor Is Involved In Project Team Chartering, Reviews Progress, Helps Remove Organizational Barriers To Project Success, And Is Often The Decision-Maker For Approval Of Final Recommendations • Master Black Belt – Full-Time Positions Dedicated To Supporting Six Sigma Efforts. “Expert” Resources To Black Belts And Teams On The Six Sigma Tools And Techniques Coach And Assist Black Belts And Team Members. Train The Black Belts, Champions, And Employees As Needed. • Black Belt (Team Leader) – Full-time position where the Black Belt Is Accountable, Usually To The Champion, For The Project / Team Results. The Black Belt Is Responsible For The Project / Team’s Progress, Provides Leadership In Planning The Project / Team’s Work, Applies Six Sigma Tools And Teaches Team Members How To Apply Them, Often Leads Team Meetings, And Ensures That Decisions Are Made By The Team In A Timely Manner To Meet Its’ Goals • Green Belt (Team Leader) – Part-time position where the Green Belt Is Accountable, Usually To The Champion, For The Project / Team Results. The Green Belt Is Responsible For The Project / Team’s Progress, Provides Leadership In Planning The Project / Team’s Work, Applies Six Sigma Tools And Teaches Team Members How To Apply Them, Often Leads Team Meetings, And Ensures That Decisions Are Made By The Team In A Timely Manner To Meet Its’ Goals • Team Members – Team Members Are The Individuals Who Comprise The Six Sigma Project Team. Team Members Are Individually And Collectively Accountable For Specific Tasks That Will Result In The Team’s Final Recommendation. When Team Members Are Responsible For A Particular Aspect Of A Project, They Often Will Make Their Own Decisions 39
BQC – Roles & Responsibility Six Sigma Steering Committee - BQC – Assures [Company Name]’s Six Sigma implementation plan: • Has appropriate resources allocated • Has appropriate scope and is involving all required elements of the organization • Is consistent with [Company Name]’s culture of Exceeding customer expectation – Develop a communication plan to energize the organization around the Six Sigma implementation. – Remove roadblocks to facilitate implementation. – Review the status of training / project implementation on a regular basis. – Establish [Company Name]’s business metrics and goals, assess progress towards goals, analyze strengths and weaknesses of implementation, and provide strategic direction as necessary. – Verify the financial (as calculated by Finance) impact of projects implemented. – Provide a forum to share best practices within the organization. 40
Table of Contents Six Sigma Overview Pre-Tea What is Six Sigma Overview of Scope Linkage to Vision Roles and Responsibilities as Leaders/ Sponsor Pre-Tea Criteria for Project Selection Pre-Tea Criteria for BB/GB Selection Post-Tea Introduction to Process Post- Tea 41
Customer Focus Start With The Customer 1. 1. Measure the same as the customer does Measure the same as the customer does 2. 2. Determine your capability as the customer sees it Determine your capability as the customer sees it 3. 3. Understand the variance in the output signal Understand the variance in the output signal 4. 4. Find the in-process keys to impact the customer Find the in-process keys to impact the customer 42
Customer Focus What I Want to be What the Exceeding What I What I What I Customer Customer Am (?) Am(?) Am(?) Wants Expectations Competition ? Unhappy Status Quo Delighted Customers Customers Performance Continuum How Important 43 Is This GAP?
Project Selection Objective: 1. What exactly is the problem being addressed in measurable terms? Need: 2. Why is the project worth doing? 3. Is the project tied to a high importance customer CTQ? 4. What are the consequences of not doing this project? 5. How would it fit with business initiatives and targets? Scope: 6. Is the scope reasonable? Can the problem be effectively broken apart into projects with reasonable scope? Expectations: 7. Is there a clear owner in the organization for the problem and for the benefits of improving? 8. What specific goals would project be trying to achieve? What would constitute stretch results? 44
Project Objectives What exactly is the problem being addressed in measurable terms? PROBLEM The problem this project is going to solve is: - Takes too long to submit the quotation to customer - The productivity is very poor in our company - There is too much documentation in our work MEASURABLE In measurable terms that means: - Improve time of submission of quotation from the time enquiry comes from customer - Improve productivity by 15 % - Reduce the paperwork by 20% 45
Project CTQs (Critical to Quality) Who are your customers? What do you provide your customers? What is critical to quality for your customers? What are your internal processes for providing your product or service to customers? What CTQ is this project addressing? 46
Project Need Why is this project worth doing? What activities have higher or equal priority? Customer [Company Name] Why is it important to do now? How does it fit with the business initiatives and targets? Customer [Company Name] What are the consequences of not doing this project? Customer [Company Name] 47
Project Need Write down threat and opportunity for short term and long term for the problem you are addressing in your project Threat Opportunity Short Term 1 3 2 4 Long Term 48
Expectations What specific goals must be met? When must they be met? For each goal, what milestones are critical and must be met? What would constitute stretch results? 49
Project Scoping 50
Project Scoping How far down should I scope my project? Why? High level Why? problem Initial Why? Contributor Secondary Level A Why? Contributor Project Level B Level Level C ??? Level D Project Level When you can no longer answer the “Why?” with confidence, you have arrived at the project level. 51
Project Scoping Why? AHT too Why? high AHT for Pavilion P.L. is too high Why? AHT for Team Level A -11 is too high Why? AHT for New Level B Agents is too high Level C ??? Level D Project Level Our project then becomes in measurable terms: Improving the AHT for New Batches from 30 min. to 20 min. 52
Project Scoping What must this project What (if anything) is out of accomplish? bounds for the team? What resources are available to What (if any) constraints must the team? the team work under? 53
Criteria for BB / GB Selection  Business Acumen  Project and Process Management  Data Affinity  Result Orientation  Relationship Building and Influence  Coaching and Mentoring  Team Leadership  Change Leadership 54
Curriculum for Green Belt  Receive 5 days training  Understand the statistical tools and practice them  Work on the project  Monthly presentation to the Project Sponsor / MBB  Close the project  Clear Green Belt Certification Test 55
Table of Contents Six Sigma Overview Pre-Tea What is Six Sigma Overview of Scope Linkage to Vision Roles and Responsibilities as Leaders/ Sponsor Pre-Tea Criteria for Project Selection Pre-Tea Criteria for BB/GB Selection Post-Tea Introduction to Process Post- Tea 56
DFSS (DMADOV) vs DMAIC DEFINE IDENTIFY NO PROCESS ? YES MEASURE ANALYSE DESIGN NO CAPABLE ? YES OPTIMISE IMPROVE VALIDATE CONTROL 57
DMAIC Process How much and Define the Measure What’s wrong what I can project (Y) & Y & X’s with X’s improve make the team & plan Control Sustain the improvement Improve Define Measure Analyze CHECK & PLAN DO ACT 58
Six Sigma Tools Used………. • Project Scoping • SIPOC • Thought Process Mapping • Quality Metrices • Process Mapping • C&E matrix • FMEA • MSA • Concepts of DOE • DOE Strategies & Analysis • DOE • Control Strategies 59
Measurement Purpose  Document Process Map  Begin To Link CTQs to Input Variables  Establish Measurement Capabilities  Establish Baseline Process Capabilities 60
The Funnel Effect Process Map +30 Inputs All X’s C&E Matrix and FMEA 10-15 1st “Hit List” Multi-Vari Studies 8 - 10 Screened List Experimentation 4-8 Found Critical X’s Control Plans / SPC 3-6 Controlling Critical X’s Optimized Process 61
Input, Output & Process Measures Input Measures Process Measures Output Measures Measures That Are Internal To Your Process. They Include Quality And Delivery Output Measures Are The Key Quality And Measures Important To Your Measures Used To Delivery Requirements Internal Customers As Well Determine How Well Placed On Your Suppliers. As Waste And Cycle Time Customer Needs And Measures. They Are Requirements Are Met. Correlated To The Pertinent Output Measures. 62
Steps to Business Process Mapping Develop A Picture Of The Working Process As A Team Process Suppliers Inputs Outputs Customers Requirement Start 64
Define the Boundaries of Business Process START Boundary Boundary Input What Must My Suppliers Provide My Process To Meet My Needs? Process How Can I Assure That My Process Output Output Meets The Needs Of My Customer? 65
Process Map [Company Name] What You Think It Is... What It Really Is... What It Should Be... What It Could Be... 66
Industry Overview Traditional View Final Test “The Hidden Factory” RTY is the probability that a product will pass through the entire process without rework and without any defects. It is the true yield for a product at the completion of all the individual processes. Six sigma View Value Stream optimization is enabled by elimination of the hidden factory. Value Stream optimization is enabled by elimination of the hidden factory. 67
Rolled Throughput Yield Develop A Better Understanding of Your Operations To Know Where To Begin If this is your process, where do you put your key resources ? A B C D RTY 0.80 0.90 0.90 0.90 0.583 COPQ $2 / Unit $10 / Unit $ 5 / Unit $2 /Unit $19 Capacity 700 un/dy 500 un/dy 400 un/dy 200 un/dy 200 un 68 –Rolled Throughput Yield (RTY) -- A true estimate of process yield
Project Prioritization A B C D RTY 0.80 0.90 0.90 0.90 0.583 COPQ $2 / Unit $10 / Unit $ 5 / Unit $2 /Unit $19 Capacity 700 un/dy 500 un/dy 400 un/dy 200 un/dy 200 un Project # A Project # B Project # C 69
Role of Statistics Can you always measure …100% or less What is Population ……what is sample? Roll of statistics in measurement (descriptive / Inference) 1. We only use experience, not data. 2. We collect data, but just look at the numbers. 3. We group the 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. 70
Basic Statistics  Types of data  Measures of the Center of the data  Mean  Median  Mode  Measures of the Spread of Data  Range  Variance  Standard Deviation  Normal Distribution and Normal Probabilities 71
Measures of Central Tendency Mean: Arithmetic average of a set of values n − Reflects the influence of all values x = ∑ xi n − Strongly Influenced by extreme values i =1 Median: Reflects the 50% rank - the center number after a set of numbers has been sorted from low to high. − Does not include all values in calculation − Is “robust” to extreme scores The mean and median will be affected by the nature of the distribution of numbers Mode - Most Common Observation Why would we use the mean instead of the median in process Improvement? 72
Different Distributions Sketch in the Means and Medians on each Distribution. Sketch in the Means and Medians on each Distribution. Comparison of Distributions. Comparison of Distributions. 300 300 Frequency 200 200 Frequency 100 Tail 100 Tail 0 0 60 70 80 90 100 110 120 130 0 10 20 30 40 50 60 70 80 C2 C3 Negative Skew Positive Skew Comparison of Distributions. 100 Frequency 50 0 20 30 40 50 60 70 80 90 100 110 C1 Symmetric Distribution 73
Population Parameters vs Sample Statistics Examples of Examples of SAMPLE: POPULATION: 500 people Entire India randomly Average Literacy rate selected X = Sample Mean µ = Population Mean ^ σ = Sample Standard Deviation σ = Population Standard Deviation 74
Computational Equations N Population Mean ∑X i µ = i =1 N N Population Standard Deviation ∑ (X i − µ ) 2 σ =S= i=1 N n Sample Mean ^ ∑x i µ =x= i =1 n N ∑ (X 2 Sample Standard i -- X) Deviation ^ σ = s= i =1 75 n -1
Measures of Variability Range: the distance between the extreme values of a data set. (Highest - Lowest) Variance ( σ 2 ): the Average Squared Deviation of each data point from the Mean. Standard Deviation ( σ ): the Square Root of the Variance. The range is more sensitive to outliers than the variance. 76
Calculating Standard Deviation X X-X (X - X) 2 1 2 2 1 3 3 Variance 4 5 N 5 6 4 ∑ (X i − X ) 2 i=1 7 N -1 8 9 N 10 ∑ (X i − X )2 Sum Σ i=1 Mean N -1 σ square Standard Deviation σ 1.581139 77
Types of Data Attribute / Discrete Data (Qualitative)  Categories  Yes, No  Go, No go  Operator 1, Operator 2, Operator 3  Pass / Fail Variable / Continuous Data (Quantitative)  Decimal subdivisions are meaningful  Time, Pressure, Conveyor Speed 78
Variation “While every process displays Variation, some processes display controlled variation, while other processes display uncontrolled variation (Walter Shewhart). Controlled Variation is characterized by a stable and consistent pattern of variation over time. Associated with Common Causes. Uncontrolled Variation is characterized by variation that changes over time. Associated with Special Causes. Process A shows controlled variation. Process B shows uncontrolled variation X-Bar C hart for Proc es s A X-B ar C hart for P roc es s B UCL=77.20 80 75 UCL=77.27 Sample Mean Sample Mean 70 X =70.98 X =70.91 70 LCL=64.70 60 65 LCL=64.62 50 0 5 10 15 20 25 0 5 10 15 20 25 Sample Number Sample Number Special Causes 79
Stratification Customer Type Geography Company Process Etc. ALL DATA n = 2000 0 (-11, 38) 49 Sample Size , Median (Min, Max) SPAN The most powerful potential process labels are those that are known at the beginning of the process. 80
Stratification ALL DATA n = 2000 0 (-11, 38) 49 Dashboard Non-Dashboard n = 899 n = 1101 -2 (-9, 21) 30 1 (-12, 70) 82 North South East West n = 261 n = 297 n = 103 n = 238 -2 (-8, 8) 16 -2 (-10, 24) 34 -1 (-8, 15) 23 -1 (-8, 23) 32 Commercial Government Industrial Even with small sets of n = 119 n = 74 n = 68 Data, the median -2 (-10, 5) 15 -2 (-8, 9) 17 -2 (-7, 40) 47 difference appears. Credit A Credit B Credit C n = 71 n = 41 n=7 -3 (-10, 0) 10 0 (-7, 6) 13 5 (-8, 31) 39 81
Stratification Key Learning Points: • The first thing you must do is Separate the Processes. We call this Stratification. If you don’t Stratify (isolate) the processes, you will have more than one central tendency in the data set and you will never figure out what drives variance. • If you think you have found the right label to stratify the processes, make sure you double check it to see if there is another label that is influencing the way the data appears. In this case, the real process label was Credit Rating, but it appeared in the Dashboard/Non-Dashboard data. You can double check by cross-cutting the data (look at Credit Rating and Dashboard at the same time in a tabular format), or by continuing to segment to see if the central tendency indicator still moves even though we thought it was an isolated process. In this case, if you continue with Dashboard as an isolated process, you will see the median move for various segmentations (especially Credit Rating). • Once you have Stratified (isolated the processes) and you have a segment that reflects several different levels of Variance, you have the first clues to find the critical x’s that drive variance. • When you find a critical x for one of the processes, check to see if it is also the critical x for the other processes. Often the factors that drive variance in one of the processes, also drive it in another. 82
FMEA Model Prevention Detection What made failure mode to take place. Ask 5 Why’s…. Detection Cause Cause What manner my Material or process process was not able to input obey me Failure Mode Failure Mode (Defect) (Defect) Process Step Effect Effect External customer or downstream process step. Because of your process what all I will not be able to do Controls Controls 83
Measurement System Analysis A measurement system will not willingly disclose the type of distortion, inaccuracy or A measurement system will not willingly disclose the type of distortion, inaccuracy or imprecision ititis transmitting to our data. We must actively force ititto reveal its hidden effects. imprecision is transmitting to our data. We must actively force to reveal its hidden effects. CAUTION: Objects in mirror are closer than they appear 84
Measurement System Analysis Parts (Example) • Observations Inputs Outputs Inputs Measurement Outputs • Measurements Process Process • Data Product Variability Measurement Total Variability (Actual variability) Variability (Observed variability) σ2 σMeas.System 2 σObserved 2 Measurement + = System Variability - Investigated Actual(Part) through “R&R (Total) Study” The Measurement System will transmit variation to our data. 85
Establishing the Process Capability LSL USL Short-Term Capability Long-Term Capability Over time, aaprocess tends to shift by approximately 1.5σ . . Over time, process tends to shift by approximately 1.5σ 86
Visualizing the Causes Within Group • Called σ short term (σ st) • Our potential - the best we can be Time 1 • The σ reported by all 6 sigma Time 2 companies Time 3 • The trivial many Time 4 σ st + σ shift = σ total Between Groups • Called σ shift (truly a measurement in sigma's of how far the mean has shifted) • Indicates our process control • The vital few 87
Analyse Purpose To reduce the number of Process Input Variables to a manageable number To determine high risk inputs from Failure Modes and Effects analysis To determine the presence of and eliminate Noise Variables through Multi-vari Studies To plan the first improvement activities 88
Sources of Variation A common method of analysis at this stage is the variables tree. Try thinking about your process in this manner........ Customer Service Example Not resolved the call Agent to Agent Customer to Skill to Skill Call to Call Type of call Customer 89
Tools Used…….. Time Series Plot Scatter Plot 15 15 10 H Vr rs a H Vr 10 rs a 5 5 0 Index 5 10 0 May Jun Jul Date ANOVA (Analysis of Variance) Main Effects Plot - Means for HrsVar 13.0 10.5 H Vr r a 8.0 s 5.5 3.0 Date Customer Salesman Box Plot Pareto Chart Pareto Chart for : Defects 15 1000 100 HrsVar 900 10 800 80 700 Percent 600 ount 60 500 C 400 5 300 40 200 20 100 0 0 0 ev . le t io n t D bb l or ma Defect Water Util Mining Paper We i gh Ai r Bu Co De f or Count 431 293 132 120 C us tom er Percent Cum % 44.2 44.2 30.0 74.2 13.5 87.7 1 12.3 00.0 90
Regression….. Some examples: Y=Gas Mileage Y=Son’s (mpg) 30 Height 80 20 60 10 40 0 .5 1 1.5 2 60 70 80 X=Car Weight (tons) X=Dad’s Height (inches) Y=Grades Y=Selling Price (of 100%) 80 (Thousands) 35 60 25 40 5 0 .5 1 1.5 2 1 6 14 22 30 X=Study Time(Hours/Night) X=Age of Car 91
Regression….. How do you find a line that “fits” the data? How do you find a line that “fits” the data? What we are looking for is a line which will minimize the distances from the plotted points to the line.... Deviations (distances) Deviations (distances) “How much the line missed by” “How much the line missed by” * Regression Line Regression Line * Response * Variable * * (Y) * Scatter Plot Points Scatter Plot Points (actual data values) (actual data values) * * * * Input Variable (X) 92
Regression….. The R2 Statistic is Y defined as the sum of Measured squares of errors divided by sum of the Error square of difference Measured from average: Predicted Y=a+bX n ∑ (y − yi ) 2 i ^ i =1 r = 1− 2 n ∑ (y − y ) 2 i i =1 X 93
Improve What will you do for Improve – Identify solutions. – Develop change management plan. – Conduct cost / benefit analysis. – Create implementation plan. 94
Improve What will you do for Control – Define and implement ongoing measurement / monitoring plan. – Document procedures. 95
Control In the physical world, the law of entropy Target explains the gradual loss of order in a system. The same law applies to business processes. Unless we add “energy” (in the form of documentation and ongoing process controls); processes will tend to degrade overtime, losing the gains achieved by design and improvement activities. The quality plan is the structure through which we add this “energy” to business processes. g 96
Control Three Main Control Mechanism…….. Avoid Potential Problems Control Potential Problems Risk Management SPC Mistake Proofing 97
Project Sign-off Answer the following questions before the project is signed off: • What can go wrong and derail improvements ? • What controls are in place ? • Can you show me your closure plan ? • What happen when the people change ? • Are there any follow up on projects ? • Is all documentation completed ? • Is the savings verified by finance ? • Is the audit plan in place ? 98
Project Sign-off Finalize Financial Results •Calculate tangible benefits •Determine implementation costs •Calculate net financial gain •Calculate the intangible benefits e.g. cost avoidance, customer retention Tangible Benefits - Implementation Costs = Net Financial gains (Over one financial year) Bank 99
Documentation Complete Documentation Package ……..Compile and organize a record of the key aspects of your six sigma project Typical Elements of the Documentation Package •A description of the project •Problem statement & business case •A list of CTQs + Xs •Hypothesis tests •Process capability analysis •Control parameters •Audit Plan/ owner •Financial results •Operational metrics •Lessons learned and best practices Project to be signed off by GB/BB, MBB, Financial controller, Process Owner, Champion. 100
Reward & Recognition ?... 101

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Green belt training

  • 1.
    6σ Overview Greenbelt Training 1
  • 2.
    Concept of CompetitiveQuality Historically, Quality has been defined as “ Meeting the Specifications” “ Fitness for Use” Today the most acceptable definition of Quality is “ Meeting the Customer’s Requirements” 2
  • 3.
    Concept of CompetitiveQuality Will just meeting the requirements ensure future Market share ? NO ! 3
  • 4.
    Concept of CompetitiveQuality The definition of Competitive Quality is : “ Product, Process or Service Uniformity around a Target Value” The most noticeable difference in this operational definition of Quality The most noticeable difference in this operational definition of Quality is that ititrequires is that requires CONTINUOUS IMPROVEMENT CONTINUOUS IMPROVEMENT 4
  • 5.
    Uniformity Around ATarget Value WHY CHANGE ? The reason is simple, to remain or become competitive and thereby The reason is simple, to remain or become competitive and thereby increase Profitability and Market Share increase Profitability and Market Share 6
  • 6.
    The Impact ofAdded Inspection If the likelihood of detecting the defect is 70% and we have 10 consecutive inspectors with this level of capability, we would expect about 6 escaping 1,000,000 ppm defects out of every 1,000,000 defects produced. 6 ppm 3.4 ppm You can save your self by producing quality You can save your self by producing quality 7 not by Inspection not by Inspection
  • 7.
    Sigma - TheStandard Deviation 1 Sigma - 68% µ σ= Σ (X – X)2 2 Sigma - 95% 3 Sigma - 99.73 % n 1σ p(d) Upper Specification Limit (USL) Target Specification (T) T USL Lower Specification Limit (LSL) Mean of the distribution (m) Standard Deviation of the distribution (s) 3σ 8
  • 8.
    What is SixSigma A 3σ process because 3 standard deviations fit between target and spec Before Target Customer 3σ Specification 1σ 0.27% Defects up-to 6.6 % 2σ 3σ Customer Target Specification After 1σ 2σ 6σ ! 3σ No Defects! 4σ 5σ 6σ 9 Reducing Variability Is The Key To Six Sigma
  • 9.
    Philosophy of SixSigma Six Sigma focuses on : ♦ Continuous Improvement of Processes ♦Defect Prevention through the use of Statistical tools as opposed to Defect Detection through inspection. 10
  • 10.
    The Many Facetsof Six Sigma • Focus and commitment to quality • Six Sigma provides classical must be driven by top leadership problem solving tools enhanced • Leadership must be fully with a fundamental knowledge of engaged and accountable for statistics and variation 6σ success Leadership Tools Process Metrics • Focus is on statistical process • Goal is defect free products and capability and process variation processes analysis • Focus is on true capability • Products must be designed to be (rolled throughput yield) rather manufactured within process than end of line yield capability • All decisions must be data • Process capability must be driven quantified 11
  • 11.
    How Good isSix Sigma 99% Good (3.8 Sigma) 99.99966% Good (6 Sigma) 20,000 lost articles of mail per hour Seven articles lost per hour Unsafe drinking water for almost One unsafe minute every seven months 15 minutes each day 5,000 incorrect surgical operations per 1.7 incorrect operations per week week Two short or long landings at most major One short or long landing every airports each day five years 200,000 wrong drug prescriptions each 68 wrong prescriptions per year year No electricity for almost seven One hour without electricity every 34 years hours each month 12
  • 12.
    What does SixSigma means to [Company Name]…… Top Line Growth - satisfied customers are repeat customers Bottom Line Growth - it costs less to do it right the first time 13
  • 13.
    Industry Overview The Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) model consistently yields rapid, measurable, benefits Avery Dennison Results: Avery Dennison Results: AlliedSignal Results: AlliedSignal Results: • •Implemented 6s in March, 1998. Implemented 6s in March, 1998. • •Implemented 6 in 1994 for Operations. Implemented 6 in 1994 for Operations. • •52 completed projects 52 completed projects • •Initial 44months, 600 projects reduced Initial months, 600 projects reduced Forecast ‘99 savings == $18,500,000 Forecast ‘99 savings $18,500,000 defects by 68%. defects by 68%. Actual savings (through 2Q)=$5,800,000 • •Saved $175M at bottom line in ‘95; Actual savings (through 2Q)=$5,800,000 Saved $175M at bottom line in ‘95; $500M in ‘98 ! ! (not includingoverhead, $500M in ‘98 (not including overhead, • •130 projects planned or in progress 130 projects planned or in progress inventory, indirect charges, or avoidance. inventory, indirect charges, or avoidance. Annualized savings ==$35M Annualized savings $35M • •Over $2B in savings realized since 1992. Over $2B in savings realized since 1992. ‘99 impact ==$12.3M • •Fastest rate for implementing 6 yet! ‘99 impact $12.3M Fastest rate for implementing 6 yet! GE Results: Motorola Results: Motorola Results: GE Results: • •Implemented 6 program in 1987 when Implemented 6 program in 1987 when Implemented  efforts in late 1995. ••Implemented 66 efforts inlate 1995. was performing at  level. itit was performingat aa44 level. • • Targets savings over$10 BB duringnext Targets savings over $10 during next • •By 1992 it averaged a 5.21 level. few years by reducing its current COPQ By 1992 it averaged a 5.21 level. few years by reducing its current COPQ ($7B /yr.) to less than $1B annually by: ($7B /yr.) to less than $1B annually by: • •Sales productivity increased from - - Reducingscrap parts. Reducing scrap parts. Sales productivity increased from $68.9K to $110.1K per employee $68.9K to $110.1K per employee - - Reducingreworked parts. Reducing reworked parts. and savings due to US operations - - Rectifyingtransaction mistakes. Rectifying transaction mistakes. and savings due to US operations 14 improvements were over $2.2 Billion. improvements were over $2.2 Billion.
  • 14.
    Cost Opportunity Cost of Failure (% Revenue) 40% If [Company Name] is a 3σ Company, Cost of 35% Failure is Estimated to be at Least 15% of Revenue 30% 25% 20% 15% 10% 5% Defects per Million 3.4 233 6210 66,807 308,537 691,462 Sigma 6 5 4 3 2 1 A $4.5 Million Cost Reduction Opportunity! 15
  • 15.
    Six Sigma Savingin GE renc e only For Refe Six Sigma Cost and Benefits 2500 2000 2000 Cost Benefits 1500 1450 1500 Net $ Million 1050 1000 700 550 380 450 500 200 320 170 -30 0 1996 1997 1998 1999 -500 Mostly variable cost productivity and asset utilization Up front investment and staying power Up front investment and staying power Significant impact on the bottom line Significant impact on the bottom line 16
  • 16.
    How much CostReduction is possible Traditional Quality Costs (Easily Identified) Inspection Warranty Scrap 1.5 % COQ Rework Rejects (tangible) Hidden Quality Costs Lost sales (Difficult to measure) Customer Sat Long cycle times Overtime 15 % COQ Field Modifications (intangible) Late delivery More Setups T&L Excess inventory Expediting costs Lost Opportunity Lengthy Installs Customer Productivity Loss Lost Customer Loyalty Engineering change orders Employee Morale, Productivity, Turnover . .. .. .Six Sigma Reveals hidden facts and capabilities Six Sigma Reveals hidden facts and capabilities 17
  • 17.
    Six Sigma asa Goal Distribution Shifted ± 1.5s σ PPM 2 308,537 3 66,807 4 6,210 5 233 6 3.4 Process Defects Per Million Capability Opportunities 18
  • 18.
    Harvesting the Fruitof Six Sigma Sweet Fruit Design for Manufacturability 5 5 s Wall Must Address Designs s Wall - - Must Address Designs Bulk of Fruit Process Characterization and Optimization ---------------------------------- 4 4 s Wall Must Improve Internally s Wall - - Must Improve Internally Low Hanging Fruit Seven Basic Tools ---------------------------------- 3 3 s Wall Demand improvement s Wall - - Demand improvement Ground Fruit Logic and Intuition The walls crumble faster when addressing process issues 19
  • 19.
    Attacking the Problem Practical Practical Rejects for bad estimation of cost =20% average Rejects for bad estimation of cost =20% average Problem Problem • •Process characterization data set is non-normal. Process characterization data set is non-normal. Statistical Statistical • •After normalization: σST ==5.50 After normalization: σST 5.50 Problem Problem σLT ==2.36 σLT 2.36 • •DOE Results: DOE Results: Statistical Statistical - -Technology Technology - -52% 52% Solution - -Labour rate Labour rate - -24% 24% Solution - -Interaction - -19% Interaction 19% • •Install standard measurement system for each technology Install standard measurement system for each technology Practical Practical • •Reward &&recognition policy to retain experienced labours in order to Reward recognition policy to retain experienced labours in order to Solution Solution increase productivity increase productivity 20
  • 20.
    The Focus ofSix Sigma Y f(X) • Y • X1 . . . Xn • Dependent • Independent • Output • Input-Process • Effect • Cause • Symptom • Problem • Monitor • Control Would you control shooter or target to get the Gold Medal at Olympics 21
  • 21.
    Controlling the Output Y = F (x) OUTPUT SIGNAL IN-PROCESS PARAMETERS RELATIONSHIP or EQUATION THAT EXPLAINS Y IN TERMS OF X Determined by Distance traveled Car speed, traveling time Determined by Money to Spend Income, Commitments, Credit Rating OUTPUT (Y) IS DETERMINED BY THE VALUES OF THE IN-PROCESS PARAMETERS (X’s) 22
  • 22.
    Controlling the Output Y = F (x) OUTPUT SIGNAL IN-PROCESS PARAMETERS RELATIONSHIP or EQUATION THAT EXPLAINS Y IN TERMS OF X Determined by Distance traveled Car Speed traveling time Car speed, Amount of wear on brakes Selection of CDs available Amount of gas in the tank Time since last service Understanding theF Traveling time Number of passengers gives insight into the right (x)S Weather 23 Car inside temperature
  • 23.
    Controlling the Output Y = F (x) UNDERSTANDING OF F OUTPUT SIGNAL, Y VERIFY UNDERSTANDING SELECT IMPORTANT (x)S OF F QUANTIFY WITH CORRELATION How we’ve been taught to search for F 24
  • 24.
    Controlling the Output Y = F (x) POOR OR NO UNDERSTANDING OF F AIN OUTPUT SIGNAL, Y TRY AG BRAINSTORM (x)S NO CORRELATION Thousands of(x)s to choose from....... Without an understanding of F - it’s your opinion vs mine ! 25
  • 25.
    Model Y = F (x) Capturing the measurement on a Customer unit basis Understanding our output Verify Correlation to find F as the Customer sees it Learning from variance in performance on Customer Y Unlocking the process keys that control Customer impact 26
  • 26.
    What are theseopportunities….. Cost of Quality SPAN Customer Satisfaction 27
  • 27.
    Cost of Quality Defects/Million Sigma Level Cost of Quality Opportunities 2 308,000 Not Competitive 3 66,800 ($12b) 25 - 40% of Sales 6210 ($7b) 4 15 - 25% of Sales Industry Average 5 233 ($4.5b) 5 - 15% of Sales 3.4($0.3b) 6 <1% of Sales World Class 28
  • 28.
    SPAN Order-to-Delivery Time vs Customer Want Date 40 Day Span 5% of orders are >25 days 5% of orders late to request are >15 days early to request -15 days 0 +25 days Early Late Customer Want Date 29 On Time
  • 29.
    Difference between Mean& variance Average River Depth - 4ft Focus on Average can turn your business red Focus on Average can turn your business red 30
  • 30.
    Outside In Thinking Delivery cycle time (days) Insight Through Variance Baseline Improved? What WE see 12 27 24 7 13 15 7 4 16 18 8 6 20 23 25 6 11.2 15.8 14 2 10 24 What customers feel 11 2 • Using mean-based thinking, we improve 30 6 average performance by 29%, and we 16 5 break out the champagne ... Mean 15.8 11.2 • But our customer only feels the variance Std Dev 7.0 9.0 and cancels the next order! Customers feel variance, not the mean Customers feel variance, not the mean 31
  • 31.
    The Eye ofthe Beholder Customer’s How did [Company Name] influence my View A→ C Performance? Missing data during download Customer Process A B C [Company Name] Process How did I do against my [Company A→ B Obligations? Name]’s View Missing data during logical execution 32
  • 32.
    Where in [CompanyName]… ... Can Be Applied To Every Business Function Business Operations Development Training HR 6 Sigma IT CRT Methods Finance Quality Admin / Transport Projects 33
  • 33.
    Why Now? Customers & Competitors are adopting elements of this business improvement process: – Customers: • HP • Intuit – Competitors: • Wipro Spectramind • EXL • Hughes Driven by Customer Excellence at Lowest Cost Driven by Customer Excellence at Lowest Cost 34
  • 34.
    Table of Contents Six Sigma Overview Pre-Tea What is Six Sigma Overview of Scope Linkage to Vision Roles and Responsibilities as Leaders/ Sponsor Pre-Tea Criteria for Project Selection Pre-Tea Criteria for BB/GB Selection Post-Tea Introduction to Process Post- Tea 35
  • 35.
    Implementation Strategy Train…. Apply….. Review….. Every Every Participant arrives Participant arrives to training with aa well to training with well defined project with defined project with measurable savings measurable savings opportunities! opportunities! Integrate training with metrics performance to maximize the bottom line impact. Integrate training with metrics performance to maximize the bottom line impact. 36
  • 36.
    Six Sigma ProgramStructure Define Define Measure Measure Analyze Analyze Improve Improve Program Direction, Management Process Control Support, Control Owner and Marketing Leadership Black Belt Change Agents and Process Leaders Green Belt Organizational “Buy-in” Program is structured to build aaself-sustaining critical mass of Program is structured to build self-sustaining critical mass of process improvement competencies. process improvement competencies. 37
  • 37.
    Champion / FunctionalLeader Role 1. Lead the Six Sigma efforts overall in their BU 2. Provide Strategic Direction for Six Sigma Project teams 3. Track the Project’s Progress, Offer rewards as appropriate 4. Help the Black Belt / Green Belt overcome roadblocks, including seeking collaboration 5. Help find resources for the team as Needed, Allocate resources when authorized 6. Keep Black Belt / Green Belt focused on desired results 7. When immovable objects block the road, Redirect Project / Team activities 8. Serve as the Team’s Champion from Top-To-Bottom of Entire Business 9. Ensure that Project Solutions are well implemented, Gains are sustained and on-going responsibility transfers to Process Owner 38
  • 38.
    Six Sigma Roles • Champion/Sponsor/Functional Leader – The Champion Or Sponsor Is The Person(s) Who Is Accountable For And Sanctions A Six Sigma Project. The Champion Or Sponsor Is Involved In Project Team Chartering, Reviews Progress, Helps Remove Organizational Barriers To Project Success, And Is Often The Decision-Maker For Approval Of Final Recommendations • Master Black Belt – Full-Time Positions Dedicated To Supporting Six Sigma Efforts. “Expert” Resources To Black Belts And Teams On The Six Sigma Tools And Techniques Coach And Assist Black Belts And Team Members. Train The Black Belts, Champions, And Employees As Needed. • Black Belt (Team Leader) – Full-time position where the Black Belt Is Accountable, Usually To The Champion, For The Project / Team Results. The Black Belt Is Responsible For The Project / Team’s Progress, Provides Leadership In Planning The Project / Team’s Work, Applies Six Sigma Tools And Teaches Team Members How To Apply Them, Often Leads Team Meetings, And Ensures That Decisions Are Made By The Team In A Timely Manner To Meet Its’ Goals • Green Belt (Team Leader) – Part-time position where the Green Belt Is Accountable, Usually To The Champion, For The Project / Team Results. The Green Belt Is Responsible For The Project / Team’s Progress, Provides Leadership In Planning The Project / Team’s Work, Applies Six Sigma Tools And Teaches Team Members How To Apply Them, Often Leads Team Meetings, And Ensures That Decisions Are Made By The Team In A Timely Manner To Meet Its’ Goals • Team Members – Team Members Are The Individuals Who Comprise The Six Sigma Project Team. Team Members Are Individually And Collectively Accountable For Specific Tasks That Will Result In The Team’s Final Recommendation. When Team Members Are Responsible For A Particular Aspect Of A Project, They Often Will Make Their Own Decisions 39
  • 39.
    BQC – Roles& Responsibility Six Sigma Steering Committee - BQC – Assures [Company Name]’s Six Sigma implementation plan: • Has appropriate resources allocated • Has appropriate scope and is involving all required elements of the organization • Is consistent with [Company Name]’s culture of Exceeding customer expectation – Develop a communication plan to energize the organization around the Six Sigma implementation. – Remove roadblocks to facilitate implementation. – Review the status of training / project implementation on a regular basis. – Establish [Company Name]’s business metrics and goals, assess progress towards goals, analyze strengths and weaknesses of implementation, and provide strategic direction as necessary. – Verify the financial (as calculated by Finance) impact of projects implemented. – Provide a forum to share best practices within the organization. 40
  • 40.
    Table of Contents Six Sigma Overview Pre-Tea What is Six Sigma Overview of Scope Linkage to Vision Roles and Responsibilities as Leaders/ Sponsor Pre-Tea Criteria for Project Selection Pre-Tea Criteria for BB/GB Selection Post-Tea Introduction to Process Post- Tea 41
  • 41.
    Customer Focus Start With The Customer 1. 1. Measure the same as the customer does Measure the same as the customer does 2. 2. Determine your capability as the customer sees it Determine your capability as the customer sees it 3. 3. Understand the variance in the output signal Understand the variance in the output signal 4. 4. Find the in-process keys to impact the customer Find the in-process keys to impact the customer 42
  • 42.
    Customer Focus What I Want to be What the Exceeding What I What I What I Customer Customer Am (?) Am(?) Am(?) Wants Expectations Competition ? Unhappy Status Quo Delighted Customers Customers Performance Continuum How Important 43 Is This GAP?
  • 43.
    Project Selection Objective: 1. What exactly is the problem being addressed in measurable terms? Need: 2. Why is the project worth doing? 3. Is the project tied to a high importance customer CTQ? 4. What are the consequences of not doing this project? 5. How would it fit with business initiatives and targets? Scope: 6. Is the scope reasonable? Can the problem be effectively broken apart into projects with reasonable scope? Expectations: 7. Is there a clear owner in the organization for the problem and for the benefits of improving? 8. What specific goals would project be trying to achieve? What would constitute stretch results? 44
  • 44.
    Project Objectives What exactly is the problem being addressed in measurable terms? PROBLEM The problem this project is going to solve is: - Takes too long to submit the quotation to customer - The productivity is very poor in our company - There is too much documentation in our work MEASURABLE In measurable terms that means: - Improve time of submission of quotation from the time enquiry comes from customer - Improve productivity by 15 % - Reduce the paperwork by 20% 45
  • 45.
    Project CTQs (Criticalto Quality) Who are your customers? What do you provide your customers? What is critical to quality for your customers? What are your internal processes for providing your product or service to customers? What CTQ is this project addressing? 46
  • 46.
    Project Need Why is this project worth doing? What activities have higher or equal priority? Customer [Company Name] Why is it important to do now? How does it fit with the business initiatives and targets? Customer [Company Name] What are the consequences of not doing this project? Customer [Company Name] 47
  • 47.
    Project Need Write down threat and opportunity for short term and long term for the problem you are addressing in your project Threat Opportunity Short Term 1 3 2 4 Long Term 48
  • 48.
    Expectations What specific goals must be met? When must they be met? For each goal, what milestones are critical and must be met? What would constitute stretch results? 49
  • 49.
  • 50.
    Project Scoping How far down should I scope my project? Why? High level Why? problem Initial Why? Contributor Secondary Level A Why? Contributor Project Level B Level Level C ??? Level D Project Level When you can no longer answer the “Why?” with confidence, you have arrived at the project level. 51
  • 51.
    Project Scoping Why? AHT too Why? high AHT for Pavilion P.L. is too high Why? AHT for Team Level A -11 is too high Why? AHT for New Level B Agents is too high Level C ??? Level D Project Level Our project then becomes in measurable terms: Improving the AHT for New Batches from 30 min. to 20 min. 52
  • 52.
    Project Scoping What must this project What (if anything) is out of accomplish? bounds for the team? What resources are available to What (if any) constraints must the team? the team work under? 53
  • 53.
    Criteria for BB/ GB Selection  Business Acumen  Project and Process Management  Data Affinity  Result Orientation  Relationship Building and Influence  Coaching and Mentoring  Team Leadership  Change Leadership 54
  • 54.
    Curriculum for GreenBelt  Receive 5 days training  Understand the statistical tools and practice them  Work on the project  Monthly presentation to the Project Sponsor / MBB  Close the project  Clear Green Belt Certification Test 55
  • 55.
    Table of Contents Six Sigma Overview Pre-Tea What is Six Sigma Overview of Scope Linkage to Vision Roles and Responsibilities as Leaders/ Sponsor Pre-Tea Criteria for Project Selection Pre-Tea Criteria for BB/GB Selection Post-Tea Introduction to Process Post- Tea 56
  • 56.
    DFSS (DMADOV) vsDMAIC DEFINE IDENTIFY NO PROCESS ? YES MEASURE ANALYSE DESIGN NO CAPABLE ? YES OPTIMISE IMPROVE VALIDATE CONTROL 57
  • 57.
    DMAIC Process How much and Define the Measure What’s wrong what I can project (Y) & Y & X’s with X’s improve make the team & plan Control Sustain the improvement Improve Define Measure Analyze CHECK & PLAN DO ACT 58
  • 58.
    Six Sigma ToolsUsed………. • Project Scoping • SIPOC • Thought Process Mapping • Quality Metrices • Process Mapping • C&E matrix • FMEA • MSA • Concepts of DOE • DOE Strategies & Analysis • DOE • Control Strategies 59
  • 59.
    Measurement Purpose  Document Process Map  Begin To Link CTQs to Input Variables  Establish Measurement Capabilities  Establish Baseline Process Capabilities 60
  • 60.
    The Funnel Effect Process Map +30 Inputs All X’s C&E Matrix and FMEA 10-15 1st “Hit List” Multi-Vari Studies 8 - 10 Screened List Experimentation 4-8 Found Critical X’s Control Plans / SPC 3-6 Controlling Critical X’s Optimized Process 61
  • 61.
    Input, Output &Process Measures Input Measures Process Measures Output Measures Measures That Are Internal To Your Process. They Include Quality And Delivery Output Measures Are The Key Quality And Measures Important To Your Measures Used To Delivery Requirements Internal Customers As Well Determine How Well Placed On Your Suppliers. As Waste And Cycle Time Customer Needs And Measures. They Are Requirements Are Met. Correlated To The Pertinent Output Measures. 62
  • 62.
    Steps to BusinessProcess Mapping Develop A Picture Of The Working Process As A Team Process Suppliers Inputs Outputs Customers Requirement Start 64
  • 63.
    Define the Boundariesof Business Process START Boundary Boundary Input What Must My Suppliers Provide My Process To Meet My Needs? Process How Can I Assure That My Process Output Output Meets The Needs Of My Customer? 65
  • 64.
    Process Map [Company Name] What You Think It Is... What It Really Is... What It Should Be... What It Could Be... 66
  • 65.
    Industry Overview Traditional View Final Test “The Hidden Factory” RTY is the probability that a product will pass through the entire process without rework and without any defects. It is the true yield for a product at the completion of all the individual processes. Six sigma View Value Stream optimization is enabled by elimination of the hidden factory. Value Stream optimization is enabled by elimination of the hidden factory. 67
  • 66.
    Rolled Throughput Yield Develop A Better Understanding of Your Operations To Know Where To Begin If this is your process, where do you put your key resources ? A B C D RTY 0.80 0.90 0.90 0.90 0.583 COPQ $2 / Unit $10 / Unit $ 5 / Unit $2 /Unit $19 Capacity 700 un/dy 500 un/dy 400 un/dy 200 un/dy 200 un 68 –Rolled Throughput Yield (RTY) -- A true estimate of process yield
  • 67.
    Project Prioritization A B C D RTY 0.80 0.90 0.90 0.90 0.583 COPQ $2 / Unit $10 / Unit $ 5 / Unit $2 /Unit $19 Capacity 700 un/dy 500 un/dy 400 un/dy 200 un/dy 200 un Project # A Project # B Project # C 69
  • 68.
    Role of Statistics Can you always measure …100% or less What is Population ……what is sample? Roll of statistics in measurement (descriptive / Inference) 1. We only use experience, not data. 2. We collect data, but just look at the numbers. 3. We group the 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. 70
  • 69.
    Basic Statistics  Types of data  Measures of the Center of the data  Mean  Median  Mode  Measures of the Spread of Data  Range  Variance  Standard Deviation  Normal Distribution and Normal Probabilities 71
  • 70.
    Measures of CentralTendency Mean: Arithmetic average of a set of values n − Reflects the influence of all values x = ∑ xi n − Strongly Influenced by extreme values i =1 Median: Reflects the 50% rank - the center number after a set of numbers has been sorted from low to high. − Does not include all values in calculation − Is “robust” to extreme scores The mean and median will be affected by the nature of the distribution of numbers Mode - Most Common Observation Why would we use the mean instead of the median in process Improvement? 72
  • 71.
    Different Distributions Sketch in the Means and Medians on each Distribution. Sketch in the Means and Medians on each Distribution. Comparison of Distributions. Comparison of Distributions. 300 300 Frequency 200 200 Frequency 100 Tail 100 Tail 0 0 60 70 80 90 100 110 120 130 0 10 20 30 40 50 60 70 80 C2 C3 Negative Skew Positive Skew Comparison of Distributions. 100 Frequency 50 0 20 30 40 50 60 70 80 90 100 110 C1 Symmetric Distribution 73
  • 72.
    Population Parameters vsSample Statistics Examples of Examples of SAMPLE: POPULATION: 500 people Entire India randomly Average Literacy rate selected X = Sample Mean µ = Population Mean ^ σ = Sample Standard Deviation σ = Population Standard Deviation 74
  • 73.
    Computational Equations N Population Mean ∑X i µ = i =1 N N Population Standard Deviation ∑ (X i − µ ) 2 σ =S= i=1 N n Sample Mean ^ ∑x i µ =x= i =1 n N ∑ (X 2 Sample Standard i -- X) Deviation ^ σ = s= i =1 75 n -1
  • 74.
    Measures of Variability Range: the distance between the extreme values of a data set. (Highest - Lowest) Variance ( σ 2 ): the Average Squared Deviation of each data point from the Mean. Standard Deviation ( σ ): the Square Root of the Variance. The range is more sensitive to outliers than the variance. 76
  • 75.
    Calculating Standard Deviation X X-X (X - X) 2 1 2 2 1 3 3 Variance 4 5 N 5 6 4 ∑ (X i − X ) 2 i=1 7 N -1 8 9 N 10 ∑ (X i − X )2 Sum Σ i=1 Mean N -1 σ square Standard Deviation σ 1.581139 77
  • 76.
    Types of Data Attribute / Discrete Data (Qualitative)  Categories  Yes, No  Go, No go  Operator 1, Operator 2, Operator 3  Pass / Fail Variable / Continuous Data (Quantitative)  Decimal subdivisions are meaningful  Time, Pressure, Conveyor Speed 78
  • 77.
    Variation “While every process displays Variation, some processes display controlled variation, while other processes display uncontrolled variation (Walter Shewhart). Controlled Variation is characterized by a stable and consistent pattern of variation over time. Associated with Common Causes. Uncontrolled Variation is characterized by variation that changes over time. Associated with Special Causes. Process A shows controlled variation. Process B shows uncontrolled variation X-Bar C hart for Proc es s A X-B ar C hart for P roc es s B UCL=77.20 80 75 UCL=77.27 Sample Mean Sample Mean 70 X =70.98 X =70.91 70 LCL=64.70 60 65 LCL=64.62 50 0 5 10 15 20 25 0 5 10 15 20 25 Sample Number Sample Number Special Causes 79
  • 78.
    Stratification Customer Type Geography Company Process Etc. ALL DATA n = 2000 0 (-11, 38) 49 Sample Size , Median (Min, Max) SPAN The most powerful potential process labels are those that are known at the beginning of the process. 80
  • 79.
    Stratification ALL DATA n = 2000 0 (-11, 38) 49 Dashboard Non-Dashboard n = 899 n = 1101 -2 (-9, 21) 30 1 (-12, 70) 82 North South East West n = 261 n = 297 n = 103 n = 238 -2 (-8, 8) 16 -2 (-10, 24) 34 -1 (-8, 15) 23 -1 (-8, 23) 32 Commercial Government Industrial Even with small sets of n = 119 n = 74 n = 68 Data, the median -2 (-10, 5) 15 -2 (-8, 9) 17 -2 (-7, 40) 47 difference appears. Credit A Credit B Credit C n = 71 n = 41 n=7 -3 (-10, 0) 10 0 (-7, 6) 13 5 (-8, 31) 39 81
  • 80.
    Stratification Key LearningPoints: • The first thing you must do is Separate the Processes. We call this Stratification. If you don’t Stratify (isolate) the processes, you will have more than one central tendency in the data set and you will never figure out what drives variance. • If you think you have found the right label to stratify the processes, make sure you double check it to see if there is another label that is influencing the way the data appears. In this case, the real process label was Credit Rating, but it appeared in the Dashboard/Non-Dashboard data. You can double check by cross-cutting the data (look at Credit Rating and Dashboard at the same time in a tabular format), or by continuing to segment to see if the central tendency indicator still moves even though we thought it was an isolated process. In this case, if you continue with Dashboard as an isolated process, you will see the median move for various segmentations (especially Credit Rating). • Once you have Stratified (isolated the processes) and you have a segment that reflects several different levels of Variance, you have the first clues to find the critical x’s that drive variance. • When you find a critical x for one of the processes, check to see if it is also the critical x for the other processes. Often the factors that drive variance in one of the processes, also drive it in another. 82
  • 81.
    FMEA Model Prevention Detection What made failure mode to take place. Ask 5 Why’s…. Detection Cause Cause What manner my Material or process process was not able to input obey me Failure Mode Failure Mode (Defect) (Defect) Process Step Effect Effect External customer or downstream process step. Because of your process what all I will not be able to do Controls Controls 83
  • 82.
    Measurement System Analysis A measurement system will not willingly disclose the type of distortion, inaccuracy or A measurement system will not willingly disclose the type of distortion, inaccuracy or imprecision ititis transmitting to our data. We must actively force ititto reveal its hidden effects. imprecision is transmitting to our data. We must actively force to reveal its hidden effects. CAUTION: Objects in mirror are closer than they appear 84
  • 83.
    Measurement System Analysis Parts (Example) • Observations Inputs Outputs Inputs Measurement Outputs • Measurements Process Process • Data Product Variability Measurement Total Variability (Actual variability) Variability (Observed variability) σ2 σMeas.System 2 σObserved 2 Measurement + = System Variability - Investigated Actual(Part) through “R&R (Total) Study” The Measurement System will transmit variation to our data. 85
  • 84.
    Establishing the ProcessCapability LSL USL Short-Term Capability Long-Term Capability Over time, aaprocess tends to shift by approximately 1.5σ . . Over time, process tends to shift by approximately 1.5σ 86
  • 85.
    Visualizing the Causes Within Group • Called σ short term (σ st) • Our potential - the best we can be Time 1 • The σ reported by all 6 sigma Time 2 companies Time 3 • The trivial many Time 4 σ st + σ shift = σ total Between Groups • Called σ shift (truly a measurement in sigma's of how far the mean has shifted) • Indicates our process control • The vital few 87
  • 86.
    Analyse Purpose To reduce the number of Process Input Variables to a manageable number To determine high risk inputs from Failure Modes and Effects analysis To determine the presence of and eliminate Noise Variables through Multi-vari Studies To plan the first improvement activities 88
  • 87.
    Sources of Variation A common method of analysis at this stage is the variables tree. Try thinking about your process in this manner........ Customer Service Example Not resolved the call Agent to Agent Customer to Skill to Skill Call to Call Type of call Customer 89
  • 88.
    Tools Used…….. Time Series Plot Scatter Plot 15 15 10 H Vr rs a H Vr 10 rs a 5 5 0 Index 5 10 0 May Jun Jul Date ANOVA (Analysis of Variance) Main Effects Plot - Means for HrsVar 13.0 10.5 H Vr r a 8.0 s 5.5 3.0 Date Customer Salesman Box Plot Pareto Chart Pareto Chart for : Defects 15 1000 100 HrsVar 900 10 800 80 700 Percent 600 ount 60 500 C 400 5 300 40 200 20 100 0 0 0 ev . le t io n t D bb l or ma Defect Water Util Mining Paper We i gh Ai r Bu Co De f or Count 431 293 132 120 C us tom er Percent Cum % 44.2 44.2 30.0 74.2 13.5 87.7 1 12.3 00.0 90
  • 89.
    Regression….. Some examples: Y=Gas Mileage Y=Son’s (mpg) 30 Height 80 20 60 10 40 0 .5 1 1.5 2 60 70 80 X=Car Weight (tons) X=Dad’s Height (inches) Y=Grades Y=Selling Price (of 100%) 80 (Thousands) 35 60 25 40 5 0 .5 1 1.5 2 1 6 14 22 30 X=Study Time(Hours/Night) X=Age of Car 91
  • 90.
    Regression….. How do you find a line that “fits” the data? How do you find a line that “fits” the data? What we are looking for is a line which will minimize the distances from the plotted points to the line.... Deviations (distances) Deviations (distances) “How much the line missed by” “How much the line missed by” * Regression Line Regression Line * Response * Variable * * (Y) * Scatter Plot Points Scatter Plot Points (actual data values) (actual data values) * * * * Input Variable (X) 92
  • 91.
    Regression….. The R2 Statisticis Y defined as the sum of Measured squares of errors divided by sum of the Error square of difference Measured from average: Predicted Y=a+bX n ∑ (y − yi ) 2 i ^ i =1 r = 1− 2 n ∑ (y − y ) 2 i i =1 X 93
  • 92.
    Improve What will you do for Improve – Identify solutions. – Develop change management plan. – Conduct cost / benefit analysis. – Create implementation plan. 94
  • 93.
    Improve What will you do for Control – Define and implement ongoing measurement / monitoring plan. – Document procedures. 95
  • 94.
    Control In the physical world, the law of entropy Target explains the gradual loss of order in a system. The same law applies to business processes. Unless we add “energy” (in the form of documentation and ongoing process controls); processes will tend to degrade overtime, losing the gains achieved by design and improvement activities. The quality plan is the structure through which we add this “energy” to business processes. g 96
  • 95.
    Control Three Main Control Mechanism…….. Avoid Potential Problems Control Potential Problems Risk Management SPC Mistake Proofing 97
  • 96.
    Project Sign-off Answer the following questions before the project is signed off: • What can go wrong and derail improvements ? • What controls are in place ? • Can you show me your closure plan ? • What happen when the people change ? • Are there any follow up on projects ? • Is all documentation completed ? • Is the savings verified by finance ? • Is the audit plan in place ? 98
  • 97.
    Project Sign-off Finalize Financial Results •Calculate tangible benefits •Determine implementation costs •Calculate net financial gain •Calculate the intangible benefits e.g. cost avoidance, customer retention Tangible Benefits - Implementation Costs = Net Financial gains (Over one financial year) Bank 99
  • 98.
    Documentation Complete Documentation Package ……..Compile and organize a record of the key aspects of your six sigma project Typical Elements of the Documentation Package •A description of the project •Problem statement & business case •A list of CTQs + Xs •Hypothesis tests •Process capability analysis •Control parameters •Audit Plan/ owner •Financial results •Operational metrics •Lessons learned and best practices Project to be signed off by GB/BB, MBB, Financial controller, Process Owner, Champion. 100
  • 99.

Editor's Notes

  • #2 Materials List: Name placards Other concepts to teach: PPM, Sigma, RTYield Director of Engineering to cover
  • #9 10
  • #10 4 4 3 Six Sigma is a problem solving methodology using statistical techniques to Gather, Examine, Modify and Sustain quality improvements. Each project follows the same 4 steps, with the ultimate goal being to raise a process’s sigma level, thus reducing defects. The graph explains what a sigma is and shows why a 2 sigma process has more defects than a 6 sigma process.
  • #13 3
  • #14 11
  • #15 Six Sigma programs have consistently yielded excellent return on investment – we want them to be thinking in terms of investment, not cost. Wall Street has recognized the Six Sigma track record, resulting in significant increases in shareholder value. Of course there is no free ride with Wall Street, these programs have had to demonstrate consistent results year over year. The CEOs of these companies have made strong, public commitments to their Six Sigma programs and have attributed a significant portion of their successes to the results of those efforts.
  • #16 38
  • #19 Sigma is a statistical unit of measure which reflects process capability. Six sigma means that a process results in only 3.4 defects per million opportunities.
  • #28 11
  • #29 4
  • #30 RAY KOLBERG WILL DISCUSS THE TREMENDOUS PROGRESS PLASTICS HAS MADE, BUT HERE IS A SNAP SHOT. 5% OF ALL TRANSACTIONS ARE DELIVERED AT LEAST 15 DAYS EARLIER THAN THE CUSTOMER’S REQUEST. AND WE SEE THAT 5% CAN BE AS LATE AS 25 DAYS OR MORE. ON THE AVERAGE, HOWEVER, THE ORDER GETS DELIVERED WHEN THE CUSTOMER WANTED IT. IT SAYS THAT WE HAVE THE STRUCTURAL CAPABILITY TO DO WHAT THE CUSTOMER WANTS BUT …
  • #34 7
  • #35 Director of Engineering presenting GM Shainin Red X Strategies (hardy perennials) for current product problems. Delphi has committed to increase the Shainin resources to address Hardy perennials Design for Six Sigma for new product development Delphi has committed to have 20 DFSS projects initiated by the end of CY2000 Ford Six Sigma across the enterprise Shainin Variation Reduction DaimlerChrysler Six Sigma across the enterprise Shainin Variation Reduction Delphi’s competition is starting to adopt these processes as well
  • #36 Materials List: Name placards Other concepts to teach: PPM, Sigma, RTYield Director of Engineering to cover
  • #37 All our training centers on immediate application of the tools to solve a business problem – as captured in a ‘project’. The tools are not difficult to understand, it is the application of the tools in a real-world, team-based problem solving effort that is the challenge and the primary focus of our coaching and mentoring.
  • #38 Our program is designed to build all the key elements to enable complete integration of methodology into the business and leave behind a wholly owned, self-sustaining structure. Each of these roles is crucial in the successful integration of the discipline. Change training to development, change title to ‘Six Sigma Program Structure’ Emphasize building critical mass Drop DMAIC
  • #39 Complete a self-assessment of your performance on each Champion role in the past . How effectively have you performed each role? (rate on a scale from 1 = poor, to 5 = excellent)
  • #42 Materials List: Name placards Other concepts to teach: PPM, Sigma, RTYield Director of Engineering to cover
  • #45 24
  • #46 25 Take the real example and use that for the whole program
  • #47 27
  • #48 28
  • #49 28
  • #50 31
  • #51 32
  • #52 33
  • #53 34
  • #54 35
  • #55 Materials List: Name placards Other concepts to teach: PPM, Sigma, RTYield Director of Engineering to cover
  • #56 Materials List: Name placards Other concepts to teach: PPM, Sigma, RTYield Director of Engineering to cover
  • #57 Materials List: Name placards Other concepts to teach: PPM, Sigma, RTYield Director of Engineering to cover
  • #58 Key Messages: We are in this phase. Your notes :
  • #59 How does each division define success? What other metrics are needed? Warranty discussion -Delphi is being held responsible for a larger share of our GM warranty impact. NA vehicle manufacturers experienced $6 billion in warranty costs in 1999.
  • #62 34
  • #63 Think of measurements occurring at three stages of the process. Typically, output measurements are the most important. These are measures of how well customer needs and requirements are being met or exceeded. If one were to think of a stream of water, this would be the most downstream measure of the process. The second family of measures is called “process measure.” These more “upstream” measure are taken at critical points in the process. It is desired that these measures not be data which is easy to collect, but data correlated to the pertinent output measure. The final major family of measures is input measures. These often overlooked measures are contributions to the process that are transformed into value for the customer. An example may prove helpful. If one were to look at a person’s health, the most downstream measurement would be whether they are alive or dead. While of critical importance to the customer, what affects this downstream measurement? As we move further upstream in the process, we may find that a person’s weight is related to their health. What affects weight? In this example, caloric intake and exercise are two examples of process measurements that ultimately affect the customer requirements. Further, the input data of what type of exercise equipment and where one shops for food shows the importance of input measurements as well. What Critical-To-Quality characteristics can you measure at each point in your process map, whether they be input, process, or output related? Rule Of Thumb: Target 1-3 measures in each category input, process, output measures.
  • #65 Define business process to be reviewed Name it. Agree on beginning and end of process Bound it. Use brainstorming and storyboarding to identify all the outputs, customers, suppliers &amp; inputs. Identify the primary outputs, customers, suppliers and input. Brainstorm the customers’ requirements for the primary outputs. Identify the process steps using brainstorming and storyboarding techniques. Hints – start by rapidly writing process steps on cards and placing them on the wall. Write large. One step per card. Don’t try to establish order. All steps should begin with a verb. Don’t discuss process steps in detail. Arrange the detailed process steps in a sequence (e.g., the life cycle or natural workflow). Also draw in arrows to show major and secondary paths. Try to show decisions as different paths the work can take. Validate the process with a “walk through” of the actual process. Add many missed steps, decision points or rework loops. Analyze the map looking for: Rework (REs) Bottlenecks Nonvalue-added steps Bureaucracy Delays and wait time Total cycle time Capability of the process to meet customer requirements Critical hand-offs Cost
  • #66 Establishing the start and stop points of a process is a crucial step in process mapping. By defining these boundaries, the process improvement team is better able to identify all the important steps, events and operations that constitute the process. Typically, the start point of a process is the first step that receives the inputs from suppliers. Typically, the end point is the delivery of the product or service to the customer interface. Most improvement teams will underestimate the amount of the time needed to reach agreement on the start and stop points of a particular process.
  • #67 There are four major versions of a process map. First what individuals who touch the process think it is. It is important to reveal the thinking of each individual within a team as to what they think the process is first. Second, reconciling what the process map is into what it really is is a second version of the process. These first two versions of the process constitute what is referred to as the “As Is” process map. A thorough “As Is” process map is one of the short-term goals of good process mapping. As the team moves forward and does process analysis and problem-solving, they will move toward the third version of the process map – the “Should Be” map. At this point, a check must be made as to whether customer needs and requirements have been met or exceeded. If they have not, the entire process must be reengineered (i.e., redone from scratch) which would result in what some call the “Could Be” process map.
  • #68 A clear understanding of product Value Stream , including all the rework buried in the unacknowledged hidden factory, will reveal the true savings potential. Six Sigma seeks accurate definition of the value stream process, including every contact between man or machine and the product, to identify the targets for COPQ reduction. Use the term Value Stream Mapping
  • #90 9 9
  • #91 9 9
  • #95 How does each division define success? What other metrics are needed? Warranty discussion -Delphi is being held responsible for a larger share of our GM warranty impact. NA vehicle manufacturers experienced $6 billion in warranty costs in 1999.
  • #96 How does each division define success? What other metrics are needed? Warranty discussion -Delphi is being held responsible for a larger share of our GM warranty impact. NA vehicle manufacturers experienced $6 billion in warranty costs in 1999.
  • #97 11
  • #98 69
  • #99 High-level roles and responsibilities
  • #100 High-level roles and responsibilities
  • #101 High-level roles and responsibilities
  • #102 High-level roles and responsibilities