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