NG BB 31 Cause and Effect (XY) Matrix
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This document provides information about creating a cause and effect (XY) matrix for process improvement. It discusses the steps to create a XY matrix, including identifying key customer requirements and process inputs, rating their importance and relationship, and calculating scores to determine which inputs have the largest impact on outputs. An example is provided about using a XY matrix to identify which factors most affect customer satisfaction with coffee at an all ranks club.
NG BB 31 Cause and Effect (XY) Matrix
- 1. UNCLASSIFIED / FOUO UNCLASSIFIED / FOUO National Guard Black Belt Training Module 31 Cause and Effect (XY) Matrix UNCLASSIFIED / FOUO UNCLASSIFIED / FOUO
- 2. UNCLASSIFIED / FOUO CPI Roadmap – Analyze 8-STEP PROCESS 6. See 1.Validate 2. Identify 3. Set 4. Determine 5. Develop 7. Confirm 8. Standardize Counter- the Performance Improvement Root Counter- Results Successful Measures Problem Gaps Targets Cause Measures & Process Processes Through Define Measure Analyze Improve Control ACTIVITIES TOOLS • Value Stream Analysis • Identify Potential Root Causes • Process Constraint ID • Reduce List of Potential Root • Takt Time Analysis Causes • Cause and Effect Analysis • Brainstorming • Confirm Root Cause to Output • 5 Whys Relationship • Affinity Diagram • Estimate Impact of Root Causes • Pareto on Key Outputs • Cause and Effect Matrix • FMEA • Prioritize Root Causes • Hypothesis Tests • Complete Analyze Tollgate • ANOVA • Chi Square • Simple and Multiple Regression Note: Activities and tools vary by project. Lists provided here are not necessarily all-inclusive. UNCLASSIFIED / FOUO
- 3. UNCLASSIFIED / FOUO Learning Objectives Learn the steps to create a Cause and Effect (C&E) matrix Learn how to link the C&E matrix to other tools Perform an exercise to actually create a C&E matrix Cause and Effect Matrix UNCLASSIFIED / FOUO 3
- 4. UNCLASSIFIED / FOUO C&E Matrix Overview The team develops an understanding of the greatest sources of variation within the process and pinpoints the critical few key process input variables (KPIVs) that must be addressed to improve the key process output variables (KPOVs) Idea Generation Tools Process Map C&E Matrices FMEA Cause and Effect Matrix UNCLASSIFIED / FOUO 4
- 5. UNCLASSIFIED / FOUO Application Examples Distribution – An analyst wants to know which items have the greatest effect on providing material on time Administrative – A manager wants to determine which process inputs and steps have the most impact on user satisfaction and processing speed and accuracy Cause and Effect Matrix UNCLASSIFIED / FOUO 5
- 6. UNCLASSIFIED / FOUO C&E Matrix What A cause and effect matrix relates process steps to inputs and correlates to process outputs Customer requirements are ranked by order of importance and then inputs and outputs are rated by their interaction impact It relates the key inputs to the key outputs (customer requirements) using process maps and the Cause & Effect Diagram as primary sources Cause and Effect Matrix UNCLASSIFIED / FOUO 6
- 7. UNCLASSIFIED / FOUO C&E Matrix Purpose Why To determine what key input variables should get the most attention, such that their performance improvement will best meet key output variable requirements To identify which input variables (causes) most influence the key process output variable (effect) Cause and Effect Matrix UNCLASSIFIED / FOUO 7
- 8. UNCLASSIFIED / FOUO C&E Matrix Method How Identify key customer requirements (outputs) from the process map and VOC/VOB analysis Outputs are given a priority score according to importance to the customer (usually on a 1 to 10 scale, with 10 being most important) Identify significant inputs from the SIPOC, detailed process map, value stream map and/or cause & effect diagram. Cause and Effect Matrix UNCLASSIFIED / FOUO 8
- 9. UNCLASSIFIED / FOUO C&E Matrix Method How (Cont.) Inputs are rated based on the strength of their relationship with output variables and given a correlation score as follows: Blank or zero = no correlation 1 = remote correlation 3 = moderate correlation 9 = strong correlation Cross multiply correlation scores with priority scores and add across for each input Create a Pareto chart and focus on the variables with the highest scores Cause and Effect Matrix UNCLASSIFIED / FOUO 9
- 10. UNCLASSIFIED / FOUO C&E Matrix Form XY Matrix Project: Date: 1 2 3 4 Output Variables (Y's) Output Rating Association Table Input Variables (X's) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Cause and Effect Matrix UNCLASSIFIED / FOUO 10
- 11. UNCLASSIFIED / FOUO Steps to Create an XY Matrix Basic Approach 1. Place the process output (CTS) characteristics across the top of the matrix and rank 2. Place the process inputs down the side of the matrix 3. Correlate process inputs to outputs 4. Calculate process input scores 5. Rank and pareto the process inputs Cause and Effect Matrix UNCLASSIFIED / FOUO 11
- 12. UNCLASSIFIED / FOUO Example: Coffee at the All Ranks Club A local All Ranks Club wants to improve customer satisfaction with the coffee they serve The team has completed a process map and brainstormed root cause ideas - they are ready to create a C&E matrix to identify the inputs that have the largest impact on customer satisfaction Cause and Effect Matrix UNCLASSIFIED / FOUO 12
- 13. UNCLASSIFIED / FOUO Example: Coffee at the All Ranks Club Step 1: Input Project: Coffee XY Matrix output (Y) Date: 11/9/2008 variables and 1 2 3 4 10 output ratings Output Variables (Y's) from the VOC/VOB analysis Acidity Aroma Taste Price Output Rating 9 3 3 1 Input Variables (X's) Association Table Score % Rank 1 Coffee Type 9 9 9 9 144 16.04% 2 3 Amt. of Coffee Grind Time 9 9 Step 2: Circle most 3 3 1 9 3 9 126 96 14.03% 10.69% 4 5 Water Temp. Cup Type 9 1 significant3 Xs from 3 3 1 1 1 94 28 10.47% 3.12% 6 Cup Size 1 fishbone and other 3 3 1 28 3.12% sources and list 7 Brew Time 9 3 1 1 94 10.47% 8 Type of Coffee Pot 1 1 1 3 18 2.00% 9 10 Thickness of Filter Country of Origin 3 3 0 3 inputs 0here 3 3 3 30 48 3.34% 5.35% 11 Age of Coffee 9 1 1 9 96 10.69% 12 Freshness of Beans 9 1 1 9 96 10.69% UNCLASSIFIED / FOUO
- 14. UNCLASSIFIED / FOUO Example: Coffee at the All Ranks Club XY Matrix Step 3: Correlate Project: Coffee inputs to outputs Date: 11/9/2008 using 0,1,3,9 Step 4: 1 2 3 4 10 Output Variables (Y's) rating system Calculate score for all inputs Acidity Aroma Taste Price Output Rating 9 3 3 1 Input Variables (X's) Association Table Score % Rank 1 Coffee Type 9 9 9 9 144 16.04% 2 Amt. of Coffee 9 3 9 9 126 14.03% 3 Grind Time 9 3 1 3 96 10.69% 4 Water Temp. 9 3 1 1 94 10.47% 5 Cup Type 1 3 3 1 28 3.12% 6 Cup Size 1 3 3 1 28 3.12% 7 Brew Time 9 3 1 1 94 10.47% Type of Coffee Pot 1 1 1 3 18 2.00% Calculate Score for Coffee Type 8 9 Thickness of Filter 3 0 0 3 30 3.34% 10 Country of Origin 3 3(9*9)+(9*3)+(9*3)+(9*1) = 144 3 3 48 5.35% 11 Age of Coffee 9 1 1 9 96 10.69% 12 Freshness of Beans 9 1 1 9 96 10.69% UNCLASSIFIED / FOUO
- 15. UNCLASSIFIED / FOUO Pareto Chart – Coffee Example Pareto Chart of Key Input Variables Step 5: Create a Pareto 160 140 Chart showing most important inputs for 120 further analysis 100 Score 80 60 40 20 0 pe ee e ffe e ns p. e in ilte r pe ze ot Ty ff Tim ea em Tim rig Ty Si eP e Co d Co fB T fO fF p p e ffe .o f rin of o a te r Br e w y o so Cu Cu off Co mt G Ag e ss ntr es fC A ne W ou kn eo es h C T hic yp Fr T Variable Name UNCLASSIFIED / FOUO
- 16. UNCLASSIFIED / FOUO Coffee at the All Ranks Club Conclusion The Pareto chart shows us that the 2 process inputs that have the most significant impact on our process outputs are: Coffee type Amount of coffee High-ranked process inputs would then be evaluated with hypothesis testing or other validation method Cause and Effect Matrix UNCLASSIFIED / FOUO 16
- 17. UNCLASSIFIED / FOUO Alternate Method: Focused Approach Arrive at Arrive with Delivered Take back schedule proper Dressed via correct to room Process Physical Therapy Example d time equipment properly mode promptly Outputs 5 4 4 2 4 Importance Process Steps Process Inputs Correlation of Input to Output Total 0 Patient Scheduled 5 2 0 3 0 39 Attendant Assigned 5 0 0 0 0 25 Attendant Arrives 5 0 0 0 0 25 Obtains Equipment 1 5 0 1 0 27 Transport Patient 5 0 0 0 0 25 Provide Therapy Input process steps first. Use0 0 0 0 0 0 Notifies of Return the XY Matrix 0to determine 0 0 0 5 20 Attendant Assigned highest ranking0 process steps,0 0 0 5 20 Attendant Arrives 0 0 0 0 5 20 then redo XY Matrix using inputs Patient Returned 0 0 0 0 5 20 from just those steps to determine significant Xs Adapted From The Six Sigma Handbook, p. 295, by Thomas Pyzdek Cause and Effect Matrix UNCLASSIFIED / FOUO 17
- 18. UNCLASSIFIED / FOUO Exercise: Prepare an XY Matrix Objective Create an XY Matrix for the GGA's Budget Department Instructions Build a C&E matrix from the Cause & Effect Diagram (Fishbone) List key output variables Rank importance according to VOC/VOB analysis List top process input variables (no more than 10, for the sake of time) Be prepared to report results to the group Time = 20 Minutes UNCLASSIFIED / FOUO 18
- 19. UNCLASSIFIED / FOUO Linking XY Matrix to Other CPI Tools C&E Matrix Rating of Importance to Customer 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Process Step Process Inputs Total 1 0 2 0 3 0 4 0 5 0 Capability FMEA Control Plan Summary Summary Operational Excellence Key Process Output Variable Product: Core Team: Control Plan Date (Orig): Process/Product Key Contact: Capability Summary Sheet Failure Modes and Effects Analysis Phone: Date (Rev): (FMEA) Process Measurement %R&R Sample Sample Control Process Process Step Input Output Specification (LSL, Cpk /Date Reaction Plan Technique P/T Size Frequency Method USL, Target) Customer Upper Lower Process or Measurement %R&R or P/T Sample Product Name: Prepared by: DICY Turn Steam on Scales Requirement Spec Target Spec Cp Cpk Date Actions Accuracy Technique Ratio Size Responsible: FMEA Date (Orig) ______________ (Rev) _____________ DMF Load DMF DMF Load (Output Variable) Limit Limit Accuracy Gel Time DMF Load DMF DMF Cleanliness Viscosity Process S O D R DICY Load DICY DICY Envir. Factors Step/Part E C E P Cleanliness Number Potential Failure Mode Potential Failure Effects V Potential Causes C Current Controls T N DICY Load DICY DICY Load Spin Draw Fiber Breakouts Undersized package, High SD Dirty Spinneret Visual Detection of Wraps and Accuracy Color Process panel-hours lost 2 8 broken Filaments 9 144 DICY Raw DICY Load DICY Homogeneity Filament motion Visual Sight-glass Materials 5 2 8 80 DICY Mixer Consistency DICY Load DICY Speecd Polymer defects Fuzzball Light Digets Time 8 2 9 144 DMF Load DMF DMF Raw Materials Temperature DICY Turn Steam on Preheating DICY TK 0 Solids The Key Outputs are Key Inputs The Key Inputs listed and evaluated are explored are evaluated Cause and Effect Matrix UNCLASSIFIED / FOUO 19
- 20. UNCLASSIFIED / FOUO XY Matrix (Root Cause Analysis) Template Ra ting of Importa nce to Custome r 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Requirement Total Proce ss Ste p Proce ss Input 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 10 0 11 0 12 0 13 0 14 0 15 0 16 0 17 0 18 0 19 0 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Total Lower Spec Target Upper Spec This table prov ides the initial input to the FMEA. W hen each of the output variables (requirements) are not correct, that represents potential "EFFECTS". W hen each input variable is not correct, that represents "Failure Modes". 1. List the Key Process Output Variables 2. Rate each v ariable on a 1-to-10 scale to importantance to the customer 3. List Key Process Input Variables 4. Rate each v ariables relationship to each output variable on a 1-to-10 scale 5. Select the top input variables to start the FMEA process; Determine how each selected input varable can "go wrong" and place that in the Failure Mode column of the FMEA. Required Deliverable UNCLASSIFIED / FOUO
- 21. UNCLASSIFIED / FOUO Takeaways The C&E matrix uses the voice of the customer to determine where we should focus our improvement efforts. (That is, establishing the “critical few” X’s that the team will investigate further.) Use the process map or cause & effect diagram to determine process inputs for the C&E matrix. The C&E matrix is an important prerequisite for further tools, such as FMEA, hypothesis testing and the Process Control Plan. Cause and Effect Matrix UNCLASSIFIED / FOUO 21
- 22. UNCLASSIFIED / FOUO What other comments or questions do you have? UNCLASSIFIED / FOUO
- 23. UNCLASSIFIED / FOUO References Pyzdek, Thomas, The Six Sigma Handbook (also titled: The Complete Guide to Six Sigma), QA Publishing, Tucson, Arizona, 1999 Cause and Effect Matrix UNCLASSIFIED / FOUO 23