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Analyze Phase Lean Six Sigma Template

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Lean Six Sigma Analyze Phase Tollgate Template. Includes embedded tools, notes, guidelines, and examples. Useful for Green and Black Belt Projects, Project Management, Quality control and overall business process improvements.

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Shared by: Steven Bonacorsi
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Lean Six Sigma Program Name < Last Name, First Name > Wave No: Review Date: Define Measure Analyze Improve Control LEAN SIX SIGMA Define Lean Six Sigma Program Name Measure Analyze Improve Control LEAN SIX SIGMA Analyze Phase Road Map Define Measure Analyze Improve Analyze Control Activities • • • • • • Tools • • • • • • • • • Identify Potential Root Causes Reduce List of Potential Root Causes Confirm Root Cause to Output Relationship Estimate Impact of Root Causes on Key Outputs Prioritize Root Causes Complete Analyze Gate Process Constraint ID and Takt Time Analysis Cause & Effect Analysis FMEA Hypothesis Tests/Conf. Intervals Simple & Multiple Regression ANOVA Components of Variation Conquering Product and Process Complexity Queuing Theory Bonacorsi Consulting 3 Measure Overview Process Capability CTQ: ? Unit (d) or Mean (c): ? Defect (d) or St. Dev. (c): ? DPMO (d): ? Sigma (Short Term): ? Sigma (Long Term):? MSA Results: show the percentage result of the GR&R, AR&R or other measurement systems analysis carried out in the project 40 Individual Value Analyze Graphical Analysis I -M R C h a r t o f D e l i v e r y T i m e U C L= 3 7 . 7 0 35 30 25 20 1 28 55 82 109 136 O b s e r v a tio n 163 190 217 244 LC L= 2 0 . 5 6 _ X= 2 9 .1 3 1 0 .0 M oving Range 7 .5 5 .0 2 .5 0 .0 1 28 55 82 109 136 O b s e r v a tio n 163 190 217 244 U C L= 1 0 . 5 3 __ M R = 3 .2 2 LC L= 0 Root Cause / Quick Win Root cause: Quick Win #1 Tools Used Detailed process mapping Measurement Systems Analysis Value Stream Mapping Data Collection Planning Basic Statistics Process Capability Histograms Time Series Plot Probability Plot Pareto Analysis Operational Definitions 5s Pull Control Charts Root cause: Quick Win #2 Root cause: Quick Win #3 Bonacorsi Consulting 4 Graphical Analysis Summary Normal Non-Normal Investigation What is the shape of the Project Y data? Is the Y data normally distributed? What is the normality test p-value? Analyze Data is Continuous: ?? Data Points Collected Between XX/XX/XX and XX/XX/XX Normality Central Tendency Variation Average Median or Q1 or Q3 Statistical / Graphical Analysis Histogram Normality Test Std. Dev (long term) Span (1/99) or Stability Factor (Q1/Q3) Observations/Conclusion What is the central tendency of the Mean, Median, or Quartile Values Project Y data? What is the spread of the Project Y Standard Deviation, Span, or data? Stability Factor Is the data stable over time? Run Chart Describe any other observations about the Project Y data Include any other findings regarding the data here Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 5 TPC Analysis Technical-Political-Cultural (TPC) Analysis Sources Of Resistance Definition Causes Of Resistance Rating Examples Analyze Technical Political Cultural Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 6 Sources of Variation Defect Overproduction Transportation Area 1 Area 1 Sub area 1 Sub area 1 Analyze Was the Action workout performed #1? NVA Area 1 Sub area 1 Processing Motion Area 1 Area 1 Sub area 1 Sub area 1 Inventory Waiting Was the Action workout performed #2? < Insert your variation percentage as shown in pie chart > 32% 5% 5% 5% 11% 42% Man Machine Method Measurement Mother Nature Machine Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 7 Cause and Effect Matrix Importance Rating Score Blank = no correlation 1 = remote correlation 3 = moderate correlation 9 = strong correlation Item Speed to Decision Cooperation, Seats Schedule Clarity, Feedback Meets Reach Available Options Accuracy Req Decision 10 7 6 7 10 9 Budget for Options 5 Funding Source Identified 7 Process Outputs Importance Rating Correlation of Input to Output Process Step Process Inputs To what extent does variability in these process steps/inputs impact variability across these outputs ? Develop Options Customer schedule & including price & requirements schedule Proper decision makers Approve options Database, tribal Inventory Search of knowledge known Vacant Space Interview Customer to Form Understand Form options, costs, schedule Brief customer on options, funding vehicle options Supervisor Approval Peer Review Approval Fill out Forms Accept Form Create Spreadsheet Dept Approval Approval Mgr 1 Approval Mgr 2 Identify Need Assign to Team Mark Up Floor Plan Notification Forms to requestor and Log in issue Prepare brief 9 9 9 3 9 9 9 9 3 3 3 3 3 3 3 1 9 9 1 9 9 9 9 3 3 9 3 3 3 1 9 9 9 9 9 3 3 9 9 1 Total Higher score = 3 9 459 392 261 217 216 118 111 108 51 30 30 30 30 21 21 0 0 0 0 Analyze Was the rating of importance done by Kano analysis? 16 18 15 14 17 8 7 11 12 3 4 5 6 1 13 2 9 19 19 Were all the process steps identified? What is the % of quick hits causing the problem? 3 3 Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 8 Run Charts When the points are connected with a line, a run ends when the line crosses the median Analyze A run, in this case, is one or more consecutive points on the same side of the median Median = 38 1 Run about the Median, can you count the other 8? There is a no nonrandom influence acting upon this process. There is no trend Longest Run about the median There is a nonrandom influence acting upon this process that is creating clustering There is a no nonrandom influence acting upon this process. There is no Oscillation Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 9 Pareto Plot 150 Analyze 100 80 Count 100 60 40 50 20 0 0 So ut h r No th s Ea t he Ot rs Defect Count P ercent Cum % 100 58.5 58.5 50 29.2 87.7 15 8.8 96.5 6 3.5 100.0 Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 10 Percent Scatter Plot Analyze Average Expenses decrease as Sales Increase Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 11 Linear Regression F i tt e d L i n e P l o t W a it T im e = 3 2 .0 5 + 0 .5 8 2 5 D e live r ie s 55 S R-Sq R - S q ( a d j) Analyze 95% confident that 94.1% of the variation in “Wait Time” is from the “Qty of Deliveries” 1 .1 1 8 8 5 9 4 .1 % 9 3 .9 % 50 Wait Time 45 40 35 10 15 20 25 D e liv e r ie s 30 35 Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 12 One-Sample T-Test and Dot Plot Dotplot of Improve Data (with Ho and 95% t-confidence interval for the mean) Analyze [ _ X Ho ] This Dot Plot graphically displays 95% confidence intervals that the data will fall between 23.45 and 32.75 for response time (see the red brackets and red line). It also indicates that the Mean (Red X) is at 28.1. The blue Ho marks the Target Mean. Hypothesis Test: Is the Improve data set mean different from the Target Mean mean of 30 minutes? We Are 95% Confident The Improve Mean Is Not Statistically Different 0 10 20 30 40 50 Improve Data The test statistic, T, for Ho: mean = 30 is calculated as –0.84. The P-Value of this test, or the probability of obtaining more extreme value of the test statistic by chance if the null hypothesis was true, is 0.410 (> 0.05). This is called the attained significant level, or P-Value. Therefore, Accept Ho, which means we conclude that the Improve data set mean (28.1) is NOT different than the Target mean (30). One-Sample T: Improve Data Test of mu = 30 vs mu not = 30 Variable Improve Data Variable Improve Data N 30 Mean 28.10 StDev 12.45 T -0.84 P 0.410 SE Mean 2.27 95.0% CI (23.45, 32.75) Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 13 Test for Equal Variance Test for Equal Variances for Total Time 95% Confidence Intervals for Sigmas Factor Levels Antenna Analyze Payroll 0 50 100 150 Test for Equal Variance Confirms Payroll Input Type Cycle Time is Significant F-Test Test Statistic: 0.108 P-Value : 0.001 Boxplots of Raw Data Levene's Test Test Statistic: 21.054 P-Value : 0.000 Antenna Payroll The spread of the data is statistical greater for completing the payroll form than the Antenna time tracking. 50 60 70 0 10 20 30 40 T otal T ime Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 14 One Way ANOVA Net Hours Call Open Analyze After further investigation, possible reasons proposed by the team are supplier backorders, lack of technician certifications and the distance from the supplier to the client site. 150 Boxplot: Part/ No Part Impact on Ticket Cycle Time 100 No Part Analysis of Variance for Net Hour Source DF SS MS Part/No 1 7421 7421 Error 69 59194 858 Total 70 66615 Level No Part Part N 27 44 Mean 21.99 43.05 29.29 StDev 19.95 33.70 F 8.65 P 0.004 Pooled StDev = Individual 95% CI's For Mean --+---------+---------+---------+---(--------*---------) (------*------) --+---------+---------+---------+---12 24 36 48 Because the p-value <= 0.05, we can be confident that calls requiring parts do have an impact on the ticket cycle time. Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 15 Part It is also caused by the need for 50 technicians to make a second visit to the end user to complete the part replacement. Next step will be 0 for the team to confirm these Part/No Part suspected root causes. Mood’s Median After further investigation, possible reasons proposed by the team are supplier backorders, lack of technician certifications and the distance from the supplier to the client site. It is also caused by the need for technicians to make a second visit to the end user to complete the part replacement. Next step will be for the team to confirm these suspected root causes. Chi-Square = 19.14 DF = 2 P = 0.000 Month N<= N> Median 10 88 132 8.43 11 123 121 6.57 12 111 68 4.77 Overall Median 6.63 40 Analyze Dotplots of Defects by Impact on Dot Plot: Part/ No Part Subgroup Ticket Cycle Time 30 Defects 20 10 0 After Before Subgroup Q3-Q1 12.15 10.52 7.10 Mood’s Median Test Individual 95.0% Confidence Interval’s ------+---------+---------+---------+ (--------+-------) (------+------) (-----+------) ------+---------+---------+---------+ 4.8 6.4 8.0 9.6 Because the p-value <= 0.05, we can be confident that calls requiring parts do have an impact on the ticket cycle time. Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 16 Statistical Testing for Discrete Data Chi-Square Test Expected counts (calculated by Minitab) are printed below observed counts Errors 33 40.46 27 40.90 132 107.03 32 71.35 168 132.26 392 Correct 60 52.54 67 53.10 114 138.97 132 92.65 136 171.74 509 Total 93 Analyze 1 Because this p value is less than 5% (0.05), we can be confident that department does have an impact on the proportion of correct tickets processed This is due to the fact that Department 4 has fewer people who need to add information to each ticket, which reduces the chances that an error will be made. Also, in Department 4 the customer name, address and ticket number are added directly from the contracts system without human intervention, reducing the possibility that a typo or other error type could occur that will need to be corrected later (taking more time) 2 94 3 246 4 164 5 304 Total Chi-Sq = 901 1.376 4.722 5.827 21.703 9.657 DF = 4, P-Value + 1.060 + + 3.637 + + 4.487 + + 16.714 + + 7.437 = 76.620 = 0.000 Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 17 Process Bottleneck Identification & Workload Balancing Analyze Takt Rate Analysis compares the task time of each process (or process step) to: Each other to determine the time trap Customer demand to determine if the time trap is the constraint Value Add Analysis - Current State 80 70 60 50 40 30 20 10 0 Takt Time = Net Process Time Available Number of Units to Process Takt Tim e = 55 - Task Time (seconds) -- --- 1 2 3 4 5 6 Task # BVA Time 7 8 9 10 CVA Time NVA Time Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 18 Hypothesis Test Summary Hypothesis Test (ANOVA, 1 or 2 sample t - test, Chi Squared, Regression, Test of Equal Variance, etc) Analyze Factor (x) Tested Location p Value Observations/Conclusion Was the hypothesis roadmap followed? Example: ANOVA Significant factor - 1 hour driving time from DC 0.030 to Baltimore office causes ticket cycle time to generally be longer for the Baltimore site Significant factor - on average, calls requiring 0.004 parts have double the cycle time (22 vs 43 hours) Significant factor - Department 4 has digitized 0.000 addition of customer info to ticket and less human intervention, resulting in fewer errors n/a South region accounted for 59% of the defects due to their manual process and distance from the parts warehouse Example: ANOVA Part vs. No Part What was the power and Sample Size? Example: Chi Squared Department Example: Pareto Region What are α and β risks? Describe any other observations about the root cause (x) data Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 19 Control / Impact Analysis Does the X have a high, medium, or low impact on the project Y? Analyze High Impact ? Medium Impact ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Low Impact Does the X in he teams control, influence, or out of their control? In Our Control ? ? ? In Our Influence ? ? ? Out of Our Control ? ? Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 20 In/Out of Frame Creating a visual depiction of what elements of the project are in the scope (frame) and out of the scope Vital X #8 Vital X #2 Analyze Influence Vital X #5 Vital X #3 Vital X #7 No Control Control Vital X #6 Vital X #4 Vital X #1 Vital X #9 Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 21 Systems & Structures Assessment System or Structure Staffing 1 2 Training & Development 1 2 Measurements & Reward 1 2 Communication 1 2 Organization Design 1 2 Information Systems 1 2 Resource Allocation 1 2 Analyze How should we use or modify to support "____" vision and objectives Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 22 Quick Wins 5s 4-Step Setup Reduction Inventory Reduction MSA Improvements Price reductions Reduced DOWNTIME (Non-value added steps or work) Pull System Kaizen events Other Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 23 Analyze Business Impact State financial impact of project Separate “hard or Type 1” from “soft Type 2 or 3” dollars State financial impact of future project leverage opportunities Annual Estimate Revenue Enhancement Expenses Reduction Loss Reduction Cost Avoidance Total Savings • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? • Type 1: ? • Type 2: ? • Type 3: ? Analyze Replicated Estimate Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 24 Business Impact Details Show the financial calculation savings and assumptions used. Assumption #1 (i.e. source of data, clear Operational Definitions?) Assumption #2 (i.e. hourly rate + incremental benefit cost + travel) Analyze Type 1: Describe the chain of causality that shows how you determined the Type 1 savings. (tell the story with cause–effect relationships, on how the proposed change should create the desired financial result (savings) in your project ) Type 2: Describe the chain of causality that shows how you determined the Type 2 savings. (tell the story with cause–effect relationships, on how the proposed change should create the desired financial result (savings) in your project ) Show the financial calculation savings and assumptions used. Assumption #1 (i.e. Labor rate used, period of time, etc…) Assumption #2 (i.e. contractor hrs or FTE, source of data, etc…) Describe the Type 3 Business Impact(s) areas and how these were measured Assumption #1 (i.e. project is driven by the Business strategy?) Assumption #2 (i.e. Customer service rating, employee moral, etc…) Other Questions Stakeholders agree on the project’s impact and how it will be measured in financial terms? What steps were taken to ensure the integrity & accuracy of the data? Has the project tracking worksheet been updated? Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 25 Current Status Key actions completed Issues Lessons learned Communications, team building, organizational activities Upcoming Deliverables/Tasks - 2 weeks out Due Revised Due Analyze Lean Six Sigma Project Status and Planning Deliverables/Tasks Completed last week Comments W/E: Comments For deliverables due thru: Actions Scheduled for next 2 Weeks Deliverable/Action Who Due Revised Due Comments/Resolution Need Help Issue/Risk Current Issues and Risks Who Due Revised Due Recommended Action Need Help Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 26 Next Steps Key actions Planned Lean Six Sigma Tool use Questions to answer Barrier/risk mitigation activities Analyze Lean Six Sigma Project Issue Log No. 1 2 3 4 5 6 7 8 9 10 Description/Recommendation Status Open/Closed/Hold Due Date Last Revised: Revised Due Date Resp Comments / Resolution Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 27 Analyze Stop Tollgate Checklist Tollgate Review Has the team identified the key factors (critical X’s) that have the biggest impact on process performance? Have they validated the root causes? Analyze Has the team examined the process and identified potential bottlenecks, disconnects and redundancies that could contribute to the problem statement? Has the team analyzed data about the process and its performance to help stratify the problem, understand reasons for variation in the process, and generate hypothesis as to the root causes of the current process performance? Has an evaluation been done to determine whether the problem can be solved without a fundamental ‘white paper’ recreation of the process? Has the decision been confirmed with the Project Sponsor? Has the team investigated and validated the root cause hypotheses generated earlier, to gain confidence that the “vital few” root causes have been uncovered? Does the team understand why the problem (the Quality, Cycle Time or Cost Efficiency issue identified in the Problem Statement) is being seen? Has the team been able to identify any additional ‘Quick Wins’? Have ‘learning's to-date required modification of the Project Charter? If so, have these changes been approved by the Project Sponsor and the Key Stakeholders? Have any new risks to project success been identified, added to the Risk Mitigation Plan, and a mitigation strategy put in place? Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 28 Sign Off Analyze • I concur that the Analyze phase was successfully completed on MM/DD/YYYY • I concur the project is ready to proceed to next phase: Improve Enter Name Here Green Belt/Black Belt Enter Name Here Enter Name Here Sponsor / Process Owner Deployment Champion Enter Name Here Financial Representative Enter Name Here Master Black Belt Enter Key Slide Take Away (Key Point) Here Bonacorsi Consulting 29 Bonacorsi Consulting This Training Manual and all materials, procedures and systems herein contained or depicted (the "Manual"), are the sole and exclusive property of Bonacorsi Consulting, L.L.C. The contents hereof contain proprietary trade secrets that are the private and confidential property of Bonacorsi Consulting. Unauthorized use, disclosure, or reproduction of any kind of any material contained in this Manual is expressly prohibited. The contents hereof are to be returned immediately upon termination of any relationship or agreement giving user authorization to possess or use such information or materials. Any unauthorized or illegal use shall subject the user to all remedies, both legal and equitable, available to Bonacorsi Consulting. This Manual may be altered, amended or supplemented by Bonacorsi Consulting from time to time. In the event of any inconsistency or conflict between a provision in this Manual and any federal, provincial, state or local statute, regulation, order or other law, such law will supersede the conflicting or inconsistent provision(s) of this Manual in all properties subject to that law. © 2006 by Bonacorsi Consulting, L.L.C. All Rights Reserved. Steven Bonacorsi is a Senior Master Black Belt instructor and coach. Steven Bonacorsi has trained hundreds of Master Black Belts, Black Belts, Green Belts, and Project Sponsors and Executive Leaders in Lean Six Sigma DMAIC and Design for Lean Six Sigma process improvement methodologies. Bonacorsi Consulting 30

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Steven Bonacorsi, Vice President (16+ years experience) Expertise: Certified Lean Six Sigma Master Black Belt (MBB), Certified Project Management Professional (PMP), Masters in Computer Information Systems (MS-CIS) and Business (More...)
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