about me

contact me

Steven Bonacorsi

Lean Six Sigma Master ...

President

Bonacorsi Consulting

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...

>> read more about me

Analyze Phase Lean Six Sigma Template

Tags

Steven, Bonacorsi, Analyze, Phase, Lean, Six, Sigma, Tollgate, Template

Description

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.

You must be logged in to download this document

be first to review

Analyze Analyze Improve Improve Define Define Measure Measure Control Control LEAN SIX SIGMA LEAN SIX SIGMA Lean Six Sigma Program Name Lean Six Sigma Program Name < Last Name, First Name >Wave No: Review Date: Analyze Analyze Improve Improve Define Define Measure Measure Control Control LEAN SIX SIGMA LEAN SIX SIGMA Lean Six Sigma Program Name Lean Six Sigma Program NameBonacorsi Consulting 3 Improve ImproveAnalyze Phase Road Map• 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 • 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 GateToolsActivities Control Control Measure Measure Define Define Analyze Analyze Analyze AnalyzeBonacorsi Consulting 4 Measure Overview􀂋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 projectProcess CapabilityTools UsedGraphical AnalysisRoot Cause /Quick Win􀂋Root cause:􀂄Quick Win #1􀂋Root cause:􀂄Quick Win #2􀂋Root cause:􀂄Quick Win #3ObservationIndividual Value24421719016313610982552814035302520_X=29.13UCL=37.70LCL=20.56ObservationMoving Range244217190163136109825528110.07.55.02.50.0__MR=3.22UCL=10.53LCL=0I-MR Chart of Delivery Time􀂋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 Analyze AnalyzeBonacorsi Consulting 5 Graphical Analysis SummaryData is Continuous: ?? Data Points Collected Between XX/XX/XX and XX/XX/XXNormality Central Tendency VariationNormal Average Std. Dev (long term)Non-Normal Median or Q1 or Q3 Span (1/99) or Stability Factor (Q1/Q3)InvestigationStatistical /Graphical AnalysisObservations/ConclusionHistogram Normality TestWhat is the central tendency of the Project Y data?Mean, Median, or Quartile Values What is the spread of the Project Y data?Standard Deviation, Span, or Stability Factor Is the data stable over time?Run Chart Include any other findings regarding the data hereWhat is the shape of the Project Y data? Is the Y data normally distributed? What is the normality test p-value?Describe any other observations about the Project Y data Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 6 Sources Of Resistance Definition Causes Of ResistanceRatingExamplesTechnical-Political-Cultural (TPC) Analysis TechnicalPoliticalCulturalTPC AnalysisEnter Key Slide Take Away (Key Point) Here Analyze AnalyzeBonacorsi Consulting 7 Sources of VariationNVADefectOverproductionTransportationWaitingInventoryMotion_{Area 1Sub area 1Area 1Sub area 1ProcessingArea 1Sub area 1Area 1Sub area 1Area 1Sub area 1Enter Key Slide Take Away (Key Point) HereWas the Action workout performed #1?Was the Action workout performed #2?< Insert your variation percentage as shown in pie chart >5%5%5%42%11%32%ManMachineMethodMeasurementMother NatureMachine Analyze AnalyzeBonacorsi Consulting 8 Cause and Effect Matrix Analyze AnalyzeSpeed to Reach DecisionDecision Meets ReqCooperation, Clarity, AccuracyFeedback Seats AvailableSchedule OptionsBudget for OptionsFunding Source IdentifiedProcess Outputs1076710957Importance RatingItemProcess StepProcess InputsTotal16Develop Options including price & scheduleCustomer schedule & requirements9919999345918Approve optionsProper decision makers999931939215Inventory Search of known Vacant SpaceDatabase, tribal knowledge 999326114Interview Customer to Understand FormForm3199921717Brief customer on optionsoptions, costs, schedule options, funding vehicle993332168Supervisor Approval9311187Peer Review Approval9311111Fill out Forms9310812Accept Form33513Create Spreadsheet3304Dept Approval3305Approval Mgr 13306Approval Mgr 23301Identify Need32113Assign to Team3212Mark Up Floor Plan09Notification019Forms to requestor and Log in issue019Prepare brief0Correlation of Input to OutputHigher score =Importance Rating ScoreBlank = no correlation1 = remote correlation3 = moderate correlation9 = strong correlation To what extent does variability in these process steps/inputs impact variability across these outputs ?Enter Key Slide Take Away (Key Point) HereWas the rating of importance done by Kano analysis?Were all the process steps identified? What is the % of quick hits causing the problem? Bonacorsi Consulting 9 Run Charts Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereThere is a nonon-random influence acting upon this process. There is no Oscillation Median = 38When the points are connected with a line, a run ends when the line crosses the medianA run, in this case, is one or more consecutive points on the same side of the medianThere is a non-random influence acting upon this process that is creating clustering There is a nonon-random influence acting upon this process. There is no trend 1 Run about the Median, can you count the other 8?Longest Run about the medianThere medianBonacorsi Consulting 10 SouthNorthEastOthers100 50 15 658.529.2 8.8 3.5 58.587.796.5100.0050100150020406080100DefectCountPercentCum %PercentCountPareto Plot Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 11 Scatter Plot Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereAverage Expenses decrease as Sales IncreaseBonacorsi Consulting 12 Linear Regression􀂋95% confident that 94.1% of the variation in “Wait Time”is from the “Qty of Deliveries”DeliveriesWait Time3530252015105550454035S1.11885R-Sq94.1%R-Sq(adj)93.9%Fitted Line PlotWait Time = 32.05 + 0.5825 Deliveries Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 13 50403020100Improve DataDotplot of Improve Data(with Ho and 95% t-confidence interval for the mean)[]X_HoOne-Sample T-Test and Dot PlotWe Are 95% Confident The Improve Mean Is Not Statistically DifferentOne-Sample T: Improve DataTest of mu = 30 vs mu not = 30Variable N Mean StDev SE MeanImprove Data 30 28.10 12.45 2.27Variable 95.0% CI T PImprove Data (23.45, 32.75) -0.84 0.410This 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.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).Hypothesis Test: Is the Improve data set mean different from the Target Mean mean of 30 minutes? Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 14 Test for Equal Variance15010050095% Confidence Intervals for SigmasAntennaPayroll706050403020100Boxplots of Raw DataTotal TimeP-Value : 0.000Test Statistic: 21.054Levene's TestP-Value : 0.001Test Statistic: 0.108F-TestFactor LevelsPayrollAntennaTest for Equal Variances for Total TimeThe spread of the data is statistical greater for completing the payroll form than the Antenna time tracking. Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereTest for Equal Variance Confirms Payroll Input Type Cycle Time is SignificantBonacorsi Consulting 15 No PartPart050100150Part/No PartNet Hours Call OpenAnalysis of Variance for Net HourSource DF SS MS F PPart/No 1 7421 7421 8.65 0.004Error 69 59194 858Total 70 66615Individual 95% CI's For MeanLevel N Mean StDev --+---------+---------+---------+----No Part 27 21.99 19.95 (--------*---------) Part 44 43.05 33.70 (------*------) --+---------+---------+---------+----Pooled StDev = 29.29 12 24 36 48One Way ANOVA􀂋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.Boxplot: Part/No Part Impact on Ticket Cycle Time􀂋Because the p-value <= 0.05, we can be confident that calls requiring parts dohave an impact on the ticket cycle time. Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 16 BeforeAfter403020100SubgroupDefectsDotplots of Defects by SubgroupMood’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.Dot Plot: Part/No Part Impact on Ticket Cycle Time Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereChi-Square = 19.14 DF = 2 Mood’s Median TestP = 0.000 Individual 95.0% Confidence Interval’sMonth N<= N> Median Q3-Q1 ------+---------+---------+---------+10 88 132 8.43 12.15 (--------+-------)11 123 121 6.57 10.52 (------+------)12 111 68 4.77 7.10 (-----+------)------+---------+---------+---------+Overall Median 6.63 4.8 6.4 8.0 9.6Because the p-value <= 0.05, we can be confident that calls requiring parts do have an impact on the ticket cycle time.Bonacorsi Consulting 17 Statistical Testing for Discrete DataBecause 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 processedThis 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) Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereChi-Square TestExpected counts (calculated by Minitab) are printed below observed countsErrors Correct Total1 33 60 9340.46 52.542 27 67 9440.90 53.103 132 114 246107.03 138.974 32 132 16471.35 92.655 168 136 304132.26 171.74Total 392 509 901Chi-Sq = 1.376 + 1.060 +4.722 + 3.637 +5.827 + 4.487 +21.703 + 16.714 +9.657 + 7.437 = 76.620DF = 4, P-Value = 0.000Bonacorsi Consulting 18 Process Bottleneck Identification & Workload BalancingValue Add Analysis -Current State0102030405060708012345678910Task #Task Time (seconds)CVA TimeBVA TimeNVA TimeTakt Time = 55 -------Enter Key Slide Take Away (Key Point) Here􀂋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 constraintNet Process Time AvailableNumber of Units to ProcessTakt Time = Analyze AnalyzeBonacorsi Consulting 19 Hypothesis Test SummaryHypothesis Test (ANOVA, 1 or 2 sample t -test, Chi Squared, Regression, Test of Equal Variance, etc)Factor (x) Testedp ValueObservations/ConclusionExample: ANOVALocation0.030Significant factor -1 hour driving time from DC to Baltimore office causes ticket cycle time to generally be longer for the Baltimore siteExample: ANOVAPart vs. No Part0.004Significant factor -on average, calls requiring parts have double the cycle time (22 vs 43 hours)Example: Chi SquaredDepartment0.000Significant factor -Department 4 has digitized addition of customer info to ticket and less human intervention, resulting in fewer errorsExample: ParetoRegionn/aSouth region accounted for 59% of the defects due to their manual process and distance from the parts warehouseDescribe any other observations about the root cause (x) data Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereWas the hypothesis roadmap followed?What was the power and Sample Size? What are α and β risks?Bonacorsi Consulting 20 Control /Impact Analysis Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereHigh ImpactMedium ImpactLow ImpactIn Our Control􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?In Our Influence􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?Out of Our Control􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?􀂋?Does the X have a high, medium, or low impact on the project Y?Does the X in he teams control, influence, or out of their control?Bonacorsi Consulting 21 In/Out of FrameCreating a visual depiction of what elements of the project are in the scope (frame) and out of the scopeVital X #1Vital X #2Vital X #9Vital X #8Vital X #7Vital X #6Vital X #5Vital X #4Vital X #3No ControlControlInfluence Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 22 Systems & Structures AssessmentHow should we use or modify to support "____" vision and objectives12121212121212Communication Organization Design Information Systems Resource Allocation System or Structure Staffing Training & Development Measurements & Reward Enter Key Slide Take Away (Key Point) Here Analyze AnalyzeBonacorsi Consulting 23 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􀂋OtherEnter Key Slide Take Away (Key Point) Here Analyze AnalyzeBonacorsi Consulting 24 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 opportunitiesEnter Key Slide Take Away (Key Point) HereAnnual EstimateReplicated EstimateRevenue Enhancement•Type 1: ?•Type 2: ?•Type 3: ?•Type 1: ?•Type 2: ?•Type 3: ?Expenses Reduction•Type 1: ?•Type 2: ?•Type 3: ?•Type 1: ?•Type 2: ?•Type 3: ?Loss Reduction•Type 1: ?•Type 2: ?•Type 3: ?•Type 1: ?•Type 2: ?•Type 3: ?Cost Avoidance•Type 1: ?•Type 2: ?•Type 3: ?•Type 1: ?•Type 2: ?•Type 3: ?Total Savings•Type 1: ?•Type 2: ?•Type 3: ?•Type 1: ?•Type 2: ?•Type 3: ? Analyze AnalyzeBonacorsi Consulting 25 Business Impact Details􀂋Type 1: Describe the chain of causality that shows how you determinedthe Type 1 savings. (tell the story with cause–effectrelationships, on how the proposed change should create the desired financial result (savings) in your project )􀂋Show thefinancial 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)􀂋Type 2: Describe the chain of causality that shows how you determined the Type 2 savings. (tell the story with cause–effectrelationships, on how the proposed change should create the desired financial result (savings) in your project )􀂋Showthe 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 3Business 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 Analyze AnalyzeBonacorsi Consulting 26 Current Status􀂋Key actions completed􀂋Issues􀂋Lessons learned􀂋Communications, team building, organizational activitiesW/E:DueRevised DueFor deliverables due thru:Deliverable/Action WhoDueRevised DueComments/ResolutionNeed HelpIssue/RiskWhoDueRevised DueRecommended ActionNeed HelpDeliverables/Tasks Completed last weekCommentsActions Scheduled for next 2 WeeksCurrent Issues and RisksLean Six Sigma Project Status and PlanningUpcoming Deliverables/Tasks -2 weeks outCommentsEnter Key Slide Take Away (Key Point) Here Analyze AnalyzeBonacorsi Consulting 27 Next Steps􀂋Key actions􀂋Planned Lean Six Sigma Tool use􀂋Questions to answer􀂋Barrier/risk mitigation activitiesLast Revised:No.Description/RecommendationStatus Open/Closed/HoldDue DateRevised Due DateRespComments /Resolution12345678910Lean Six Sigma Project Issue LogEnter Key Slide Take Away (Key Point) Here Analyze AnalyzeBonacorsi Consulting 28 Analyze Tollgate Checklist􀂉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 performanceto help stratify the problem, understand reasons for variation in the process, and generate hypothesis as to the rootcauses of the current process performance?􀂉Has an evaluation been done to determine whether the problem canbe solved without a fundamental ‘white paper’recreation of the process? Has the decision been confirmed withthe 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? Tollgate Review Tollgate ReviewStopStopHas the team identified the key factors (critical X’s) that have the biggest impact on process performance? Have they validated the root causes? Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 29 Sign Off• I concur that the Analyze phase was successfully completed on MM/DD/YYYY• I concur the project is ready to proceed to next phase: ImproveEnter Name Here Deployment ChampionEnter Name Here Financial RepresentativeEnter Name Here Green Belt/Black BeltEnter Name Here Master Black BeltEnter Name Here Sponsor /Process Owner Analyze AnalyzeEnter Key Slide Take Away (Key Point) HereBonacorsi Consulting 30 Bonacorsi ConsultingSteven 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. 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.

Public Domain

views:917
downloads:216
rating:3(1)
reviews:0
posted:11/9/2007
language:English}

Analyze Phase Lean Six Sigma Template

Define Phase Lean Six Sigma Template

Control Phase Lean Six Sigma Template

Improve Phase Lean Six Sigma Template

Measure Phase Lean Six Sigma Template

Lean Six Sigma DMAIC Tollgate Checklists

Lean Six Sigma Executive Overview Template

Lean Six Sigma DMAIC Roadmap

What is Six Sigma

Six Sigma Template

Lean Six Sigma Suggestion Sheet

SWOT Analysis Template

Histograms

Affinity Diagrams

Scatter Diagrams

Run Charts

Quality Function Deployment (QFD)

Prioritization Matrices

SWOT Analysis The Basics

What is SWOT Analysis

SWOT Analysis Template

SWOT Analysis Questions

SWOT Analysis Operational Definitions

SWOT Analysis for Sales and Marketing

SWOT Analysis Examples

SWOT Analysis - Focusing On Your Organization