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A Lean Six Sigma Green Belt Training. ING Business School UNIT 2 Measure UNIT 2 Measure.

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Presentation on theme: "A Lean Six Sigma Green Belt Training. ING Business School UNIT 2 Measure UNIT 2 Measure."— Presentation transcript:

1 A Lean Six Sigma Green Belt Training

2 ING Business School UNIT 2 Measure UNIT 2 Measure

3 ING Business School Ref Unit 2-1 Measure – Learning Objectives At the conclusion of this unit, you will be able to: Create detailed process map/flowchart. Develop a data collection plan to gather initial data. Stratify data to facilitate understanding. Revise the problem statement based on data. Assess financial impact of your project.

4 ING Business School Create Detailed Process Map DEFINEMEASUREANALYZEIMPROVECONTROL Gather Initial Data Stratify Data Revise Problem Statement Assess Financial Impact Overall objective: Narrow the improvement opportunity to a specific problem statement. Ref Unit 2-2a Measure – Major Activities

5 ING Business School Key Deliverables: Commonly Used Tools: Ref Unit 2-2b Measure – Key Deliverables/Commonly Used Tools Detailed process flowchart Upstream metrics/ Targets/Specification limits Data collection plan Operational Definitions Metric stratification Defect definitions Process sigma Revised problem statement Statement of cost/benefit Flowchart/Process maps Line graph/Run chart Data collection worksheet Checksheet Concentration diagram Pareto chart Histogram Control chart Cost/benefit analysis

6 ING Business School Create Detailed Process Map DEFINEMEASUREANALYZEIMPROVECONTROL Gather Initial Data Stratify Data Revise Problem Statement Assess Financial Impact Ref Unit 2-3a Measure – Major Activities

7 ING Business School Ref Unit 2-3b Process Mapping Benefits Provides a picture Promotes consistency Fosters teamwork Stimulates ownership Highlights inefficient and missing activities Gets everyone singing on the same page

8 ING Business School As-is vs. Should be “Swimlanes” Ref Unit 2-4 Functional Flowcharts Who is available Who has knowledge

9 ING Business School A An oval is used to show the inputs to start the process, or to show the output at the end of the process. A rectangle or box is used to show process activities. Each box should have only one arrow coming in, and one going out. Words in a box should begin with an “action word”, e.g., receives, sends, completes, etc. An arrow is used to show the direction or flow of process activities. A diamond is used to show where decisions occur in the process. Decisions have one arrow in and two arrows out (yes/no). A small circle with a letter or number identifies a break in the same page. A rectangle or box with dashed lines is used to list clarifying information. Ref Unit 2-5 Common Flowchart Symbols

10 ING Business School See Process Mapping Tips Ref Unit 2-6/7 Flowcharting Steps Identify and name the process Identify process boundaries Determine process level List process roles Identify activities for each role Review and validate

11 ING Business School Develop a detailed functional flowchart of your project’s process. Ref Unit 2-9 Activity

12 ING Business School DEFINEMEASUREANALYZEIMPROVECONTROL Create Detailed Process Map Stratify Data Revise Problem Statement Assess Financial Impact Gather Initial Data Why do we need data? Where does the data come from? Ref Unit 2-10 Measure – Major Activities

13 ING Business School Process SuppliersCustomers Products Services Products Services Inputs Outputs Outcome Metrics Is process acceptable? Ref Unit 2-11 Collect Outcome Metric Data

14 ING Business School Do you know the name of this tool? What does it tell us? Good Titles Data over time Good arrow Target info. Time on X axis Source info. Ref Unit 2-12 The Gap

15 ING Business School Ref Unit 2-13 Line Graph/Run Chart Helps identify cycles, shifts and trends in process performance Highlights gaps between process targets and actual performance Clarifies before and after changes in process performance Aids in predicting future performance

16 ING Business School Process SuppliersCustomers Products Services Products Services Inputs Outputs Upstream Metrics Outcome Metrics Upstream Metrics are measures of performance within a process. Ref Unit 2-14 Upstream Metrics

17 ING Business School Y = f(x) Ref Unit 2-15a Upstream Metrics Sources of Upstream Metrics Inputs from suppliers Outputs from sub-processes Handoffs from one employee or department to another Key decisions Inspection points (cont’d.)

18 ING Business School Critical Customer Requirement Service Characteristic Outcome Metric Target Upstream Metric Target “I want my policy issued quickly.” Turn Around Time % of policies not issued on time <2% not on time Time to complete underwriting <2 working days Operational Definitions: 1.On time means within 5 working days starting the day after the policy is received from agent. 2.Time to complete underwriting begins at receipt of policy from Sales, ends when underwriting approved Ref Unit 2-15b Process Metrics and Targets Example

19 ING Business School Send RFP Receive RFP Log RFP Assign RFP No Yes Prepare “No Quote” Letter Update Cust.. File Add Pricing Specs OK ? Price OK ? Price OK ? A No Yes Approve Proposal Approve Proposal Receive Response Yes O1 U1 No Log/Give to Mgr. Customer Sales Clerk Sales Engineer Marketing Rep Send RFP Want to Quote ? No Prepare Proposal A No Yes Approve Proposal Approve Proposal Yes No Send Response Sales/Marketing Manager Upstream Metric Outcome Metric Ref Unit 2-16 Process Metrics and Flowchart

20 ING Business School Create Line Graph for Outcome Metric & Define Upstream Metrics/Targets Ref Unit 2-17 Activity

21 ING Business School Ref Unit 2-18a Overview of Data Collection Information to be Covered What types of data will you need? How can you ensure the data is accurate? How much data is necessary? What tools are useful for data collection?

22 ING Business School Ref Unit 2-18b Planning for Data Collection Overall Approach Plan - Who, What, When, Where, and How the data will be collected (4Ws and 1H) Ensure - data integrity Analyze – compare first samples taken with what is needed Adjust - data collection plan as needed

23 ING Business School Ref Unit 2-19 Types of Data Continuous data: variables, measurable, e.g. time, distance, weight, money. Attribute data: discrete, counted; measures presence or absence of a characteristic, e.g. good/bad # of defects.

24 ING Business School Analyze Types of Data Ref Unit 2-20 Activity

25 ING Business School Ref Unit 2-21 Ensure Data Integrity Precise/Accurate – Data from the measurement method or device does not vary much from the actual value Repeatable – Repeated measurements of the same item or characteristic by the same person lead to the same result Reproducible – Two or more people measuring the same characteristic in the same way get the same result Stable over time – Data and measurements taken at different times by different people are done in the same way (the measurement system doesn’t change over time)

26 ING Business School Ref Unit 2-22 Operational Definitions Definition An operational definition is a precise description of how to get a consistent value for the characteristic you are trying to measure. Characteristics Specific Clear Measurable Reflects customer Perspective Givens Test and refine the definition after it is first developed Training is required to ensure that results from using the definition are consistent

27 ING Business School Ref Unit 2-23 Operational Definitions Defect – process output that is not acceptable to the customer; not within specification Defect Opportunity – A point where a CCR could be missed each time something moves through a process An opportunity is a place where a defect can reasonably occur The number of defect opportunities is related to the complexity of the process. The number of defect opportunities per unit must stay constant before and after DMAIC improvement (cont’d.)

28 ING Business School Create operational definitions for your Outcome & Upstream Metrics. Ref Unit 2-24 Activity

29 ING Business School Relates to the problem you’re studying – the data can be directly linked to the Preliminary Problem Statement Answers questions about current process performance – when is it occurring, who is involved, where is it occurring, what is happening, how is it happening Provides information about related conditions – a defect occurred on Thursday; on Thursday we were short-staffed; also on Thursday the system was down for 2 hours Cost effective – the value of the data collected is worth more than the cost of collecting the data How Much Data to Collect Ref Unit 2-25 Characteristics of Useful Data

30 ING Business School Population - “N” Usually unknown Sample – “n” Take a sample To make inferences about… Sampling is collecting some of the data from a process to make inferences about all of the data. Ref Unit 2-26 Develop a Sampling Plan

31 ING Business School Ref Unit 2-27 Develop a Sampling Plan Reliable Samples The data is representative of the population Every item has a known and usually equal chance of being included There are no systematic differences between the data you collect and the data you do not collect Unreliable Samples Samples are only collected when/where convenient The sample collection method has a pattern The process changes during data collection Faulty measurements Only a portion of people you need data from respond to your request for information (cont’d.)

32 ING Business School Ref Unit 2-28 Calculations and other information related to determining sample size is covered in BlackBelt training. Develop a Sampling Plan What does sample size depend upon? Desired sampling error – how precise you want to be (± 4%) Desired confidence level – how confident that true population rate falls between selected error rate (95%) Variation of the population – characteristics, make-up Size of the population – larger populations, larger sample (cont’d.)

33 ING Business School The use of tools in data analysis is critical – they help you visualize! Ref Unit 2-29a Tools for Collecting Data Gaps between process targets and actual performance Cycles and trends in process performance

34 ING Business School Source: X files Report Preparation Confirmation Checksheet Step Done? Completion Data Planned date Actual date Planned duration Project completed Client review & approval Final report, draft Final report review Final report revisions Desktop publishing of report Final report submission Actual duration 5d 13d 12d 9d 7d 2d 10 15d 7d 5d N/A Notes Cust requested changes Client personnel on vacation Minor changes requested Source: X files Correct cashier error OK check Checkout Line Delays Cashier Date ReasonFrequencyComments Price check needed No cashier available Register out of tape Not enough money Forgot item Wrong item Manager assistance needed Other Wendy May 19 Source: X files Frequency Plot Checksheet Package Weight Weight in ounces Source: X files Ref Unit 2-29b/30 Checksheets

35 ING Business School Ref Unit 2-33 Concentration Diagram

36 ING Business School Ref Unit 2-32 Checksheets Implementation Are all appropriate, high potential categories of data being considered? Is the right data being gathered? Does everyone understand how to fill out the checksheet? Has management clearance been given? Do the people being observed understand why the checksheet is being used? Interpretation Look for trends and patterns in the data Look for something unusual Other tools can be used with the Checksheet to help interpret the data, e.g., line graph, pareto chart, etc. Extract summary data by sub-totaling, or stratifying the data (cont’d.)

37 ING Business School Create or review the data collection plan for your project. Ref Unit 2-34 Activity

38 ING Business School Data Collection Plan Project ________________________ How measured 1 What questions do you want to answer? Data Operational Definition and Procedures WhatMeasure type/ Data type Related conditions to record 2 Sampling notes Notes 1) Be sure to test and monitor any measurement procedures/instruments. 2) “Related factors” are stratification factors or potential causes you want to monitor as you collect data. What is your plan for starting data collection? (attach details if necessary) How will the data be displayed? (Sketch below) How/where recorded (attach form) Ref Unit 2-35 Activity (cont’d.)

39 ING Business School Gather Initial Data DEFINEMEASUREANALYZEIMPROVECONTROL Create Detailed Process Map Stratify Data Revise Problem Statement Assess Financial Impact Ref Unit 2-36a Measure – Major Activities

40 ING Business School Ref Unit 2-36b What is Stratification? Stratification is classifying and separating data into related groups: Stratify Outcome Metric data sources of the gap Goal of stratification is a search for significance Use stratification to organize resources Stratification helps identify the value of the improvement

41 ING Business School Answer Questions with Data Ref Unit 2-37 Stratify By Asking Questions When did the data spike, then go down? What are reasons for the data to cycle? Is it possible to track where the policies that took the longest were written? Who wrote the policies that were not issued on time? How did it happen?

42 ING Business School non-Medical Exam Policies not issued on time Missing Info. on Application Unable to contact agent with question Insufficient follow up Lack of premium Second requirements Delayed by delivery Large amount coverage System error 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% % N=149 Source: X files Ref Unit 2-38 Pareto Chart

43 ING Business School Ref Unit 2-40 Interpreting Pareto Chart Isolate the significant few from the trivial many – example: 80% in first bar. The first category (bar) does not have to contain 80% of the total under analysis. A flat or somewhat level pareto chart usually means examine the data further. Stratify the data in different ways (frequency, severity, impact) in order to identify the most significant category. Ensure that each category has the same opportunity to contribute.

44 ING Business School How else could this data be stratified? Ref Unit 2-41 Pareto Practice

45 ING Business School Complete Pareto analysis with data provided Ref Unit 2-42a Activity

46 ING Business School XYZ Loan Processing N = Type of Error 10/23-27/01 Number of Defects Not legible Signature Calculation Late submittal Approval Missing info. Other 100% 50% 25% 75% Source: Loan Dept. 10/23-27/99 S. Martinez Ref Unit 2-42b Activity – Answer 1

47 ING Business School Source: Loan Dept. 10/23-27/99 S. Martinez XYZ Loan Processing - Cost of Defects Extended Cost - Type of Defect Not legible Approval Late submittal Signature Calculation Other Missing info. $ N = $ Co$t of Defects % 50% 25% 75% Ref Unit 2-42c Activity – Answer 2

48 ING Business School Ref Unit 2-44 Multi-level Stratification

49 ING Business School Avg. Time Request to Patient Pickup Avg. Request to Pickup Time (in minutes) at Holy Cross Hosp. Taken by Transporter Dispatcher Jan-Feb, 2004 Ref Unit 2-45a Histogram

50 ING Business School Claims Processing (Hours) FrequencyTotal 1:00-2:30 3 2:31-4: :01-5: :31-7: :01-8:30 6 8:31-10: :01-11:30 1 TOTAL 50 Ref Unit 2-45b Histogram/Frequency Chart

51 ING Business School Ref Unit 2-47 Histogram Interpretation Focus on the center of the data distribution Look at the data spread Consider the typical histogram shapes

52 ING Business School Nothing unusual. Try to find causes of variation (data spread). Determine if data is centered properly. Stratify the data to avoid two populations of data; create two histograms. Recalculate and draw the histogram again. Investigate “outliers”. Determine why the data is not centered near the average. Determine why part of the data is missing. Check your calculations. Collect more data if necessary. Normal Bi-modal Comb Skewed Precipice Ref Unit 2-48/49 Histogram Interpretation (cont’d.)

53 ING Business School Would you change anything? Ref Unit 2-50 Histogram Interpretation (cont’d.)

54 ING Business School How would you proceed? Ref Unit 2-51 Histogram Interpretation (cont’d.)

55 ING Business School Defects Too earlyToo late Delivery Time Reduce Variation Delivery Time Too early Too late Target Spread of variation is too wide compared to customer specifications Spread of variation is narrow compared to customer specifications Less Variation is Desired Expect Variation in Everything Ref Unit 2-52 Understand Data Variation

56 ING Business School Mean: The sum of the data set values, divided by the number of values in the data set. Measure Definition:Example: (12,14,16,17,14,11,18,17,24,26,23,27,14,14) Ordered Data = (11,12,14,14,14,14,16,17,17,18,23,24,26,27) Mode = 14 (11,12,14,14,14,14,16,17,17,18,23,24,26,27) Median = ( )/2 = 33/2 Median = 16.5 Mode: The most frequently occurring value in the data set Median: The value that falls exactly in the middle of the ordered data set, half of the numbers fall above, and half below. Ref Unit 2-53 Measures of Central Tendency

57 ING Business School The data below are a sample of days of absence over a year in a department. Determine the mean, median, and mode of this sample: 1, 2, 3, 3, 4, 5, 7, 9, 10, 11, 120 Mode = Median = Mean = If this data set were handed to you to analyze, what might be your reaction? Ref Unit 2-54 Activity – Calculating Central Tendency

58 ING Business School Measure / DefinitionExample Range - The difference between the highest and lowest (greatest and smallest) values. (12,14,16,17,14,11,18,17, 24, 26, 23, 27, 14, 14) Ordered Data = (11,12,14,14,14,14,16,17,17,18, 23, 24, 26, 27) Range: (27 – 11) = ________ Standard Deviation (sd) – The calculated variation between each data point in the set and the mean. (3,5,7,9,11,12,4,5,13,1,16) Ordered Data = (1,3,4,5,5,7,9,11,12,13,16) Xbar = ________ s = 4.73 Note: Standard deviation calculations are covered in BlackBelt training Ref Unit 2-55 Measures of Dispersion

59 ING Business School 68.26% of all data should fall within a distance of ±1sd from the mean 95.45% within a distance of ±2sd from the mean 99.73% with a distance of ±3sd from the mean Ref Unit 2-56 The Empirical Rule

60 ING Business School 99.73% confidence level : Xbar = 5 s = 1 Upper range limit = 5+(3x1) or 8 Lower range limit = 5 - (3x1) or % confidence level: Xbar = 5 s = 1 Upper range limit = 5+(2x1) or 7 Lower range limit = 5 - (2x1) or 3 Ref Unit 2-57 Activity – Predicting Process Output Assuming the average number of days to process a new insurance policy is 5, and the standard deviation is 1. How many days can you expect it to take to process a new insurance policy? In other words, within what range would you expect to find 99.73% of the data?

61 ING Business School Special Cause: something different happening at a certain time or place Common Cause: always present to some degree in the process Ref Unit 2-58 Causes of Variation

62 ING Business School UCL - Upper Control Limit Process Metric JASONDJFMAMJJASONDJFM LCL - Lower Control LimitCenter Line, mean, or Xbar 10 Control limits - calculated from data = ± 3 sd Data points plotted over time Data patterns are formed by two types of variation… Ref Unit 2-59 Control Charts

63 ING Business School Ref Unit 2-60 Control Charts Common Causes Inherent in any system Process with only common causes: stable, predictable, in control Special Causes Special, specific, assignable causes. Process with common causes plus factors that induce variation above that inherent to the system: unstable, unpredictable, not in statistical control 6 Signals that special causes are present (cont’d.)

64 ING Business School Ref Unit 2-61a Control Charts 1.Point Outside Control Limit Any point on or outside the limits is abnormal and requires investigation 2.Run Seven points continually on one side of the center line is abnormal, Also, 10 out of 11, 12 out of 14 or 16 out of 20 points on one side of the center line is abnormal 3.Trending Seven points in a continuous upward or downward direction is abnormal (cont’d.) 6 Signals of Special Cause

65 ING Business School Ref Unit 2-61b Control Charts 4.Approaching CL (hugging) Most points within center line and 1.5σ* indicates mixing of data from different populations, making the control limits too wide and stratification necessary 5.Cycling Any repeated up and down trend is abnormal and requires investigation 6.Approaching Control Limits 2 of 3 points outside 2σ (σ= standard deviation) line is abnormal 6 Signals of Special Cause (cont’d.)

66 ING Business School Notice that the control limits are more narrow after variation is reduced. Can you explain why? Goal of Process Improvement Ref Unit 2-62 Additional information related to control charts is covered in BlackBelt training. Control Charts (cont’d.)

67 ING Business School Ref Unit 2-63 Control Limits, Specifications & Targets Control limits (VOP) Calculated from the data Describe what the process is capable of achieving Specification limits (VOC) Set by the customer, management, or other requirements Describe what you want a process to achieve Target lines (VOB) Based on objectives external to the process Not statistically calculated (not shown)

68 ING Business School LSL USL Not In Control ( Not Stable) In Control (Stable) Not meeting Customer Specifications (Not Capable) Meeting Customer Specifications (Capable) Customer Specification Control Limit LSL USL LSL USL LSL USL Voice of the Process Voice of the Customer Ref Unit 2-64 Possible Process Conditions

69 ING Business School Stratify Upstream Data to Search for Significant Contributors to the GAP in the Outcome Metric Ref Unit 2-65 Activity

70 ING Business School DEFINEMEASUREANALYZEIMPROVECONTROL Create Detailed Process Map Gather Initial Data Stratify Data Revise Problem Statement Assess Financial Impact Ref Unit 2-66a Measure – Major Activities

71 ING Business School Data you have collected and stratified so far focuses your project on the most significant reasons for the performance gap. Ref Unit 2-66b Revise Problem Statement

72 ING Business School DO Ref Unit 2-67a Revise Problem Statement Make sure problem is of size/scope that is solvable State the problem in quantitative measurable terms (cont’d.)

73 ING Business School DO Not Ref Unit 2-67b Revise Problem Statement State a preconceived idea of what the cause(s) may be Imply a particular solution Affix blame on a person or group (cont’d.)

74 ING Business School Preliminary Problem Statement Revised Problem Statements are more Focused New products miss target launch dates 45% of the time. Nine out of the last ten new bond funds missed target launch dates by an more than three months. 20% of late payments come from product XYZ customers 85% of product XYZ customers in the U.S. account for 75% of late payments. Storage personnel are involved in 75% of back strain cases, Storage personnel were lifting something when 92% of the back strain cases occurred. Ref Unit 2-68 Narrow the Focus Revise Problem Statement (cont’d.)

75 ING Business School Identify good problem statements Ref Unit 2-69 Activity

76 ING Business School Ref Unit 2-70a Calculate Process Sigma What is Process Sigma? A reflection of the variation in your process Based on the “Yield” - how much of your process output is within specification, e.g., acceptable to the customer Requires operational definitions for both defects and defect opportunities Calculated for the outcome metric(s) Related to the revised problem statement Determined using a table

77 ING Business School Ref Unit 2-70b Calculate Process Sigma 1.Compute First Time Right yield (see Lean Six Sigma Overview, page 16) % YIELD = 1 – (defects / total defect opportunities) X Look up % YIELD in a Process Sigma Table (Appendix) Example: Assume 100 units, 5 opportunities, 7 defects % YIELD = (1 – 7 / (5 x 100)) X 100 % YIELD = (1 – (7 / 500) X 100 % YIELD = (1 –.014) X 100 % YIELD = 98.6%, and 3.7 Process Sigma

78 ING Business School Ref Unit 2-71 Calculate Process Sigma Process Sigma Target If process sigma is greater than 3.0, set a 2x defect improvement goal e.g., 1,000 DPMO to 500 DPMO. If process sigma is less than 3.0, set a 10x defect improvement goal e.g., 1,000 DPMO to 100 DPMO.

79 ING Business School Develop a Revised Problem Statement, Calculate Process Sigma, Establish an Improvement Target Ref Unit 2-72 Activity

80 ING Business School DEFINEMEASUREANALYZEIMPROVECONTROL Create Detailed Process Map Gather Initial Data Stratify Data Revise Problem Statement Assess Financial Impact Ref Unit 2-73 Measure – Major Activities

81 ING Business School Ref Unit 2-74 Cost of Poor Quality (COPQ) COPQ is the sum of costs to maintain or satisfy customer requirements after a defect has occurred. Understanding process COPQ will help identify the financial impact of the project. Get help, if needed.

82 ING Business School Conformance (Value-Adding)  Appraisal costs (necessary, value adding)  Prevention costs Non-conformance (Non-Value- Adding)  Appraisal costs (not needed, non-value- adding)  Internal failure costs  External failure costs Ref Unit 2-75 Types of Costs Cost of Poor Quality (cont’d.)

83 ING Business School Ref Unit 2-76 Cost of Poor Quality Appraisal Costs - May be Non-Value- Adding or Value-Adding Maintenance/calibration of inspection/test equipment or procedures Materials/supplies used in inspection/test Incoming inspection/test In-process inspection/test Final inspection/test Product/service audits

84 ING Business School InternalExternal Inspections or tests Rework Avoidable process losses Down time/Delays Sorting Failure analysis Repair Waste Complaint handling/adjustment Returned items Failure analysis Warranties and Allowances Lost business Lost sales Lost customers Waste Ref Unit 2-77 Failure Costs – Non-Value Add Cost of Poor Quality (cont’d.)

85 ING Business School Ref Unit 2-78 Cost of Poor Quality Prevention Costs – Value Adding New product review Process quality planning Process control Quality system audits Training Supplier review and qualification Fool proofing so defects cannot be made, e.g., automatic seat-belt restraints (cont’d.)

86 ING Business School Ref Unit 2-79 Cost of Poor Quality Project Benefits See calculations from Define step. Add newly identified benefits. See list in workbook. (cont’d.)

87 ING Business School Estimate of Project Annual Financial Impact Benefit total:(+) COPQ total: Conformance (forecast of value-adding costs) (-) Non-conformance (forecast of non-value- adding cost reductions) (+) Project total: Ref Unit 2-80 Cost of Poor Quality Financial Impact Summary Estimate annual impact Indicate if increasing stream of benefits Save worksheets (cont’d.)

88 ING Business School Ref Unit 2-81 What costs are Involved in Your Project? Activity

89 ING Business School Ref Unit 2-82 Measure Step Tollgate Questions A.Does the process map clearly convey responsibility for each activity? B.What is the plan for data collection? C.How has the data been documented? D.How was the data stratified to identify any significant reasons for the preliminary problem statement? E.What is the revised problem statement? F.What is the forecast financial impact of the project?

90 ING Business School Ref Unit 2-83a Unit Summary Having completed this unit, here are some questions you should be able to answer: 1.What are two types of data? 2.List four sources of data to be addressed in a data collection plan. 3.Name three tools that can be used to collect and stratify data? 4.What should not be included in a revised problem statement? What should? 5.What are three types of costs to be addressed in a COPQ assessment? 6.How is a control chart different from a run chart?

91 ING Business School Calculate Performance Stratify Data Frequency Plots Run Chart Plot Outcome Defect Data Develop Data Collection Plan Data Collection Plan Project ________________________ What questions do you want to answer? Data Operational Definition and Procedures What Measure type/ Data type How Measured 1 Related conditions to record 2 Sampling notes How/where recorded (attach form) Create Detailed Process Map F 1 F 3 F 4 F 2 Assess Financial Impact (COPQ) Revise Problem Statement Control Chart Check Sheet Collect Upstream Data Overall objective: Narrow the improvement opportunity to a specific problem statement. DPMO_____ Yield _____ Sigma _____ Goal _____ Understand Variation Pareto Chart To Analyze Step From Define Step Ref Unit 2-83b Project Components: MEASURE

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