lean six sigma green belt training n.
Skip this Video
Loading SlideShow in 5 Seconds..
Lean Six Sigma Green Belt Training PowerPoint Presentation
Download Presentation
Lean Six Sigma Green Belt Training

Lean Six Sigma Green Belt Training

575 Views Download Presentation
Download Presentation

Lean Six Sigma Green Belt Training

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Lean Six Sigma Green Belt Training A

  2. UNIT 2 Measure

  3. 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. Ref Unit 2-1

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

  5. 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 Measure – Key Deliverables/Commonly Used Tools Key Deliverables: Commonly Used Tools: Ref Unit 2-2b

  6. Create Detailed Process Map Measure – Major Activities DEFINE MEASURE ANALYZE IMPROVE CONTROL Assess Financial Impact Revise Problem Statement Gather Initial Data Stratify Data Ref Unit 2-3a

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

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

  9. An oval is used to show the inputs to start the process, or to show the output at the end of the process. An arrow is used to show the direction or flow of process activities. 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. A rectangle or box with dashed lines is used to list clarifying information. 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 Common Flowchart Symbols Ref Unit 2-5

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

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

  12. Gather Initial Data Measure – Major Activities DEFINE MEASURE ANALYZE IMPROVE CONTROL Assess Financial Impact Create Detailed Process Map Revise Problem Statement Stratify Data Why do we need data? Where does the data come from? Ref Unit 2-10

  13. Outputs Inputs Products Products Suppliers Customers Process Services Services Outcome Metrics Collect Outcome Metric Data Is process acceptable? Ref Unit 2-11

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

  15. 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 Ref Unit 2-13

  16. Outputs Inputs Products Products Suppliers Customers Process Services Services Upstream Metrics Outcome Metrics Upstream Metrics Upstream Metrics are measures of performance within a process. Ref Unit 2-14

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

  18. Process Metrics and Targets Example • Operational Definitions: • On time means within 5 working days starting the day after the policy is received from agent. • Time to complete underwriting begins at receipt of policy from Sales, ends when underwriting approved Ref Unit 2-15b

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

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

  21. 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? Ref Unit 2-18a

  22. 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 Ref Unit 2-18b

  23. 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. Ref Unit 2-19

  24. Activity Analyze Types of Data Ref Unit 2-20

  25. 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) Ref Unit 2-21

  26. 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 Reflectscustomer 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 Operational Definitions Ref Unit 2-22

  27. Operational Definitions (cont’d.) 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 Ref Unit 2-23

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

  29. Characteristics of Useful Data • 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

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

  31. 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 Develop a Sampling Plan (cont’d.) Ref Unit 2-27

  32. Calculations and other information related to determining sample size is covered in BlackBelt training. Develop a Sampling Plan (cont’d.) 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 Ref Unit 2-28

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

  34. Checkout Line Delays Wendy May 19 Date Cashier Report Preparation Confirmation Checksheet Reason Frequency Comments Price check needed Completion Data Source: X files Planned date Planned duration Actual date Actualduration No cashier available Step Done? Notes Register out of tape Cust requestedchanges Project completed 6-12 6-26 N/A N/A Not enough money Client review &approval Forgot item Client personnelon vacation 6-17 7-6 5d 10 Wrong item Correct cashier error Manager assistance needed 6-30 7-21 13d 15d Final report, draft OK check Final report review Other 7 -12 7-28 12d 7d Source: X files Minor changesrequested Final report revisions 7-21 8-2 9d 5d Desktop publishing ofreport 7-28 7d 7-30 2d Final report submission Frequency Plot Checksheet Package Weight 16.0 16.1 16.2 16.3 16.4 16.5 16.6 16.7 16.8 Weight in ounces Checksheets Source: X files Source: X files Ref Unit 2-29b/30

  35. Concentration Diagram Ref Unit 2-33

  36. 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 Checksheets (cont’d.) Ref Unit 2-32

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

  38. Data Collection Plan Project ________________________ What questions do you want to answer? Data Operational Definition and Procedures What Measure type/ Data type Related conditionsto record2 How/where recorded (attach form) How measured1 Sampling notes What is your plan for starting data collection? (attach details if necessary) How will the data be displayed? (Sketch below) 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. Activity (cont’d.) Ref Unit 2-35

  39. Gather Initial Data Measure – Major Activities DEFINE MEASURE ANALYZE IMPROVE CONTROL Assess Financial Impact Create Detailed Process Map Revise Problem Statement Stratify Data Ref Unit 2-36a

  40. 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 Ref Unit 2-36b

  41. % of Policies Not Issued On Time 25% Good Good 20% 15% Not Issued on Time Not Issued on Time Source: X Files GAP 10% Target = <2% 5% % % 0% 1st Qtr. 1st Qtr. 2nd Qtr. 2nd Qtr. 3rd Qtr. 3rd Qtr. 4th Qtr. 4th Qtr. 1st Qtr. 1st Qtr. 2nd Qtr. 2nd Qtr. 3rd Qtr. 3rd Qtr. 4th Qtr. 4th Qtr. 1st Qtr. 1st Qtr. 2nd Qtr. 2nd Qtr. 2003 2004 2005 Period 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? Answer Questions with Data Ref Unit 2-37

  42. non-Medical Exam Policies not issued on time 200410-200502 100.00% 140 90.00% N=149 120 80.00% 70.00% 100 60.00% 80 50.00% 60 40.00% 30.00% 40 Source: X files 20.00% 20 10.00% 0 0.00% Missing Info. on Application Unable to contact agent with question Insufficient follow up Lack of Second Delayed by Large amount coverage System error premium requirements delivery Pareto Chart Ref Unit 2-38

  43. 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. Ref Unit 2-40

  44. Reasons Proposals Take Longer Than 3 Days To Present to Manager for Approval 80 80 100% n = 80 70 70 70 60 60 60 50 50 50 50% 40 40 40 # Late Proposals Sales & Marketing Dept. Jan – Jun, 2003 30 30 30 20 20 20 10 10 10 0% 0 0 0 Other RFP not assigned Not aware of deadline Waiting for price info. Waiting for service specs. Researching service info. Pareto Practice How else could this data be stratified? Ref Unit 2-41

  45. Activity Complete Pareto analysis with data provided Ref Unit 2-42a

  46. XYZ Loan Processing 10/23-27/01 48 100% 40 75% 30 Number of Defects 50% N = 48 20 25% 10 12 10 7 6 6 4 3 0 Other Approval Signature Calculation Not legible Missing info. Late submittal Source: Loan Dept. 10/23-27/99 S. Martinez Type of Error Activity – Answer 1 Ref Unit 2-42b

  47. XYZ Loan Processing - Cost of Defects 100% $3008 2500 N = $3008 75% 2000 Source: Loan Dept. 10/23-27/99 S. Martinez Co$t of Defects 1500 50% 1000 1158 25% 500 469 456 408 350 104 0 63 Other Not legible Approval Missing info. Signature Calculation Late submittal Extended Cost - Type of Defect Activity – Answer 2 Ref Unit 2-42c

  48. Multi-level Stratification Ref Unit 2-44

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

  50. Histogram/Frequency Chart Ref Unit 2-45b