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Six Sigma Introduction Dzw
Six Sigma Introduction Dzw
Six Sigma Introduction Dzw
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Six Sigma Introduction Dzw

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First steps in Six Sigma

First steps in Six Sigma

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  • 1. Basic principles of Six Sigma First steps in business excellence
  • 2. DMAIC in 15 StepsDefine1. Select Project CTQ’s2. Create Project Charter3. Develop High Level ProcessMeasure DEFINE4. Identify Project Output Metric5. Develop Data Collection Plan6. Establish Process Baseline CONTROL MEASUREAnalyze7. Identify Root Causes8. Validate Root Causes & Determine Vital Few9. Quantify the OpportunityImprove IMPROVE ANALYZE10. Identify Solution11. Refine and Test solution12. Cost Benefit CalculationControl13. Implement Process Control14. Prepare Roll-Out Solution15. Project ClosureSix Sigma Overview Page 2
  • 3. Introduction (1) Truly managing a business is about every employee having the mindset andWhat is Process Management? tools to manage their work…(processes). Process management provides the framework to ensure that key processes are monitored and improvedProjects alone do not drive six sigma - for this we need the mindset and throughout the business.techniques of process management.Virtually everything we do is a process, from the activities we do at our workto brushing our teeth.A process is defined as a collection of activities that takes one or more kindsof input and creates output that is of value to the customer.To get a common understanding of how activities are done, it is important tomap these activities as part of an entire process.e.g.: START ENDSix Sigma Overview Page 3
  • 4. Introduction (2)What is Six Sigma?Six Sigma…¦ Is a management philosophy which encourages the business to look at their processes as seen and felt by the customer. By involving everyone, Six Sigma leads to greater collaboration among employees as they understand their roles and responsibilities in the big process picture and their relationship to customers. Six Sigma requires everyone to focus on processes and customers so that it is no longer the interest of just one or two departments but works to the advantage of everyone. Six Sigma requires a strong customer focus which in turn encourages process- thinking by everyone, not just departments¦ Is a data-driven methodology that provides businesses with the tools to improve the capability of their business processes. This increase in performance and decrease in process variation leads to defect reduction and vast improvement in profits, employee moral, quality of product and customer satisfaction¦ Refers to a goal of reducing defects to near zero. In statistical terms, the Greek letter Sigma is used to measure the variability in any process and represents the standard deviation of a populationSix Sigma Overview Page 4
  • 5. Introduction (3)What is Six Sigma?Six Sigma… For instance, three customers order books online and the company promises to deliver within 5 days. The first order arrives in 2 days, the second order arrives in 3 days and the third customer receives the books in 10 days. On average the process delivers on target, however the customer feels the variation (of 10 days).¦ The aim of Six Sigma is to reduce the variation in order to achieve small standard deviations so that almost all of your products or services meet or exceed customer expectations¦ Measures a company’s performance level by the Sigma level of their business processes. A performance level of Six Sigma equates to 3.4 defects per million opportunities. A defect is defined as anything that does not meet customer requirementsSix Sigma Overview Page 5
  • 6. Variation ExerciseIn your table teams, take a moment to come up with a list ofprocesses that have significant variation, where you are thecustomer. For instance, mobile phone coverage, publictransportation, pizza delivery time etc.Identify the two processes that seem to have the most variation.As a customer of these processes, answer the following questions: How do you react to the variation you experience?What impacts you more – the average process performance or yourindividual experience?Six Sigma Overview Page 6
  • 7. Six Sigma Is…¦ An extremely disciplined process What would this look like in daily life?¦ By measuring how many "defects" you have in a process, you can systematically figure out how to eliminate them Example 1s 2s 3s 4s 6s¦ Get as close to "zero defects" as possible Pieces of lost mail¦ Sigma Performance Levels per year (1,600 per 1,106 493 107 10 <1 year) Sigma Defects per Million Incorrect business Yield orders (250,000 a 172,924 77,135 16,694 1,553 0.9 Level Opportunities (DPMO) year) 1 690,000 31% Calls each day which 2 308,537 69,2% exceed the two 2,654 1,185 275 24 3/year minute on-hold time 3 66,807 93,32% (80,000 a month) 4 6,210 99,379% Wrong drug prescriptions each 13,800,000 6,160,000 1,336,000 124,200 68 5 230 99,977% year (20,000,000 a year) 6 3,4 99,99966% No electricity per 21 days 10 days 2 days 5 hours 1/34 month yearsSix Sigma Overview Page 7
  • 8. What Are The Key Elements Of Six Sigma? The Customer ? Delighting Customers ? Customers are the center of our universe: they define quality! The Process ? Outside-In Thinking ? Quality requires you to look at your business from the customer´s perspective, not yours (“Outside-In”) ? With this knowledge you can identify where you can add significant value or improvement from their perspective (CTQ´s) The Employee ? Leadership Commitment ? People create results. Essential to our quality approach is involving all associates. Our Company is 100% committed to providing opportunities and incentives for employees to focus their talents and energies on satisfying customers -and ALL employeesSix Sigma Overview Page 8
  • 9. Why Six Sigma? Encourage a process management mindset beginning and ending with the customer Meet customer expectations for higher quality Provide a competitive differentiation in the market Build greater pride and satisfaction in the team Drive other key goals like productivity and growth Reduce costsWhy now… Globalization and instant access to information, products and services have changed the way customers conduct business Todays competitive environment leaves no room for error We must delight our customers and relentlessly look for new ways to exceed their expectations The average percentage of a big company gross revenues that were spent due to poor quality on checking, correcting mistakes and rework etc… was close to 50% Six Sigma changes the structure of a company – it becomes “the way we work” in everything they do and in every product they designSix Sigma Overview Page 9
  • 10. What Can Six Sigma Do For Us? Have you ever experienced excessive wait times for a customer service or delivery? Have you ever had an idea to simplify a process but never had the means to do it? Have you ever had customers complain about the same issue repeatedly?One of the world’s best-known advocates for quality, W. Edwards Deming,states that “85% of all quality problems are due to symptoms of amalfunctioning system e.g. processes and not people”. The fundamentalobjective of the Six Sigma methodology is the implementation of ameasurement-based strategy that focuses o n process improvement andvariation reduction through the application of Six Sigma improvementprojects. Rather than jumping to a solution before the real problem has beenidentified, the Six Sigma methodology pursues the following process:Practical Problem Statistical Problem Statistical Solution Practical SolutionBy getting everyone involved in the initiative a common language andunderstanding will be prevalent through out the business which makes iteasier to address improvement initiatives more quickly.Six Sigma Overview Page 10
  • 11. Roles In A Six Sigma OrganizationTo support the Six Sigma initiative a quality department is establishedconsisting of the:Quality LeaderMaster Black Belts (MBB)Black Belts (BB)These functions are full-time positions. MBB´s and BB´s normaly rotate backto line function on 18-30 months schedule after completion of theircertification requirements.Green Belts (GB) stay in their regular position and act as part-time projectleaders. These projects are generally smaller in scale and directly related totheir day-to-day jobs. The Six Sigma change agents are the driving force forimplementing the change successfully.The progress of the projects is reviewed on a monthly basis by the BusinessQuality Council (BQC) which consists of selected staff members.In addition all projects are supported by a Quality Financial Analyst whoassists in the project calculations and tracking of the benefits. The QualityFinancial Analyst is a full-time resource of the Finance department.Six Sigma: Roles & Responsibilities Page 12
  • 12. Master Black BeltWhat is expected of you as a MBB? Expert and change agent who train and mentor Black Belts/Green Belts In-depth understanding of the philosophy, goals, and application of the theory Strong statistical knowledge and utilization of tools Train/coach Black Belts and Green Belts Drive/direct/steer projects to success Advise managers and communicate status to business leadership and project teams Approve projects, tollgates and project closure Certification requirements: Pass exam, coach 10 projects and lead 2 projects Training: (3 weeks) DMAIC methodology is taught in-depth with a strong focus on statistical tools. Participants receive change tools & facilitation skills to support them in coaching and guiding teams through improvement projectsSix Sigma: Roles & Responsibilities Page 13
  • 13. Black BeltWhat is expected of you as a BB? Lead Six Sigma project teams Have an aptitude for statistics and a strong interest in understanding and making breakthrough improvements in processes Ensure process issues are addressed quickly and improvements implemented Execute and deliver on project results Communicate project status Guide GB projects and schedule, educate others on tools Demonstrate credible application of tools Certification requirements: Pass exam, lead 2 projects Training: (3 weeks) DMAIC methodology is taught in-depth with a strong focus on statistical tools. Participants receive change tools & facilitation skills to support them in coaching and guiding teams through improvement projectsSix Sigma: Roles & Responsibilities Page 14
  • 14. Green BeltWhat is expected of you as a GB? Carry out Six Sigma projects related to your job Incorporate tools/methodology of Six Sigma into current jobs to make improvements in processes Understand 6 Sigma methodology Communicate project status Deliver on project results (at least one project) Use tools to improve processes Sustain process performance after improvement Certification requirements: Pass exam, lead 1 project Training (2 weeks) DMAIC methodology and basic tools are taught in detail and provide participants with a strong foundation for leading improvement projectsSix Sigma: Roles & Responsibilities Page 15
  • 15. ChampionWhat is expected of you as a Champion? Deliver strategic direction for the project team-setting a rationale and a goal aligned with business priorities Provide resources (time, support, money) Support implementation and ensure alignment with business strategy Advocate team’s efforts to top management and Business Quality Council Learn the importance of data-driven management through continuous involvement with the team Training (3 days): Ensure knowledge of Six Sigma strategy including all organizational impacts, understand DMAIC cycle, understand roles and responsibilities within Six SigmaSix Sigma: Roles & Responsibilities Page 16
  • 16. Business Quality CouncilWhat is expected of you as a member of theBusiness Quality Council? Set general direction for quality Select processes for improvement Identify a champion for each improvement team Approve Team Charters Co-ordinate / integrates different projectsApprove recommended solutions and fundsCapture the gains from projects business-wideApprove projects for certificationSix Sigma: Roles & Responsibilities Page 17
  • 17. The Starting Point Every participant should have an assigned project which they can define in Six Sigma terms. This phase will address the definition of the project. Customer ¦ What motivates it? Expectations & Requirements ¦ Who will it impact? ¦ What is there to gain by doing it?Any IDEA for a project where a process is to be improved should be drivenby your customers’ needs.Before starting, it is important to determine the following: Who’s the customer? Internal or external? How does the customer perceive the current output of the process? Who are the stakeholders in the process? What processes are involved? What is the current business strategy?Six Sigma: Project Selection Page 18
  • 18. Where Do We Get Ideas For Projects? IDEA Input/feedback from Customers Customer complaints Surveys Brainstorming Focus Groups Outcome or impact of other projects Internal needs assessment Mystery ShoppingSix Sigma: Project Selection Page 19
  • 19. Project Selection Some don’ts when selecting a Project:Several points must be considered when selecting a ¦ Create “world hunger” projects. Even more common than “too manyproject: projects” are “too big projects”. Better learn from a small project than be frustrated by a monster project that goes on and on and on …¦ Think of your processes and base project selection on solid criteria ¦ Fail to explain the reason a project has been selected. People like to¦ Balance efficiency/cost-cutting projects with projects directly benefiting know that they are working on something important to the company and external customers the customer¦ Make it measurable. This is the key to doing a Six Sigma project. Whether ¦ Start too many projects early in the Six Sigma roll-out. Improvement in monetary units, reducing defects, improving cycle time or increasing teams learning improvement and design methods need lots of care and feeding by their Champions, and Champions need to learn from their customer satisfaction, this must be measured! teams¦ The project should be realistic and doable¦ A clear handoff/mandate from Champion to Project Team Leader. A clear project rationale and Project Charter will get the project off to a good startSix Sigma: Project Selection Page 20
  • 20. Project Selection ProcessOne of the challenges of project selection is to choose from all the possibleactivities one can undertake, and decide which have the greatest potentialand therefore should be done first.1. Review where you are now, current business situation (based on existing data)2. Develop a list of potential projects and describe the pain, goal and rationale for each3. Screen out those that don’t meet basic criteria4. Operationalize criteria for the final choices5. Apply the criteria and select the projects6. Evaluate the set of projects selected7. Draft a charter for each selected projectSix Sigma: Project Selection Page 21
  • 21. Steps For Project Selection Process (1)1. Review up-to-date internal and external sources of information about the business. Comparison with competitors, customer surveys, marketplace analysis, complaint data can all stimulate questions that can lead to possible projects Where are we failing to meet customer requirements? What do they complain about most? Where are we behind competitors? Where is our market going? What new customer needs might be on the horizon?2. Identify potential projects and describe the pain, goal and rationale for each The pain: who is suffering because of the problem (include both customers and employees)? In what ways do they differ? The goal: what would you like to accomplish? The rationale: why would it make sense to work on this project now (especially when compared to other improvement opportunities)?3. Screen the possibilities by working through the list of potential projects and select those which meet the following basic criteria: A significant gap between current and desired/needed performance exists Cause of the problem is unknown or not clearly understood Solution is not predeterminedSix Sigma: Project Selection Page 22
  • 22. Steps For Project Selection Process (2)4. Operationalize remaining criteria for final project selections. It is necessary to know specifically what costs and outcomes are important to the business What business benefits are key? How will feasibility be determined? Time, money, resources? What organizational learning or other changes are important?5. Evaluate remaining projects and select best candidates Objective: (Purpose or focus of the choice being made) Criteria Key factors to be weighed in the Alternatives Total decision (results or implementation) • • (Sum of • (Choices or options (Scores 1-5 and information scores • being considered – relating each alternative to or • Projects, Tools, the criteria – beware of results • Solutions, etc.) assumptions ) of priority )6. Evaluate set of projects selected as a whole to determine whether the organization stands a good chance of successfully completing all projects selected7. Draft a charter for each selected projectSix Sigma: Project Selection Page 23
  • 23. Project Reviews (1)Ongoing project team self assessmentIn realty project reviews occur every time a Six Sigma team meets. The teamconstantly must assess its own:Process:¦ How well is the team working?¦ Is the DMAIC process being followed?¦ Are the right problem solving tools being used correctly?Product:¦ Are the tasks and deliverables getting done on schedule and within budget?¦ What have we learned about our problem?¦ How close are we to finding and implementing the solution?Six Sigma: Project Reviews Page 24
  • 24. Project Reviews (2)Monthly project reviewRegularly (monthly in a typical Six Sigma project) the MBB (or the externalconsultant) should meet with each project team. At the review meeting, theproject team (not the GB/BB) answers the following standard reviewquestions:¦ What did we say we were going to do?¦ What did we actually do?¦ If we didn’t do what we said we were going to do, why not?¦ What are we going to do either to get back on track or follow a new track?¦ What did we learn?¦ What do we need in order to do better during next month?The review meeting is more like a self assessment report. The role of thereviewer is to ensure that:¦ The team is using data that supports what’s being said¦ The DMAIC process is rigorously and properly used¦ The right problem solving tools are being used and correctly¦ There are no technical errors, either in the application or in the interpretation of the tools.¦ The project plans remains realistic but aggressiveSix Sigma: Project Reviews Page 25
  • 25. Project Reviews (3)The BQC reviewThe Business Quality Council consists of senior managers in the business,gathered in a forum to help them learn a new way to manage the business bydirect experience with Six Sigma teams. In this natural leadership role, thisgroup plans and executes the Six Sigma implementation plan and theongoing reviews of the projects.For the Six Sigma Strategy this group must:¦ Develop a strong rationale for doing Six Sigma which is specific to the company’s needs¦ Plan and actively participate in the implementation¦ Create a vision and an internal change marketing plan to sell Six Sigma to the key customers inside the organization¦ Become powerful advocates¦ Set clear objectives¦ Hold itself and others accountable for the success or failure of Six Sigma¦ Demand solid measures of results, including measures of defects and yields¦ Communicate results and set-backsSix Sigma: Project Reviews Page 26
  • 26. Measuring Team Success Dynamics Measure Of Success Did the results meet the team´s specific Results performance goals? Results Did the results meet c ustomer expectations (internal and external)? Were our goals challenging enough? Did our plans or team processes work for the task(s) at hand? Were we able to adjust when needed? Was our process well -coordinated and Success Process facilitated? Were roles and responsibilities clear and Dynamics executed effectively? Of A Team Did our team employ our skills and talents effectively? Did team members support each other and share responsibility for success? Did team members establish trusting Process Relationship Relationship relationships in which members felt valued? Overall, did the team maintain a sense of team spirit and commitment to the team´s purpose?Meeting Skills Page 27
  • 27. Goals:Setting Up Meetings ¦ Before the meeting you can: - Ask people to provide you with their desired outcomesGoals - Draft a final list based on their input, or - Distribute a list of desired outcomes and ask for input ? What is your purpose/outcome/goal? - Amend the list as appropriate ? Is a meeting the right format for this? ¦ At the beginning of a meeting:Roles - Get clarification and agreement on desired outcomes - If time assigned in agenda – start doing it now! ? Who needs to attend and what are their roles? Roles: ? Who are stakeholders that need to be informed? ¦ Possible Roles in Meetings:Process - Leader - Participants ? Did you distribute an agenda? - Facilitator - Note Taker ? Did you reserve a room? - Time Keeper ? Did you provide equipment/material needed? - Expert on Demand ? Did you arrive early to check the room for any surprises? Interpersonal Relationship (for complex meetings)Interpersonal Relationship ¦ Identify stakeholders of a meeting - any person who is: ? What is the background of the people attending? - Responsible for the final decision ? What relationships exist – can any conflicts be expected? - In a position to implement the decision or prevent it from being implemented ? Do you need ground rules? - Likely to be affected by the outcomeRun Stakeholder Analysis:List stakeholders - Decide how they affect the outcome of the meeting - List risks/wins - Select attendees of the meetingMeeting Skills Page 28
  • 28. Agenda (1) An agenda is a road map to guide the meeting, which the group can consciously amend as it moves through the meeting Agenda planning is the process of designing the flow of topics, process steps, and time necessary to accomplish the desired outcomes of a meeting Other products of agenda planning are: ? A logistics plan ? A strategy for dealing with potential pitfalls ? A visual image of successMeeting Skills Page 29
  • 29. Agenda (2)Your agenda should contain: Purpose for the meeting and desired outcomes Who´s calling the meeting The date, place, start and stop time Meeting Leader, Facilitator, Participants, Guests... Items for action Presenter for each action item Meetings procedure and decision making model Any preparation suggestions Follow-up items to bring forward from the last meetingMeeting Skills Page 30
  • 30. Meeting Follow UpUse minutes… As a reminder to members on agreements To include other stakeholders who didn´t attend As a tool to keep commitment high between meetings Paperless if at all possibleInclude in minutes… Stated purpose and outcomes Agenda Summary of agreements made Unfinished agenda items Parking Lots LogisticsMeeting Skills Page 31
  • 31. Summary Meeting Skills Commit to prepare for the meetings (min. 50% of meeting time) Cancel meetings that are not the right forum Distribute an agenda (before the meeting!) Make sure required material is available Get group agreement on purpose and outcomes Plan methods to best accomplish purpose (process and tools) Rotate role of recorder Establish group groundrules (make them available in meeting rooms) Team focuses on content – Facilitator on process (clarify Role s & Responsibilities) Debrief meetings (integrate time in agenda) Distribute minutes asap Follow up on commitments to action from last meeting (always!)Meeting Skills Page 32
  • 32. DefineDefine the problem and what customer requiresThis step defines the project and identifies the customer requirements (CTQ –critical to quality) to determine what the impact of the problem is on thecustomer. To establish the customer CTQs the team must gather Voice of theCustomer information using survey tools. This information is then translatedinto specific and measurable CTQs around which the improvement project willbe focused. The team defines a Project Charter in order to create theboundaries and goals of the project as well as a High-Level Process Mapdescribing the process being improved.DMAIC Overview Page 33
  • 33. MeasureMeasure the defects and process operationThis step focuses on collecting data about the problem identified in Define.The Project Output Metric is identified which is the key metric for the projectas well as a measure of the output of the process which is directly linked tothe customer needs. Before collecting the data, the measurement systemneeds to be validated to ensure that the process with which we are collectingthe data is correct. Once we have the data we are able to display theVariation of our results.DMAIC Overview Page 34
  • 34. AnalyzeAnalyze the data and discover causes of defectsIn this step we take a closer look at the results of our data in order todetermine what causes the variation in our process performance. With thehelp of statistical tools it becomes possible to take a closer look at the data.Once some hypotheses of possible causes have been identified, they arefurther narrowed down to Root Causes.DMAIC Overview Page 35
  • 35. ImproveImprove the process to remove causes of defectsThis step focuses on finding solutions to those performance characteristicswhich must be improved to achieve the goal. The Root Causes are addressedand solutions are identified which are then tested and further refined throughPotential Problem Analysis. The solutions are piloted in order to assess if thenew process functions correctly as well as determining final changes beforeimplementing the solution completely.DMAIC Overview Page 36
  • 36. ControlControl and Monitor your improvementOnce the solution is identified, a Process Control Plan is established. Thisplan consists of a new process map and the controls in place which monitorbehavior of the new process. In case the process performance changes, aResponse Plan is created which includes information on how to react towardsthese changes. After the Control Plan is created, the next step is theimplementation plan of the solution. Before handing the new process over tothe process owner, the team closely monitors the performance of the processand validate the financial benefits.DMAIC Overview Page 37
  • 37. Define Roadmap DEFINE MEASURE ANALYZE IMPROVE CONTROL 1. Select Project CTQ’s: Deliverables: • Identify who your customers are and transform their needs into CTQ’s • Determine project focus and select process for improvement Customers Voice of the Customer Requirements: Project Customer (VOC) Critical to Quality (CTQ) Focus 2. Create Project Charter: Deliverables: • Problem Statement Project Charter • Goal Statement • Project Scope • Business Case • Team Roles • Milestones 3. Develop High Level Process Map: Deliverables: • Map process selected for improvement (high-level) • Connect Customers, Output, Suppliers and Input to S I P O C the processDefine Overview Page 38
  • 38. Define ObjectivesThe Define Phase: Begins with defining who your customers are and what their expectations & requirements are for your products and services. These requirements are then translated into customer CTQs (Critical to Quality) Focuses on bounding the project. It is essential that team goals, project boundaries, & project focus (what is in/out of scope) are established Uses Process Mapping to create a clearer picture of what the process boundaries are for the project teamDefine Overview Page 39
  • 39. Select Project CTQs Using data gathered from your customers, it is possible to identify what the customer expects of your product or service. These customer needs are usually very general and vague “I need an answer soon. “I need accurate information.” CTQs (critical to quality) are customer needs translated into critical process requirements that are specific and measurable. A fully developed CTQ has five elements: Output Characteristic, Project Output Metric, Target, Specification/Tolerance Limits and Defect Definition Define Timely Response (Output Characteristic) Variance between time to request and actual delivery (Project Output Metric)Customer Requirement Customer receives Customer request date product on customer CTQ (Target) request date Measure Variance not greater than 1 day (specification/tolerance Limit) Any response taking more than 12 hrs (defect definition)Define – Step 1: Select Project CTQ’s Page 40
  • 40. Who Is The Customer? At a project level, the outside-in perspective helps you to understand what the customer wants relative to our process. While the scope of a project may be at the subprocess level, you should be able to link process CTQs to higher level VOC CTQs obtained from the customer. Identify which customer group will be impacted - this narrows the scope/focus of the project Are they internal or external customers? ? An external customer is the person or company that ordered the output and is the end user ? An internal customer is someone in your organization who must use the output from your process to further create or refine the final output for the external customer How does the customer view your process? What does the customer look at to measure your performance? What does the customer need from me to fulfill his process?Define – Step 1: Select Project CTQ’s Page 41
  • 41. Define Customer SegmentsIt is important to look at your customers and segment them into logical The importance of Customer Segmentationgroups. This allows the team to focus the customer research on the most Not all customers have the same needs or priorities. Segmenting customersimportant customers for the project: allows you to more clearly understand the needs of different groups and focus your improvement efforts accordingly. If you have many types of customers, breaking them down into different subgroups allows you to Review your list of customers develop targeted measurement indicators and strategies for each group. To do this, review your list of customers. List some possible categories to Determine logical customer segments: describe your potential customers. All customers are important, but some ? location, size, type of business, market segment etc. customers will use your services more frequently or could be more critical to your business than others. This means you will devote more time and resources to them. Locaction: Size: Others: Type of deal Market SegmentDefine – Step 1: Select Project CTQ’s Page 42
  • 42. Where Can We Find Customer Information? The team builds a database on customer information using various Customer Surveys resources as listed to the left. Measuring customer information, gives the team the opportunity to develop strategies to meet customer needs. Personal Visits Usually what the c ustomer wants is: Questionnaires ¦ Reacting to competitiveness in the market place Interviews ¦ On-time and accurate deliverables as per customer request Customer Complaints ¦ The technical (quality) performance of a product or service Benchmarking Data Market Strategies Focus GroupsDefine – Step 1: Select Project CTQ’s Page 43
  • 43. Voice Of The Customer (VOC) (1)Voice of the Customer is defined as what is important or critical to the quality 1. It is nec essary to review existing customer data and select which information is relevant for the project. If your business already hasof the process we are focusing on … according to the customer! data, check to see what information it is: - General Information about customers needs - Satisfaction level with current performance Customers - Performance relative to other alternatives - Specific performance targets and other requirements What are our customers saying? What is important to them ? 2. Determine what still needs to be collected in order to receive the information needed for the project Do we know what the customer wants based on their need (not based on what our process is delivering)? 3. Once the team has identified the information needed th en VOC tools must be selected to help gather the information Review existing Customer data Check with Marketing or Quality Department whether the information you need has already been collected. This will avoid double work for the Team and the Customer Select data to be collected. If you can not find existing data, then it is necessary to collect additional VOC data in order to determine the CTQs for your project Choose VOC tools to collect dataDefine – Step 1: Select Project CTQ’s Page 44
  • 44. Voice Of The Customer (VOC) (2)Consider the following before collecting VOC data: What budget is available to your team for collecting VOC data? Are there any time constraints? Will the team be able to collect the data or are external resources required? Will the collector’s bias influence what the customer is saying? Ask questions from the customer’s view Explain Team’s intent for collecting VOC data and ensure customer expectations are aligned with our intentions/actionsDefine – Step 1: Select Project CTQ’s Page 45
  • 45. Voice Of The Customer (VOC) - Methods Customer Surveys (in person, telephone, mail, online) Focus Groups Interviews Customer Feedback & Complaint LogMarket Research Studies and Reports Beyour own customer- Mystery ShoppingDefine – Step 1: Select Project CTQ’s Page 46
  • 46. Review survey objectives Determine appropriate sample Identify specific areas of desired information Write draft questions and determine measurement scales Determine coding requirements Design the survey Pilot the survey–both the individual questions as well as the total survey against the objectives Revise and finalizeDefine – Step 1: Select Project CTQ’s Page 47
  • 47. VOC Data Analyis Once the data is collected, the process teams must go through severalOnce the VOC Data is collected, it is necessary to: additional steps in order to determine the Project CTQs. A number of tools are available to help your team move from qualitative, unprioritized VOC to Organize all customer data prioritized CTQs. The specific tool a team chooses is dependent upon the Identify the customer concern/issue amount of data collected as well as the complexity of the information. Always validate your CTQs with your customer. Translate VOC to specific requirements Define CTQs for specific requirements Prioritize CTQs Validate with customerDefine – Step 1: Select Project CTQ’s Page 48
  • 48. Organize Customer Data The customer data the team gathered is most often expressed as complaintsExamples of Customer Data: or stated in abstract terms. This makes it more difficult for the data to be meaningful for the process. By listening to the voice of the customer (VOC),“I keep getting transferred to different representatives.” (from a customer) we can carefully translate their language into their key issues and needs. This is not rewriting the voice of the customer. It is a translation of what the customer said to specific process requirements for the business.“Keep on receiving incorrect information on my monthly statements.” (from anend customer)“Customers keep calling this week with questions about the new promotion.”(from a service representative)“My customer was confused about getting several calls from different servicereps looking for the same information.” (from a sales representative)“The phone must have rung eight times before a service rep answered thephone.” (from a customer)Define – Step 1: Select Project CTQ’s Page 49
  • 49. Draft Output Characteristics It is helpful when translating customer needs into requirements to associate The team translates what the customers say into something observable and the need with a clear image. measurable. The following questions can be used as a guideline for defining clear, objective requirement statements: Once the Output Characteristic is drafted, the team should share this with others outside the team to check whether it’s clear, specific and easy to understand. What clues or observable factors will indicate we are achieving this requirement? Will we be able to objectively observe and/or measure this factor? Translation Matrix Customer Concern or Customer Ouput Comments Issue Requirement Characteristic„It takes so long Speed of loan The customer Cycle timeto process the application cycle receives loanloan application.“ time approval on customer request date„I keep getting Speaking to too The first time the Service level,transferred to many incorrect customer calls knowledgeabledifferent people he/she reaches rep.representatives.“ the correct person Define – Step 1: Select Project CTQ’s Page 50
  • 50. Validate & Revise The Output Characteristic It is better to ensure that the customer has expectations you are able to ALWAYS check back with the customer, survey data, sales meet than to surprise them when you don’t. reps, service reps in order to validate the requirement and see whether the statement accurately describes what the customer wants Should a gap exist between the customer requirement and what the business delivers, it is important to identify a requirement that is realisticDefine – Step 1: Select Project CTQ’s Page 51
  • 51. Requirement TreeAnother way of translating customer information into requirements is by Requirement Treebuilding a requirement tree which displays a visual picture. It is helpful when The requirement tree is used to organize information into a logical hierarchydealing with complex processes with complicated VOC data because it of customer requirements.provides a clear structure to identifying customer requirements. ¦ From the gathered VOC data, create major tree headings. These should be broad, general customer needs ¦ Then, continue to break these headings into more detail until the Accessibility to Loan specific customer requirement is identified. The completed diagram should follow a logical flow from general to specific, from broad to narrow Easily available information Simple loan statements Clear overview of loan status Straight-forward, easy process anywhere Easy access 24 hour access to $ Various access channelsDefine – Step 1: Select Project CTQ’s Page 52
  • 52. Develop CTQ – Output CharacteristicAfter completing the customer requirements, the CTQ can be developed. Output Characteristic: A word or phrase that describes some aspec t of the product or serviceThe first CTQ element to be identified is the Output Characteristic. Once (output).customer requirements are known, they must be translated into CTQs. Project Output Metric:CTQs have five elements The key project metric defined from the customer’s perspective. A definition of how the output characteristic is to be quantified. There may be severalCTQs link the process output to customer satisfaction. ways of quantifying a given characteristic. Target: Define Where we will “aim” our product/service. If there were no variation in the product/service, this is the value we would always achieve. Timely Response (Output Characteristic) Specification Limits: How much variation the customer is willing to “tolerate” in the delivery of our Variance between time to request and actual product or service. delivery Customer Requirement (Project Output Metric) Defect Definition: Definition of what the customer describes as a defect. Any time the process Customer receives product on customer CTQ Customer request date does not meet their requirements (CTQs). (Target) request date Measure Important: Once priority CTQs are identified, re-evaluate the team charter. Variance not greater Revise any sections impacted by your new information. Are your problem than 1 day (specification/tolerance statement and CTQs aligned? Have you scoped your project to work on the Limit) one or two top priorities for the customer? Revise the charter as necessary, and reconfirm it with your Champion. Any response taking Any response taking more than 12 hrs more than 12 hrs (defect definition)Define – Step 1: Select Project CTQ’s Page 53
  • 53. Analyzing & Prioritizing CustomerRequirements Kano AnalysisNow that the customer requirements have been identified, the team must Based on the ground-breaking work of Dr. Noriaki Kano. A key figure in theprioritize them. Not all customer requirements are created equal, nor do Japanese quality movement, Dr. Kano realized the importance of dividingcustomers regard every defect as equally serious. In addition, what satisfied customer requirements into three categories:your customers last year may not satisfy them next year and so on. ¦ Dissatisfiers or basic requirementsOne approach to prioritizing the customer requirements is using Kano ¦ SatisfiersAnalysis. ¦ Delighters Kano Model: High Customer Satisfaction Satisfiers Core Competitive Core Competitive Delighters Requirements Innovation Done poorly Done very well Dissatisfiers Basic Requirements Low Customer SatisfactionDefine – Step 1: Select Project CTQ’s Page 54
  • 54. Kano AnalysisDissatisfiers or basic requirements Example: Hotel room Dissatisfier or basic requirement:This type of requirement is also known as a “Must be”. This means that these ¦ Bedfeatures or performance requirements must be present to meet the minimalexpectations of customers. The customer probably won’t notice if these ¦ Bathroomfeatures or performance standards are met, but they will notice, and be ¦ Telephonegreatly dissatisfied, if they are missing. ¦ TVSatisfiers Satisfier: ¦ Bed is extra comfortable (or a waterbed)This type of requirement is also known as the “more is better” requirement.The better or worse you perform on these requirements, the higher or lower ¦ Room serviceyour customer satisfaction will be. Price is certainly the most prevalent in this ¦ Friendly staffcategory – the less the customer pays for a certain set of features orcapabilities, the happier the customer usually is. Assuming that your Delighters:organization is meeting the basic customer requirements, many of your ¦ Mint on pillowprocess improvement priorities will fall with in this category. ¦ Fruit basketDelightersThese are features that go beyond what customers expect. In serviceindustries, the delighters are often unexpected services that go the extra mile.Define – Step 1: Select Project CTQ’s Page 55
  • 55. Define Roadmap The Define Phase focuses on three areas: Begins with defining who your customers are and what their expectations & requirements are for your products and services. These requirements are then translated into customer CTQs (Critical to Quality). DEFINE MEASURE ANALYZE IMPROVE CONTROL To bound the project, it is essential that team goals, project boundaries, & 1. Select Project CTQ’s : project focus (what is in/out of scope) are established. Deliverables : • Identify who your customers are and transform their needs into CTQ’ s • Determine project focus and select process for improvement In addition, we have to map the process we are trying to improve. This gives Customers the team a clearer picture of what the process boundaries are. Voice of the Customer Requirements : Project Customer (VOC) Critical to Quality (CTQ) Focus 2. Create Project Charter: Deliverables : • Problem Statement Project Charter • Goal Statement • Project Scope • Business Case • Team Roles • Milestones 3. Develop High Level Process Map: Deliverables: • Map process selected for improvement (high- level) • Connect Customers, Output, Suppliers and Input to S I P O C the processDefine – Step 1: Select Project CTQ’s Page 56
  • 56. Why Create A Project Charter?A Project Charter is a document that provides direction A first draft of the Project Charter is prepared by the Champion. The team reviews what has already been provided and fills in the missing blanks until itand a framework for the Project Teams. is something that the team can work with. The Project Charter goes back to the Champion to double check if it is still in line with his/her expectations.The Project Charter: Clarifies what is expected of the team Keeps the team focused Keeps the team aligned with organizational priorities Transfers the project from the champion to the improvement teamDefine – Step 2: Create Project Charter Page 57
  • 57. Deliverables Of A Project Charter Business Case - An overview of the value and need for the project. What are the financial, customer, and strategic benefits of doing the project and why do it now Problem Statement - An explanation of the issue and reasons for doing the project. It is important not to assign a cause, a solution, or a blame for the problem here. The statement must be concise, specific and measurable Goal Statement - An explanation of the opportunity the project will bring and the type of result to be achieved. Normally this does not include a specific target because precise data about the problem has not been collected yet Project Scope - Description of the focus of the project. These will give the team a general idea of the resources available to them and what solutions they may not want to consider etc. Team Roles - Explanation of positions and responsibilities of team Milestones - A detailed project plan with key steps and target completion datesDefine – Step 2: Create Project Charter Page 58
  • 58. The Business Case States the reasons why the project should be a key business priority and should come from the Champion Provides the broad definition of the issue assigned to the Black Belt and TeamA Business Case answers: ? How will this project drive business initiatives and goals? ? How will this project impact the customer? ? Why is it important to do now? Why is it a priority? ? What are the consequences of not doing it now? ? What are the expected financial benefits (revenue and/or cost reduction)?Define – Step 2: Create Project Charter Page 59
  • 59. The Problem Statement The Problem Statement should NOT: A description in a few sentences of the symptoms arising from the problem to be addressed ¦ State an opinion about what’s wrong . A Problem Statement must focus on an issue that can be objectively observed and measured. For Similar to the Business Case (sometimes they are almost if example: “The new software is too difficult to use” is based on a value not exactly the same) but often the Problem Statement will be judgement. The software may be hard to use, but the question is: What pain or trouble do you see or feel?. A better problem statement would more specific be “Usage of the new software is only 60% of forecast as measured by the log-in counts”A Problem Statement answers: ¦ Describe the cause of the problem. The statement should only ? What is wrong? include the effects or symptoms of a problem as the reason for doing the project is to uncover the causes of the problem ? Where is the problem occurring? ¦ Prescribe a solution . If reliable data exists that confirm the cause of a ? How big is the problem? problem, then go ahead and implement the solution – you don’t need to have a team work through DMAIC just to do what a project manager ? What’s the impact of the problem? would doDefine – Step 2: Create Project Charter Page 60
  • 60. The Goal Statement The Goal Statement should NOT: Related to the Problem Statement: A Goal Statement describes what will be achieved to overcome the problem ¦ State how the goal will be achieved . This would imply a solution to the problem. For example: “Reduce defects on the customer application by 50% by October 31, 2004 by installing a website.” The last part “byA Goal Statement describes: installing a website ” is a solution. It is essential that we first find out what is causing the problem before we install a solution or, we may fail ? What is to be accomplished to solve the original problem (and may have spent a lot of time and ? A measurable target for desired results money on a website) ? A projected completion date to reach the goalDefine – Step 2: Create Project Charter Page 61
  • 61. The Project Scope Project Team’s should think about what elements/topics they will address in Outlines the scope of the project along with constraints their projec t and what not. They should clearly outline what is within the (where does the project start and stop?) project scope and what is not. Constraints refer to limits placed on resources, time, and If the team can not decide whether one of the topics is in or out of the scope, money they must go back and clarify this with their Champion. By listing the Projec t Scope a clear definition for the project boundaries willThe Project Scope outlines: be established. It is essential that agreement is reached on these ? The focus of the project – what is definitely to be boundaries in order to avoid false expectations later on. The team has to have a clear understanding of the scope as well as the Steering Committee. considered By communicating the project boundaries the team creates transparency for their project. ? Gives an idea of resources available ? What solutions not to be considered For instance, clearly labeling that “additional Headcount” or “new IT software” is out of scope for the project, will prevent that the team will come up with such solutions including these elements. On the same account, it can also happen at some point that Management asks “what about hiringTo help Scope the Project, the tool “In the Frame/Out of new people?”. The team can then give a clear answer and tell Managementthe Frame” can be used (on the following page). that this was clearly out of the scope of the project as defined and agreed on in the beginning of the project scope.Define – Step 2: Create Project Charter Page 62
  • 62. Scoping The Project In/Out of the FrameIn The Frame/Out Of The Frame This is a visual tool based on the analogy of a picture frame. It challengesDraw a large square “picture frame” on a flip chart (or use tape on a wall) and use this metaphor to help the team to identify the aspects of the project which are “in the frame”the team identify what falls inside the picture of their project and what falls out. This may be in terms of (meaning clearly within the scope of work), “out of the frame,” or “on thescope, goals, and roles etc. frame” (meaning this is either up for debate, or some aspects are in the scope of work but only in a partial way). Brainstorm Ideas/Elements for: ¦ Timing ¦ Organizations involved ¦ Processes involved ¦ Levels involved ¦ Results/targets for the project ¦ Measurements of success ¦ Who should be on the team Uses Useful when you feel there are many boundary issues facing the team (differences of opinion as to what is and isn’t in the scope of work). Timing This tool can be used at an early meeting of the team to further clarify what has already been stated in the charter with the Team Sponsor. It can be used in an ongoing way to update the projec t scope as the project unfolds.Define – Step 2: Create Project Charter Page 63
  • 63. Team Roles Example: The team should represent all of the steps of the process The team is responsible for all steps of DMAIC. The team will review the under analysis charter with the Champion, and will schedule tollgate reviews according to the project plan. The Team Leader will meet with the Champion on an ad- Well-defined roles help ensure smooth working relationships hoc basis for any special needs or problems. The Team Leader will confer within the team and with key Stakeholders in the organization with the MBB on a bi -weekly basis to check progress and get tips on using DMAIC tools. The MBB will sit in on tollgate preparation meetings to offer advice.Clarification of Team Roles includes: ? How should the Champion work with the team? ? How does the team make decisions? ? Are the right members on the team? Functionally? Hierarchically? ? What are the working guidelines of the team?Define – Step 2: Create Project Charter Page 64
  • 64. Milestones Early on, your team should establish target dates for completing key tasks in Milestones provide a sense of urgency, a feeling of the DMAIC process. At a minimum, your team should set dates for tollgate accomplishment during the project – and help ensure reviews – end-of-phase reviews with your Champion to review what you’ve found, your next steps, and any i ssues you need to resolve before moving achieving timely results forward.Milestones include: There are many software products which can help you create a team project plan to record and monitor progress. Businesses use MS Project (Microsoft). ? What are the key steps and target completion dates? ? Are the tollgate reviews defined? ? Are these targets aggressive yet realistic? ? Are the milestones shared and continuously updated?Define – Step 2: Create Project Charter Page 65
  • 65. Project Charter Example Problem Business Statement Case Mistakes on loan applications have Direct loans represent a key market niche increased by approx. 25% in the last 6 for the company. This section could grow by months. This leads to a growing number of 35% over the next 2 years. Incorrect rejected loans (20%) due to incorrect risk applications cause the risk assessment to assessment. reject 20% based on wrong information. Goal Statement Reduce the number of errors by 70% on an application especially where the risk assessment is critical to approving the loan. Champion: Mr. Smith Project Scope Team Roles MBB: Ms. Jones In Scope: Direct loans, Sales, Application GB or BB: Ms. O‘Conner processing Team: Mr. Johnson, Mr. Brown, Out of scope : Corporate loans Ms. James No money is available for buying new EoD: Mr. Mosley (Finance) equipment/software or assigning new people to the operation. Milestones Jan Feb Mar Apr May Jun Jul Define Team can implement any decisions based Measure on good data after discussion with Analyze Improve Champion. ControlDefine – Step 2: Create Project Charter Page 66
  • 66. Define Roadmap The Define Phase focuses on three areas: Begins with defining who your customers are and what their expectations & requirements are for your products and services. These requirements are then translated into customer CTQs (Critical to Quality).DEFINE MEASURE ANALYZE IMPROVE CONTROL To bound the project, it is essential that team goals, project boundaries, & project focus (what is in/out of scope) are established.1. Select Project CTQ’s : Deliverables : In addition, we have to map the process we are trying to improve. This gives • Identify who your customers are andtransform their needs into CTQ’ s • Determine project focus and select process for improvement the team a clearer picture of what the process boundaries are. Customers Voice of the Customer Requirements : Project Customer (VOC) Critical to Quality (CTQ) Focus2. Create Project Charter: Deliverables : • Problem Statement Project Charter • Goal Statement • Project Scope • Business Case • Team Roles • Milestones3. Develop High Level Process Map: Deliverables: • Map process selected for improvement (high-level) • Connect Customers, Output, Suppliers and Input to S I P O C the process Define – Step 2: Create Project Charter Page 67
  • 67. Define The Process Virtually everything we do is a process, from the activities we do at our jobsA Process is a series of steps or a collection of activities to brushing our teeth. Some processes are formal and logical, others informal and at times chaotic. A process is defined as a combination ofthat takes one or more inputs and transforms them into factors or activities that takes one or more inputs and adds value to createoutputs that are of value to the customer. some result (an output), whether that is a product or service. Processes should ultimately provide value to customers. INPUT PROCESS OUTPUTDefine – Step 3: Develop High Level Process Map Page 68
  • 68. High-Level Process Mapping Mapping the Process with just enough detail will give the foundation forBenefits: getting started with measurement and analysis. In general, Six Sigma teams start with a high-level process map with only a few details that only show the major steps involved. Almost like a snapshot ? A structure for thinking through a complex process in a of the process. Later during the project, the team returns to the high-level simplified, visible manner process map and builds on this to look at various parts in more detail. ? An ability to “see” the entire process as a team ? An ability to “see” that changes are not made in a vacuum and will carry through, affecting the entire process down the line ? The magnification of non value-added areas or steps ? The ability to identify cycle times for each step in the processDefine – Step 3: Develop High Level Process Map Page 69
  • 69. Different Levels Of A Process A SIPOC process map could be drawn for any process at level 1, 2, 3, or so on. SIPOC is a technique for drawing a process map at its simplest level. In Analyze you will learn more detailed process mapping techniques. Check to see if your business has mapped its core process. Identify w here your SIPOC fits into the business’s core process.ore Process Ap p catt on Ap plliic a iion Ap Custome rer Ma rkettiing Ma k e ting Ma ke ng S a es S alle s S Billliin g i ng (Level I) P roces sing P o ces iin g P oces ng Serrv ice Serv ce Se v c e ApplicationA Information Information In ApplicationSubprocess Customer Request eq Request for R Approval/noA processing pplication is formation back to (Level 2) loan uest pproval/no approval creates foror f processed is is approval p a backtometo cus ack to b r processedrp customer uc account loanloan proval ocessed stomer Subprocess(Level 3 and below) Define – Step 3: Develop High Level Process Map Page 70
  • 70. SIPOC (1) Customer (External or Internal) ¦ Receives output of your process Supplier Input Process Output Customer Output ¦ The result of a process. The deliverables of the process; such as S I P O C START products, services, processes, plans, and resources Process ¦ A series of steps or actions that lead to a desired result or -output Input STOP ¦ Identify the Inputs required for the Process to function properly Supplier ¦ Identify the Suppliers of the Inputs that are required by the ProcessProcess mapping is the graphic display of steps, events and operations thatconstitute a process. The SIPOC map (which stand for Supplier, Input,Process, Output and Customer) is a simple tool that facilitates thedocumentation of any business process. It helps to create a “picture” of theprocess involved in the project by creating a “high-level” flowchart.Define – Step 3: Develop High Level Process Map Page 71
  • 71. SIPOC (2) 1. Define the process to be reviewed. Name it. Agree on the beginning and end of the process Supplier Input Process Output Customer 2. Identify the process steps using brainstorming and storyboarding techniques S I P O C 3. Use brainstorming and storyboarding techniques to identify all the IDE outputs, customers, suppliers, and inputs. Distinguish primary outputs, customers, suppliers, and input from secondary ones START 4. Brainstorm the customer’s requirements for the primary outputs Hints: Start by rapidly writing process steps on cards. Write large and only one step per card. Don’t try to establish order. Don’t discuss process steps in detail. Once all ideas have been captured on cards, group the notes into STOP categories. Once all the notes have been categorized, name the category. The name of the category is usually one of the high- level process steps.Process Map: START ENDDefine – Step 3: Develop High Level Process Map Page 72
  • 72. Establish Boundaries From The CustomerPerspective Most improvement teams will underestimate the amount of the time needed to reach agreement on the start and stop p oints of a particular process. For example, when teams are asked to silently brainstorm the start point of Establishing the start and stop points of a process is a crucial ordering a beer do you think all agree readily on “calling the waiter”? Some first step in process mapping. By defining these boundaries, believe the start point is the time when one starts feeling thirsty, others think the team is able to identify all the important steps, events and it is when walking into a bar. Likewise, is the stop point of ordering a beer when the beer is on the table? Or is it, as some say, when the beer is operations that constitute the process consumed? Wherever the boundaries are established, they need to be from Typically, the start point of a process is the first step that the customer’s perspecti ve. receives the inputs from suppliers. Typically, the end point is the delivery of the product or service to the customer interfaceDefine – Step 3: Develop High Level Process Map Page 73
  • 73. Facilitating the Team during DefineAs a Project Leader, here’s some advice to help guide the team through During the Define Phase, you will notice the followingDefine: team developments: ¦ Further Clarification of Team’s goals¦ Team-building: give some time for the team to come together and get to ¦ Greater understanding of their own roles and responsibilities know each other. ¦ Building up relationships with other team members¦ Groundrules: have the team come up with groundrules early on and make sure you have everyone’s buy-in and understanding. These will help you This is called the “Forming” stage of team development. The team is usually run your meetings effectively. anxious to get started on the project, and may come up with solutions before the cause of the problem is known. The Project leader has to give direction¦ Agenda: always prepare an agenda for every meeting. This gives to the team and guide them through DMAIC. structure to the meetings and allows people to prepare accordingly.¦ Project Charter: make sure that the Project Charter is updated and reflects the work of the Team as well as that of the Champion. It is important that the Team feels that this project is their own.¦ Project plan: from the first meeting on, keep an up to date project plan which is accessible for everyone. This way the team knows where they are going and what milestones they have to reach by when.¦ Project Champion: make sure the project Champion is involved up front, but don’t let the Champion take over the team – that’s the responsibility of the Project Leader¦ Shared responsibility: have team members rotate responsibilities of the meeting and passing around the job of facilitator, time-keeper, scribe, recorder. This generally creates a greater sense of ownership of the projectDefine – Step 3: Develop High Level Process Map Page 74
  • 74. Measure Roadmap DEFINE MEASURE ANALYZE IMPROVE CONTROL 4. Identify Project Output Metric: Deliverables: • Develop the metric to measure Process Performance • Complete CTQ with Project Output Metric, Target, Specification Limits, Define and a Defect Definition Timely Response Timely Response (Output Characteristic) (Output Characteristic) • Use a Quality Function Deployment to narrow down key output metric Variance between time to request and actual delivery • Understand types of data Customer Requirement (Project Output Metric) Customer receives Customer request date product on customer CTQ Types of Data request date (Target) request date Measure Variance not greater than 1 day (specification/tolerance Limit) Limit) Any response taking Discrete Continuous more than 12 hrs (defectdefinition) P o p u l a ti o n Sample (N) (n) 5. Develop Data Collection Plan: Identify WHAT to collect 1. Deliverables: • Identify WHAT to collect and create Operational Definition Create operational definition • Determine Segmentation factors 2. • Use Data Collection sheets to assist in collecting the data Validate data Normal Distribution • Validate the data collection plan and ensure consistency in collection 3. F r e q u e n cy data collection Create sample plan & • Describe and understand the variation collect data CTQ 6. Establish Process Baseline: Voi c e o f th e C u st o m er Voi c e o f th e Pr o c es s Deliverables: Upper • Compare the Voice of the Customer to the Voice of Specification Limit the Process • Take a closer look at the normal curve – how well is the proces performing Defects • Proportion defective & Yield calculations First-Pass Yield and Final YieldMeasure Overview Page 75
  • 75. Measure Objectives Identify the Project Output metric (key output measure) The Measure phase achieves the following: 1. Identify the Project Output metric. Define the performance standards for Project Output including specification limits, defect and opportunity definitions 2. Use the 4 -step data collection process. 3. Understand the current performance of the Project Output metric for Identify segmentation factors for Project Output metric - Before and after comparisons Develop a Data Collection Plan - Benchmarking against competitors and other companies - Understanding process stability Collect data to baseline the current Process - Separating long -term and short-term variability Validate the measurement system - Comparing sigma capability to other processes Study the variation in Project Output metric data and establish data type Calculating the capability of the process in terms of process sigmaMeasure Overview Page 76
  • 76. Why Measure? A measure describes the performance:Measurement can be applied to any type of process or product to ¦ At a point in timeassess performance ¦ Over a period of timeFor a process: ¦ At a point in the process ¦ Overall for a set of process steps Time required to complete process steps Measurement costs time and money; the benefits of having a measure need Timely execution of process to outweigh the costs of collecting it. A key question to keep in mind as you think about a particular measure is: “What does this measure enable us to Number of errors in different process steps do?” If you don’t have a clear answer related to the management or Percent yield of a process improvement of the process, reassess the value of collecting that particular measure.For a product: Errors in a product Product arrived/shipped on time Number of products shipped per monthMeasure Overview Page 77
  • 77. Types of Data (1)Since the Measure Phase focuses on collecting the data to be analyzed forimprovement, it is important to know what type of data the team will beworking with.Type of data determines: Choice of data display and analysis tools Amount of data required: continuous data often requires a smaller sample size than discrete data Information about current and historical process performanceMeasure – Step 4: Identify Project Output Metric Page 78
  • 78. Types of Data (2) Sometimes it gets tricky determining whether data is discrete or continuousDiscrete Data because discrete data may show up in a continuous form.Anything that can be categorized or designated as either/or. For example: Your team finds that 42.8% of the customers borrow between €40,000 -Discrete measures are used often for artificial scales like the ones on surveys, €60,000. Just because you have decimal places and numbers there doeswhere people are asked to rate on a scale from 1 to 5. not mean the data is continuous. The team is still counting people who shareExamples: a common charac teristic or attribute – they fall into the same category¦ Male/Female (€40,000 - €60,000).¦ Defect/No Defect The same goes for continuous data showing up in a discrete form.¦ Day Of Week (M/T/W/Th/F) For example:¦ Accept/Reject Delivery times can be measured as “on time” or “late” (discrete categories) rather than in days , hours, minutes (continuous data). On many carContinuous Data dashboards, the oil pressure gauges display continuous data but have been replaced by warning lights that tell the driver that the pressure is low, versus OK.Anything that results from being measured on a continuum or scale.Examples:¦ time,(hours, minutes, seconds)¦ temperature (degrees) etc. Data Discrete Continuous Attribute Count Ordered (Defectives) (Defects) Categories (%) (#) (1st, 2nd, etc.)Measure – Step 4: Identify Project Output Metric Page 79
  • 79. Types of Data (3) Discrete data is important because Six Sigma performance is based onTo distinguish whether data is discrete or continuous, think about the unit you measuring the defects. These defects are usually discrete data, orare measuring and consider if it is possible to divide the unit in half. If the continuous data which is converted i nto discrete categories.answer is yes, the measure is continuous, and if the answer is no, the unit is Continuous data is preferred because it gives a better depiction of the truea discrete measure. performance of the process and the variation in the process being measured. If the team begins with continuous data, it can always be converted into discrete categories (loan amount categories, duration of loan etc.). However, Unit being measured Dividing the Unit if the team begins with discrete data, it is usually impossible to convert it to continuous data. Half a customer complaint does not makeCustomer Complaints sense – discrete measure Half a defect does not make sense –Defects per Application discrete measureHours to process Half an hour makes sense – continuousapplication measureAverage temperature per Half a degree makes sense – continuoushour measureMeasure – Step 4: Identify Project Output Metric Page 80
  • 80. The Project Output MetricThe Project Output metric is the key measure for the project and is defined Some Key Questions:from the customer’s perspective. ¦ If the Project Output Metric changes, will my customer feel the impact? A customer-focused Project Output metric allows us to assess ¦ Does the Project Output Metric match with how the customer describes the process from the customer’s perspective the process? ¦ Does the Project Output Metric link to one of the Big Ys for your Changes in the values of a good Project Output metric will business? predict changes in the degree to which the process meets the customer CTQs As you are thinking about which metric to choose as your Project Output metric, make sure that you consider these questions. If the answer to any A Project Output metric expresses the “voice of the process” one of them is “no”, you need to re-examine your Project Output Metric. Changes in input or process conditions drive changes in true output measures Project Output metric data is the first key to understanding process performance and the starting point for understanding how to control process outputMeasure – Step 4: Identify Project Output Metric Page 81
  • 81. Identify Project Output Metric (1)In the Define phase, the first element of the CTQ (output characteristic) was ¦ Project Output metric: the key project metric defined from the customer’s perspectiveidentified. ¦ Target: the optimal value for the output metricIn the Measure phase, the 4 remaining elements of the CTQ are defined. ¦ Specification/tolerance limits: the window or range of acceptable Output values. Also called “performance standards” ¦ Defect Definiti on: description of a defect Define Timely Response (Output Characteristic) Variance between time to request and actual delivery (Project Output Metric) Customer Requirement Customer receives Customer request date product on customer CTQ (Target) request date Measure Variance not greater than 1 day (specification/tolerance Limit) Any response taking more than 12 hrs (defect definition)Measure – Step 4: Identify Project Output Metric Page 82
  • 82. Identify Project Output Metric (2) The first step of the Measure phase is selecting your Project Output metric.For your key CTQ, how does the customer define The Project Output metric is the focus of your DMAIC project.process performance? ¦ Begin with the CTQ Output characteristic you identified in Define and identify the Project Output metric from the customer’s perspective ¦ The key customer you identified in Define can be internal or external but should always be the i mmediate recipient of the output of yourExample: Cycle Time processof Credit Decision What’s wrong with the metric? Where does measurement begin? Start Cycle time internal Stop measurement From the customer’s perspective, “start” is when the customer sends the Receive complete application from customer Contact customer to receive decision application (complete or incomplete). ¦ Customer may not care/know if some required information is missing ¦ Travel time to get from customer to business is included in the cycle time ¦ Must include travel time to customer, e.g., faxed decision may be Input Process Process Internal View Process Output delayed minutes or hours Stop Start Cycle time Customer Stop Measurement Customer Customer sends receives receives application decision decision Customer ViewMeasure – Step 4: Identify Project Output Metric Page 83
  • 83. Focus on the Customer It is essential that we continue to focus on the customer. Even in theContinuous focus on the Customer: measure phase, in order to understand our processes we have to look at them from the customer’s perspective. Select the Project Output metric that the customer uses to judge your performance Measure the same as the customer does Understand the variation in the Project Output Metric Use data to find the process keys that drive the VariationMeasure – Step 4: Identify Project Output Metric Page 84
  • 84. Quality Function Deployment (QFD) Quality Function Deployment (QFD) is a systematic process for motivating a QFD is used to translate customer needs and expectations business to focus on its customers. into CTQs It is used by cross-functional teams to identify and resolve issues involved in providing products, processes, services and strategies which will more than It is a structured methodology to identify and translate satisfy their customers. customer needs and wants into technical requirements and A prerequisite to QFD is Market Research. This is the process of understanding what the customer wants, how important these benefits are, measurable features and characteristics and how well different providers of products that address these benefits are perceived to perform.Measure – Step 4: Identify Project Output Metric Page 85
  • 85. The QFD Matrix Small Business Loan Service Product/Service Requirements & Process Steps Customer Addressed By Name Initial/Add’l Info. Requests Req’d Loan Amount App’d Relationship Matrix Relationship Matrix /Req’d Loan Ratio) (# Add’l Requests /Loan ) (Process – Disb. Time) Variety Of Loan Types Knowledgeable Reps . (Phone Answer Time) ( Assessment Score) Availability Of Reps. (% Of Customers ) Strong Strong Moderate Moderate Weak Weak Loan Appl . Time (Interest Rates) (# Loan Types) Interest Rate Weight Weight 99 3 3 11 Priority ( App’d Customer Needs Customer Needs Easy Access To Capital Easy Access To Capital 4.8 4.8 Low Interest Rate Low Interest Rate 4.7 4.7 Quick Loan Response Quick Loan Response 4.3 4.3 Talk To Knowledgeable Person Talk To Knowledgeable Person 4.0 4.0 No Unnecessary Data Requests No Unnecessary Data Requests 3.8 3.8 Professional Service Professional Service 3.5 3.5 Friendly Service Friendly Service 3.2 3.2 Easy Access To Loan Info. Easy Access To Loan Info. 3.0 3.0 Variety Of Terms/ Conditions Variety Of Terms/ Conditions 4.3 4.3 CTQ Priority 56 55 53 95 41 52 66 53 56 55 53 95 41 52 66 53Where would you focus the project?Measure – Step 4: Identify Project Output Metric Page 86
  • 86. The QFD Matrix (2)Refrigerator Example: Correlations Strong Positive Positive Negative Target Direction Refrig. Temp. Range Compressor energy Volume efficiency Warranty period % shelf and tray efficiency rating area adjustable Manufactoring (total/usable ) (on/off cycle) More is Better Refrig . Temp. Importance Strong Negative efficiency Insulation (years) variation costs Less is Better What A Specific Amount Low energy consumption 4 5 5 Maintains temperature 3 1 3 3 Preserves food & freshness 3 1 5 5 Easy access and visibility 4 1 Handles large items 4 1 3 3 Reliable 5 5 Low price 3 5Measure – Step 4: Identify Project Output Metric Page 87
  • 87. How to develop the QFD Matrix The rows of the QFD matrix are the needs (VOC) and the columns are the characteristics or measures associated with the CTQ’s. The cells are completed by asking the following question: “If we design the Product/Service Requirements & Process Steps service to perform to the target specified for the measure, to what extent would we have met the customers need ?” Use values of 0 (blank) for no correlation, 1 for low correlation, 3 for medium correlation and 9 for high correlation. Relationship Matrix Given the importance of the needs (in the rows corresponding to each need), the importance of each CTQ is calculated by matrix multiplication. Strong Moderate Weak 3. This is the output of the QFD exercise, rule of thumb is that about one - third Priority Weight 9 3 1 of the cells should be filled. Customer Needs 5 Easy Steps: 1. Identify WHAT does the customer want? 2. How important is it? To the customer – on a scale from 1 -5. 3. HOW to satisfy the customer requirement. 1. 4. 2. 2 4. 5. Evaluate the impact of each product/service requirement & process steps on the customer wants. Calculate the overall impact on the customer wants. (function importance * CTQ rating) = Impact CTQ Priority 5.Measure – Step 4: Identify Project Output Metric Page 88
  • 88. QFD – Take AwaysWhat to look for: Blank rows imply that a measure does not exist for the need Blank columns indicate that the measure is redundant because it does not correlate with any of the needs Which function/process and importance ratings indicate a high impactTips The process of working on a QFD may look simple, but requires effort Many of the entries look obvious– after they are written down If there aren’t some “tough spots” the first time, it probably isn’t being done right! Focus on the end-user customer Charts are not the objective Charts are the means for achieving the objective QFD is a valuable decision support tool, not a decision makerMeasure – Step 4: Identify Project Output Metric Page 89
  • 89. Project Output Metric Cross-Check Review Project Output Metric: ¦ All quality projects should be aligned to a Business Output metric and Business Output Metric CTQ for the business. This ensures that project activity is organized and targeted to impact specific CTQs that the customer will feel Key output metrics that are aligned with strategic goals/objectives of ¦ Not all Outputs are useful measures of business performance or the business. Business Output customer impact. Your Project Output metric should be correlated to a higher level Business Output or CTQ. You should be able to describe Metrics provide a direct measure of the link between your Project Output metric and the related Business business performance Output or CTQ in specific terms Process Output Metric Key output metrics that summarize process performance Project Output Metric Key project metric defined from the customer´s perspective X1 X2 X3 Factors which influence the outputMeasure – Step 4: Identify Project Output Metric Page 90
  • 90. Identify Target, Specification Limits andDefect Definition Target: ¦ Optimal value for OutputOnce the Project output metric has been established, the target, specificationlimits, and defect definition can be established. Specification/Tolerance Limit(s): ¦ Range of acceptable output values for Y. Also called “performance standards” Define Defect Definition: ¦ Definition of what the customer describes as a defect. Any time the Timely Response process does not meet their requirements (CTQs) (Output Characteristic) ? Information about where to set target and specification limits comes from the Variance between time customer. This information can be collected VOC data. to request and actual delivery (Project Output Metric) ?Customer Requirement Customer receives Customer request date product on customer CTQ (Target) request date Measure Variance not greater than 1 day (specification/tolerance Limit) Any response taking more than 12 hrs (defect definition)Measure – Step 4: Identify Project Output Metric Page 91
  • 91. Project Output Metric The definitions are based on the Project Output metric and perfo rmanceDefinitions of Six Sigma Output Performance standards and will be used later in the Measure phase to calculate Process Sigma or capability. The “defective” terminology is used when there is moreMeasures: than one defect opportunity per item/unit. A single item/unit could have more than one defect – the total number of defects is important because itUnit: An item being processed, or the final product or service being delivered represents the overall magnitude of the problem. It only takes one defect pereither to internal customers (other employees working for the same company unit to represent a problem from a customer’s perspective. So looking at theas the team) or external customers (the paying customers). percent of units with a least one defect gives us a perspective of how the customer sees the overall process performance. Notice that if items/units contain a number of defects, it is possible to reduceDefect: Any failure to meet a customer requirement or performance the overall total number of defects without having much impact on thestandard. percent of defective units. We need to be aware of both the total number of defects and the percent of units containing defects.Defect Opportunity: A chance that a product or service might fail to meeta customer requirement or performance standard.Defective: An item/unit with one or more defectsMeasure – Step 4: Identify Project Output Metric Page 92
  • 92. Output Performance Measures Of the terms on the previous page, defect opportunity is the trickiest andSix Sigma performance measures are usually based on defects produced by most critical for calculating a reliable sigma capability figure. The defectthe process. opportunity element of Six Sigma calculation is what enables us to compare processes of different complexity.2 guidelines for identifying defect opportunities: Example: Any time a rep types an application every key stroke could theoretically be1. Focus on defects that are important to the customer. counted as a defect opportunity. However, this is impractical and would2. Defect opportunities reflect the number of places where clump important defects along with many unimportant defects. Often, reports, forms, and applications have standard templates that are filled something in a process can go wrong, not all the ways it can automatic ally with identical text. The key in these kinds of situations is to go wrong. focus on defects that are important to and would be noticed by either the customer or the next step in your process.Measure – Step 4: Identify Project Output Metric Page 93
  • 93. Basic Measurement Principles Observation first, then measurement Measuring data is an expensive process. It costs a lot of time, resources, training etc. to collect the correct data needed for analysis. Type of data Therefore, the first step is to watch what happens with the process, o r talk to Develop a measurement process people involved. A lot can be learned by simply observing a process at work. It will become clear where people have to redo a step to correct errors. Maybe the team will observe the face of the customer who walks away either delighted or disappo inted with the service or it might be observed that there is little consistency in how different people perform a step. If one can observe an event (or even its effects) it can be measured. Once we can measure it, it can be improvedMeasure – Step 4: Identify Project Output Metric Page 94
  • 94. Data Collection Plan In Define, the team identified the main issue the project will focus on as well as critical customer requirements. 1. Identify WHAT to collect: Identify WHAT to Start by measuring to validate the team’s understanding of the size and frequency of the problem and how well the current process is meeting collect customer requirements. 1. 2. Create Operational Definition: Without having precise definitions for the data the team is trying to measure, it will be difficult to obtain valid and coherent data. Different people will count Create operational different things in different ways. Therefore the team comes up with an operational definition. definition 3. Validate Data Collection: 2. Collecting data is also a process – a measurement process. To ensure that the variation we observe in the data we collect is true, it is essential to minimize the variation in the data collection process. Validate data 4. Create Sample Plan & Collect Data: collection In data collection, sampling means measuring some of the items in a group 3. or process to represent them all. It is usually too difficult and expensive to count everything. Implement the data collection plan. Create sample plan & collect data 4.Measure – Step 5: Develop Data Collection Plan Page 95
  • 95. Identify WHAT to collect1. Identify WHAT to Collect 1. Be clear about the data collection goals to ensure the right data is collected.WHAT are we going to collect and why? State the questions to be answered and have a clear plan for analysis of your data. Many analysis tools have specific data requirements. If your data is in the wrong form or format, you may not be able to use it in your analysis. State the purpose of the data collection Identify what data is requiredSome questions to ask: What key questions do you need to answer? What data will provide the answers? What data do I need to measure performance against customer needs? How will the data be displayed and analyzed? What data is already available?Measure – Step 5: Develop Data Collection Plan Page 96
  • 96. Identify WHAT to collectSegmentation Introduction 1.Before collecting data, it is important to consider gathering segmentation Example:information in order to more easily pinpoint the patterns and causes of Think about collecting complaint data about cash loans. The data has beenproblems. collected – what are some questions the data should answer: ¦ Are there any diffe rences in region?Segmentation: By identifying potentially related factors, this method splits ¦ Are there any differences per branch?the data into smaller groups or categories in order to identify and comparedifferences in between these groups or categories. ¦ Are there differences by month? The Segmentation Factors must be identified and collected at These questions represent different ways the team can „slice and dice“ the the same time as the data is gathered data for analysis. Think about Segmentation Factors beforehand and build Importance of Segmentation: these factors/questions into the data collection plan Segmentation of data can give clues and further information about the root causes of problems. For instance, the team may find out that the customers in Region A complain three times more often than the rest of the regions. This would raise further questions such as: what is it about Region A and their processes that causes so many complaints? What do the other Regions do better?Measure – Step 5: Develop Data Collection Plan Page 97
  • 97. Identify WHAT to collectSome Segmentation Factors 1. Example: Application cycle time Why collect data?: People • Branch ¦ Obtain an understanding for the cycle time performance of credit approvals process • Customer Size ¦ Identify differences in performance • Customer Type WHAT data is needed?: Reasons • Reason for complaints ¦ Cycle time data for individual credit applications • Reason for service requirement ¦ Data on possible segmentation factors of the process: customer • Degree of satisfaction information, time/date application received within product type, processing center) Time • Month • AM/PM It is better to collect as many segmentation factors as possible. Once the data is collected the team can analyze the data as much as possible. It will • Day of week be too difficult to go back and collect data again when segmentation factors are missing. Location • Region • Market • CityMeasure – Step 5: Develop Data Collection Plan Page 98
  • 98. Create operational definition2. Create Operational Definition 2. It is essential that the team clearly defines each metric to be collected andDevelop specific instructions: the data collection process for obtaining the information. This ensures consistency. Attention to these details will help ensure that the data you collect will give you an accurate picture of the variation in your process. Clear operational definitions for all metrics Specific descriptions and instructions on how the measurement will be doneSome questions to ask: How will the team collect the data? How will the team record the data? What time period will be required for data collection? What sampling plan will be used?Measure – Step 5: Develop Data Collection Plan Page 99
  • 99. Create operational definitionOperational Definition Defined 2. To ensure that the Operational Definition is clear & concise, consider theOperational Definition: following: ¦ Different ways that people can interpret the same wordsA clear, understandable description of what is to be ¦ Changes or situations that may emerge which require specialobserved and measured so that different people interpret interpretationthe data and instructions consistently. ¦ Events or observations that can fit under more than one grouping/category or that might be interpreted and measured in several Remove ambiguity ways Ensure consistent understanding Provide clear instructions to measure the characteristic Identify what to measureMeasure – Step 5: Develop Data Collection Plan Page 100
  • 100. Create operational definitionElements of an Operational Definition 2. What will be measured? Example: ¦ What will be measured: Customer satisfaction in Region A What the measure is not ¦ What the measure is not: are “customer comments” included under Who will measure? complaints? Definition of the measure ¦ Who will measure: 2 Customer Service reps, 2 Team members How often will be measured? ¦ Definition of the measure: Sati sfaction: 80% of customers giving us a score of 90-100 How will the measure be obtained? ¦ How often will be measured: 1 month, 10 times a day ¦ How will the measure be obtained: start: incoming call of customer (first ring), stop: when customer hangs up The more precise and accurate the better. Leave no room for interpretation. Test it with colleagues before implementing it.Measure – Step 5: Develop Data Collection Plan Page 101
  • 101. Create operational definitionScale of Scrutiny 2. The scale of scrutiny is how finely you measure your process. MeasuringChoosing your measurement scale: What one level smaller than your customer allows you to more fully understand and capture the variation in the process.level of measurement is appropriate? Measure onescale or level smaller than what yourcustomer measuresExamples: Customer measures cycle time in days; team measures in hours Customer measures cycle time in hours; team measures in minutesMeasure – Step 5: Develop Data Collection Plan Page 102
  • 102. Create operational definitionCreating Data Collection Sheets 2. Once the team has decided what to collect and identified the segmentation Keep it simple – clear concise forms reduces the risk of factors it is essential that the data is collected correctly. A data collection errors sheet provides the structure needed for the collection process. All the decisions need to be documented on the data collection sheet to ensure Clear labels – there should be no question about where data consistency when gathering data. should go on the sheets The quality of the data collected depends on how well the data collection Name & date – this allows the team to keep track of which process and sheets are organized and prepared. data collector, at what day/time gathered information Leave room for comments – should questions arise or for specific remarks Include key factors to stratify the dataMeasure – Step 5: Develop Data Collection Plan Page 103
  • 103. Create operational definition Check Sheets 2. Check Sheet: Example: These types of data collection forms are used most often. It is a simple method to capture an error or event when it occurs.Name: _______________________Date: ___________Time:_______Application # Rep. Wrong Incorrect Signature Peronal Info Other: Comments: address amount missing missing421568 HR533891 TL908731 GF321760 GF Spouse‘s information missing759309 TL367289 HR936748 HR873651 TL283029 GF Measure – Step 5: Develop Data Collection Plan Page 104
  • 104. Create operational definitionFrequency Plot Check Sheets 2. Frequency Plot Check Sheet: Records a measure of an item along a scale or continuum. The FrequencyExample Plot generates a picture which illustrates how often events/errors occur. The Frequency Plot can also be displayed vertically. This check sheet should be used with continuous data. X X X X X X X X X X X X X X X X X X X X X X X X 0 1 2 3 4 5 6 7 8 Application Form Processing Cycle Time (hours)Measure – Step 5: Develop Data Collection Plan Page 105
  • 105. Create operational definitionConcentration Diagram 2. Concentration Diagram Check Sheet:Example: This check sheet shows a picture of an object or document being observed on which collectors mark where defects actually occur. Name: EECCEC Date: EE Address: EE Date of Birth: EEE Loan Amount: IIEIA Type of credit: EEEEEE Interest Rate: Duration: EEAEA Monthly Rate: AEAEAE Securities: EECCECCC Remarks: Signature: EE E: entry missing C: Copy of document missing I: incorrect Loan Amoount A: Arimthmetic errorMeasure – Step 5: Develop Data Collection Plan Page 106
  • 106. Create operational definitionSampling (1) 2. Now that the team has decided what and how they are going to collect data,Sampling is the practice of gathering a subset of the total the next step is to identify how much data must be collected in order to havedata available from a process or a population. It is often trustworthy and representative data for analysis. The validity of the data is impacted by many things such as, operationaltoo difficult and expensive to measure the whole definitions, data collection procedures and recording.population.However, if you only pick out a few (a sample), how can one be confident thatthis represents the whole group?Measure – Step 5: Develop Data Collection Plan Page 107
  • 107. Create operational definitionSampling (2) 2.Population (N): The entire set of objects or activities for a process Examples: : the mean (arithmetic average) calculated for a population ¦ Population = deck of cards, sample = 10 of diamonds, ace of hearts, : the standard deviation calculated for a population king of clubs ¦ Population = people arriving at a bank today; sample = every 5th person entering the bank today Sampling allows us to collect only a portion of the data that is available or could be available, and drawing conclusions about the total population (statistical inference). Population Sample (n) (N)Sample (n): A portion of the whole collection of items (population).x : the mean (arithmetic average) of a samples: the standard deviation of a sampleMeasure – Step 5: Develop Data Collection Plan Page 108
  • 108. Create operational definitionSampling (3) 2. One of the first questions to ask is “Do I need to sample?” The major reasonThe team should sample when: sampling is done is for efficiency reasons – it is often too costly or time consuming to measure all of the data. Sampling provides a good alternative Collecting the entire data is impractical or too expensive to collect data in an effective and efficient manner. If the circumstances surrounding the data collection plan do not justify sampling, then sampling Data collection can be a destructive process should not be done. This is often the case in low volume processes (e.g., deal processes). When measuring a high-volume processThe team should not sample when: Breaking the population into a subgroup may not accurately display the process. This in turn could lead to incorrect analysis upon which conclusions are then drawn. For instance, when every unit is unique – e.g., commercial dealsMeasure – Step 5: Develop Data Collection Plan Page 109
  • 109. Create operational definitionValidate Sampling 2. It is essential when sampling that the sample is valid. This means that theObtaining a representative sample: subgroup actually represents the whole population. Regardless of the situation, a sample must be “representative” of the Ensures that every part of the target population is represented population. For practical purposes a sample is representative if it accurately represents the target population. Considerations that may hinder collection (random sampling) of a representative sample include: The customer’s view is captured ¦ The cost and ease of obtaining samples ¦ Time constraintsHow to guarantee a representative sample: ¦ Unknown characteristics of the population Creating a sampling plan and strategy Samples that are not representative of a target population are called biased Understand special characteristics of the population before samples. Often, the biases are not recognized until the collected data has been analyzed. samplingMeasure – Step 5: Develop Data Collection Plan Page 110
  • 110. Create operational definitionBiased Sampling 2.Bias in a sample is the presence or influence of any factor that causes the Examples:population or process being sampled to appear different from what it actually ¦ Gathering data early in the morning when there is not a lot going on.is. Bias is introduced into a sample when data is collected without regard to This ignores data when things are busy which might be very differentkey factors that may influence it. data ¦ Surveying only those customers who had a score over 90 on the lastThis will influence your interpretation and conclusions about the problem or customer satisfaction surveyprocess. ¦ Using data that was collected in 1998Types of bias: Bias is introduced when the operational definitions and collectors procedures¦ Convenience Sampling: Collecting data because it is easy to collect are inconsistent.¦ Judgement Sampling : Making educated guesses about which items or people are representative of the process¦ Environmental Sampling: When the environment has changed from the time the sample was taken to the time the sample is used for analysisMeasure – Step 5: Develop Data Collection Plan Page 111
  • 111. Create operational definitionDefine Sampling Process 2.Population Sampling Population Sampling: - I have 95% confidence that the mean of the population is between ? Make probability statements about the population from 1.5 and 2.5 seconds the sample - Use sample size formula ? For instance, this process assumes that we have a large, Process Sampling: standing pool of water (or data), and if we take a spoonful at any point, it will represent the rest of the water (or - Are shifts, trends, or cycles occurring? - Use rational subgrouping data). Population Sample (n) (N)Process Sampling ? Assess the stability of the population over time ? This approach requires taking a sample from a running stream of water that may be changing minute by minute, depending on what you are measuring. Process Process SampleMeasure – Step 5: Develop Data Collection Plan Page 112
  • 112. Create operational definitionPopulation Sampling (1) 2. Random samples are computer generated using MinitabTM or a randomRandom Sampling approach number table.Random sampling means that every item in a population or process has anequal chance to be selected for counting. Using random sampling protectsagainst bias being introduced in the sampling process and helps in obtaininga representative sample. Random sampling is done by assigning computer-generated random numbers to the items being surveyed. Population Sample (N) (n)Each item has an equal chance of being selected.Measure – Step 5: Develop Data Collection Plan Page 113
  • 113. Create operational definitionPopulation Sampling (2) 2. Example:Stratified Random Sampling If your company has a customer base of 100,000 customers, and your teamStratified random sampling is used when the population has different g roups wants to observe a sample to determine customer satisfaction, it is highly(strata) and we need to ensure that those groups are fairly represented in the unlikely that the team is interested in what 100,000 customers have to say. The team knows there are 4 Regions of different sizes and therefore wantedsample. In stratified random sampling, independent samples are drawn from to the sample to have the same proportion. The team first separated theeach group. The size of each sample is proportional to the relative size of the customers into 4 groups and then pulled a random sample from each.group.A stratified random sample helps avoid gaps that may arise when data iscollected over a large population where key subgroups of the population areunderrepresented. Population Sample Region 2 Region 1 111111 222 33333333333 444444 Region 4 Region 3Measure – Step 5: Develop Data Collection Plan Page 114
  • 114. Create operational definitionProcess Sampling (1) 2. Systematic sampling is typic ally used in process sampling situations whenSystematic Sampling data is collected “real time” during process operation. It is important that a frequency for sampling is selected. Systematic sampling involves taking samples according to some systematic rule – e.g., every 4 th unit, the first five units every hour, etc.This method is recommended for most business processes. By systematicsampling of a process we mean taking data samples at certain intervals(every hour, or every 5 th item).However, one must be very cautious that the systematic sampling does notcorrespond to some hidden pattern that will bias the data. For instance,sampling every 20th application might result in the fact that you always getapplications checked by the same rep rather than the 9 other reps whoseapplications are ignored. Process SampleSampling frequency must be determined – sampling every nth hour, day, itemetc.Measure – Step 5: Develop Data Collection Plan Page 115
  • 115. Create operational definitionProcess Sampling(2) 2. Creating Rational Subgroups:Rational Subgrouping Form subgroups with items produced under similar conditions.Rational subgrouping is the process of putting measurements into meaningful To ensure items in a subgroup were produced under similar conditions, select items produced close together in time.groups to better understand the important sources of variation. Rational Subgrouping over time is the most common approach; subgrouping can besubgrouping is typically used in process sampling situations when data is done by other suspected sources of variation (e.g., location, customer,collected “real time” during process operations. supplier, etc.). For example, sampling three statements per hour that that were generated under the same circumstances. Process SampleMeasure – Step 5: Develop Data Collection Plan Page 116
  • 116. Create operational definitionDetermine Sample Size (1) 2.Some guidelines (Rules of Thumb) Tool or Statistic Minimum Sample SizeAverage 5-10Standard Deviation 25-30Proportion Defective (P) 100 & nP > 5Histogram or Pareto Chart 100Scatter Diagram 25Control Chart 20n= sample sizeP= Probability of defectiveMeasure – Step 5: Develop Data Collection Plan Page 117
  • 117. Create operational definitionDetermine Sample Size (2) 2.¦ To estimate the population average to within +/- „? “ with 95% confidence, you will need a sample size of: n = (1,96s/?)2¦ To estimate the population proportion to within +/- „? “ with 95% confidence, you will need a sample size of: n = (1,96/? )2*p(1-p)¦ Note that to estimate the average, you need to know the standard deviation, and to estimate the proportion, you need to know it already! For this reason, we often begin with the “Rule of Thumb” sample sizes, and if they are not sufficient, we have estimates of s or p to use in the exact formulas, and can calculate how much more data is neededn = sample sizep = probability defective? = precisionMeasure – Step 5: Develop Data Collection Plan Page 118
  • 118. Validate data collection3. Validate Data Collection (1) 3.Going back to the data collection plan, the team needs to ensure that themeasurements are accurate and reliable. Measurement practices and devicesthemselves are subject to variation. No matter how well the people aretrained. It is likely that they will vary slightly in how they collect data.Measuring devices (instruments) are know to degrade in precision over time. Total Variation = Process Variation + Measurement VariationWhen the team collects the data, we will be seeing the process through theway we measure and collect the data. The variation that is observed is neverjust the true process variation – it will always include the variation in themeasurement system.It is important that the team focuses on reducing the measurement variationbefore collecti ng the data to analyze the process variation.Measure – Step 5: Develop Data Collection Plan Page 119
  • 119. Validate data collection3. Validate Data Collection (2) 3.Measuring or collecting data is a process. This measurement process needsto be examined as well in order to validate that the variation in themeasurement process represents only a small fraction of the overall variationin the data.There are a variety of methods used to examine data consistency andstability of measurement systems. The approach used depends on the type ofdata being measured.1. Determine which method is appropriate based on the type of data collectedTwo Approaches: For continuous data - a “Gage R&R” (repeatability and reproducibility) study is performed For discrete data - a Discrete Data Analysis is performedMeasure – Step 5: Develop Data Collection Plan Page 120
  • 120. Validate data collection3. Validate Data Collection (3) 3.Gage R & R Example and Calculation: _ _ CAUTION! R AND X DIFF ARE THE DRIVERS FOR ALL THE REMAINING Oper ator A B C CALCULATIONS BE SURE THEY ARE Sample 1st 2nd 3rd 1st 2nd 3rd 1st 2nd 3rd of Trial Trial Trial Range Range Trial Trial Trial Range Trial Trial Trial Range CORRECT 1 7.1 7.3 7.2 0.2 7.6 7.5 7.5 0.1 7.0 7.1 7.1 0.1 RA 0.24 2 13.2 13.3 13.4 0.2 13.4 13.7 13.6 0.3 13.0 13.3 13.3 0.3 3 2.1 2.1 2.1 0.0 2.6 2.5 2.6 0.1 2.2 2.0 2.0 0.2 RB 0.25 4 27.2 27.5 27.5 0.3 28.2 28.1 28.2 0.1 27.6 27.8 27.4 0.4 MAX X 16.44 R C 0.23 5 18.9 18.8 18.5 0.4 19.1 19.4 19.1 0.3 19.0 18.8 18.8 0.2 MIN X 16.00 SUM 6 3.1 3.1 3.3 0.2 3.6 3.6 3.7 0.1 3.2 3.2 3.3 0.1 = X DIFF 0.44 0.24 7 21.3 21.5 21.6 0.3 22.2 22.0 22.0 0.2 21.7 21.7 21.4 0.3 R 8 6.4 6.4 6.6 0.2 7.2 6.9 6.8 0.4 6.5 6.7 6.7 0.2 9 38.2 38.5 38.6 0.4 38.6 38.8 39.1 0.5 38.7 38.6 38.5 0.2 10 21.8 21.8 21.6 0.2 21.6 21.9 22.0 0.4 21.6 21.9 21.8 0.3 Totals 0.24 0.25 0.23 _ SUM RA SUM RB SUM RC AVERAGE XA 16.00 AVERAGE XB 16.44 AVERAGE XC 16.06Measure – Step 5: Develop Data Collection Plan Page 121
  • 121. Validate data collection3. Validate Data Collection (4) 3.Gage R & R Example and Calculation: Gage R&R Report Calculations: Repeatability (EV) and Reproducibility (AV) Part No. & Name Date & Signature Gage Name Characteristic Gage No. From Data Sheet Total Tolerance = 6 R= 0.24 Xdiff = 0.44 MEASUREMENT UNIT ANALYSIS % TOLERANCE ANALYSIS Repeatability: Equipment Variation (EV) [Within Variation] No. Trials (m) 2 3 % EV = 100 [(EV) / (Tolerance ) ] EV = (R) x (a) = 100 [( 0.732 ) / (6)] a 4.56 3.05 = 12.2 = ( 0.24 ) x ( 3.05 ) = 0.732 Reproducibility: Appraiser Variation (AV) [Between Variation] Operators 2 3 % AV = 100 [(AV) / ( Tolerance)] [(X diff ) x (b)]2 - [ (EV)2 / (n x m)] = 100 [( 1.18 ) / ( 6 )] b 3.65 2.70 = 19.7 = [( 0.44 ) x ( 2.70 )]2 - [( 0.732 )2 / ( 30 )] n = number of parts = 1.18 m = number of trials (repeated measurements) Gage R&R Gage R&R % R&R = 100 Tolerance (EV) 2 + (AV)2 = 100 1.39 = ( 0.732 )2 + ( 1.18 )2 6 = 23.2 = 1.39Measure – Step 5: Develop Data Collection Plan Page 122
  • 122. Validate data collection3. Validate Data Collection (5) 3.2. Determine which factors of measurement error are most relevant for the study (accuracy, repeatability, reproducibility, stability)¦ Accuracy – How precise is the measurement? Accuracy focuses on the differences between observed average measurement and a standard¦ Repeatability – How much variation is there between the measurements? If the same person measures the same unit with the same measuring device, will the same results be achieved every time?¦ Reproducibility – If two or more people or device measure the same thing, will the same results be produced? Reproducibility is the variation when two or more people measure the same unit with the same measuring equipment¦ Stability – How much accuracy, repeatability, and reproducibility change over time? Do we get the same variation in measures as we did a week ago? A month ago? Stability is the variation obtained when the same person measures the same unit with the same equipment over an extended period of time3. Measure units repeatedly. How items are measured depends on the aspect being quantified4. Determine if the measurement process must be improved. How much error is allowed for the data and how the process will be improved if the error is too bigMeasure – Step 5: Develop Data Collection Plan Page 123
  • 123. Validate data collection3. Validate Data Collection (6) 3.Determine which aspects of measurement error arerelevant for validating the data collection process.Accuracy:Is the difference between an observed averagemeasurement and a standard. Accuracy Standard Value Observed AverageValidating accuracy is the process of quantifying the amount of bias(inaccuracy) in the measurement process. In service applications this mostoften involves testing the judgment of people carrying out themeasurements.The most common approach for correcting inaccuracy in a measurementprocess is calibration. This is usually a problem when the people orequipment doing the measuring tend to “drift” over time.Measure – Step 5: Develop Data Collection Plan Page 124
  • 124. Validate data collection3. Validate Data Collection (7) 3.RepeatabilityIs the variation when one person repeatedly measures thesame unit with the same measuring equipment. Repeatability (Minimum variation)Repeatability represents the ability of the measurement process toconsistently repeat measurements. Repeatability is determined by taking oneperson, or one measurement device, and measuring the same units or itemsrepeatedly. Differences between the repeated measurements represent theability of the person or measurement device to be consistent.Validating repeatability is the process of quantifying the amount ofinconsistency in the measurement process. In service applications thisinvolves testing the judgement of people carrying out the measurements, andwhether or not those judgements measurements) are consistent over time.Measure – Step 5: Develop Data Collection Plan Page 125
  • 125. Validate data collection3. Validate Data Collection (8) 3.ReproducibilityIs the variation when two or more people measure the sameunit with the same measuring equipment. Person 1 Person 2 ReproducibilityReproducibility is very similar to repeatability. The only difference is thatinstead of looking at the consistency of one person, we are looking at theconsistency between people.Validating reproducibility is the process of quantifying the amount ofinconsistency in the measurement process across people or measurementdevices. In service applications this most often involves testing the judgementof people carrying out the measurements, and whether or not thosejudgements (measurements) are consistent across people.Measure – Step 5: Develop Data Collection Plan Page 126
  • 126. Validate data collection3. Validate Data Collection (9) 3. What is the impact of the error (whetherStability accuracy, repeatability, reproducibility, or stability) on the measurement process?Is the variation obtained when the same person measuresthe same unit with the same equipment over an extended ¦ Examine context of business environmen t, process, and customerperiod of time. ¦ How critical is the measurement? ¦ What are the risks of making an error? ¦ Review results of the study ¦ General guidelines for Gage R&R for Continuous Data: - Gage R&R less than 10%: Measurement system acceptable - Gage R&R 10%-30%: Measurement system may be acceptable - Gage R&R over 30%: Measurement system not acceptable3. Stability Validate Data Collection process (5) Time 1 Time 2Stability is similar to repeatability except that the units are re-measured overan extended period of time. The analysis of stability is conducted in the sameway as repeatability.5. Review the measure process periodically to ensure accurate and consistent measurements.Measure – Step 5: Develop Data Collection Plan Page 127
  • 127. Create sample plan & collect data4. Validate Sample Plan and Collect Data 4.Prepare the working environment: Communicate the “what” and “why” to the data collectors and process participants Explain what the team is going to do with the data; including your plan to share the results with the data collectors, keeping identities confidential etc.Test the Data Collection Procedures: Be careful who is chosen to collect data – avoid making data collection a reward or punishment Train everyone who will be collecting data Pilot the data collection process and adjust as needed Confirm understanding of operational definitions Make data collection procedures error-proofMonitor accuracy and refine procedures as appropriate: Supervise ongoing data collection efforts and monitor both the procedures and equipment (if any) used to gather the dataMeasure – Step 5: Develop Data Collection Plan Page 128
  • 128. Understanding the Data (1) Another important aspect of process improvement is the measurement,Describe and display Variation reduction and control of variation. Variation is present in all process, whether they are personal processes (brushing your teeth, going to work) or business processes (application cycle time, time to payment). The output of a process Understand that Variation in the data represents the voice of will vary as it is repeatedly performed. Although the customers may accept the process some variation, when variation is too extreme customers will be dissatisfied. Recognize two general types of Variation – Common Cause and Special Cause – and the implication of the different causes Use appropriate tools to study Variation Understand process variation to identify and control/eliminate the primary sources or causes of the VariationMeasure – Step 5: Develop Data Collection Plan Page 129
  • 129. Understanding the Data (2) The first step is to graphically display the data If the team is studying variation for a specific time frame, then the following tools can be used to display the data collected. Histogram Frequency Measurement item/categoryGraphs for Continuous Data Graphs for Discrete Data¦ Histogramm ¦ Bar Chart¦ Frequency Diagram ¦ Pie Chart¦ Box Plot¦ Multi-Vari-Chart Measure – Step 5: Develop Data Collection Plan Page 130
  • 130. Understanding the Data (3) If the team is studying variation over time, then the following tools can be used to display the data collected. Run Chart Measurement Unit TimeGraphs for Continuous Data Graphs for Discrete Data¦ Control Chart ¦ Control Chart¦ Run Chart Measure – Step 5: Develop Data Collection Plan Page 131
  • 131. Understanding the Data (4) Key QuestionsHistograms ¦ What is the shape of the distribution – symmetrical, lopsided, cliff-like shape, twin peaks, flat? Histogram ¦ What is the central tendency (“center” or “average”) of the distribution? ¦ What is the variation (“spread”) of the distribution – wide or narrow? Different measures are used to describe central tendency (center) and variation (spread). The shape of a distribution dictates which measures are Frequency most appropriate. Measurement item/categoryMost often, Histograms are the first tool used to generate a rough picture ofthe data collected. The visual display of the data provides i nsight and cluesinto how the process is operating.Histograms provide a picture of the location or center of the data, thedispersion, spread, or variation of the data, the shape of the data, andevidence of extreme or outlying points.Measure – Step 5: Develop Data Collection Plan Page 132
  • 132. Understanding the Data (5) Shape of the Data Normal Distribution Bi-modal Distribution Skewed DistributionFrequency Frequency Frequency The shape of a data set can be determined by examining a histogram, or, if testing the distribution for normality, using a “Normal Probability Plot.” There are many different shapes a data set may assume. The plots above illustrate three common shapes. A normal distribution, a bimodal distribution, and a skewed distribution. Because of its predictive qualities, the normal distribution is of special interest. Measure – Step 5: Develop Data Collection Plan Page 133
  • 133. Understanding the Data (6)The Normal CurveWhat is the Normal Curve:A probability distribution where the most frequently occurring value is in themiddle and other probabilities tail off symmetrically in both directions.Elements of the Normal Curve: Curve theoretically does not reach zero Curve can be divided in half with equal pieces falling either side of the most frequently occurring value The peak of the curve represents the center of the process The area under the curve represents virtually 100% of the product the process is capable of producingMeasure – Step 5: Develop Data Collection Plan Page 134
  • 134. Understanding the Data (7) The normal curve can be divided into a series of segments. Each segment isThe Normal Curve mathematically called a standard deviation from the mean. It is also noted by the small s. As you can see, the curve is first segmented into one standard deviation which represents approximately 34% of whatever you are measuring. Because the curve is symmetrical, going one standard deviation in the other direction represents approximately 68% of whatever it is you are measuring. Going out +/– 2 standard deviations is equal to approximately 95% of whatever you are measuring and +/– 3 standard deviations is equal to 99.73% of whatever you are measuring. Most common statistical terms 34.13% 34.13% and analysis tools are based on a normal data distribution. If we use these tools with a data set that is not normal, the accuracy of the tools may be compromised. 13.60% 13.60% 2.14% 2.14% 0.13% 0.13% -3s -2s -1s X +1s +2s +3s 68.26% 95.46% 99.73% 68.26% Fall Within +- 1 Standard Deviation 95.46% Fall Within +- 2 Standard Deviation 99.73% Fall Within +- 3 Standard DeviationMeasure – Step 5: Develop Data Collection Plan Page 135
  • 135. Normal Probability Plot (1) Why Is A Normality Test Useful?Another way to describe shape Many statistical tests (tests of means and tests of variances) assume that the data being tested is normally distributed. A normality test is used to Normal Probability Plot for Length determine if that assumption is valid. ML Estimates - 95% CI When Should I Use A Normality Test? ML Estimates There are two occasions when you should use a normality test: Mean 61,2825 99 ¦ When you are first trying to characterize raw data, normality testing is StDev 9,31969 95 used in conjunction with graphical tools such as histograms and box 90 Goodness of Fit plots 80 AD* 0,636 ¦ When you are analyzing your data, and you need to calculate basic Perce nt 70 60 50 statistics such as Z values or to employ statistical tests that assume 40 30 normality, such as t-Test and ANOVA 20 10 5 1 30 40 50 60 70 80 90 DataWhat Is A Normality Test?A normality test is a statistical process used to determine if a sample, or anygroup of data, fits a standard normal distribution. A normality test can bedone mathematically or graphically. A normality test can be thought of as a“litmus test” for determining if a distribution is a normal distribution. The Y axisis the cumulative % of data points which fall below the value on the X axisMeasure – Step 5: Develop Data Collection Plan Page 136
  • 136. Normal Probability Plot (2) Straight Line Bimodal Curve Skewed Curve Long tailed 20 6 6 7 5 5 Frequency 6 Frequency Frequency 4Frequency 5 4 4 10 3 3 3 2 2 2 1 1 1 0 0 0 0 12 13 14 15 16 17 18 19 7 9 11 13 15 17 19 21 23 0 10 20 30 40 50 60 70 80 90 7 9 11 13 15 17 19 21 23 99 99 95 95 90 90 PercentagePercentage Percentage Percentage 80 80 70 70 60 60 50 50 40 40 30 30 20 20 10 10 5 5 1 1 0 10 20 30 0 10 20 30What does the distribution look like on the Normality Curve:The Normal Probability Plot is another way besides the histogram to plot dataand look for normality.Normal data, when plotted with the data value on the X-axis and speciallyspaced percentiles of the normal distribution on the Y-axis, will fall on astraight line. 95% confidence limits are shown around the line.In the top diagram on the left, we see that all of the data points roughly form astraight line and fall within the limits. We would conclude that there is noserious departure from normality in this data. In the other diagrams, we seethat many of the data points fall outside the limits and do not form a straightline. We would therefore conclude these data sets significantly depart fromthe normal distribution.Measure – Step 5: Develop Data Collection Plan Page 137
  • 137. Understanding the Data (8) When looking at a histogram of the data, a good guess can be made aboutCentral Tendency where the central tendency of the process is. A more precise estimate of central tendency can be made using descriptiveShows the main emphasis and focal point of the process statistics such as the mean, median, or quartile values. It is important to know the distribution shape because it dictates which metrics should be used for analysis. ¦ Mean (x): x ¦ Median: ¦ Quartile (Q1, Q3) Q1 Q3Measure – Step 5: Develop Data Collection Plan Page 138
  • 138. Understanding the Data (9)Calculating Central Tendency:Mean:Sometimes called the average, is the most likely or expected value. Theformula for the mean is: ? xi 1. Sum of all values X= n 2. Divided by number of data pointsMedian:The median is literally the middle of the data set where 50% of the data isgreater than the median, and 50% of the data is less than the median. Themost commonly used symbol for the median is X. The procedure forcalculating the median is:¦ Order the numbers from smallest to largest¦ If the number of values (N) is odd the median is the middle value. For example, if the ordered values are 3, 4, 6, 9, 20 the median is 6¦ If the number of values (N) is even, the median is the average of the two middle values. For example, if the ordered values are 1,5,8,9,12,18 the median is 8.5Q1/Q3:Q1 is the data point that divides the lowest 25% of the data set from theremaining 75% and is used to describe performance when the data is skewedtoward the right. Q3 is the data point that divides the highest 25% of the dataset from the remaining 75% and is used to describe performance when thedata is skewed toward the left.Measure – Step 5: Develop Data Collection Plan Page 139
  • 139. Understanding the Data (10) Using descriptive statistics, the spread of the data can be examined.Dispersion: represents the variation of the process Standard Deviation: It is the average distance a given point is away from the mean. s 1. Subtract each data value from the mean 5. Take the square root of the result 2. Square each Standard Deviation difference n ? (x - xi)2 I=1 3. Sum up these values n-1 4. Divide by one less of the data values Span: Span Span is used to indicate the amount of variati on in a long -tailed distribution. It is the distance between the two extremes of the data set. Since span should not be determined by only one or two data points, in general P95 and P5 is used (although this changes depending upon sample size). The span is the number of data points between P95 and P5. Stability Factor: The stability factor (SF) is the ratio of the first quartile and third quartile values. The formula for Stability Factor is: SF = Q1/Q3 In general the Q1 Q3 Q1 Q3 stability factor is interpreted such that the closer SF is to one, the less Stability factor variation there is in the process, and the closer SF is to 0, the more variation there is in the process. (SF) = Q1/Q3Measure – Step 5: Develop Data Collection Plan Page 140
  • 140. Displaying Variation For A Period of Time (1) Collect Data Graphically display it using a Histogram Describe the data using statistical measures ? Central tendency (center) of the data ? Variation (spread) of the data ? Shape (pattern) of the dataHistograms combined with basic descriptive statistics provide a clear pictureof the current performance of a process.Measure – Step 5: Develop Data Collection Plan Page 141
  • 141. Displaying Variation For A Period of Time (2)Taking a closer look at Histograms – below there are severalhistograms showing possible causes and corrective action forunusual patterns. Histogram Histogram Observation Observation Conclusion Conclusion Action Action Five or fewer Measurement Improve the distinct values process not measurement sensitive enough process One value is Measurement Look for causes common process may of bias be biased Zig-zag pattern Inconsistent Standardize how rounding measure is takenMeasure – Step 5: Develop Data Collection Plan Page 142
  • 142. Displaying Variation For A Period of Time (3)Box Plots are graphical summaries of the patterns of variation in sets of data. Outlier * Highest value Q3 Value (75%) Median Q1 value (25%) Lowest valueMeasure – Step 5: Develop Data Collection Plan Page 143
  • 143. Displaying Variation Over Time (4)Run Charts Median A graphical tool to monitor Project Output over time Gives a general understanding of the Variation in a processRun Charts are simple time ordered plots of data. On these plots one canperform tests for certain patterns in the data. Presence of these patternsindicate special causes.Measure – Step 5: Develop Data Collection Plan Page 144
  • 144. Types of Variation If one of these patterns is present in the data we conclude that there are Common Cause special causes. We then investigate those specific data points that are correlated with the special cause signals. Special CauseTo interpret Run Charts you look for patterns that indicate the presence ofspecial causes. Those patterns are: ? Shift: 8 or more consecutive points on the same side of the centerline ? Same Value: 7 or more consecutive points having the same value ? Trend: 7 or more consecutive points increasing or decreasing ? Cycle: 14 or more consecutive points up and down Shift Same value Trend CycleMeasure – Step 5: Develop Data Collection Plan Page 145
  • 145. Establish Process BaselineCalculating Process Sigma gives the team the ability to compare the Process Sigma is a common metric for comparison.Voice of the Customer, expressed as a CTQ, to the Voice of the Processes with different kinds of measures are difficult to compare. In orderProcess, expressed as process variation. to compare apples with oranges they have to have the same measurement value. We need a means of comparing processes that are measured differently. Process Sigma is one measure of capability that we can use to express process performance with respect to customer requiremen ts for any process. CTQ Voice of the Customer Voice of the ProcessIt provides a standard for evaluating how “capable” the process is of meetingthe customers’ CTQs. As our capability increases so does the sigma value –the larger the better.Terminology:s = Standard deviation of a sample? ?= Standard deviation of a populationZ ST = Statistical unit of measure that reflects process capabilityMeasure – Step 6: Establish Process Baseline Page 146
  • 146. Process Sigma Defects per MillionProcess Sigma (Zst) Yield Opportunities (DPMO) 1 690.000 31% 2 308.537 69,2% 3 66.807 93,32% 4 6.210 99,379% 5 230 99,977% 6 3.4 99,99966%(*Values include +/- 1. shift)Measure – Step 6: Establish Process Baseline Page 147
  • 147. Calculating Process Sigma2 Methods: No Yes Are defect counts <5 (or non-defects <5) Yes Is data continuous? No Increase sample size or Increase sample size or collect continuous data collect continuous data Use Discrete Path See MBB for See MBB for transformation transformation Calculate DPMO Calculate DPMO No IIsdattarroughly s daa oughly norrmaly distribuuted? no mall ly distrib ted? Yes Use Continuous Path Look up in Look up in Sigma Table Sigma Table S Draw picture and label x, s, LSL USL USL, LSL x Skip ififno USL: Find shaded area to the right of USL Skip no USL: Find shaded area to the right of USL ( Area 1 = 1 – norm dist. USL – x Area 1 = 1 – norm dist. USL – x s s ) Skip if no LSL: Find shaded area to left of LSL Skip if no LSL: Find shaded area to left of LSL Area 2 = norm dist. LSL – x Area ( dist. LSL – x s s ) Total Area = Area 1 + Area 2 Total Area = Area 1 + Area 2 Yield = (1 – Total area) 100% Yield = (1 – Total area) 100% Sigma table: Look up yield to determine Process Sigma Sigma table: Look up yield to determine Process SigmaMeasure – Step 6: Establish Process Baseline Page 148
  • 148. Normal Curve Probabilities Normal Distribution Standard Deviation Uses actual data: Standardizes data to: Average = 30 Average = 0 Standard Deviation = 5 Standard Deviation = 1 68% 95% 99,7% - + Values: 15 20 25 30 35 40 45 Z-Values: -3 -2 -1 0 1 2 3Z score is a unit of measure that is equivalent to the number of standarddeviations a value is away from the mean value.Measure – Step 6: Establish Process Baseline Page 149
  • 149. Calculating Standard Normal for anyDistribution Standard Normal Mean = 0 2 -1 0 1 2 ? s=1 Mean = 27 s=8 11 19 27 35 43 49 Mean = X s=s X ? ?2s X ? ?s X X X+s X + 2s USL X– or X of interest – X Converting to Z = Standard Normal s In this example: USL – X 49 - 27 = = 2,75 s 8Measure – Step 6: Establish Process Baseline Page 150
  • 150. Process Capability Analysis (1) This is a distribution for the Project Output (Application Processing length). Process Capability Analysis is a means of comparing the total process Application processing length is the amount of time required to process an performance to the specifications set for the process. The team compares the application. To measure capability for a one-sided specification, we need to actual Project Output Performance to the customer CTQs as defined earlier in determine the fraction of total process performance that is greater than the the measure phase. 45-minute specification. Estimating the percentage of defects allows us to use this data to compare it against the normal distribution and obtain an In cases where a one-sided specification exists, it measures how often the estimate for Process Sigma. Project Output metric falls in the desired range of possible output. Length of Application Processing Calculate % defects that are May outside the Upper Specification Limit Upper Upper 400 Specification = 45 Specification Limit LimitNumber of Applications 200 0 0 15 30 45 Minutes Actual Process Output Actual Process Output Performance (Variation) Performance (Variation) Defects Measure – Step 6: Establish Process Baseline Page 151
  • 151. Process Capability Analysis (2) While the normal distribution theoretically never really touches the x-axis, the Process Capability is a measure in “Standard Deviation Units (Z)” of how far area underneath the curve at points beyond three standard deviations is so the process mean is from the performance standard. small it is difficult to display and/or view. The distribution appears to “touch” the x-axis at +/- 3s. In the case of many Project Output measurements, a natural boundary•Z = # standard deviation units between the specification limit and the mean exists. For example, the lower boundary for call answering time is zero – it is USL USL - X a natural boundary and not necessarily dictated by the customer. In these•Z = s process cases, only one Z -score – the distance from the mean to the customer specification – is calculated in standard deviation units. At 6 X - LSL•Z = LSL Sigma performance, the distance from the process mean to the customer s specification is at least six standard deviation units. How far (in standard deviation units) is the mean from the specification (Lines A+B) Lower Upper specification specification limit limit A B ? s -3 -2 -1 +1 +2 +3 - 3 -2 -1 +1 +2 + 3 Measure – Step 6: Establish Process Baseline Page 152
  • 152. Review Key Terms The definitions are based on the Project Output metric and performanceDefinitions of Six Sigma Output Performance standards and will be used later in the Measure phase to calculate Process Sigma or capability. The “defective” terminology is used when there is moreMeasures: than one defect opportunity per item/unit. A single item/unit could have more than one defect – the total number of defects is important because itUnit: An item being processed, or the final product or service being represents the overall magnitude of the problem. It only takes one defect perdelivered either to internal customers (other employees working for the same unit to represent a problem from a customer’s perspective so looking at thecompany as the team) or external customers (the paying customers). percent of units with a last one defect gives us a perspective of how the customer sees the overall process performance.Defect: Any failure to meet a customer requirement or performance Notice that if items/units contain a number of defects, it is possible to reducestandard. the overall total number of defects without having much impact on the percent of defective units. We need to be aware of both the total number of defects and the percent of units containing defects.Defect Opportunity: A chance that a product or service might fail tomeet a customer requirement or performance standard.Defective: An item/unit with one or more defectsMeasure – Step 6: Establish Process Baseline Page 153
  • 153. Guidelines For Counting Defects The defect opportunity must be important to the customer (relate to a CTQ) The number of opportunities per unit can be used to compare performance of processes and outputs of different complexities. The higher the complexity, the higher the number of opportunities per unit Only count defects that can reasonably happen – if it has never been a problem, don’t count it. Don’t inflate opportunities per unit to drive up sigma Only one opportunity is counted if one defect automatically leads to another. Make sure opportunities per unit stay constant before and after improvement (unless an opportunity for defect is eliminated as a result of a solution)Measure – Step 6: Establish Process Baseline Page 154
  • 154. Proportion Defective & Yield Calculation (1)The Proportion Defective Count and Yields are related measures. Yield represents the percent of good products or services (measured in %) Defect Counts monitor the number of times things go wrong and are measured in Defects Per Opportunity –(DPO) or Defects Per Million Opportunities (DPMO) Calculations: D D D DPO = DPMO = 1.000.000 • Yield = 1 – N•O N•O N•OD = Number of defectsN = Number of unitsO = Opportunities Per Unit*To find corresponding Process Sigma value, look up in “Abridged ProcessSigma Conversion Table”, page 141.Measure – Step 6: Establish Process Baseline Page 155
  • 155. Proportion Defective & Yield Calculation (2)Calculate Final Yield & First-Pass YieldFinal: 2,000 1,957 Input Output Units Units Defectives= 43 units Final Yield = .9785 Process = 3.5Imagine a service process (see figure above) where data was collected andthe output of the process shows a Final Yield of .9785 (97.85) and a sigmaleve l of 3.5. Of the original 2,000 Units that entered the process only 1,957came out “defect-free” at the end of the process.Measure – Step 6: Establish Process Baseline Page 156
  • 156. Proportion Defective & Yield Calculation (3) Therefore, of the 2,000 units only 1,897 remained “defect free” throughoutHowever, if we look inside this process, we will notice that it has 3 major sub- the whole process. The other 103 needed some rework. Some of that reworkprocesses. The company catches and reworks defects, and over the course was beneficial since customers received 1,957 “defect free” units.of a whole process, 103 units have to be reworked before delivery to the Calculations:paying customers.First-Pass: Final: D2 D2 Final DPO = D2 Final DPMO = 1.000.000 • Final Yield = 1 – N•O N•O N•O 2,000 .9825 Yield .987 Yield .979 Yield 1,897 First-Pass: Input Output = 3.6 = 3.7 = 3.5 D Units Units First-Pass DPO = D 1 First-Pass Yield = 1 – 1965 1939 1897 First-Pass DPMO = 1.000.000 • N•O N•O Units Units Units D1 1 N•O Rework Rework Rework 35 Units 26 Units 42 Units Defectives= 103 units First Pass Yield = .959 Process = 3.2Measure – Step 6: Establish Process Baseline Page 157
  • 157. Proportion Defective & Yield Calculation (4) As was illustrated in the previous example, once you take into account allCalculate Final Yield & First-Pass Yield the rework that has to take place, the percentage of “defect free” falls to 95.9%:The comparison of these two types of yield introduces two important SixSigma terms: The comparison of these two measures of yield points out the difference between focusing only on outputs (final yield) versus looking at what Final Yield : measures how many units finally come through happens inside a process (first-pass yield). Yields that are measured only as the process without defects outputs hide defects and the costs associated with them. In some service businesses estimates have shown that the costs associated with a low first- First-Pass Yield : measures the number of units that made it pass yield can reach 20% or more of total sales revenues. through the first time without needed reworkTo calculate Process Sigma, First-Pass Yield is used for theFollowing reasons: Defects once produced add waste and cost (some costs are easy to quantify and some not) Even the best inspection processes cannot catch all defects The payback is generally bigger to keep defects from occurringMeasure – Step 6: Establish Process Baseline Page 158
  • 158. Abridged Process Sigma Conversion Table Defects Defects Defects Defects Defects Defects Defects Defects Defects Defects Long Term Process- Long Term Process - per per per per per per per per per per Yield Sigma (ST) Yield Sigma (ST) 1.000.000 100.000 10.000 1.000 100 1.000.000 100.000 10.000 1.000 100 99.99966% 6.0 3.4 0.34 0.034 0.0034 0.00034 93.320% 3.0 66,800 6,680 668 66.8 6.68 99.9995% 5.9 5 0.5 0.05 0.005 0.0005 91.920% 2.9 80,800 8,080 808 80.8 8.08 99.9992% 5.8 8 0.8 0.08 0.008 0.0008 90.320% 2.8 96,800 9,680 968 96.8 9.68 99.9990% 5.7 10 1 0.1 0.01 0.001 88.50% 2.7 115,000 11,500 1,150 115 11.5 99.9980% 5.6 20 2 0.2 0.02 0.002 86.50% 2.6 135,000 13,500 1,350 135 13.5 99.9970% 5.5 30 3 0.3 0.03 0.003 84.20% 2.5 158,000 15,800 1,580 158 15.8 99.9960% 5.4 40 4 0.4 0.04 0.004 81.60% 2.4 184,000 18,400 1,840 184 18.4 99.9930% 5.3 70 7 0.7 0.07 0.007 78.80% 2.3 212,000 21,200 2,120 212 21.2 99.9900% 5.2 100 10 1.0 0.1 0.01 75.80% 2.2 242,000 24,200 2,420 242 24.2 99.9850% 5.1 150 15 1.5 0.15 0.015 72.60% 2.1 274,000 27,400 2,740 274 27.4 99.9770% 5.0 230 23 2.3 0.23 0.023 69.20% 2.0 308,000 30,800 3,080 308 30.8 99.9670% 4.9 330 33 3.3 0.33 0.033 65.60% 1.9 344,000 34,400 3,440 344 34.4 99.9520% 4.8 480 48 4.8 0.48 0.048 61.80% 1.8 382,000 38,200 3,820 382 38.2 99.9320% 4.7 680 68 6.8 0.68 0.068 58.00% 1.7 420,000 42,000 4,200 420 42 99.9040% 4.6 960 96 9.6 0.96 0.096 54.00% 1.6 460,000 46,000 4,600 460 46 99.8650% 4.5 1,350 135 13.5 1.35 0.135 50% 1.5 500,000 50,000 5,000 500 50 99.8140% 4.4 1,860 186 18.6 1.86 0.186 46% 1.4 540,000 54,000 5,400 540 54 99.7450% 4.3 2,550 255 25.5 2.55 0.255 43% 1.3 570,000 57,000 5,700 570 57 99.6540% 4.2 3,460 346 34.6 3.46 0.346 39% 1.2 610,000 61,000 6,100 610 61 99.5340% 4.1 4,660 466 46.6 4.66 0.466 35% 1.1 650,000 65,000 6,500 650 65 99.3790% 4.0 6,210 621 62.1 6.21 0.621 31% 1.0 690,000 69,000 6,900 690 69 99.1810% 3.9 8,190 819 81.9 8.19 0.819 28% 0.9 720,000 72,000 7,200 720 72 98.930% 3.8 10,700 1,070 107 10.7 1.07 25% 0.8 750,000 75,000 7,500 750 75 98.610% 3.7 13,900 1,390 139 13.9 1.39 22% 0.7 780,000 78,000 7,800 780 78 98.220% 3.6 17,800 1,780 178 17.8 1.78 19% 0.6 810,000 81,000 8,100 810 81 97.730% 3.5 22,700 2,270 227 22.7 2.27 16% 0.5 840,000 84,000 8,400 840 84 97.130% 3.4 28,700 2,870 287 28.7 2.87 14% 0.4 860,000 86,000 8,600 860 86 96.410% 3.3 35,900 3,590 359 35.9 3.59 12% 0.3 880,000 88,000 8,800 880 88 95.540% 3.2 44,600 4,460 446 44.6 4.46 10% 0.2 900,000 90,000 9,000 900 90 94.520% 3.1 54,800 5,480 548 54.8 5.48 8% 0.1 920,000 92,000 9,200 920 92Measure – Step 6: Establish Process Baseline Page 159 Note: Subtract 1,5 to get long-term Sigma level
  • 159. Short Term and Long term Variation (1)Consider the following scenarios: 100 data points in 1 day 1 data point a day Team for 100 days Team A BTwo Six Sigma teams are studying the same process and measuring thesame quality characteristic or defect. Team A collects 100 data points all onthe same day. Team B collects one data point a day for 100 days. If youplotted the data on a frequency plot, which do you think would show morevariation?We’d expect Team B’s data to show more variation than in Team A becausea process will change a lot more over the course of 50 days than it will in oneday. A 100-day range would cover changes in customer behavior, monthlyinstallments, customer service over a period of time etc. All these eventswould be less likely to happen (or would not be as pronounced) in the courseof a single day.The lesson to learn from these examples is that over the long run, or in thewidest application, processes experience much more variation than they do inthe short term or limited applications.Measure – Step 6: Establish Process Baseline Page 160
  • 160. Short Term and Long term Variation (2) Time frame 1 Time frame 2 Short-Term Time frame 3 Distribution Time frame 4 Lower Upper specification Specification limit LimitThe smaller distributions above indicate what can happen in the short termprocess. If you compiled all this data together, you would get the long-termdistribution as shown at the bottom.Measure – Step 6: Establish Process Baseline Page 161
  • 161. Short Term and Long term Variation andSigma CapabilityThe difference between short-term and long-term variation has a directrelationship to process capability as well. If you look at the previous diagramagain, you can notice the relationship between the various distribution curvesand the specification limits drawn on the chart. As you can see, in the shortterm, the process can drift closer to one of the specification limits, then backin the other direction. This leads to 2 key concepts: Short-term capability: the best the process can be if centered Long-term capability: sustained reproducibility of the processLet’s say you have a process that has a short-term process capability of 3.2 .We know that over time, the process will likely shift in one direction or theother.Experience has shown that this shift often reducescapability by 1.5? : that means that your 3.2? is actuallyonly “1.7? capable” in the long run.Here’s the dubious part. The sigma conversion table used with the sigmacalculations described earlier has the 1,5 shift built in to it. Oddly, the tableassumes you are using long -term data to collect short-term capability.However, you can use a separate Z conversion table to calculate both thelong -term and short-term of your processes.Measure – Step 6: Establish Process Baseline Page 162
  • 162. Standard Normal Table Tabled area Look up value -4,5 ? Decimal 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 -4 0.000032 0.000021 0.000013 0.000009 0.000005 0.000003 0.000002 0.000001 0.000001 0.000000 -3 0.001350 0.000968 0.000687 0.000483 0.000337 0.000233 0.000159 0.000108 0.000072 0.000048 -2 0.022750 0.017864 0.013903 0.010724 0.008198 0.006210 0.004661 0.003467 0.002555 0.001866 -1 0.158655 0.135666 0.115070 0.096801 0.080757 0.066807 0.054799 0.044565 0.035930 0.028716Whole -0 0.500000 0.460172 0.420740 0.382089 0.344578 0.308538 0.274253 0.241964 0.211855 0.184060number 0 0.500000 0.539828 0.579260 0.617911 0.655422 0.691462 0.725747 0.758036 0.788145 0.815940 1 0.841345 0.864334 0.884930 0.903199 0.919243 0.933193 0.945201 0.955435 0.964070 0.971284 2 0.977250 0.982136 0.986097 0.989276 0.991802 0.993790 0.995339 0.996533 0.997445 0.998134 3 0.998650 0.999032 0.999313 0.999517 0.999663 0.999767 0.999841 0.999892 0.999928 0.999952 4 0.999968 0.999979 0.999987 0.999991 0.999995 0.999997 0.999998 0.999999 0.999999 1.000000Measure – Step 6: Establish Process Baseline Page 163
  • 163. Standard Normal Table InstructionsTo read the Standard Normal Table:The area under the curve can be found by selecting the row that correspondswith the whole number portion of the sigma value. Then locate the propercolumn for the remaining portion of the sigma value. For example, 0.0 is themean of the distribution in the normal curve. Looking up the area for 0.0yields .50 or 50%. This is logical since half the data points are above andbelow the mean. Example: -2,6 0,004661 Decimal 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.000032 0.000021 0.000013 0.000009 0.000005 0.000003 0.000002 0.000001 0.000001 0.000000 4 - 0.001350 0.000968 0.000687 0.000483 0.000337 0.000233 0.000159 0.000108 0.000072 0.000048 3 -Whole Number 0.022750 0.017864 0.013903 0.010724 0.008198 0.006210 0.004661 0.003467 0.002555 0.001866 2 - 0.158655 0.135666 0.115070 0.096801 0.080757 0.066807 0.054799 0.044565 0.035930 0.028716 1 - 0.500000 0.460172 0.420740 0.382089 0.344578 0.308538 0.274253 0.241964 0.211855 0.184060 0 - 0.500000 0.539828 0.579260 0.617911 0.655422 0.691462 0.725747 0.758036 0.788145 0.815940 0 0.841345 0.864334 0.884930 0.903199 0.919243 0.933193 0.945201 0.955435 0.964070 0.971284 1 0.977250 0.982136 0.986097 0.989276 0.991802 0.993790 0.995339 0.996533 0.997445 0.998134 2 3 0.998650 0.999032 0.999313 0.999517 0.999663 0.999767 0.999841 0.999892 0.999928 0.999952 4 0.999968 0.999979 0.999987 0.999991 0.999995 0.999997 0.999998 0.999999 0.999999 1.000000Measure – Step 6: Establish Process Baseline Page 164
  • 164. Facilitating the Team during MeasureAs a Project Leader, here’s some advice to help guide the team through During the Measure Phase, you will notice theMeasure: following team developments:¦ Train/educate team members: the tools that are used may be new to ¦ Project Charter is challenged by Team, wondering what the Champion was thinking when the project was created some team members therefore it is important that you train the team members in the tools and assignments. This way they know what is ¦ Complaints arise that collecting data is too much work and interferes expected of them. with their daily job¦ Shared responsibility: make sure that everyone in the team has an ¦ Team assignments may go uncompleted and milestones may be missed assignment for each meeting. There is a lot to do in the early meetings, from collecting customer information to developing a high-level process This is called the “Storming” stage of team development. It is a natural part map. Make sure everyone is on board and actively involved. of the team’s evolution. Knowing that this stage is expected when teams¦ Acknowledge the Storming phase: Often teams will get impatient as they come together, the Project Leader can be prepared to work through this begin to realize the vastness of the problem they are working on. stage. Recognize that this is a natural development phase teams go through.¦ Record progress: when strong emotions arise, it comes from the team wanting to do a good job. The team wants to do something, not just have another meeting. Make sure you recognize the progress of the team and build on this to keep the momentum going. Teams are usually motivated by small wins.¦ Work together: have team members work in smaller groups or pairs. Working with a partner helps keep team members honest and encourages them do deliver what they promised.Measure – Step 6: Establish Process Baseline Page 165
  • 165. Analyze Roadmap DEFINE MEASURE ANALYZE IMPROVE CONTROL 7. Identify Root Causes Deliverables: • Start analyzing total project Y data fom measure Phase • Determine possible causes and narrow down to the root causes Project Data Possible Causes Potential Root Causes ? X1, X2, X3,…X n The 5 X2 Neu Alt A Why‘s B 8. Validate Root Causes & Determine Vital Few Deliverable s : • Test the root cause and narrow down to the vital few Hypothesis Testing Regression Validate Root Causes The vital few X2 X2 A Neu Neu Alt Alt X B 9. Quantify the Opportunity Deliverables: • Estimate of financial benefitAnalyze Overview Page 166
  • 166. Analyze Tools Step Step 7: Identify Root CausesPurpose: To determine what is causing the problem by focusing on the casualrelationships between those factors (causes) that contribute to the variation in aprocess. Step 7.1. Segmentation and Stratification Subprocess Mapping & Process Map Analysis Step 7.2. Cause & Effect Diagram The 5 Why’s Control Impact Matrix Graphical Analysis Tools Step Step 8: Validate Root Causes & Determine Vital Few Purpose: To select the Root Cause(s) the team will focus their improvement efforts on through the rest of the project. Regression Analysis Scatter Diagrams Hypotheses Testing Step 9: Quantify the Opportunity Purpose: To increase the understanding of the potential financial benefit that the business will enjoy as a result of the project. Determine Financial Opportuntiy Outcome VeriVerified Root Cause Verified Root Cause Verified Root Cause fied Root Cause Estimate of financial benefit Estimate of financial benefit Estimate ofAnalyze Overview Page 167
  • 167. Why Analyze ? Throughout the Analyze phase, data collection and analysis efforts intensify1. Use the process data to understand the problem and identify as the team relies almost exclusively on the data to drive their decision the vital few Root Causes in order to reduce variation that the making process. customer experiences In the Analyze phase, we will be analyzing upstream va riables, or input and2. Eliminate actions based on intuition and preconceived ideas process variables (Xs), to determine how they affect output variables (Ys) and to what extent.3. Recalibrate project scope Keep your improvement strategy (reduce variation and/or shift the mean) in4. Establish performance goals for the process mind throughout Analyze.5. Develop sustainable process improvements that will lead to long-term benefits6. Determine potential benefit of project7. Find The Xs That Drive Variation That The Customer FeelsThe consequences of failing to analyze data are inaccurateconclusions and wasted resources for inappropriate solutionsAnalyze Overview Page 168
  • 168. Key Concept The Project Output (Y) is also known as the dependent variable. The Project Output is determined by the values of the process variables X. These are the independent variables. Any changes in the Xs will have an impact on the Y (dependent variable). During this phase the team will obtain a clear understanding of the relationship between X and Y. Understanding this relationship will enable the team to pinpoint the key Xs that drive the variation in Y (Process Output). Y = f (x) Y: Project Output f: Transfer function – relationship that explains Y in terms of X X: Process variables (input)Analyze – Step 7: Identify Root Causes Page 169
  • 169. Identify Xs The results or output we get (the Ys) are a function of the process and inputBuilding on Y= f(x), the most important Xs need to be identified to variables (the Xs). In Analyze, we will study the process and the data indetermine which ones have the biggest effect on our Project Output. order to gain understanding of how it all fits together. Process - Input Variables Output (Xs) (Ys) X X X Process variables (Xs)Analyze – Step 7: Identify Root Causes Page 170
  • 170. Identify Root CausesHow to identify Cause and Effect - Root CauseAnalysisWe need to understand where we are and the data we have from themeasure phase in order to identify Cause and Effect relations and which RootCauses are driving them. Narrows the problem to a few key causes – Root Causes, key drivers Allows the team to focus on those Root Causes Uses data collection and analysis tools to determine root causes Sets the stage for sustainable solutions to address the “vital few Xs” For the Team: Keep Focused On The Improvement Strategy determined In MeasureFinding root cause is the key prerequisite to developing solutions.Analyze – Step 7: Identify Root Causes Page 171
  • 171. Two Approaches Teams will usually use both type of approaches in their projects in order toData Analysis: drill down into the process in search for the key Xs. Once the team has identified which Xs have the biggest impact on the Project Output, they will move on to the Improve phase in order to identify a solution to address the Using data collected to find patterns, trends, and other root causes. differences that can suggest, support, or reject theories about the causes or defects.Process Analysis: A detailed investigation of the existing key processes that supply customer requirements in order to identify cycle time, rework, downtime and other non-value added steps for the customer.Analyze – Step 7: Identify Root Causes Page 172
  • 172. Two Approaches: Different ToolsData Analysis - Segmentation/Stratification - Pareto Diagrams - Control Charts - Histograms/Box Plots - Multi-Vari Charts - Cause & Effect Diagrams - Regression/Correlation - Scatter Plots - Hypothesis Testing - Design Of ExperimentsProcess Analysis Core Process rr e t Applilcc titonn App i aa io Customer M ar e tttiin g rk e t ng g Sales s ng Billlngg iin (Level I) P oc es ng s Prro ce ss i ng Service v - Subprocess Mapping Application omer Application A Information Inf Subprocess Cusomerr Custtome RequesR for Request equ t pplication is is is Approval/noA back to ormation processing - Process Map Analysis (Level 2) est foror loan f loan loan processedd pr oc es se ro cessed p approv al pproval/no approval p proval a cback ack b ustomer to to customer ust c creates account - Moments of Truth Subprocess (Level 3 and below) - Nature of Work (NVA/VA)Analyze – Step 7: Identify Root Causes Page 173
  • 173. Data Analysis ApproachAn easy process to follow:1. Use the data gathered for Project Output metric (Y) and segmentation factors Completed in2. Use a Normality Plot of the Project Output data to determine Measure Phase summary metrics3. Segment individual processes by external factors ? Compare metrics for each segment ? Display segmented data4. Stratify different processes for individual analysis (as is indicated by the “average” or “central tendency” metric)5. Continue segmentation analysis for one process to identify subgroups that contain differing amounts of variation (as indicated by variation metric)6. Compare subgroups to identify key Xs that are responsible for driving the variationAnalyze – Step 7: Identify Root Causes Page 174
  • 174. Tool 1: Segmentation And Stratification (1) 1. Gather data for Project Output metric and segmentation factor 2. Use a normality plot to determine summary metrics Total Project output metric (Loan Cycle time) Small Loans Medium Loans Large Loans 3. Segment by external factors and compare metrics Ø=5 Ø=6 Ø = 20 4. Stratify distinct processes where S=4 S<= 2 S =6 indicated by central tendency metrics same/similar Average Same Processes Different Average = Different Processes Large Loans Large Loans Large Loans Large Loans 5. Continue Segmentation Location A Location B analysis for one process to identify subgroups that contain differing amounts of variation 6. Compare subgroups to Root Cause identify key Xs that are Analysis variation drivers ?Analyze – Step 7: Identify Root Causes Page 175
  • 175. Tool 1: Segmentation And Stratification (2) Segmenting the Project Output will identify areas where the process is3. Segment individual processes by external functioning very consistently and identify the areas where the process is showing a lot of variation. However, the comparison of these groups, givesfactors a lot more insight of how the process works. By segmenting the Project Output data from many different angles to identify all possible sources ofRemember the Segmentation Factors we identified in the Measure variation, the team will identify key Xs that drive the variations in the ProjectPhase to help collect data? We are going to us them now to analyze Output.the data set.What is Segmentation?Segmentation means splitting the Project Output data into different groups tosearch for differences in averages and variation among the groups.Using a graphical analysis tool: First, display the segmented data in order to identify potential differences between the different categories Then, determine the appropriate metrics and compare central tendency (average) and variation (spread) metrics for the segments to identify areas of unequal performanceAnalyze – Step 7: Identify Root Causes Page 176
  • 176. Tool 1: Segmentation & Stratification (3) Here we see an example of Project Output data. In this case it is the cycleExample: time to process a loan application. Histogram The team decides to segment the data by Regions. What does the team learn from segmenting the data into Region A and Region B? Frequency 5 10 15 20 25 30 35 40 45 Amount in Days 45 40 35 30 25 20 15 10 Region A Region BAnalyze – Step 7: Identify Root Causes Page 177
  • 177. Various Graphical Analysis Tools Histograms Multi -Vari-Chart Underwriting Cycle Time 45 48 40 35 38 30 25 28 20 15 18 10 8 Region A Region B 1 2 3 4 5 6 7 8 9 10 11 12 Month X = Mean Run Chart Product B Comparing Box Plots 140 120 100 60 80 60 40 20 0 1 2 3 4 5 6 7 8 June 30 Cycle Time Run Chart 140 Product A 120 # Defects 100 80 10 60 40 London Paris Rome Amsterdam Vienna Munich 20 Location 0 1 2 3 4 5 6 7 8 JulyAnalyze – Step 7: Identify Root Causes Page 178
  • 178. Tool 1: Segmentation And Stratification (4) Take a look at the example to the left:4. Stratify different processes for individual ¦ Which products have similar central tendencies?analysis as is indicated by the “average” or “central ¦ What does this mean?tendency” metric When the central tendencies are different, stratify. It is necessary to separate these processes because they are different from the others andWhat is Stratification? probably have different causes (Xs).Stratification is an analysis technique that uses statistical indicators of central When the central tendencies are similar, do not stratify. These processestendency (mean, Q1, Q3, and median) to make decisions about when need to be analyzed together in order to learn from the differences in theseparate categories of data are different enough to be considered distinct variation.processes and kept separate in continued analysis. The aim of stratification isto discover differences within the Project Output that have different root causefunctions. Factor: Central Tendency Spread Q3 SF Product 1 62 .38 Product 2 45 .56 Product 3 87 .84 Product 4 118 .61 Product 5 89 .92 Product 6 88 .54Analyze – Step 7: Identify Root Causes Page 179
  • 179. Tool 1: Segmentation And Stratification (5)5. Continue segmentation analysis for one processto identify subgroups that contain differingamounts of variation (as indicated by variationmetric)This matrix will guide your decision-making process asyou segment and stratify your data Same Spread Different Spread Same CT Try a different Proceed with Segmentation Root Cause factor Analysis Stratify Stratify Different CT seperate separate processes and processes and segment each segment each one oneAnalyze – Step 7: Identify Root Causes Page 180
  • 180. Tool 1: Segmentation And Stratification (6) Use Root Cause Analysis tools to determine why Product 5 has less6. Compare subgroups to identify key Xs that are variation than Product 3 and 6. Looking closer at these processes, what can we learn from Product 5 toresponsible for driving the variation improve 3 and 6? To make correct interpretations of the data, it is important to have atleast 30 data points in each segment. Factor: Central Tendency Spread Q3 SF Product 1 62 .38 Product 2 45 .56 Product 3 87 .84 Product 4 118 .61 Product 5 89 .92 Product 6 88 .54Analyze – Step 7: Identify Root Causes Page 181
  • 181. Data Analysis and Process Mapping X = 8, s = 15 X = 8, s = 10As soon as the team has gone through the data analysis steps, they move onto root cause analysis. The first thing the team will do once they haveidentified processes with similar averages and different variations, is tosubprocess map those processes. This is important in order to discoverwhere the differences in variation occur.Analyze – Step 7: Identify Root Causes Page 182
  • 182. Tool 2: Process Analysis (1) Definitions: Process Project Y (Dependent Variable): Product or service produced or delivered by the process. Process Xs (Independent Variable) Those variables that influence the outpu t and are generally controllable by those who operate the process. - Input Xs (Independent Variable) Materials and information used by the process to create the outputs. InputsInput Variables Output are often outside the control of the process operator. (Xs) (Ys) Remember Y=f(X 1 ,X 2 , ..., X n ) or in words: The results we get (the Ys) are a function of the process and input variables (the Xs). In Analyze, we will study the process and the data in order to gain understanding of how it all fits together. X X X Process variables (Xs) Analyze – Step 7: Identify Root Causes Page 183
  • 183. Tool 2: Process Map Analysis (2)Once the data has been fully segmented and stratified, you can begin lookingfor the Xs responsible for the variation in the process.First we look at: Different methods of sub process mappingThen at analyzing the Process Maps: Nature of work (value-added vs. non value-added) Flow of work Moments of truth (cycle time analysis) Process Map Analysis helps C r VA 1 2 3 4 5 6 Summe % narrow your focus on where NVA VA to look for potential root VE NVA Summe VE causes SummeAnalyze – Step 7: Identify Root Causes Page 184
  • 184. Subprocess Mapping Guidelines for Building a Sub process Map: ¦ Focus on the “As -is” situation – In order to discover where problems are occurring in a process, it is essential that the team focuses on the current situation. Often teams will jump ahead to how the process should work, but this is done in the next phase. ¦ Determine Start and Stop points – As was done for the high-level process map, this must be completed for the subprocess maps as well. This should be relatively easy when the high-level process maps were done thoroughly. ¦ Brainstorm Steps – Start by rapidly writing process steps on cards. Write large, one step per card. All steps should begin with a verb. Starting each step description with a verb (e.g., “Review application”; “Insert data”) helps you focus on action in the process. Don’t try to establish order immediately. It’s usually much easier to identify the steps before completing the actual map. ¦ When determining who does the step, it is better to keep it at a As-is Subprocess Map Should-be functions level, otherwise leave it out. It should be avoided that a Subprocess Map person is equated with a certain process step. ¦ Combine and Clarify – Make sure brainstormed steps are clear and don’t overlap. ¦ Organize in “Flow” – Creating the map is last. With all steps visible, it’s typically much easier to create a meaningful map without getting stuck on one or two minor issues. ¦ Outside-in focus – is the customer involved in your subprocess step? If so, how?Analyze – Step 7: Identify Root Causes Page 185
  • 185. Subprocess Mapping Methods Process Flowchart:Process Flowchart This is the most commonly used process mapping tool. Four symbols are Receive Review Data Enter Process used frequently: oval (start and stop points), rectangle (process step), application data correct ? data application diamond (decision step) and arrow. (direction of flow). It is generally used when the process is fairly small and simple, or when documenting the work done by a single person or group. Correct data Alternate Path Method: The “alternative path ” process map method arose from reengineering efforts,Alternate Path Method where the mapping of very large processes made “decision diamonds” more of a hindrance than help. In this technique, diverging or alternative “paths” Additional are noted by split arrows. Teams can then note rela tive percentages of info from times/incidences the process follows for each path. customer 75 There are many process mapping software tools available that simplify the Enter Receive account Service 15 Prepare Inform depiction of a process map, often adding pictures to illustrate the process Review complaint info 25 complaint information customer step more clearly. Prepare Deployment or Cross-Functional Map: 85 alternatives This method focuses on who performs which tasks and which steps are performed at the same time. It provides a clear visual perspective of theDeployment or Cross-Functional Map hand-offs and relationships between the people involved in the process. Who does what: Fill in Customer application Sign contract Review Verh Enter data Prepare contract Revise contract Revise contract Final contract Final contract Service Rep- Verh andeln application Risk Mgmt Review application Review application Revise contract Flow of ProcessAnalyze – Step 7: Identify Root Causes Page 186
  • 186. Process Map Analysis (3) Analyzing the process maps assists the team in determining where current Nature of work (value-added vs. nonvalue-added) problems and issues are. The reason the team is taking such a close look at the subprocess level is to identify where these problems might occur. At Flow of work the same time, the team is also identifying possible opportunities of where certain process steps can be simplified. Moments of truth (cycle time analysis)Analyze – Step 7: Identify Root Causes Page 187
  • 187. Process Map Analysis (4) Value-enabling work is just a different type of non value-added work. WhileNature of Work this terminology can be difficult, it does support the perspective: “If the customer isn’t willing to pay for it, it must be non value-added – by definition.”Value-Added Work: Value-enabling may be tasks and steps that are still needed given today’s condition. Consider what it would be like if things were perfect. For example,These are process steps which are essential. They have a direct impact on would you still inspect an item if the process were at Six Sigma? Would youthe product or service. The most important aspect is that the customer is search for the 3 defects in a million? Certainly checking is, at best, value-willing to pay for them. Defects and customer dissatisfaction are often felt enabling – never value-added.here when they are not done correct the first time. Non value-Added Work Symptoms:Non value-Added Work: ¦ Various approvals are needed to get things doneThese process steps are considered non-essential to produce and deliver the ¦ The policies address only control issuesproduct or service to meet the customer’s needs and requirements. The ¦ There are more managers than workerscustomer is not willing to pay for them. ¦ Rework is a common characteristic of most processesValue-Enabling Work:These steps are not fundamental to the customer and the customer will notpay for them, however, these steps “enable” the value-adding tasks to bedone better.Analyze – Step 7: Identify Root Causes Page 188
  • 188. Process Map Analysis (5) In order to examine the flow of work, it is easiest to break the process flowFlow of Work into components and investigate how th ese components go through the process.Process Time For instance, “become a letter in the mailing system” and tracing its path through the process. This is similar to a process flowchart, however thisThe total time that a unit of work is having something done to it other than allows the value-added and non value-added steps to be identified.time due to delays or waiting. It includes the time taken for value-added steps,internal failure, external failure, control, inspection, preparation/set-up, andmove.Delay TimeTotal time in which a unit of work is waiting to have something done to it. Toanalyze the flow of work, break the process flow down to its lowestcomponent, and analyze the movement of the component through theprocess.Cycle TimeThe total time from the point in which a customer requests a good or serviceuntil the good or service is delivered to the customer. Cycle time includesprocess time and delay time.Analyze – Step 7: Identify Root Causes Page 189
  • 189. Process Map Analysis (6)Moment of TruthAny moment where the customer is able to make a decision aboutthe quality of the product or service. This judgement can be eithergood or bad.In a process, “A moment of Truth” occurs every time the process comes intocontact with the customer and the customer can make a valid opinion aboutthe process of the service or product.From the customer’s view, the process is a set of service encounters. In thiscase, the customers believe the steps should be simple: apply for the loanand receive the money.In the best of cases, the customer is unaware of all the hard work, delays,and hand-offs which go into making their loan a reality. It occurs behind thescenes.Analyze – Step 7: Identify Root Causes Page 190
  • 190. Analyze RoadmapSummary Identify Possible CausesAt this point, you should have: Identified segments within Project Output data where significant variation occurs Identified segments within Project Output data where minimal variation exists Compared the differences in performance between segments via process map analysis or further data analysis to identify key Xs that may drive variation in the OutputNext, you will: Focus your investigation toward input and process variables that will lead to potential root causes Use Root Cause Analysis and Cause & Effect thinking to drill down on potential root causes that are deeper in process Your investigation is at the point where the focus becomes increasingly narrow and moves deeper into the process in order to identify root causes.Analyze – Step 7: Identify Root Causes Page 191
  • 191. Analyze Roadmap DEFINE MEASURE ANALYZE IMPROVE CONTROL 7. Identify Root Causes Deliverables: • Start analyzing total project Y data fom measure Phase • Determine possible causes and narrow down to the root causes Project Data Possible Causes Potential Root Causes ? X1, X2, X3,…X n The 5 X2 Neu Alt A Why‘s B 8. Validate Root Causes & Determine Vital Few Deliverable s : • Test the root cause and narrow down to the vital few Hypothesis Testing B Regression X2 X2 Neu Neu Alt Alt Validate Root Causes A BAnalyze – Step 7: Identify Root Causes Page 192
  • 192. Analyze RoadmapThe vital few X 9. Quantify the Opportunity Deliverables: • Estimate of financial benefitAnalyze – Step 7: Identify Root Causes Page 193
  • 193. Analyze Tools Step Step 7: Identify Root CausesPurpose: To determine what is causing the problem by focusing on the casualrelationships between those factors (causes) that contribute to the variation in aprocess. Step 7.1. Segmentation and Stratification Subprocess Mapping & Process Map Analysis Step 7.2. Cause & Effect Diagram The 5 Why’s Control Impact Matrix Graphical Analysis Tools Step Step 8: Validate Root Causes & Determine Vital Few Purpose: To select the Root Cause(s) the team will focus their improvement efforts on through the rest of the project. Regression Analysis Scatter Diagrams Hypotheses Testing Step 9: Quantify the Opportunity Purpose: To increase the understanding of the potential financial benefit that the business will enjoy as a result of the project. Determine Financial Opportuntiy Outcome VeriVerified Root Cause Verified Root Cause Verified Root Cause fied Root Cause Estimate of financial benefit Estimate of financial benefit Estimate ofAnalyze – Step 7: Identify Root Causes Page 194
  • 194. Summary Identify Possible CausesAt this point, you should have: Identified segments within Project Output data where significant variation occurs Identified segments within Project Output data where minimal variation exists Compared the differences in performance between segments via process map analysis or further data analysis to identify key Xs that may drive variation in your output (Y)Next, you will: Focus your investigation toward input and process variables that will lead to potential root causes Use Root Cause Analysis and Cause & Effect thinking to drill down on potential Root Causes that are deeper in process Your investigation is at the point where the focus becomes increasingly narrow and moves deeper into the process in order to identify Root CausesAnalyze – Step 7: Identify Root Causes Page 195
  • 195. Tool 1: Cause & Effect Diagram A visual tool used by a team to brainstorm and logically organize possible causes for a specific Machines Methods Materials problem or effect ¦ Summarize potential high-level causes Mögliche High-level Gründe (X-We- te) v - High-le- el (X-Werte) r - Effect ¦ Provide visual display of potential causes Y ¦ Stimulate the identification of deeper potential causes The Cause & Effect Diagram is the foundation of the Analyze phase and is used to generate a comprehensive list of possible Xs. It is also known as the Measurement Mother Nature People Ishikawa Diagram and the “fishbone diagram”.Analyze – Step 7: Identify Root Causes Page 196
  • 196. Tool 1: How to Identify The Questio Or QuestionEffect? Identify the question or effect (Y) that goes at the head of the diagram. The question is developed from . the data and process map analysis that was 60 performed on the critical segmentation factors from Cycle Time 30 the Project Output Metric. The question is framed in the form of a “why.” x x 10 Charlotte Cincinnati Dallas Philadelphia Omaha Phoenix Location For example: ¦ Why are the bills late? Ys ¦ ¦ Why is region A more stable than region B? Why do more defects occur in product C? occu The effect (Y) on the Cause & Effect diagram is at a lower level in the x x process than the Project Output. 1 1 2 2 3 3 4 4 5 5 6 6 Sum Sum % % Cr Cr VA VA NVA NVA VE VE Sum Sum eAnalyze – Step 7: Identify Root Causes Page 197
  • 197. Tool 1: Cause & Effect Diagram - How ToConstruct It? Proces Map Though sometimes Analysis overlooked, be sure to put a box around the Why is there Difference in effect and draw a long the Variation in cycle time arrow from left to right to between small and medium the box. Visually , it helps loans to keep your team focused on the effect. Data Analysis Measurements Methods Materials As a group, brainstorm the major causes of the problem statement posed Why Is there Difference in the effect box. In the Variation in cycle Sometimes it is helpful to time between small and use the “typical” major medium Loans cause category (5 M´s & 1 P). It is best for your team to come to consensus on the major causes . Machines Mother Nature People Measurements Methods Once the “framework ” of the Rework with Cause & Effect Diagram is set applicants up, your team should begin Data on comps missing No tracking of assignements brainstorming possible causes . Why Is there Difference In per approvers You can brainstorm by the Variation in cycle time between small and category, or just come up with Too few approvers medium Loans ideas and then place them in - System Downtime the appropriate category . Slow Review your ideas to make approval sure you’ve considered all the categories. People MachinesAnalyze – Step 7: Identify Root Causes Page 198 198
  • 198. Tool 2: The Five WhysThe “Five Whys” Drill Deep Into The Process To Example:Identify Potential Root Cause(s) The project team has verified that the X (in this case a complicated form) accounts for the difference in cycle times between small an d medium loans. Ask “why” five times to identify deeper causes for an X They use the Five Whys to drill deeper in the process. Use process data to answer each “why” question 1. Why do complicated forms cause delays in the underwriting steps? - Because underwriters receive incomplete applications 2. Why do they receive incomplete applications? - Because customers don’t fill out the form accurately or completely 3. Why don’t customers fill out the form accurately or completely? - Because the format is confusing 4. Why is the format confusing? - Because the directions are hard to read 5. Why are the directions hard to read? - Because the font size is too smallAnalyze – Step 7: Identify Root Causes Page 199
  • 199. Tool 3: Control/Impact Matrix Use your team’s process knowledge and business experience to list possible Xs in a Control/Impact Matrix. Then use process data to verify or disprove placement of the Xs. IMPACT Prioritization Steps High Medium Low Using the Control/Impact Matrix shown above, examine each X in light of two questions: ¦ What is the impact of this X on our process? In our ¦ Is this X in our team’s control or out of our team’s control? Control With your team, place each X in the appropriate box on the matrix. TheCONTROL validated matrix is a guide to addressing the Xs. ¦ Begin with the “High Impact/In Our Control” category ¦ Use process data to verify or disapprove your assertions Out of ¦ Out of control Xs may require special solutions and CAP tools for Control successful sustainable solutionsAnalyze – Step 7: Identify Root Causes Page 200
  • 200. Tool 3: Control/Impact Matrix-ExampleMeasurements Methods Why is there a Difference in the Variation in cycle time between small and medium Loans? People Machines IMPACT High Medium Low • Too many defects • Too long for • Complexity In our • Complicated form customer customer • Evaluation of risk Control • Too much review number number worthiness • Duplication of CONTROL effort • Too long to get • Not enough staff Out of credit report • Not well trained ControlAnalyze – Step 7: Identify Root Causes Page 201
  • 201. Tool 4: Graphical Analysis Tools-OverviewVerify List Of Xs With Data¦ Examine “High Impact Xs”¦ Use data to determine whether each X has a significant influence on the problem¦ For significant Xs labeled “Out Of Our Control” identify individuals or groups that need to be part of the improvement process to ensure a successful resultGraphical Analysis ToolsIn this step, you will be collecting and analyzing data on those Xs that havebeen identified as “In Our Control/High Impact” in order to verify that theyaccount for a significant proportion of the total variation in your process.Some of the tools you will be using are:¦ Stratification¦ Pareto Diagrams¦ Run/Control Charts¦ Histograms/Bar ChartsHelpful questions to verify an X¦ Is there one defect category that occurs more frequently than others?¦ What factors contribute the most to the variation in Project Output?¦ Do results differ across factors?Analyze – Step 7: Identify Root Causes Page 202
  • 202. Tool 4: Graphical Analysis Tools-Examples Histograms Multi-Vari-Chart Underwriting Cycle Time 45 48 40 35 38 30 25 28 20 15 18 10 8 Region A Region B 1 2 3 4 5 6 7 8 9 10 11 12 Month X = Mean Run Chart Product B Comparing Box Plots 140 120 100 60 80 60 40 20 0 1 2 3 4 5 6 7 8 June 30 Cycle Time Run Chart 140 Product A 120 # Defects 100 80 10 60 40 London Paris Rome Amsterdam Vienna Munich 20 Location 0 1 2 3 4 5 6 7 8 JulyAnalyze – Step 7: Identify Root Causes Page 203
  • 203. Tool 4: Pareto Chart Is there a defect that occurs frequently? A fully documented Pareto chart will include the “Cumulative Summation line” or Cum Sum line, which depicts the running total of the frequency of each subsequent bar (segmentation factor). The right-hand axis on the Segment data to look for a significant factor that influences the process graph will show the cumulative percent of defects. By reading the Cum Sum line against the cumulative percentage, your team can determine which of 1. April – 30. June the segmentation levels comprise 80% of total for the problem, and direct 200 10 their attention to those levels. Number of units : 5,000 180 *f = Frequency 9 (Cum Sum -Linie) The Pareto chart is an important tool to further focus improvement efforts. 0 160 8 However, the top bars on the chart are not root causes and the team may f* of D+B+F need to fully investigate each category in order to pinpoint the root cause. Cumulative Percentage 140 f* of D+B 7 Like the “Five Whys”, the Pareto chart can be used in an iterative fashion in 0 order to cascade deeper into a process.Frequency 120 6 f* of D 100 5 0 80 4 LEGEND 60 3 0 A: illegible 40 2 B: Bank Info incomplete C: Missing signature 20 1 D: Personal information 0 incomplete E: Employment history 0 incomplete D B F A C E Other Type of defect The Pareto chart is a bar chart with the bars (Segmentation level) arranged in descending order. It is an essential tool to help prioritize improvement targets by identifying the top 20% of the problems that cause 80% of the poor performance. Analyze – Step 7: Identify Root Causes Page 204
  • 204. Validate Root Causes & Determin Vital Few DetermineOverviewBy now you have identified process differences b segmenting, stratifying and bygraphical display of your process and data. These differences lead tohypotheses about Root Causes. In this section, the focus turns to a morerigorous statistical approach to identifying differences via Regression Analysisand Hypothesis Testing, in order to validate the Root Cause and determinethe Vital Few. Summary Metrics and Graphical Analysis Statistical Tools Regression Hypothesis FOCUS NOW Analysis testingAnalyze – Step 8: Validate Root Causes & Determine Vital Few Page 205
  • 205. Tool 1: Scatter Diagram (1) The premise behind a Scatter Diagram is that a change in a critical X willA Scatter Diagram is an important graphical tool for exploring the relationship produce a change in the effect (Y).between predictor variables (Xs) and the response variable (Ys) (i.e. cause For a DMAIC project, the X will usually be the suspected cause. The Projectand the effect) Output will be a measure of the problem being analyzed. If the cause is correct, the Y variable should change as X changes – in other words, they’re related. In the example, the team was interested in the relationship between the size 40 of the loan (amount of dollars) and the cycle time. A relationship appears to 35 exist between X and Y because the data points roughly form a straight line. Cycle time (Days) (y) 30 25 20 15 10 5 1T 2T 3T 4T 5T 6T 7T 8T 9T 10T Size of loan (X)Analyze – Step 8: Validate Root Causes & Determine Vital Few Page 206
  • 206. Tool 1: Scatter Diagram (2) This is a plot of the population of Oldenburg at the end of each year againstWarning, correlation does not imply causation the number of storks observed in that year, 1930-1936. Even strong correlations do not imply causation. (For example, there will likely be a positive correlation – but not causation – between the occurrence of vapor-locks in automobiles and the use of public swimming pools.) 100 200 300 80 80 Population in thousands 70 70 60 60 50 50 100 200 300 Number of StorksAnalyze – Step 8: Validate Root Causes & Determine Vital Few Page 207
  • 207. Tool 1: Scatter Diagram – Analysis ¦ Mixing up the “X” and the “Y” Variables:Common Mistakes: In analyzing variables for potential cause and effect, the process variable as the predictor is on the “X” axis and the output or process Mixing up the “X” and the “Y” variables performance variable as the response is on the “Y” axis Data is not paired correctly ¦ Data is not Paired Correctly: Scatter Diagrams require that the “X” and “Y” variables be paired. It Improper scaling – scatter diagram not square means that there has to be a logical correspondence between the data to appropriately study the correlation. For example, if one examines the Incorrect increment spacing between tick marks relationship between length of time to approve loans and number of telephone calls to the applicant, the paired data would be based on a specific loan application. Taking a sample of loan applications, it will be necessary to know the length of the time to approve and the number of telephone calls for each loan ¦ Improper scaling – scatter diagram not square: To ensure proper interpretation, it is necessary to use the fullest possible extent of both the “X” and “Y” axis to cover the range of the data collected. Improper scaling can result in the pattern being obscured ¦ Incorrect increment spacing between tick marks: The increment, or the space width between tick marks on the Scatter Diagram, should be a value that makes it easy to plot the data and easy to read. A general guideline is to have between 5 to 15 increments of equal width along the full length of each axisAnalyze – Step 8: Validate Root Causes & Determine Vital Few Page 208
  • 208. Tool 1: Scatter Diagram – Interpretation Interpretation Of A Scatter Diagram Range for x variable too small Range for Y variable too large Common Patterns In The Data 140 140 130 ¦ See whether the potential cause variable and the effect variable are 120 120 related to one another.revenue 100 revenue in 110 Range Of The Predictor Variable (Xs) n Mio$ Mio $ 80 100 ¦ The range is the difference between the largest and smallest values. 60 90 80 ¦ Check that the range of the potential cause variable is wide enough to 40 70 show possible relationships with the effect variable. 20 0 60 Irregularities In The Data Pattern 0 5 10 15 20 0 2 4 6 8 10 % Price decrease ¦ Check whether the data pattern indicates possible problems in the data. % Price decrease Correct range for X and Y 140 120 revenue in Mio$ 100 80 0 2 4 6 8 % Price decrease Analyze – Step 8: Validate Root Causes & Determine Vital Few Page 209
  • 209. Tool 2: Regression Analysis (1) Let’s look at an example from a customer service center where speed of answer is an important CTQ. There w as concern over the number of customers who were hanging up while trying to reach the call center. 5,0% Abandon rate represents the percentage of customers who hung up. The call center staff wanted to explore the relationship between answer speed 4,5% and abandon rate. They created a Scatter Diagram to graphically display the data collected. 4,0% Though more data may be needed, the data suggests a possible positive 3,5% correlation. As time to answer increases, the abandon rate increases. Abandon Rate Rate 3,0% 3,0% 2,5% 2,5% 2,0% Abandon 1,5% 1,0% 0,5% 0,0% 0,0% 0,0 5,0 10,0 15,0 0,0 022 ,0 25,0 30,0 35,0 Answer Speed (Sec.)Analyze – Step 8: Validate Root Causes & Determine Vital Few Page 210
  • 210. Tool 2: Regression Analysis (2) Do you recall these plots? Here are theRegression Measures Of Correlation approximate r’s for each: The correlation coefficient “r” measures the strength of linear relationships When a relationship exists, the variables are said to be y r = –1.0 y r = +1.0 correlated x x ? Perfect negative relationship r = –1.0 ? No linear correlation r = 0 r = +.7 r = –.7 y y ? Perfect positive relationship r = +1.0 As a rule of thumb, look for r ?.7 (manufacturing) or r >.4 x x (service) r=0 r2 measures the percent of variation in Y explained by the y r=0 y linear relationship of X and Y x xAnalyze – Step 8: Validate Root Causes & Determine Vital Few Page 211
  • 211. Tool 2: Regression Analysis Defined Visually, the “line of best fit” is represented on a Scatter Diagram by a dark line. Mathematically, the line is represented by a mathematical formula, Y = b0 + b1X1 Y =b0 +b1 X1 , that is referred to as the regression equation. The regression equation is used to make predictions of process output performance, Y, Line of best fit based on a given value of the process or input variable, X. The values b 0 Regressions-Equation and b 1 are calculated and established using the values plotted on the Y = b0 + b1X1 Scatter Diagram. Minitab will calculate both the line of best fit and theY Where regression equation. b0 = Predicted value of Y when x1=0 b1 = Slope of Line Change in Y per Unit Change in x1 X1 Analyze – Step 8: Validate Root Causes & Determine Vital Few Page 212
  • 212. Tool 2: Regression Equation To mathematically estimate Y use the regression equation: Define the regression equation in terms of the two variables: 50 Y=29.6684 + .0175 (X) becomes Predicted Cycle Tim e = 29.6684 + 0.0175 (loan amount) ) Cycle me e (days) Plug in the value of X (loan amount) tim ays 40 ( d Y = .29.6684 + 0.1075(400) Y Y = 29.6684 + 7.0 Y = 36.6684 ti 30 To visually estimate predicted Y, use the line of best fit: 20 ¦ Draw a line vertically from the value of X to the line of best fit. ¦ Draw a line horizontally from the line of best fit to the Y axis. 0 100 200 300 400 500 600 700 800 ¦ Y is the value at which the horizontal line crosses the Y axis. (Y at 37 days) Loan amount (k)Analyze – Step 8: Validate Root Causes & Determine Vital Few Page 213
  • 213. Identify Vital Fews ¦ Has a strong correlation been established between the Y and theY = F(x) identified vital root cause(s)? x1 x2 ¦ If the impact of the vital few Xs is reduced/eliminated, will the impact on the Project Output Metric be significant? Y ¦ Will the customer see and feel the change in the process as a result? x3 x4 Impact high low ¦ Have you relied on data to drive your decision? Make certain all assertions have been validated with data and that the Input statistical significance of the vital few Xs has been firmly established. X1 1 X2 Control Output X3 X4 Analyze – Step 8: Validate Root Causes & Determine Vital Few Page 214
  • 214. Quantify The Opportunity – OverviewWHAT: Quantify the Opportunity step is when the team estimates the One of the most troublesome tasks forpotential benefit of their project. Although the estimate includes tangible and Improvement Teams is Quantifying Theintangible benefits, a dollar figure will be estimated for only the tangible Opportunity.benefits. No cost factors are involved at this time. Several issues are typically raised: ¦ What is the difference between quantifying the opportunity andWHY: To provide the financial rationale of continuing the project, and to cost/benefit analysis?assess the allowable spending on the specific solution(s) that will be identified ¦ What standards should teams be using in calculations?in Improve Phase. ¦ Is there a standard methodology for calculating the fi nancial impact?WHEN: Usually after the verification of the vital few root causes For Quantify the Opportunity, you will refine the estimated financial opportunity first stated in the Charter during Define. Based on the data collected and analyzed earlier, this new figure will reflect your project’s anticipated reductio n in defects. This financial opportunity will be revisited again in Improve (cost/benefit analysis) as well as in Control (verification of financial benefits).Analyze – Step 9: Quantify The Opportunity Page 215
  • 215. Key Differences From Cost BenefitCalculation The intent of Quantify The Opportunity is to increase the understanding of the potential dollar benefit that the business will enjoy as a result of your project Quantify The Opportunity numbers are gross in the sense that theyQuantify The Opportunity estimate the benefit only. The purpose of Quantify The Opportunity is to make sure that teams are working on the right projects, i.e., projects that Done in the Analyze phase have a significant financial impact. In contrast, the cost/benefit analysis performed in Improve examines the Not for a specific solution cost/benefit of a specific solution. It represents the overall financial viability of implementing the solution. These numbers must be more precise and Gross numbers represent net numbers (the cost to implement the solution is factored in). Scope: The entire processCost/Benefit Analysis Done in the Improve stage Calculated for a specific solution Net numbers Scope: A portion of the processAnalyze – Step 9: Quantify The Opportunity Page 216
  • 216. Quantify The Opportunity Is there a Standard Methodology for QuantifyingRecommended Allowable Six Sigma Benefits: The Opportunity? Directly linked to Six Sigma project or group of projects The recommended duration to track your financial opportunity is twelve months for cost savings projects, and incremental revenue (year-over-year) Incremental and able to be audited for incremental revenue projects. From a documented baseline Inputs Offset by project execution costs and quality organization ¦ The Vital Few Xs costs (via Cost/Benefit Analysis) ¦ Estimated defect reduction ¦ Overall Financial Guidelines Reported for current period and annualized ¦ MBB/Quality Financial AnalystRecommended Non-Allowable Six Sigma Benefits Cost and benefits from projects that are not Six Sigma projects Normal applied overhead covering products, distribution and office operations Avoidance of incurring future costs Avoidance of losing future salesAnalyze – Step 9: Quantify The Opportunity Page 217
  • 217. Tangible Benefits (1)Estimate tangible benefits from:The estimate of tangible benefits is based on both the level of defectreduction and the vital few Xs.¦ Cost Savings resulting from any change that reduces expenditures in the process, such as: - Scrap/rework reduction - Head count reduction and reduced overtime - Price concession expenditure reduction - Operating concession expenditure reduction/warranty cost reduction - Operating expenses directly identifiable - Reduced plant and equipment depreciation or lease expense from improved utilization - Material cost reduction - Direct (hourly) labor utilization¦ Cash flow benefits include: - Reduced facilities and equipment resulting from increased capacity or efficiency - Reduced accounts receivable resulting from improved collection and decreased claims - Reduced accounts receivable resulting from improved payment terms - Reduced inventory resulting from improved process efficiencyAnalyze – Step 9: Quantify The Opportunity Page 218
  • 218. Tangible Benefits (2)Estimate tangible benefits from:¦ Interest includes interest income (increased investment income) and interest expense savings (reduced cost interest).¦ Incremental revenue is estimated by judging the final capability that the process will achieve as a result of your project. The calculation of incremental revenue includes: - Product or service sales revenue resulting from increased capacity (based on actual utilization of increased capacity) - Product or service sales revenue from improved product quality or service levels - Product or service sales revenue resulting from improved commercial process - Increased net sales billed from the improved processAnalyze – Step 9: Quantify The Opportunity Page 219
  • 219. Intangible Benefits Intangible benefits should not be reported as quality savings because theyEstimate intangible benefits from: are difficult to quantify. Nonetheless, they are valuable project outcomes that add to net worth and can be used to justify the value of a project. Cost avoidance Intangible benefits were first estimated in the Define phase when writing the Customer retention Charter. Now is the time to revisit those benefits and make any necessary changes. Employee morale Assess the expected change that will occur as a result of your process improvement. No formal guidelines exist for allocating monetary value to these benefits. Check with your business to see what guidelines have been established.Analyze – Step 9: Quantify The Opportunity Page 220
  • 220. Improve Roadmap DEFINE MEASURE ANALYZE IMPROVE CONTROL 10. Identify Solution Deliverables: • Starting with CTQ and the vita few root causes generate solution ideas vital • Screen possible solution and select solution Idea 2 Idea 3 Idea 1 Idea 4 Generate Ideas Modelling & odelling Root Benchmarking Simulation Simulatio Brainwriting Solution A B B C D E E CTQs +Design of +- Desi+ +- + + gn Creative thinking E ++ +ment+ -xp - eri + s of - + - + - Experiments+ - 11. Refine and test solution Deliverable s : • Refine solution, identify possibl errors/threats possible • Pilot solution for better understanding • If necessary come back to refining solution o Potential problem analysis Pilot solution Solution Error proofing FMEA 12. Cost Benefit Calculation Deliverables: • Calculation of financial benefi for selected solution benefitImprove Overview Page 221
  • 221. Improve Tools Step 10: Identify solution Purpose: To identify solution based on vital few root causes coming out of the Analysis Phase Solution generation tools Solution screening tool Test solution Step 11: Refine and test Solution Purpose: Test solution and screen for potential errors/failure, after this pilot solution to see the impact Potential problem analysis Error proofing Failure mode and effects Analysis Pilot plannning Verification of results Step 12: Cost Benefit Calculation Purpose: To increase the understanding of the dollar benefit that the business will enjoy as a result of the implemented solution Cost Benefit calculation identified possible Best solution to Cost Benefit Outcome solution address vital X tested CalculationImprove Overview Page 222
  • 222. Transition From Analyze To Improve Maintain the customer’s perspective whenIn Analyze developing your solution Identify the Root Cause(s) that drives the Variation in Project The starting point for Improve is the root cause(s) and data analysis completed in Analyze. Using the Improve tools, you will develop solutions to Output reduce the impact of the verified root cause(s).In Improve Develop a solution designed specifically to reduce/eliminate the impact of the root cause on your Project Output Metric so that the process is able to meet the customer CTQs ? Begin with the key Xs ? Keep the customer’s process in mindThe developement of a solution follows a spiral pathAs you approach to the center you will collect data to narow down yoursolution. CTQs Vital Xs Best SolutionImprove Overview Page 223
  • 223. Improve Introduction: Any solution th at is selected must drive the process toward moreKeep in mind successfully meeting the customer CTQs that were identified in the Define phase. Furthermore, the team must develop the solution from the customer’s perspective. Finally, maintain focus on the identified root cause(s). The Verified Root Causes solution must target the root cause in order to successfully Customer perspective of the solution reduce the impact the root cause has or to eliminate it all together. Customer CTQ‘sImprove Overview Page 224
  • 224. Identify Solution – Introduction (1) When the Root Causes are clearly defined and the possible solutions are Possible path for solution development more obvious, Design Of Experiments may be the best path to a good solution. In situations where the Root Cause is a combination of factors or process issues, and the solution is not obvious, a creative thinking approach may be a more productive path to a good solution.Solution ist notobvious Root Causes Solution is X1 X2 OR X3 X4 X1 X2 Obvious Out of the Box Thinking the Structured Approach •Generate new solution ideas , • Investigate Specific Xs , •Test • Test •Refine • Refine • Both approaches require experimentation • Both approaches result in one or more good solution options Improve – Step 10: Identify Solution Page 225
  • 225. Identify Solution – Introduction (2) Try to look beyond existing process paradigms and think in terms of what the Now is the time to think of new ways to eliminate/reduce the customer needs your process to do. impact of the root cause Now is NOT the time to reply on “favorite” solutions or routine attempts to fix an old problem, i.e.: ? Re-train the people ? Implement a new IT process ? Standardize the processImprove – Step 10: Identify Solution Page 226
  • 226. Generate IdeasOverview tools The effectiveness of your team’s work in the “Identify And Test Solutions” step is dependent upon your ability to think creatively about potential solutions. The following pages provide several different tools that can be Process Benchmarking used to spark “out-of-the-box” thinking. Idea generation tools are intended to Brainstorming help teams move outside of their typical way of thinking and into a more creative or thoughtful mode. Some of the tools will be familiar while others Brain Writing/Creative Thinking are new. Try to encourage your team to try some new techniques even though the techniques may feel somewhat awkward or contrived at first. Best PracticesImprove – Step 10: Identify Solution Page 227
  • 227. Tool 1: Benchmarking (1)What Is Benchmarking? ¦ Benchmarking is an important tool in the improvement of your process for several reasons: First, it helps you identify potential Xs by Compare performance of an existing process against other comparing your process to the benchmarked process. Second, it may companies’ best in class practices encourage innovative or direct applications of solutions from other businesses to your product or process. And finally, Benchmarking can Determine how those companies achieved their performance help to build acceptance for your project’s results when they are levels compared to Benchmark Data obtained from industry leaders. Successful Benchmarking always focuses on improvements for the Use the information to improve its own performance future instead of mistakes of the past. ¦ Literature searches can yield a good deal of valuable BenchmarkingUse Benchmarking both for comparison of performance as well as to information, but the best information typically comes from a site visit tounderstand the potential for improvement a willing partner. Because Benchmarking involves sharing internal business information and processes with external organizations, most companies have developed procedures to monitor and manage their involvement in Benchmarking Visits. Before you plan an on-site visit to any external companies, c heck with your business management about your own policies. ¦ Don’t limit your Benchmarking search to processes that are only exactly the same. Try to think of analogous processes that might help you generate even more ideas.Improve – Step 10: Identify Solution Page 228
  • 228. Tool 1: Benchmarking (2) The Benchmarking code of conductBenchmarking Protocol And Ethics Keep It Legal Policy regarding Benchmarking protocol should be ¦ Avoid discussion or actions that might lead to or imply restraint of trade communicated to all employees involved, prior to contacting - Bribery external organizations. Guidelines should address the - Dealing arrangements following areas: - Price fixing - Misappropriation ? Misrepresentation – do not misrepresent your identity in Be willing to give what you get order to gather information ¦ Be willing to provide the same level of information that you request ? Information requests – a request should be made only for Respect confidentiality information your organization would be willing to share ¦ Information obtained must not be communicated outside the partnering with another company organizations without consent of participating benchmarking partners ? Sensitive/proprietary information – avoid direct Keep information internal benchmarking of sensitive or proprietary information ¦ Use information obtained only for the purpose of improving processes ? Confidentiality – treat all information as confidential ¦ External use of the partner’s name or data requires permission Don’t refer without permission ¦ Obtain an individual’s permission before providing his/her name in response to a request Be prepared at initial contact ¦ Demonstrate commitment to the efficiency and effectiveness of the benchmarking process with adequate preparation at each process stepImprove – Step 10: Identify Solution Page 229
  • 229. Tool 2: Brainstorming/ModifiedBrainstorming ChannelsOnce the inventive principles pertinent to your Root Cause have been We’ve already seen this approach in cause and effect analysis. Theidentified, use brainstorming to find the best application of the principles to objective is to begin by listing categories of ideas for the issue at hand.your problem. Then, as the team brainstorms, it can change channels when new ideas slow down. The objective is to generate a broad range of ideas (several tBasic Brainstorming Guidelines: channels), as well as a large quantity (as many ideas as possible in each e channel). Allow silent time to think Analogy Collect as many ideas as possible In this method, the team brainstorms around a related or analogous issue – brainstorm which helps unblock people’s thinking. For example, rather than brainstorm s Do not discuss or evaluate ideas ways to ensure complete information on a loan form, they might look at ways informatio to get complete information on a youth sports team application. Ideas on the o Document ideas analogy then need to be translated to the real situation.Modified Brainstorming: Anti-Solution This is probably the easiest of these methods. Simply brainstorm the oSome simple amendments to traditional brainstormin can help expand the brainstorming opposite of your objective (e.g., how to ensure we get no information on the (e.g.number and quality of ideas. loan form). Brainwriting Channeling Analogy Anti-Solution Solution Brainwriting Individually, team members record their solution idea on paper. Papers are recor then exchanged and as each team member receives a new paper, he/she tries to build on it, modify the written statement, or document a totally new A/A 1 AA idea. At the end of the time, the ideas are collected, reviewed, and ranked by the team.Improve – Step 10: Identify Solution Page 230
  • 230. Solution Screening Tools – OverviewThe next step is to screen out solutions that are not acceptable. Screen yourlist of potential solutions against the following questions: To Screen Out Unacceptable Solutions ¦ “Musts” requirements are the minimum requirements that must be met Does the solution address the root cause? for your chosen solution. If a solution does not meet “musts” criteria, it Would the customer be satisfied with this solution? should be eliminated from further consideration ¦ One method to establish “musts” criteria is to specify and clarify what Are controllership/compliance issues adequately addressed they are with your Champion and customers (if possible) before by this solution? initiating the Improve phase (e.g., hold a project review meeting). It is extremely helpful and efficient to have “musts” criteria stated,If the answer to any of these questions is “no,” the solution is most likely understood, and agreed to by all involved in the improvement effortunacceptable. Examples: ¦ CustomerCTQs ¦ Business CTQs ¦ Laws ¦ Company policy ¦ Customer “must be” requirements ¦ Business “must be” requirements ¦ Budget constraints ¦ Timeline constraintsImprove – Step 10: Identify Solution Page 231
  • 231. Tool 1: Criteria Based Matrix (1) Once unacceptable solutions have been eliminated, the criteria-based matrix can help teams choose the most appropriate solution. Though requiring considerable time for more discussion, the technique allows teams to make decisions and understand the rationale for the decision. The key difference Likely Solution in this approach is the discussion and identification of the criteria and the Solution A Solution B weighting of the criteria (e.g., 10 – most important, 1 – least important). Sometimes, the discussion of the criteria alone will help teams determine the top solution.Criteria Weight1. List each criterion here2. Xxxxxxxxxxxxxxxxxx3. Xxxxxxxxxxxxxxxxxx4. Xxxxxxxxxxxxxxxxxx5. Xxxxxxxxxxxxxxxxxx TotalImprove – Step 10: Identify Solution Page 232
  • 232. Tool 1: Criteria Based Matrix (2)Process For Criteria-Based Matrix All solutions that have been screened for acceptability can now be examined via the Record a final list of solutions criteria-based matrix Screen against musts Unlike the “musts” criteria, “want” criteria are used to compare the relative benefits of different solutions. “Want” criteria can include items such as: less Create a list of “want” criteria training, lower cost, brief implementation, etc. Weight the list of “want” criteria Once the list of “want” criteria is generated, the top “want” is identified and labeled as a 10. The rest of the “wants” are ranked relative to that “want.” Compare the list of solutions to the weighted criteria The solutions are then compared to each “want.” The solution that best fulfills that “want” is ranked “10” and the other Tally and discuss total scores for each solution solutions are ranked relative to th at solution.Improve – Step 10: Identify Solution Page 233
  • 233. Tool 1: Criteria Based Matrix-Example Imagine that you are buying a house. You have already decided what your “musts” criteria are and they include budget (how much can you spend) and size (square footage). Although you have looked at many houses, only two meet the “must” criteria. Likely Solution Solution A Solution B Now you are ready to compare these two houses on the want criteria you have already established. After closely examining the list, you decide theWant criteria “top want” is good schools (you don’t want to have to pay fo r private schools, too!) and you ranked that “want” a 10. The rest of the criteria are rankedCriteria Weight relative to that “want”.1. Big Yard 2 4 8 10 202. Neighborhood with kids 8 The next step is to compare the two houses against each specific criteria. 10 80 5 40 The house that BEST meets the criteria is ranked “10” and th e other house3. Good schools 10 10 100 8 80 is ranked relative to that 10. For example, House #2 best met the “big yard”4. Proximity to work 9 81 90 criteria so it was given a rank of 10. House #1 was given a rank of 8 9 10 because although it had a big yard, it wasn’t as good as House #2.5. Three Car garage 6 10 60 4 24 After both houses have been ranked on all criteria, multiply the weight by the score for each criteria to get the weighted score for each criteria. Total the scores and you will be able to then discuss the results of the matrix. Note: Total 329 254 The final totals that are obtained are less important than the discussion of the relative merits of each solution that occurs as teams use this tool.Improve – Step 10: Identify Solution Page 234
  • 234. Tool 2: “Should Be” Mapping Develop A “Should Be” Map For Realistic, Viable The solution selection tools in the previous p ages can lead to either a short list of 2 -3 potential solutions or one specific solution. Either way, you will now Solution Alternatives gather data on these solutions in order to determine which is most effective. The “should be” map will be used as a foundation for documenting new procedures, a step that will occur in the Control phase. This map willWhat You Think It Is... What It Really Is... What It Should Be... What It Could Be... incorporate any of the process step changes that have been identified as a result of the potential solution. Make sure that the new map accurately reflects the process. Also, keep in mind that when the solution is implemented, the “should be” map then becomes the new “as is” map. For whatever solution is chosen, a “should be” map for each potential solution must be developed at this point. Improve – Step 10: Identify Solution Page 235
  • 235. Identifying Solution/Testing Solution –Overview Benefits of Testing Solutions ? Confirm relationship Y=f(X) ? Improve the solution to better meet customer CTQs ? Provide an opportunity for feedback ? Increase buy-in for a possible solution Tools For Testing Solutions ? Modeling ? Simulation ? Design Of ExperimentsImprove – Step 10: Identify Solution Page 236
  • 236. Tool 1: Modeling Physical models, suc as blueprints, such mock-ups, and prototypes Mathematical models, such as pricing4 = ƒ (xx,,,,xx,,,xx)))) models, risk models, and financial 4 = ƒ(x11 ,x222 ,xx ((x 1 x 333 x1 ((x modelsImprove – Step 10: Identify Solution Page 237
  • 237. Tool 2: SimulationTypes of Simulations Simulation can help you:Computer Simulation ¦ Identify interactions and specific problems in an existing or proposed processA computer model that describes relationships and interactions ¦ Develop a realistic model for a process ¦ Predict the behavior of the process under different conditionsDiscrete Event Simulation ¦ Optimize process performanceDiscrete event simulation is conducted for processes that are dictated byevents at distinct points in time; each occurrence of an event impacts thecurrent state of the process. Examples of discrete events are arrivals ofphone calls at a call center. Timing in a discrete model increasesincrementally based on the arrival and departure of the inputs or resources.ProcessModel™ is an example of a software tool for running discrete eventmodels.Continuous SimulationContinuous simulation is used for processes whose variables or parametersdo not experience distinct start and end points. Examples of this variable typeare heat added to an oven, mixing rate, or fluid flow. In a simulation model,these parameters may change continuously over the execution time of thesimulation run. CrystalBall™ is an example of a software tool for runningcontinuous models.Simulation is a powerful analysis tool used to experiment with a detailedprocess model to determine how the process output Y will respond tochanges in its structure, inputs, or surroundings Xs. Using simulation, you cangenerate process data needed to make decisions about the design andoperation of your process. While it will not solve specific problems, simulationcan help you evaluate alternate solutions by providing quantitative measuresunder a variety of conditions. Different process situations need different typesof simulations.Improve – Step 10: Identify Solution Page 238
  • 238. Tool 3: Design Of Experiments (DOE) -ApproachDesign Of Experiments is an approach for effectively and efficiently exploringthe cause and effect relationship between numerous process variables (Xs)and a process performance variable (Y).Design Of Experiments Approach To verify the “vital few” X(s) that impact the quality of Project Y(s) To identify the best combination of X-values to optimize process performance and meet customer CTQs DOE can be applied in either the Analyze or Improve phases of DMAIC, or both. In analyzing a problem, DOE can be very powerful in isolating the vital few causes from the many factors affecting a process. In Identifying and Testing Solutions, a team can apply DOE to compare the results of several possible solutions. The team can develop a more effective final solution by measuring effectiveness of the improvements in actionImprove – Step 10: Identify Solution Page 239
  • 239. Tool 3: Design Of Experiments (DOE) –BenefitsDOE Benefits Can be used to identify “Vital Few” sources of variation Defines the relationship between the inputs and outputs Allows you to measure the influence of the “Vital Few” variables on a response variable Is more effective and efficient than testing one factor at a time Minimizes the number of test runs you have to make to draw valid conclusions about X and Y linkagesImprove – Step 10: Identify Solution Page 240
  • 240. Tool 3: DOE Terminology (1) Remember that the dependent variable (Y) is measured from the customer’s perspective. DOE allows us to identify the Xs that are the key drivers of variation in the Y. Independent Variables – Xs • Also called factors "Project Y" Dependent • Factors or variables we select in advance • The causes Independent X (5Ms a nd 1P) (x) (x) (x) Dependent Variables – Y M M M • Also called responses Project Y • The quantity (Y) that we measure to determine the impact of the Xs P M M • The effect (x) (x) (x) Levels For example: Y = cycle time The test settings for X X 1 = type of application Levels = new, old X 2 = # of associates Levels = 1, 2, 3Improve – Step 10: Identify Solution Page 241
  • 241. Tool 3: DOE- Terminology (2) Main effects Main effectsMain Effects Cycle Time Cycle TimeDifferences between each factor level Y YFor example: Is the cycle time different for: X Xa) New or old application forms? new ald 1 2 3 Type of applications Number ofb) 1, 2, or 3 associates? associatesInteractionsDifferences between two or more factor level combinations Interactions neuFor example: Is cycle time different when: Cycle Time •new, 1 associate old, 1 associate alt • Ynew, 2 associates old, 2 associatesnew, 3 associates old, 3 associates X 1 2 3 Number of associatesImprove – Step 10: Identify Solution Page 242
  • 242. Tool 3: Steps For DOE (1)1. Define the problem2. State the Hypothesis3. Identify the dependent (Y) and independent (X) variables4. Determine the test levels for each independent variable5. Calculate the number of trials to test all combinations of test levels6. Construct the experimental trials table7. Run the experiment8. Summarize the data9. Draw conclusions and make recommendationsImprove – Step 10: Identify Solution Page 243
  • 243. Tool 3: Steps For DOE (2)1. Define the problem The mileage on my new car is not up to advertised standards; “I want to improve my car’s mileage”2. State the Hypothesis Some combination of speed, gas octane, and tire pressure will provide me with the optimum gas mileage3. Identify the dependent (Y) and independent (X) variables Dependent Variable: ? Gas Mileage (Y) Independent Variables: ? Tire Pressure (X) ? Octane (X) ? Speed (X)4. Determine the test levels for each independent variable Independent Variables (Xs) (Factors) Level + Level - Tire Pressure (psig) Octane Speed (mph) Y is called the dependent variable because its value depends upon the level setting for X. X is called the independent variable because its value is set independently. X will sometimes be called an experimental factor. Level - represents the low value of the levels. Level + represents the high value of the levels.Improve – Step 10: Identify Solution Page 244
  • 244. Tool 3: Steps For DOE (3)5. Calculate the number of trials to test all combinations of test levels ? Number of test levels number of factors =23 = 8 trials6. Construct the experimental trials table Tire pressure Octane Speed Mileage - - - + - - - + - + + - - - + + - + - + + + + + ? How many trials would be necessary if there were 4 variables each at 2 levels? How many variables would there be before the cost became too expensive? ? What would be a different type of experiment that would not require all possible runs? ? The experimental trials table represent all possible combinations of the three factor levelsImprove – Step 10: Identify Solution Page 245
  • 245. Tool 3: Steps For DOE (4) In this experiment, only one run of each experimental trial was conducted.7. Run the experiment Additional runs would increase the confidence level for the results. Replication is a repeat of all experimental trials to obtain additional data to Tire pressure Octane Speed Mileage increase the degree of confidence in the experimental results. Replications are used when: - (30) - (87) - (55) 26 ¦ The interactions are of critical importance. + (35) - (87) -(55) 27 - (30) +(92) -(55) 30 ¦ Data is difficult to obtain. Replications will supply an extra data point when data from an experimental trial is lost. + (35) +(92) -(55) 33 - (30) -(87) +(65) 18 ¦ You need to increase the degree of confidence in the experimental results. + (35) -(87) +(65) 21 - (30) +(92) +(65) 19 ¦ You need to reduce the risk of failure when implementing solutions. + (35) +(92) +(65) 22What effects (main and interaction) seem to be significant? Main effect is the effect of one X on the Y Interaction effects are the combined effects of two or more Xs on the YImprove – Step 10: Identify Solution Page 246
  • 246. Tool 3: Steps For DOE (5) The Pareto Chart shows the relative importance of each main effect and8. Summarize the data interaction in the experiment. The length of each bar shows relative impact. Bars that cross the dashed line have significant impact on the Y.Pareto Chart of the Effects (Response is Mileage, Alpha = .05) What is the best speed to get the best gas mileage? The Main Effect Plots show the average value for each of the levels of the C three independent variables. Each average is based on 4 data p oints. B A: Pressure A BC B: Octane AC C: Speed ABC AB 0 1 2 3 4 5 6 7 8 9 # of miles per gallon Which factor has the biggest effect on gas mileage?Main Effects Plot (data means for Mileage) - +– + – + 28 26 Mileage 24 22 20 30 Pressure 35 87 Octane 92 55 Speed 65Improve – Step 10: Identify Solution Page 247
  • 247. Tool 3: Steps For DOE (6)8. Summarize the data (continued) Cube plot for gas (milage) -,+,+ +,+,+ 19 22 Pressure, Octane, Speed -,+,- +,+,- 33 30 + - ,-,+ +,- ,+ Octane 18 21 + 27 - - Speed 26 - + - ,- ,- Tire pressure +,-,-Each corner of the cube represents an experimental trial from the trial table¦ For example, when tire pressure is -, octane is -, and speed is -, the gas mileage is 26¦ Can you tell which combination of tire pressure, octane and speed is the best by looking at the cube?¦ The cube shows the result of the interaction between tire pressure, octane and speed9. Draw conclusions and make recommendations¦ Speed has an important effect on gas mileage - Drive at 55 to get the best gas mileage¦ Tire pressure doesn’t significantly affect gas mileage - Set tire pressure for best tire wear results¦ Octane doesn’t significantly affect gas mileage - Buy the octane that optimizes cost or engine cleanlinessImprove – Step 10: Identify Solution Page 248
  • 248. Refine and Test Solution - OverviewTools for analyzing potential problems and refiningsolutions: Potential Problem Analysis Errorproofing Failure Modes and Effects Analysis (FMEA)Identifying the risk/problems associated with a particular solution is criticallyimportant to the overall success of your project. The tools listed above willhelp you thoroughly examine your solution for risks or problems. The depth ofanalysis required depends upon the level of complexity of both the processbeing improved as well as the complexity of the solution.Improve – Step 11: Refine and Test Solution Page 249
  • 249. Tool 1: Potential Problem Analysis These questions are effective at helping your team thoughtfully and criticallyFour Questions To Help You Think About analyze the full effect of your solution. Thinking about unintended consequences is an effective way to beginUnintended Consequences examining your solution for risk/problems. Critically evaluating the solution for the full range of results – both intended and unintended – will help your Changes to the organization: team more fully prepare a successful solution implementation. ? What does this idea for improvement enhance or Other Questions To Consider: promote? (Can be positive or negative enhancement) ¦ Does the solution drain resources from another area? ? What happens when it is taken to the limit or extreme? ¦ How will the solution impact: Shifts in program focus or emphasis: - Existing processes? - Systems and structures? ? What does this idea make obsolete? Or leave behind? - Demand for resources? ? What does this idea retrieve or bring back?Improve – Step 11: Refine and Test Solution Page 250
  • 250. Tool 2: Inspection / Errorproofing ¦ To prevent errors, a “natural” tendency is to add inspection stepsTo experience first-hand the value of inspection as ¦ Effectiveness of inspection: If each inspec tor detects 70% of errors anda quality control method: inspectors are “in series,” then: What How Who Process Error rate % # Inspectors to reach 6 Sigma 10% 9 ¦ Individually, read the 1% 7 paragraph printed below. 0,10% 5 Read through it only once. 0,00% 3 Count the “f´s” ¦ As you read, count the Individuals number of letter “f´s” you find. ¦ The alternative to inspection: Errorproof! ¦ Record your count in the Once your team has analyzed potential problems with your solution, you space provided. must design elements or steps which can help you prevent those problems from occurring. The chart above demonstrates why it is not good enough to simply add a step for inspection or quality control at the end of a process to fix problems – it is simply too costly. The team will need to think creativelyThe necessity of training farm hands for first-class farms in the fatherly about how to deal with the problem at its root.handling of farm livestock is foremost in the minds of farm owners. Since theforefathers of the farm owners trained the farm hands for first-class farms inthe fatherly handling of farm livestock, the farm owners feel they should carryon with the family tradition of training farm hands of first-class farms in thefatherly handling of farm livestock because they believe it is the basis of goodfundamental farm management.Please record the total number of “f’s” counted:Improve – Step 11: Refine and Test Solution Page 251
  • 251. Tool 2: Inspection / Errorproofing - Example Other examples:Railroad Crossing ¦ Return envelope window: Customer has to return pay stub with payment ¦ Customer authorized billing: Signed installation record triggers billing to Safety precautions at discretion prevent pre-billing error Implicit rules of driverMinimize Driver must come to a complete Explicit Rulesopportunity for stoperror Low-Level Bells ring, lights blind, and physical automatic arm descends as train intervention approachesEliminate High-Level Traffic routed arround track, i.e.,opportunity for physical under/overpasserror InterventionA process that is truly errorproofed is one where a participant doesn’t havethe option of making an error. In the example above, the last option has“errorproofed” the railroad crossing. Depending on the type and complexity ofyour process as well as your available resources (time and money) you willhave to decide at which level you can errorproof.Improve – Step 11: Refine and Test Solution Page 252
  • 252. Tool 3: Failure Mode Effects Analysis (FMEA)FMEA (Failure Modes And Effects Analysis):A tool to identify and evaluate possible product or process failures and therisks associated with them. Use the FMEA to build a plan for reducing oreliminating that risk.FMEA is typically used to identify and assess risk for complex processes.However, even if your process is not complex, FMEA is still useful in helpingthe team to look critically at risks.Product Or Service Design FMEAUncover problems that may result in:¦ Safety hazards¦ Malfunctions¦ Shortened product life or decreased service satisfactionAsk, “How can the product or service fail?”Process FMEAUncover process problems that may result in:¦ Safety hazards¦ Defects in product or service production process¦ Reduced process efficiencyAsk, “How can people, materials, equipment, methods, and environmentcause process problems?”Improve – Step 11: Refine and Test Solution Page 253
  • 253. Tool 3: Why Use A FMEA? To identify and prioritize parts of the product or process that need further improvement To ensure the quality, reliability, and safety of products and services To increase customer satisfaction by preventing or reducing impact of errors To document and track actions taken to reduce risk To develop action plans to avoid risk/defectsFMEA can help to ensure that your solution will be successful. FMEA will beused again in the Control phase to help develop the response plan.When To Use FMEA? When a service, product or process is created, improved, or redesigned When existing products, services, or processes are used in new ways or in new environments In the Improve phase of DMAIC to expose potential problems in the solutionProcess FMEAs are living documents that need to be updated as the teamlearns more about a process or as the process changes.Improve – Step 11: Refine and Test Solution Page 254
  • 254. Tool 3: FMEA Design Worksheet Process /Produc t : FMEA Date: (original) FMEA Team: (Revised) : Black Belt: Page: of FMEA Process Action results Occurence Occurence Detection Detection Responsibility Severity Severity Potential Potential Recommended and target RPN RPN Item/Process Potential Effect(s) of cause(s) of Current Action taken Step Failure mode Controls Action completion date failure failure Total Risk priority Number Resulting Risk priority NumberImprove – Step 11: Refine and Test Solution Page 255
  • 255. Tool 3: Steps for FMEA1. Review the product, service, or process2. Brainstorm and group possible failure modes3. List one or more potential effects for each failure mode Answer the question: If the failure occurs, what are the consequences?4. Assign a severity rating for each effect5. Assign an occurrence rating for each failure cause6. Assign a detection rating for each failure mode7. Calculate risk priority number (RPN) for each effect8. Use the RPNs to select high priority failure modes9. Plan to reduce or eliminate the risk associated with high priority failure modes10. Carry out the plans11. Recompute RPNTo do a FMEA effectively, you must have knowledge and expertise on theprocess you are assessing. Be sure to validate your assessment with keystakeholders.Improve – Step 11: Refine and Test Solution Page 256
  • 256. Tool 3: FMEA Ratings (1)FMEA: Severity Rating ScaleSeverity – the consequences of a failure should it occur Bad/Severe Rating Criteria – a failure could: Failure 10 Injure a customer or employee 9 Be illegal/cause controllership issues 8 Render the product or service unfit for use 7 Cause extreme customer dissatisfaction 6 Result in partial malfunction 5 Cause a loss of performance which is likely to result in a complaint 4 Cause minor performance loss 3 Cause a minor nuisance, but be overcome with no performance loss 2 Be unnoticed and have only minor effect on performance Good 1 Be unnoticed and not affect the performance The above example can be modified to fit a specific service, product, or process.Improve – Step 11: Refine and Test Solution Page 257
  • 257. Tool 3: FMEA Ratings (2)Occurence Rating ScaleOccurrence – The Likelihood Or Frequency Of Failure Bad Rating Time period Probability 10 More than once per day > 30% 9 Once every 3-4 days 30% 8 Once per week 5% 7 Once per month 1% 6 Once every 3 months .03% 5 Once every 6 months 1 Per 10,000 4 Once per year 6 Per 100,000 3 Once every 1-3 years 6 Per Million 2 Once every 3-6 years 3 Per 10 Million 1 Once every 6-100 years 2 Per Billion Good The above example can be modified to fit a specific service, product, or process.Improve – Step 11: Refine and Test Solution Page 258
  • 258. Tool 3: FMEA Ratings (3)Detection RatingThe likelihood of a failure being detected before its effect is realized Rating DefinitionBad 10 Defect caused by failure is not detectable 9 Occasional units are checked for defect 8 Units are systematically sampled and inspected 7 All units are manually inspected 6 Units are manually inspected with mistake-proofing modifications 5 Process is monitored (SPC) and manually inspected 4 SPC is used with an immediate reaction to out-of-control conditions 3 SPC as above with 100% inspection surrounding out-of-control conditions 2 All units are automatically inspectedGood 1 Defect is obvious and can be kept from affecting the customerThe above is an example and can be modified to fit a specific service, product or process.Total RPN is determined by multiplying all of the individual scores.This total is useful only to compare the revised total against theoriginal, and not to compare between different products orprocesses.Improve – Step 11: Refine and Test Solution Page 259
  • 259. Tool 3: FMEA Tips Use Brainstorming and/or data analysis methods to identify key failure modes ? Critical process or project steps ? High cost and/or customer impact ? High probability (problems we see often) Remember: Numbers are judgments Identify proactive/preventive steps to reduce likelihood of failure Have damage control steps – a recovery plan in case of failure ? Errorproofing Use to help prioritize future improvement efforts Part of the value of the FMEA is the discussion that is generated as a result of its useFMEA is a very useful technique when used wisely. Follow these guidelinesto ensure your analyses help “fail-safe” your process and/or project.Improve – Step 11: Refine and Test Solution Page 260
  • 260. Tool 4: Pilot A SolutionPilot definitionA test of all or part of a proposed solution on a small scale in order to betterunderstand its effects and to learn about how to make the full scaleimplementation more effectiveBenefits of piloting Improved solution that meets customer CTQs Refined implementation plans Lower risk of failure by identifying and fixing problems Confirmation of expected results and relationships (of X and Y) Increased opportunity for feedback and buy-in Gets an early version of a solution out quickly to a particular segmentImprove – Step 11: Refine and Test Solution Page 261
  • 261. Tool 4: When To Pilot The pilot test has become an excellent vehicle for transferring technology by The scope of the change is large demonstrating results through a committed group of employees and managers. The change could cause far-reaching unintended consequences Implementing the change will be a costly process The change would be difficult to reverseImprove – Step 11: Refine and Test Solution Page 262
  • 262. Tool 4: 8 Steps For A Pilot (1)1. Ensure strong leadership from top management ? Clearly seen to be committed ? Possess an understanding of new solution ? Assist in the selection of the steering committee2. Select a steering committee ? Appoint a project leader (who will work full time as the liaison between the pilot area and management) ? Provide resources ? Conduct periodic reviews ? Include employees from the Pilot area3. Thoroughly plan the Pilot ? Develop Data Collection Plan ? Establish improvement goals ? Review and “measure” current operations ? Set target scheduleImprove – Step 11: Refine and Test Solution Page 263
  • 263. Tool 4: 8 Steps For A Pilot (2)4. Conduct briefings ? For management, steering committee and project team ? Management and teams should have access to all necessary material/publications/videos, etc.5. Prepare a comprehensive communication plan to sell the pilot to affected employees ? Get management approval ? Conduct employee briefings ? Explain team participation ? Present Cost Benefit Calculation6. Train employees ? Include all affected workers ? Check for employee understanding ? Answer employee concerns ? Review pilot plan (may need to be modified)Improve – Step 11: Refine and Test Solution Page 264
  • 264. Tool 4: 8 Steps For A Pilot (3) When it is too expensive to Pilot, or any solution involves a change that once7. Monitor Pilot implementation made is difficult to reverse, teams can consider simulation or modeling as an alternative . ? Record observations ? Ensure feedback of results to: ? Employees ? Steering committee ? Project team ? Management8. Debrief/make necessary changes after pilot ? Record findings in writing ? Note problems encountered and lessons learned ? Document benefits ? Make a formal presentationImprove – Step 11: Refine and Test Solution Page 265
  • 265. Tool 4: Verification of A PilotUse the information gained from asking the questions below to determine ifyour results support full roll-out of your solution across the business.To assess the effectiveness of a solution:1. Calculate the new process capability (sigma) and compare it with the improvement goal and the original process2. Compare before and after visual tools so you can analyze the data visually3. Use Hypothesis Testing to see if a significant statistical difference exists between the old versus the new processConsider overall effectiveness: Was the process improvement successful in satisfying the needs of the customer? Did the solution result in any additional benefits?Assess the execution of the pilot:1. Was the schedule met?2. Were instructions clear?3. Were instructions followed?4. What extra information did people need?5. What forms/tools were helpful? What could have helped?6. What unexpected difficulties were encountered?Improve – Step 11: Refine and Test Solution Page 266
  • 266. Tool 4: Pilot Tips The improvement team should be present as much as possible during the pilot process; what they learn and observe will be worth the time they invest Collect data on process and external factors that may be influential If possible, make sure that the full range of inputs and process conditions are tested in the pilot Expect “scale-up” issues after even the most successful pilots Identify critical differences between the pilot environment and the full-scale implementation environment; note potential issues/problems for full-scale planImprove – Step 11: Refine and Test Solution Page 267
  • 267. Cost Benefit Calculation – Overview (1) Communicates in financial terms why it makes good business It is important to quantify the benefits of your project and compare them to sense to implement your selected solution(s) the cost of pursuing the solution. This Cost Benefit Calculation allows you to determine if the project has clear financial payback. It will help you to May include such calculations as net present value, internal aggregate benefits, align them with business measurements, and track rate of return, return on equity, payback period, and other them. information of interest In most cases, your project will have intangible benefits which are difficult or Uses the methodology preferred by your business impossible for you to quantify. In other cases, your project may reduce costs or increase revenues in ways which are easier to quantify. This Cost Benefit Identifies the criteria against which you can measure financial Calculation could then strengthen your case for project implementation with success senior management. Helps involve others in the project solution by creating buy-in In either case, it is more important to report your benefits than to allow and support concerns about accuracy of your quantification to prevent you from reporting. Experience has shown that teams typically undervalue the impact of their projects.Improve – Step 12: Cost Benefit Calculation Page 268
  • 268. Cost Benefit Calculation – Overview (2)When do you perform a Cost Benefit Calculation?¦ Perform a Cost Benefit Calculation before fully implementing your project or when deciding on a solution.¦ If the justification for the project is to cut costs, the Cost Benefit Calculation should clearly support your case.¦ If the justification is to improve quality, the implementation costs, at a minimum, should be addressed.What should you consider?¦ Concentrate on direct costs and direct benefits.¦ Consider the activities affected by the implementation of the project and determine the appropriate measurement variable. The process manager should have information to help you determine the impact and appropriate measurement. Standard or average rates can be used and obtained from the process manager or the finance department.Improve – Step 12: Cost Benefit Calculation Page 269
  • 269. Cost Benefit Calculation – Overview (3) Benefits A Cost Benefit Calculation allows you to quantify the financial aspects of allow your project. Some benefits will be difficult to quantify. Such benefits should wil be separately listed as unquantified. Be cautious with cost avoidance benefits. Unless you have documented baseline of costs over time, it will be difficult to prove the benefits of your project. When such costs are not historically measured, you may n eed to categorize cost avoidance as ma unquantified or intangible. Costs Cost Benefits Benefit The cost section of a Cost Benefit Calculation includes the costs incurred to research and implement the project. Only incremental costs should be considered in this analysis. Incremental costs are costs which are only being Incrementa incurred because of your decision to pursue your solution. For example, if decisio you recommended that a new computer be purchased in order to improve w Benefits Cost Of Implementation t customer service, the purchase cost of the computer would be an purchas • Quality improvements • Equipment and materials incremental cost of the project. Additional examples of project project • Cost reductions • Training implementation costs would be team members’ time on the project, programming time to code system improvements, and printing and material syste • Documentable cost avoidance • Improvemen team labor Improvement costs. • Revenue generation • Trave and living expenses TravelImprove – Step 12: Cost Benefit Calculation Page 270
  • 270. Cost Benefit Calculation – Types Of Costs You may also look at the following costs:Cost reductions or avoidances Incremental Costs – additional costs that would be incurred from theThese are typically costs already tracked by the accounting system, referred recommended change or action plan.to as direct costs. Indirect costs are those less tangible costs not tracked by Opportunity Costs – the potential benefit that is lost or sacrificed when thethe accounting system. choice of one course of action requires the giving up of an alternative courseMany studies have been done to estimate the relationship between direct and of action.indirect costs. For most businesses, the indirect cost benefits of a project aremany times the direct costs. This is analogous to an iceberg: you only see thetip of the iceberg above the water.Cumulative Cost/BenefitThis compares the total cost of implementation to the measurable benefits.This will reflect the project’s financial impact, over time. Some projects havelimited costs and will show an immediate payback. Others will take timebefore the costs are recovered.The break-even or payback time is the time it takes for the cumulativebenefits to exactly equal the project cost. To determine if the payback periodis appropriate, compare it to:¦ The impact of the project¦ The length of time the process will existImprove – Step 12: Cost Benefit Calculation Page 271
  • 271. Cost Benefit Calculation – Example ExampleCosts (First Year) Benefits (Yearly) A problem -solving team used a Cost Benefit Calculation to find out if a solution was practical from the cost point-of-view. Members had beenEquipment 3.000 Increased capacity (reduced cycle time) 750 looking at the problem of rework in their department. While analyzing theTraining 500 Reduce Rejects by 50% 4.000 problem for cause, they discovered that the largest piece of the problem wasTravel and living 250 Reduce labor hours for the job 500 rejects. They identified various ways of improving their existing machinesTeam labor 500 Reduces interest expense 750 and processes. They also considered implementing a more intensive inspection process. Finally they decided that a new piece of equipmentTotal cost $ 4.250 Total Benefit $ 6.000 costing $3,000 was the best alternative. The team performed a Cost Benefit Calculation – considering all the costs associated with getting the new equipment up and running – to find out if the solution they had chosen was cost-effective. They examined the cost/benefit and assumed a 10% Required Return rate.Improve – Step 12: Cost Benefit Calculation Page 272
  • 272. Cost Benefit Calculation - Tips Concentrate on tangible costs and benefits; use indirect costs that are generally acceptable to all stakeholders Use the process map and personnel in associated departments to identify cost and benefit information Keep the analysis simple; focus on cost of implementation and a few key benefits that clearly exceed the cost Use standard methods and rates in your calculations List all activities that contribute to either cost or benefit and identify as much as possible how these activities will be measured Keep the presentation simple and easy to understandImprove – Step 12: Cost Benefit Calculation Page 273
  • 273. Control Roadmap DEFINE MEASUR MEASURE ANALYZE IMPROVE CONTROL 13. Implement Process Control s: Deliverables: • Ensure Full implementatio of solution including monitoring system implementation Documentation Monitoring Response Plan 14. Prepare Roll-Out Solution Deliverables : • Roll out from Project statu into operational business status Influence Strategy Resources Implementation And Roll-out $ TOP $ $ The $ Plan QxA=T 15. Project Closure Deliverables: • Validation of financial benefit • Ensure full hand-over an communication and Team Celebration! Communicate Learning dbQ dbControl - Overview Page 274
  • 274. Control Overview Step 13: Implement Process ControlPurpose: Ensure a full monitoring system for the newly implemented process Process Management Chart Documentation Selecting Control ChartsControl Limit CalculationsInterpreting Control ChartsResponse Plan Step 14: Prepare Roll-Out SolutionPurpose: Hand over to Process Owner and to the organization Change Acceleration Process (CAP) Stakeholder Analysis Implementation Plan Elements Step 15: Close projectPurpose: Communication of final results and closure of project Documentation package Communication of learnings Team closure Fully Implemented Results Of ProjectOutcome Process Control Plan Solution CommunicatedControl - Overview Page 275
  • 275. Why Control? One of the most common problems improvement teams face is holding the gains. For example, in the chart, a project team found the root causes and selected a solution that resulted in significant improvement. However, making the solution recommendation is only half the battle. In many cases, teams are not empowered to implement the solution. The hand -off to an implementation team causes several difficulties: ¦ The process owner/team may not be as familiar with the data, analysis and/or solution and may make compromises that weaken the solution. Improvement ¦ Clear documentation for how the improved process is supposed to operate is unavailable. ¦ Clear documentation for how to respond when a problem occurs is unavailable. A thorough process control monitoring plan will successfully address these issues. However, in order for the plan to be effective, it needs to be smoothly and efficiently rolled out to the key stakeholders as well as the business at large. Before Successful No Controls Improvement Implementation In Place Time Keep The Process In Control So The Customer Remains SatisfiedControl - Overview Page 276
  • 276. Process Control IntroductionOutside-In Perspective Focus on the customer perspective must be maintained throughout the Control phase Identify measures for the Control Plan that track key customer CTQs Check with the customer to make sure the solution has improved the process from his/her viewControl – Step 13: Implement Process Control Page 277
  • 277. Tool 1: Process Management Charts A Process Management Chart is a tool that is the foundation for the ProcessA Process Management Chart is a flowchart and Control Plan. It has proven to be useful in developing, summarizing andmatrix which helps you manage a process by implementing a plan for process control.summarizing: Process Management Charts also underscore the ownership of the process by the process owner. The process owner is typically a business manager with primary responsibility for the ongoing performance of the process being improved. Since the process owner is responsible for holding the gains • The deployment flowchart (“should be” map) achieved by the improvement team, the process management chart is a Documentation • Who does these steps and when valuable tool for the management of that process. • Where more detailed work instructions can be found • Measures of key drivers of process performance • Where data is taken on the process and on the product/service • Who takes the data Monitoring • How (by what methods ) measurements are taken and recorded • When (how often ) data is collected • Measurement process reviews • Who takes action based on the data Response Plan • What action to take • Where to find trouble-shooting proceduresControl – Step 13: Implement Process Control Page 278
  • 278. Tool 1: Process Management Charts – Example Process Management Charts provide, on one page, essential information on the following: who does what, when and sometimes where and why regarding the doing, checking (monitoring) and acting (responding to Documentation Monitoring Response Plan signals) of the process under study.The Plan For Doing The Work Checking The Work The Response To Special Causes Deployment Detail On Key Process Key Process Monitoring Method For Containment Monitoring Method For Containment Procedure Procedure Procedure Flowchart Flowchart Key Tasks And Output Recording Standards Recording For Process For System Measures Measures Data Data Adjustment Improvement Improvement For Each Identifies Identifies Diagram Which Identifies In A For Each For Each Describes Identifies Who Key Step In Should Who Should Illustrates Word OrOr A Word Measure, Measure, Measure, What What Must Be In The The Do What Do What Process Steps Process Steps The Phrase The Phrase The Describes Describes Describes Describes Done To Gain Done To Gain Organization Organization Process, With The Separated By Process, Measures To Any How The With The Sufficient Needs What Separated By Shows How Measures To Any How The Output Of Sufficient Needs What Function. Shows How Be Imprtant Monitored Output Of Understanding Data In What Function. The Task Be Imprtant Monitored The Understanding Data In What Shows The Task Monitored In Target, Data The Of This Form In Order Shows Should Be Monitored In Target, Data Defective Of This Form In Order Transfers Each Critical Numeric Should Be Defective Process So To Make A Transfers Should Be Done, Or Each Critical Numeric Should Be Process. Between Step (e.g. Limits, Or Recorded That TheSo Process To Make A Sound Functions, And Refers Or A Done, To Process. Decision Between Defects, Step (e.g. Tolerances Limits, Or (e.g. Recorded Describes Associates That The Sound Which Function Functions, And Document A Refers To "Timeliness", Defects, To Which A Tolerances Checklist, (e.g. What Should Know What Associates Regarding Decision Describes Is Responsible Which Document etc. Process A Run Chart, Be Done For Adjustments New Systems Which Function "Timeliness", To Which Checklist, What Should Know What Regarding At Responsible Is Which Step. Describes Which Should Scatter Run Chart, Those Who And Or Remedies etc. Begins With Process Be Done For Adjustments New Systems The Step. Describes Conform If Accommodati At Which Step. Those "Vital Should Diagram, Scatter Were Those Who And Or Deeper At Remedies The Step. Begins With It Is Pareto , etc. Damadged ons Are Levels In The Signs" "Vital Conform If Diagram, Were Accommodati At Deeper Those Which Running By These Routinely Organization Are Related It Is Pareto , etc. Describes, Damadged ons Are Levels In The Signs" Which Well. Defects . Necessary To (e.g., To Problems Running If By These Routinely Organization Are Related Describes, Prevent A Changes In That Have Standards Well. Necessary, Defines Defects . Necessary To (e.g., Designs To Problems If Recurrence Of Basic Been May Come Who What This Problem. Prevent A Or Policies). Changes In That Have Experienced. Standards From Necessary, Should Defines Adjustments Recurrence Of Basic Designs Been Customers, May Come Who The Record What Be Should Regulatory Data And Made To This Problem. Or Policies). Experienced. From Should Adjustments Policies, Customers, How. Record The AssureThat Should Be (ISO), Or Regulatory Data And There Will Made To Process Policies, How. Be No AssureThat Knowledge (ISO), Or Defects In There Will Expertise. Process The Next Be No Knowledge Iteration. Defects In Expertise. The Next Iteration. Control – Step 13: Implement Process Control Page 279
  • 279. Tool 2: DocumentationDocumentation is a necessary step to ensure thatthe learning gained via improvement is shared andinstitutionalizedOften, processes evolve in an ad hoc fashion. How to accomplish eachprocess activity is usually left up to the individual and thus, muchorganizational knowledge resides only in the minds of associates. Improvedprocesses require new or revised documentation about their component partsor activities for many reasons: As a training aid As an implementation tool (reduces process variation and enhances best practices) To institutionalize change To describe the flow of the process and standard procedures for operating the process including process flowcharts and work area layouts To provide approved information for all current and future employees who will need it To increase organizational learning and provide training materials To ensure consistent operating procedures and reduce process variationControl – Step 13: Implement Process Control Page 280
  • 280. Tool 2: Levels of Documentation Earlier we learned about levels of a process:L ¦ Coree Process management chartv ¦ Subprocessel ¦ Microprocess Process map/flowcharts (e.g., deploymento It is useful to associate different types of process documentation withf flowchart) different levels of the process.det Proceduresail Checklist Control – Step 13: Implement Process Control Page 281
  • 281. Tool 2: Documentation Deployment Flowcharts This is a Flowchart that clearly shows who does what in what sequence. In a deployment flowchart the people or groups who are involved in the process are listed across the top. The process steps appear in the column under the Research Administration Marketing person or group who carries them out. The sequence of steps flow from theCombines two top of the chart to the bottom. Steps that occur at the same time are drawn Step 1 in parallel with a branched line leading from the previous step into bothkey features: parallel steps. Step 2 A common mistake is to put the first step in each column at the top of the page instead of placing each step lower on the page than the preceding• The sequence of steps in a step. This mistake makes the Flowchart very hard to interpret. (Steps 3, 4, process (business process and 5 above are placed lower than the preceding steps.) Step 3 map) Showing Relationships• Who is responsible for each This kind of Flowchart is particularly helpful in processes with many hand- offs, where information or material is passed back and forth among people step? or groups. Each time a flowline crosses from one column to another, that is a Step 4 Step 5 hand-off. In crossing between columns, the flowline also depicts a customer- supplier relationship: one person or group is supplying another person or group with information, materials, etc. Handoff areas are prone to errors and confusion. People may not know Step 6 when they should get involved, when to expect to receive something from other groups, and so on. Making the hand-offs clear is a key benefit of using Step 7 deployment flowcharts instead of some other kind of flowchart. Hand-off points are also good places to collect data to help determine how often problems occur and which type of problem occurs most often. Control – Step 13: Implement Process Control Page 282
  • 282. Tool 2: Documentation – Procedure (1)A Procedure is the documented sequence of steps and other instructionsnecessary to carry out an activityWhat is a Procedure?Procedure sheets are the details behind the activities documented on theprocess management chart. They serve as a vehicle for every employee –from senior executives to hourly workers – to gain an understanding in theircontext of the improvement. Procedures are both a training aid and a meansto ensure successful implementation.Questions to ask when there is trouble: Do we have a Standard Procedure? Does the employee know the Standard Procedure? Does the employee use the Standard Procedure? (Do we enforce the Standard Procedure?)Control – Step 13: Implement Process Control Page 283
  • 283. Tool 2: Documentation – Procedure (2)PurposeTo gather technology and process skill in written form and to make it easierfor everyone to do his/her work.Contents Procedures should be at such a level that the job can be performed well by associates who are not fully trained They should be specific. Tell precisely what actions to take and when and where to take them. Make it clear where people’s responsibilities lie They should describe how to prevent product and service variation. Thus, they must describe underlying cause and effect relationships They must be able to be followed. Ensure that there are no contradictory or unrealistic instructions Priorities must be considered. Most processes are only seriously affected by a few casual factors. Focus on these causal factorsControl – Step 13: Implement Process Control Page 284
  • 284. Tool 2: Documentation - Pitfalls Pitfalls In Writing ProceduresPitfalls in writing procedures ¦ Forgetting that the procedures are to be used by people performing Not involving the affected persons in the creation of the activities - Work instruction must be legible procedures - They should be written to be as brief as possible, while covering Not testing the Procedures all items sufficiently - They must be consistent with the educational level of the users Omitting information - Ensure they are in the language of the users – e.g., are your ? Results to be obtained workers literate in English? ¦ Not including the persons performing the activities in the creation of ? How to do a step procedures Lowering the importance of procedures - This pitfall can result in theoretical procedures not reflecting the real world ? Not readily available - When affected persons are not involved, procedures often omit critical steps ? Ignored by management ¦ Not testing the procedure prior to full-scale implementation can create No method to update procedures bad feelings and often poor results ? Obsolete procedures not destroyed ¦ Not stating the result to be obtained Procedure documentation not readily available ¦ Not telling people how to do a step - Telling someone to “check for errors” without a checklist and types of errors causes uneven output ¦ Telling workers to ignore procedures or certain parts of them ¦ Not having a method to update procedures ¦ Not making the procedures readily available to people ¦ Procedures in a book in the main office are uselessControl – Step 13: Implement Process Control Page 285
  • 285. Review Of Variation (1) Variation is a fact of life. There will always be fluctuations in our process.Review Of Variation Input, process and output measures vary and variation is a consta nt energy in all processes. All repetitive activities of a process have a certain amount of Graphically displaying measures provides a basic description of the variation fluctuation and its sources. Input, process and output measures will fluctuate This flluctuation is called Variation Variation is the voice of the processMeasurement Frequency Time Measurement Run Chart HistogramControl – Step 13: Implement Process Control Page 286
  • 286. Review Of Variation (2) Data collection is crucial to our understanding of5Ms & 1P variation. Further, in any process, variation must be seen as the enemy. Sources of variation follow: Xs ¦ Machines The various appliances used in the transformation from inputs into Machines Methods Materials outputs. For example, a PC can turn various sources of information into an organized manual that then relates to a training service ¦ Methods The procedures, formal or otherwise, that transform inputs into outputs. Why Why WhyW For example, there is a standard procedure for billing collections in Prrocess P ocess Variation ? Variation ? hy most businesses “Y” Vari Variation “Y” ¦ Materials ? The components, tangible or otherwise, that are transformed from inputs into outputs. For example, paper, ink, etc., are transformed into Measurements Mother Nature People marketing materials ¦ Measurements The tools that monitor a process’s performance. For example, a Xs doctor’s blood pressure reading of a patient would determine subsequent activity related to treatment ¦ Mother Nature The environmental elements within a process that influence a customer CTQ. For example, in a training session, failure to regulate the thermostat can result in a non-conducive learning environment ¦ People The staffing that influences how well we meet customer needs and requirements. While often dominant in a service industry, this is an area still too often blamed for failure to meet or exceed customer requirementsControl – Step 13: Implement Process Control Page 287
  • 287. Review Of Variation (3 ) Sometimes in a service environment, the5Ms & 1P following categories are used: ¦ Policies Higher level decision rules or management practices ¦ Procedures Xs The way in which tasks are performed Machines Methods Materials ¦ Plant The building, equipment, work space, and environmental factors that affect performance Why Why ¦ People W The human element Process Process Variation ? Variation ? hy ¦ Parts “Y” Vari Variation “Y” Systems, documents, and other supplies that are needed to perform ? the service Measurements Mother Nature People XsControl – Step 13: Implement Process Control Page 288
  • 288. Review Of Variation (4) Common CausesTwo Types Of Variation Common causes are those causes that are built into the process by the interaction of the 5Ms and 1P. Common causes affect everyone working in the process, and affect all of the outcomes. Common causes are always present and thus are predictable Type Of Definition Characteristics Variation Special Causes Common Cause No Undue Expected circumstances related to one of the 5Ms or 1P. Special causes are not Influence By always present, do not affect everyone working in the process, do not affect Predictable Predictable all of the outcomes, and are not predictable. The distinction between Any Of The common and special causes is important to determine the basic strategy for 5Ms and 1P Normal process improvement and control. Unexpected Unexpected Special Cause Undue Influence By Unpredictable Any Of The Not Normal 5Ms and 1PControl – Step 13: Implement Process Control Page 289
  • 289. Review Of Variation (5)Special Cause Patterns: Run Charts Pattern Plot Conclude Action Example Shifts 8 or more points in a row Find out what was Customer o the same side of the on different about the complaints media indicate a shift in median process around the increase a key element of the time that the shift due to process. occurred. change in policy. Trends 7 or more points in a row Find out what was Market continuousl increasing continuously different about the growth or o continuously or process around the decline decreasing indicate a time that the trend trend. started. Same Value A sequence of 7 or Find out if Cycle time more points having measurement measured the same value. device is stuck, or if to nearest the metric has poor day. resolution.Control – Step 13: Implement Process Control Page 290
  • 290. Review Of Variation (6)Responding to Special and Common Cause Understanding the source of Variation is important to devising a sound strategy for process control and improvement. The source of Variation hasVariation different improvement strategies important consequences for the type of actions required. If a process exhibits special cause variation the appropriate action is to investigate those specific data points related to the special cause signals. In Measurement most cases the investigation will reveal important causal factors (Xs) related to the Special Cause(s). The results of the investigation should be integrated into an action plan for immediately addressing the special causes. Common If a process exhibits common cause variation the appropriate action is to Common Cause or Special Special Cause investigate all of the data points. Finding the “Vital Few” causal factors (Xs) Cause? that explain Common Cause Variation is more difficult than finding causal MEASURE MEASURE MEASURE MEASURE factors for Special Causes because they are not as obvious. The Analyze phase of DMAIC focuses on this more challenging investigation. Investigate all of the Investigate the specific variation by identifying data points related to the "vital few" process the special causes Xs and input Xs MEASURE MEASURE ANALYZE ANALYZE Develop solutions Develop solutions for for special causes the "vital few" process and implement as and input Xs appropriate IMPROVE IMPROVE MEASUREControl – Step 13: Implement Process Control Page 291
  • 291. Summary Of Variation To improve any process, it is useful to understand its Variation All Variation is caused by common and/or special causes There are two major classifications of causes which help you select appropriate managerial actions: ? If all Variation is due to “Common Causes,” the result will be a predictable or stable system ? If some Variation is from “Special Causes,” the result is an unstable or unpredictable system Variation causes customer dissatisfactionControl – Step 13: Implement Process Control Page 292
  • 292. Tool 3: Control Charts (1) Control charts are used to distinguish betweenVariation and Control Charts Common and Special Causes of Variation and use that understanding to control and improve processes. Control Charts are characterized by two things: 40 Upper control limit 1. The average, or centerline, which represents the middle point about which plotted measures are expected to vary randomly 2. Control limits, both upper and lower, which represent the performance 30 boundaries you can expect for the process. Although measures vary, Measurement one would not expect to see plotted measures outside of these boundaries if the process operated predictably Average 20 10 Lower control limit 0 0 10 20 Time Order of SampleControl – Step 13: Implement Process Control Page 293
  • 293. Tool 3: Control Charts (2) Dividing the Control Chart into zones can aid in detecting Special CauseDetermining If Your Process Is "Out Of Control" Variation. Each of the zones represent standard deviations from the mean. Zone C, for example, is + and - one standard deviation from the average. Minitab can check for violations to these guidelines: Upper Control Limit ¦ One or more points fall outside of the control limits Zone A A (UCL) ¦ Two data points out of three consecutive data points are on the same side of the average in Zone A or beyond. Zone B B ¦ Four da ta points out of five consecutive data points are on the same side of the average in Zone B or beyond. Zone C C ¦ Nine consecutive points are on one side of the average Average ¦ There are six consecutive points, increasing or decreasing Zone C C Zone B ¦ Fifteen consecutive data points are within Zone C (above and below the average). Zone A Lower Control Limit ¦ There are eight points in a row beyond Zone C (above or below the average). (LCL) Source: Memory Jogger Plus, ©1994 GOAL/QPCControl – Step 13: Implement Process Control Page 294
  • 294. Tool 3: Control Charts (3)Control Limits vs. Specification LimitsControl Limits¦ Defined based on process performance (+/- 3 estimated standard deviations from the mean)¦ Help determine if your process is “in control” (without Special Cause Variation)¦ Plotted on Control Charts¦ Change when there is a verified, significant change to your process¦ Represent the voice of the processCustomer Specification Limits¦ Defined based on feedback from the customer(s)¦ Help determine if your process is producing defects¦ Plotted on Histograms (not Control Charts)¦ Change when your customers say they do!¦ Represent the Voice Of The CustomerControl – Step 13: Implement Process Control Page 295
  • 295. Tool 3: Control Charts (4)Control Limits vs. Specification Limit (2) Limits It is possible to have a stable (in control process that has control) unacceptable variation Assume both process A and B are statisticall perform ing “in statistically control” PROCESS A PROCESS B Lower Upper Lower Upper Spec. Limit Spec. Limit Spec. Limit Spec. Limit Process A has acceptable Process B has unacceptable variation when evaluated against variation when evaluated against customer specification limits customer specification limits When a process is in statistical contro and has unacceptable control Variation, work on the reduction of variatio due to Common variation Causes To reduce Common Cause Variation, make improvements to the Vital Few 5Ms and 1PControl – Step 13: Implement Process Control Page 296
  • 296. Tool 3: Control Charts (5) The measures that you choose to monitor in the control plan are the criticalSelecting Measures For Control Charts measures for your process. These are the process management measures that the process owner will rely on to track process performance ove r time. Process Input- Output Variables (Ys) (Xs) Key input and Key output process measures measures (X) (Y) from the that track customer´s variables perspective identified in Process-Variables your project as (Xs) key drivers of Project Y variables It is important to measure the process and not the peopleControl – Step 13: Implement Process Control Page 297
  • 297. Tool 3: Control Charts (6)Selecting Measures for Control Charts (2) Following the 4 -step data collection plan will ensure that the data collected on an ongoing basis will accurately reflect the variation in the process. Since this data will be collected over a long period of time, measurement process reviews to ensure consistency should be a major concern for both theHow Do I Monitor The Control Plan? project team as well as the process owner after the hand-off. Make sure that periodic audits of the data collection are an integral part of the overall control plan. Develop Ensure Data Collect Data & Establish Data Operational Consistency & Monitor Collection Goals Definitions & Stability Consistency ProceduresUse the 4-step data collection plan in order to develop aprocess that will protect the integrity of the dataControl – Step 13: Implement Process Control Page 298
  • 298. Tool 3: Control Charts (7)When to use a Control Chart In the early stages of process improvement a control chart will typically show special cause. Use the strategy illustrated in the flow chart to guide your decision about when to begin using control charts. * Are there ** Select Are there special No appropriate No Transfer to Plot data on special a run chart cause control chart cause process signals ? and calculate signals ? owner control limits Yes Yes Eliminate Continue using run special *** chart and work to causes remove special cause variation Recalculate limits * Look for obvious trends , shifts, cycles , etc. Go through this loop one time only. ** Collect a minimum of 20 data points on the run chart before calculating control limits *** If possible, identify and eliminate special causes for points out of limits. After three times through this loop, use limits and watch control chart to see if it settles down, i.e., no more special causes . After about 20 samples , recalculate limits.Control – Step 13: Implement Process Control Page 299
  • 299. Summary Of Variation And Control Charts Control Limits are calculated from the process data; specification limits come from the customer; they are both important Process Variation can be stable and still be unacceptable; to reduce Common Cause Variation, make fundamental improvements to the Vital Few 5M´s and 1P Variation is the “voice of the process” – learn to listen and understand it Use Control ChartsControl – Step 13: Implement Process Control Page 300
  • 300. How To Select Control Charts? There are many different types of control charts. The chart is a helpful guide to decide which type of chart to use when. The primary determinant of which Continuous or type of control chart to use is the type of data being analyzed. s Discrete Data ? The two types of charts used with continuous data are the X-bar and R chart (used with rational subgroup data), and the Individuals chart (used when Continuous Discrete rational subgroups cannot be formed). If the data being analyzed is discrete e we need to determine what type of discrete data we have: classification or typ count. Rational Constant Lot With classification data (e.g., good/bad, on/off, on- time/not on-time, etc.) , Subgroups Size? where the sample size is not constant, a p -chart (percent defective) is used. If the sample size is constant an np-chart is used. Note: the p -chart can be used with a constant or variable sample size. No Yes No Yes If the data is a discrete count (e.g., number of defects) and the opportunity for defects is constant, then a c -chart is used. When the opportunity for defects varies, a u -chart is used. us Sample size Defects or Defects or < 10? Defective? ? Defective? X - mR X-R X-S u p c npControl – Step 13: Implement Process Control Page 301
  • 301. Selecting Control Charts - Summary Determine if the data to be plotted is discrete or continuous For continuous data, if the sample size is: ? One, then use X and moving range charts ? 2-9, then use X-bar and range charts ? Greater than 9, then use X-bar and S-charts For discrete data, determine if measuring defectives or defects, and for: ? Defectives, equal sample size: use np-charts ? Defectives, unequal sample size: use p-charts ? Defects, equal sample size: use c -charts ? Defects, unequal sample size: use u-chartsControl – Step 13: Implement Process Control Page 302
  • 302. Control Limit Calculations The formulas for calculating control limits are shown on the following pages There are different tables for continuous and discrete data Both continuous and discrete data Control Charts have Control Limits that are placed +/- 3 estimated sigma from the average lineControl Limit Calculations - FormulasContinuous Data Control Limits are calculated using control chart factors and the Range-Bar (an estimate of short-term sigma) Control Chart factors were invented by Shewart in the 1920’s to avoid long-hand calculation Control Chart factors are shown in the table according to the sample size for each subgroup Individual Control Charts are considered to have a sample of size 2, the number of data points make up the moving rangeDiscrete Data Control Limits are calculated using a formula that estimates sigma without the necessity to transform the data The normal estimate for sigma (under radical) is then multiplied by threeControl – Step 13: Implement Process Control Page 303
  • 303. ControlLimit Calculations- Continuous DataTable Type Control 5amplo Central UM" Controllimits Chart Size n Avemge and Range (Xt •Xl + ..X.) UCL.,=+A X= < 10, but • LCL, =- A R usually 3 to 5 (R t + R2 +...R,J UCL,= D x andR R= • LCL,= D Average Mel (X, •X:,•...X:.> UCL., =+ A 1! X= Sta1ldatd D<Wfallon usually • LCL,= X - A,S > 10 <s + +... sw = UCL..s = 84 X ands K LCL,= 8,> lv1 0ia•l 0 and Ranga X= c·Xx,•... XJ UCL = J1 + A !: , < 10, but • LCL= X-A J!l usually 3 to 5 (R1 + Rz •...RW UCL,= D R X and R J!l = • LCL,.= DR (Xl + Xz + ...XJ UCt.=X • e R, lndvkluals and i 1< = LCL, = i< - E! Moving Range • l. 1 R. = I(X. 1 - X)I UCL,= Ol m ! X and R,. (R l + R+•..RM) LCL,= D J!m l R..= K· l k = # of subgtoups, X = mooian valueWithin eaCh subgroup -x= -¥-Control- Step 13: Implement Process Control Page 304
  • 304. Control Limit Calculations- Table OfConstants &Imp• lland RChan lland s Chart s1 ... n A, o, o, A, a, B, c• • 2 1.880 0 3.267 2.659 0 3.267 .7979 3 1.023 0 2.574 1.954 0 2.568 .8862 4 0.729 0 2.282 1.628 0 2.266 .9213 5 0.577 0 2.114 1.427 0 2.059 .9400 6 0.483 0 2.004 1.287 0.030 1.970 .9515 7 0.419 0.076 1.924 1.182 0.118 1.882 .9594 8 0.373 0.136 1.864 1.099 0.185 1.815 .9650 9 0.337 0.184 1.816 1.032 0.239 1.761 .9693 10 0.308 0.223 1.777 0.975 0.284 1.716 .9727 &lmplo lt and R Chait X and R... Chart Size n ii., o, o, e, 0, o, d, 2 - 0 3.267 2.659 0 3.267 1.126 3 1.187 0 2.574 1.772 0 2.574 1.693 4 - 0 2.262 1.457 0 2.282 2.059 5 0.691 0 2.114 1.290 0 2.114 2.326 6 - 0 2.004 1.184 0 2.004 2.534 7 0.509 0.076 1.924 1.109 O.o76 1.924 2.704 8 - 0.136 1.864 1.054 0.136 1.864 2.847 9 0.412 0.184 1.816 1.010 0.184 1.816 2.970 10 - 0.223 1.777 0.975 0.223 1.777 3.078 --usohl lln estimating tho procoss staodald deviation . aControl- Step 13: Implement Process Control Page 305
  • 305. ControlLimit Calculations- Discrete DataTable Type Control Sam.... Control Limits Central Une Chart SIZ<I f faction ooroctlve For each subgroup: •lJCt..= 3 Jp( p l; Vaflable, p= npln ) usua SO lly FOC an subgroups: p-Chart II= nPI!n ·LCt..="P · J o( / l 3 NumbO-r Constant, usually For each subgroup: UCL,.= np + 3 J np(l • ill Defoctlve np = # def clivoo LCL,.=nji- 3 J >50 For allsubgroups: nChart njl = np!k np(l• pJ Number of For each subgroup: Defects c = #defects UCL,=+ 3 Jc c-Chart Nomoorof Constant For ausubgroups: = elk For each subgroup: LCt._ =c- 3 rc ·ucL.= u•3 J+ O.lects Per u = c/n Uni t Variable Forallsubgtoups: n = l:cl!:n ./+ •LCL,. =ii- 3 u-Chart np = #defectives This formula cteates changingcontrol c tJ of defects lmits. To a void this, use averageS3fllIO n = sample size within slzos0 for those S30l!IOS that ate IMthin each subgroup ±20% of the average salt1)1e size. k #of subgroups Ca cutato fndlvidualllmits tot tho samplos elCooedlng t 2()(1. If the Lower C01 Urrit (LCL)is a 1tro1 negative nuritler.sot thO LCL to zero.Control- Step 13: Implement Process Control Page 306
  • 306. Control Charts – Summary (1) All Control Charts have the same form ? Time plot of data ? Statistical limits placed +/- 3s from center line Choose the Control Chart according to: ? Data type ? Sample size Interpret and act on the control chart ? Investigate Special Causes of Variation ? Assess baseline sigma in order to understand if we are performing to customer CTQs ? Shrink Common Cause Variation by making fundamental changes in the Vital Few 5M´s and 1P Maintain the control chart ? Make notes on the Control Chart to indicate problems, changes, or important events ? Recalculate the Control Limits when necessaryControl – Step 13: Implement Process Control Page 307
  • 307. Control Charts – Summary (2) ¦ Do not recalculate Control Limits unless the process has changed.When should Control Limits be recalculated? ¦ Recalculate only when Special Cause Variation has been detected and removed or when a permanent, desired change has occurred in the When Special Cause Variation is identified and controlled and process. the process is operating at a new level or with reduced ¦ Only data after the change should be used to calculate the new Control variation Limits. When errors were made in the original calculation When the methods of data collection or Operational Definitions have changed When a fundamental change has been made to the process and the change has had a detectable impact on the performance of the processAs long as the process does not change, the control limits should not berecalculated.Control – Step 13: Implement Process Control Page 308
  • 308. Control Charts – ErrorsCommon errors in using Control Charts Management/Process Owners do not understand/trust the concept Charts aren’t kept up-to-date Special Cause Variation goes unnoticed Non-random patterns are not studied for special causes Poor or erroneous measurements are used Data on charts is not current Specifications are plotted on chartsControl – Step 13: Implement Process Control Page 309
  • 309. Control Charts – Tips Immediately search for a cause when the Control Chart indicates a special cause has occurred Seek ways to prevent that special cause from recurring, or – if results are good – retain that lesson Make fundamental changes to vital few 5M´s and 1P to reduce Variation due to Common Causes Use Control Charts on an ongoing basis; make Control Charts a running record of the processControl – Step 13: Implement Process Control Page 310
  • 310. Tool 4: Response Plan (1) A Response Plan is a documented method for how a process owner/team should respond to any out-of-control conditions that may occur in a process A good Response Plan will help ensure a timely and appropriate response to processing problems as they occur, thereby decreasing the risk of defects getting to the customerControl – Step 13: Implement Process Control Page 311
  • 311. Tool 4: Response Plan (2)Provide a response plan for each monitored X andY, with: Specific action to be taken Timing of action Owner of action Response Plan Measure Action Timing Owner X1 X2 X2Control – Step 13: Implement Process Control Page 312
  • 312. Tool 4: Response Plan (3)Revisit Risk Assessment Potential Problem Analysis Errorproofing FMEAMeasurement Process Reviews Periodic audits of the data collection procedures for the control plan are a necessary part of an effective Process Control Monitoring Plan You must be certain that the data reflects the actual variation of the process rather than process Variation plus measurement VariationControl – Step 13: Implement Process Control Page 313
  • 313. Project Closure – OverviewKey areas of focus Project results must be documented and a communication plan must be created in order to: Validate benefits to customer and business ¦ Communicate the team’s success/knowledge business-wide. Re-calculate process sigma and document results ¦ Project documentation provides a record of the key aspects of your Six Sigma project, of the rationale behind process changes and the Project documentation/translate learnings across company resulting benefits. The documentation is a permanent record of your team’s work and will serve as a resource and guide for others who can benefit from your project. This documentation will serve as the foundation in your efforts to translate learnings across the company. ¦ The team should include information on the net benefit resulting from project completion. The net benefit will include both tangible and intangible benefits, as developed in your Cost Benefit Calculation, and reconfirmed in your pilot results Remember: the intangible benefits are not measurable for accounting purposes.Control – Step 15: Project Closure Page 314
  • 314. Your team has gained a significant amount of knowledge as it has followedDocumentation Package the path of DMAIC. This knowledge includes both content (discovering new information about your Process, what the Root Cause is, etc.) as well as The knowledge gained by your team needs to be saved and process (Hypoth esis Testing, calculating sigma, writing CTQs, etc.) Other shared individuals, as well as project teams, can benefit from having access to both types of knowledge. This knowledge can help shorten the subsequent Documentation that has occurred throughout DMAIC learning curves of other teams, as well as to share best practices. becomes finalized Although you should be documenting your project as the team progresses The documentation will include vital information about your through DMAIC, the documentation package is finalized at the end of the project from which others can benefit project. Your team will develop a packet of information/ documentation that willOnce the documentation is complete, critically examine the package from a include vital information about your project. The exact nature of thisRisk Analysis perspective documentation varies from business to business, but usually includes the following topic areas: ¦ An abstract of project ¦ The problem statement ¦ Baseline data on process performance ¦ A list of vital Xs ¦ The solution ¦ Control mechanisms ¦ Performance metrics ¦ Lessons learned/best practices ¦ Translation opportunities The documentation usually comes in the form of: ¦ Project binders ¦ Templates ¦ Storyboards ¦ Electronic databasesControl – Step 15: Project Closure Page 315
  • 315. Translation Opportunities (1) Translation opportunities are key learnings from your project that may be Translation opportunities are key learnings from your project applicable to other projects. that could translate to other similar or analogous projects Sharing the key learnings from your team’s project gives others the chance Spreading project knowledge throughout the business will to learn from your hard work, knowledge, and innovation. give others the chance to benefit from your team’s experience These key learnings will also help to: At the end of DMAIC, special effort is made to identify ¦ Avoid wasting resources solving the same problem translation opportunities ¦ Speed up p rocess improvement Work to identify other individuals, processes, departments, ¦ Achieve more gains in customer satisfaction and businesses that could benefit from your knowledge ¦ Enable us to reach Six SigmaControl – Step 15: Project Closure Page 316
  • 316. Translation Opportunities (2) Identify similar processes by classifying your process and searching yourThree opportunities for translation: business for areas that may benefit from your project. You can think about similar processes in three ways : Direct Translation – same process/similar product or service 1. Direct translation – the same process and a similar product/service Customization – same process/different product or service 2. Customization – the same process, but a different product or service that may require some additional attention Adaptation – similar process, some applicability 3. Adaptation –a similar process,but only with some elements of the solution that may applyControl – Step 15: Project Closure Page 317
  • 317. What is the new Process Sigma? Does it meet the target forthe project?What is the Control Plan? What is being measured? How areControl Charts being used? How well and consistently is theprocess performing? Is a Response Plan in place for whenthe process measures indicate “out of control”?Has the process been standardized? Show theDocumentation that will support this improvement. How hasjob training been affected?Who is the process owner? How will responsibility forcontinued monitoring and improvement be transferred fromthe team to the owner?What systems and structures (rewards, measures, staffing,training, information, etc.) still need to change in order toinstitutionalize our improvements?What are some other areas of the business that can benefitfrom your learnings? How can we most effectively share ourlearnings with them?What is the next problem that should be addressed in thisprocess?What did you, as a team, learn about the process of makingimprovements? Page 318

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