The purpose of the Measure phase is to understand and document the current state of the processes to be improved, collect the detailed voice of the Customer informa- tion, baseline the current state, and validate the measurement system. The activities performed and tools applied during the Measure phase are discussed below.
1. Define the current process 2. Define the detailed VOC
3. Define the Voice of the Process (VOP) and current performance 4. Validate the measurement system
5. Define the COPQ.
Figure 2.14 shows the main activities mapped to the tools or deliverables most typically used during that step.
Define Phase
Define the Current Process
The first step of the Measure phase is to profile the current state. SIPOC and process mapping are excellent tools to document the current process steps, the information that is used, the people who perform the work, and the internal and external custom- ers of the services. In a process improvement effort there are typically three levels of process maps that are used to help by documenting the current or AS-IS process.
Figure 2.15 shows the three levels and where they should be applied.
An example of a level 2 process map for making a Peanut Butter and Jelly Sandwich is shown in Fig. 2.16.
Fig. 2.15 Process map level and purpose
Fig. 2.14 Measure phase activities and tools/deliverables
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It is also important to identify any process measures and related metrics that are used to measure quality and productivity of the processes. The current profile of the people and cultural state should be understood, including the level of skills and training of the employees, and their resistance or acceptance levels to change.
The steps to complete a process map are:
1. Identify level (one, two, or three) to map and document 2. Define the process boundaries
3. Identify the major activities within the process
4. Identify the process steps and uncover complexities using Brainstorming and Storyboarding techniques
5. Arrange the steps in time sequence and differentiate operations by symbol 6. Validate the Process Map by a “walk through” of the actual process and by hav-
ing other process experts review it for consistency.
Define Detailed Voice of Customer (VOC)
In the Measure phase, the voice of the customer information should be collected to define the customers’ expectations and requirements with respect to the service delivery process. VOC is an expression for listening to the external customer and
Fig. 2.16 Process map for making a Peanut Butter & Jelly Sandwich Measure Phase
understanding their requirements for your product or service. Examples of require- ments are their expectations for responsiveness, such as turnaround time on vendor (customer) invoices, or error-rates, such as employee (customer) expectations of no errors on their paycheck. The voice of the customer can be captured through interviewing, surveys, focus groups with the customers, complaint cards, warranty information, competitive shopping. Quality Function Deployment (QFD) can be used to organize the voice of the customer information.
Personal interviews are an effective way to gain the voice of the customer, however, it can be expensive and training of interviewers is important to avoid interviewer bias. However, additional questioning can occur to eliminate misun- derstanding. The objectives of the interview should be clearly defined before the interviews are held.
Customer Surveys
Customer surveys are a typical way to collect VOC data. The response rate on surveys tends to be low, 20 % is a “good” response rate. It can also be extremely difficult to develop a survey that avoids and asks the questions that are desired.
Customer survey collection can be quite expensive. The steps to create a customer survey are (Malone 2005):
1. Conceptualization. Identify the survey objective and develop the concept of the survey, and what questions you are trying to answer from the survey.
2. Construction. Develop the survey questions. A focus group can be used to develop and/or test the questions to see if they are easily understood.
3. Pilot (try out). Pilot the questions by having a focus group of representative people from your population. You would have them to review the questions, identify any unclear or confusing questions, and tell you what they think about the questions asked. You would not use the data collected during the pilot in the actual results of the surveys.
4. Item analysis. Item analysis provides a statistical analysis to determine which questions answer the same objectives, as a way to reduce the number of questions.
It is important to minimize the number of questions and the total time required to take the survey. Typically, the survey time should be 10 minutes or less.
5. Revision. Revise the survey questions, and roll out the customer survey, or pilot again if necessary.
Focus Groups
Focus groups are an effective way to collect VOC data. A small representative group, typically 7 to 10 people are brought together and asked to respond to pre- determined questions. The focus group objective should be developed and the questions should support the objective. The participants should be selected by a
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common set of characteristics. The goal of a focus group is to gather a common set of themes related to the focus group objective. There is no set sample size for focus groups. Multiple focus groups are typically run until no additional themes are derived. Advantages of focus groups are:
• They tend to have good face validity, meaning that the responses are in the words of the focus group participants;
• Typically, more comments are derived in an interview with one person at a time;
• The facilitator can probe for additional information and clarification;
• Information is obtained relatively, inexpensively.
Some of the disadvantages of focus groups are:
• The facilitator skills dictate the quality of the responses;
• They can be difficult to schedule;
• It can be difficult to analyze the dialog due to participant interactions.
Affinity diagrams organize interview, survey, and focus group data after collec- tion. The affinity diagram organizes the data into themes or categories. The themes can first be generated, and then the data can be organized into the themes, or the detailed data can be grouped into the themes. An example of a simple affinity dia- gram for ways to study for a Six Sigma Black Belt exam is shown in Fig. 2.17.
Data Collection Plan
A data collection plan should be developed to identify the data to be collected that are related to the CTS criteria.
The data collection plan ensures:
• Measurement of CTS metrics.
• Identification of the right mechanisms to perform the data collection.
• Collection and analysis of data.
• Definition of how and who is responsible to collect the data.
Figure 2.18 shows a data collection plan.
Fig. 2.17 Affinity diagram for Six Sigma Black Belt exam preparation Measure Phase
The steps for creating a data collection plan in the Measure phase are:
1. Define the CTS 2. Develop Metrics
3. Identify data collection mechanism (s) 4. Identify analysis mechanism (s) 5. Develop sampling plans 6. Develop sampling instructions.
A description of each step in the data collection plan development follows:
1. Define the CTS criteria (George et al. 2005):
CTS is a characteristic of a product or service which fulfills a critical cus- tomer requirement or a customer process requirement. CTS’s are the basic elements to be used in driving process measurement, improvement, and control.
2. Develop metrics: In this step, metrics are identified that help to measure and assess improvement related to the identified CTS’. Some rules of thumb for selecting metrics are to (Evans and Lindsey 2002):
• Consider the vital few versus the trivial many.
• Metrics should focus on the past, the present, and the future.
• Metrics should be linked to meet the needs of shareholders, customers, and employees.
It is vital to develop an operational definition for each metric, so it is clearly understood how the data will be collected by anyone that collects it. The opera- tional definition should include a clear description of a measurement, including the process of collection. Include the purpose and metric measurement. It should iden- tify what to measure, how to measure it, and how the consistency of the measure will be ensured. A summary of an operational definition follows.
Fig. 2.18 Data collection plan for software application development Six Sigma project
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Operational Definition
Defining the Measure, Definition.
A clear, concise description of a measurement and the process by which it is to be collected.
Purpose. Provides the meaning of the operational definition, to provide a com- mon understanding of how it will be measured.
Clear way to measure the process.
• Identifies what to measure
• Identifies how to measure
• Makes sure the measuring is consistent.
3. Identify data collection mechanism(s): Next you can identify how you will col- lect the data for the metrics. Some data collection mechanisms include: cus- tomer surveys, observation, work sampling, time studies, customer complaint data, emails, websites, and focus groups.
4. Identify analysis mechanism(s): Before collecting data, consider how you will analyze the data to ensure that you collect the data in a manner that enables the analysis. Analysis mechanisms can include the type of statistical tests or graph- ical analysis that will be performed. The analysis mechanisms can dictate the factors and levels for which you may collect the data.
5. Develop sampling plans: In this step you should determine how you will sample the data, and the sample size for your samples. Several types of sampling are:
• Simple Random Sample: Each unit has an equal chance of being sampled.
• Stratified sample: The N (population size) items are divided into subpopula- tions or strata, and then a simple random sample is taken from each strata.
This is used to decrease the sample size and cost of sampling.
• Systematic sample: N (population size) items are placed into k groups. The first item is chosen at random, the rest of the sample selecting every kth item.
• Cluster Sample: N items are divided into clusters. This is used for wide geo- graphic regions.
6. Develop sampling instructions: Clearly identify who will be sampled, where you will sample, and when and how you will take your sample data.
Quality Function Deployment
Quality Function Deployment and the House of Quality is an excellent tool to help to translate the customer requirements from the Voice of the Customer into the technical requirements of your product, process, or service. It can also be used to relate the customer requirements to potential improvement recommendations developed during the Improve phase. Figure 2.19 shows the format for the House of Quality.
Measure Phase
The steps for creating a House of Quality are (Evans and Lindsey 2002):
1. Define the customer requirements or CTS’ characteristics from the Voice of the Customer data. The customer can provide an importance rating for each CTS.
2. Develop the technical requirements with the organization’s design team.
3. Perform a competitive analysis, having the customer’s rank your product, pro- cess, or service against each CTS to each of your competitors.
4. Develop the relationship correlation matrix by identifying the strength of relationship between each CTS and each technical requirement. Typically a numerical scale of 9 (high strength of relationship), 3 (medium strength of rela- tionship), 1 (low strength of relationship), and blank (no relationship).
5. Develop the tradeoffs or relationship between the technical requirements in the roof of the House of Quality. You can identify a positive (+) relationship between the technical requirements, as one requirement increases the other also increases; no relationship (blank) or a negative (−) relationship, there is an inverse relationship between the two technical requirements. An example of a positive relationship can be illustrated in the design of a fishing pole. The line gauge and tensile strength both increase as the other increases. A negative relationship can be illustrated by line buoyancy and tensile strength. As tensile strength of the line increases, the buoyancy will be less.
6. The priorities of the technical requirements can be summarized by multiply- ing the importance weightings of the customer requirements by the strength of the relationships in the correlation matrix. This helps to identify which of the technical requirements should be incorporated into the design of the product, process, or service first.
Fig. 2.19 Quality function deployment house of quality
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Define the Voice of the Process (VOP) and Current Performance
There are many tools that can be used to assess the VOP and current performance.
We will discuss the VOP matrix, Pareto charts, benchmarking, check sheets, and histograms.
VOP Matrix
A VOP matrix, developed by the author, can be used to achieve integration and synergy between the DMAIC phases and the critical components of the process to enhance problem solving. The VOP matrix includes the CTS, the related process factors that impact the CTS, the operational definition that describes how the CTS will be meas- ured, the metric, and the target for the metric. An example of a VOP matrix for the inventory asset management process for a college in a university is shown in Fig. 2.20.
Pareto Chart
A Pareto chart helps to identify critical areas causing the majority of the problems.
It provides a summary of the vital few rather than the trivial many. It demonstrates the Pareto principle that 80 % of the problems are created by 20 % of the causes,
Fig. 2.20 VOP matrix for inventory asset management process Measure Phase
so that these root causes can be investigated in the Analyze phase. It helps us to arrange the problems in order of importance and focus on eliminating the prob- lems in the order of highest frequency of occurrence.
Following are the steps for creating a Pareto Chart.
Step 1 Define the data categories, defect, or problem types.
Step 2 Determine how the relative importance is defined (dollars, number of occurrences).
Step 3 Collect the data, compute the cumulative frequency of the data categories.
Step 4 Plot a bar graph, showing the relative importance of each problem area in descending order. Identify the vital few to focus on.
An example of a Pareto chart (Fig. 2.21) that identifies the resolution catego- ries for problems reported to an Information Systems Help Desk for a financial application.
Benchmarking
Benchmarking is a tool that provides a review of best practices to be potentially applied to improve your processes. In a Six Sigma project, process benchmarking is typically performed. The organization should document the process that they will benchmark, then select who they will benchmark. It is not necessary to benchmark a company in the same industry, but to focus on the process to be benchmarked, and select an organization that is known for having world class or best practice
Fig. 2.21 Pareto chart of resolution categories to an information systems to help desk
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processes. The next step is to work with the organization to collect the data and understand how the data can be used to identify ways to improve your processes and identify potential improvement opportunities to be implemented in the Improve phase. This is similar to Motorola’s benchmarking process (Evans and Lindsey 2002). It is important to be careful when process benchmarking to ensure that you are comparing apples to apples, meaning that the organization’s characteristics are similar to your own, so that the benchmarked process applies to your process.
Check Sheet
A check sheet is a graphical tool that can be used to collect data on the process and types of defects so that root causes can be analyzed in the Analyze phase. The steps to create a check sheet are:
Step 1 Choose a characteristic to track, i.e., defect types Step 2 Set up the data collection check sheet
Step 3 Collect data using the check sheet.
An example of a check sheet for potential errors when loading data for an on- line research system is shown in Fig. 2.22.
A Pareto Chart can then be created from the data collected on a check sheet.
Histogram
A histogram is a graphical tool that provides a picture of the centering, shape, and variance of a data distribution. Minitab or Excel is commonly used to create a
Fig. 2.22 Check sheet for errors loading data Measure Phase
histogram. It is always important to graph the data in a histogram as the first step to understanding the data.
Statistics
Statistics can also be used to assess the VOP related to the metrics that are meas- ured. Once the data is collected, it can be tested to see if the data distribution fol- lows a Normal Distribution, using a test for normality. The null hypothesis is that the data is Normal. If the null hypothesis is not rejected, then the statistics that would describe the Normal distribution are the mean and the standard deviation.
The mean is the average of the sample data. The mean describes the central loca- tion of a Normal distribution. The sample standard deviation is the square root of the sum of the differences between each data value and the mean divided by the sample size less one. Standard deviation (Sigma) is a measure of variation of the data. 99.997 % of all data points within the normal distribution are within Six Sigma.
Validate the Measurement System
It is important to validate the measurement system to ensure that you are capturing the correct data and that the data reflects what is happening. It is also important to be able to assess a change in the process with our measuring system as well as the measurement system error. We must ensure that the measurement system is stable over time and collecting the data that allows us to make appropriate decisions.
Measurement Systems Analysis
A measurement systems analysis includes the following steps (Gitlow and Levine 2005):
1. Prepare a flow chart of the ideal measurement system 2. Prepare a flow chart of the current measurement system
3. Identify the gaps between the ideal and current measurement systems 4. Perform a Gage Repeatability & Reproducibility (R&R) study The measurement process variation is due to two main types of variation:
• Repeatability related to the gage
• Reproducibility related to the operator.
The Gage R&R study assesses both the repeatability and the reproducibility.
Minitab or other statistical software can be used to assess the measurement system error, and improve the measurement system if necessary.
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Define the Cost of Poor Quality (COPQ)
Cost of Poor Quality (COPQ)
The last step in the Measure phase can be to assess the COPQ related to your Six Sigma project. The COPQ identifies the cost related to poor quality or not doing things right the first time. The COPQ translates defects, errors, and wastes into the language of management which is cost or dollars. There are four categories of COPQ: (1) prevention; (2) appraisal; (3) internal failures; and (4) external failures.
Prevention costs are all the costs expended to prevent errors from being made or, the costs involved in helping the employee do the job right every time.
Appraisal costs are the results of evaluating already completed output and audit- ing the process to measure conformance to established criteria and procedures.
Internal failure cost is defined as the cost incurred by the company as a result of errors detected before the output is accepted by the company’s customer. External failure cost is incurred by the producer because the external customer is supplied with an unacceptable product or service.
Examples of prevention costs are:
• Methods improvements
• Training
• Planning for improvement
• Procedures
• Quality improvement projects
• Quality reporting
• Data gathering and analysis
• Preventive maintenance
• SPC training costs
• ISO 9000 training costs.
Examples of appraisal costs are:
• Inspections
• Process Audits (SPC, ISO)
• Testing activity and equipment depreciation allowances
• Product audits and reviews
• Receiving inspections and testing
• Reviews (meeting time)
• Data collection
• Outside endorsements and certifications.
Examples of internal failure costs are:
• Reaudit, Retest, and Rework
• Defects and their impacts
• Unscheduled lost time
• Unscheduled overtime
Measure Phase