An Introduction to Six Sigma

FIRST INTRODUCED at the Motorola Corporation in the mid-eighties, Six Sigma is a total quality initiative aimed at reducing defects in selected business processes to 3.4 per million or less, or a 99.999%-plus rate of acceptable performance. Through an established methodology involving statistical measures, Six Sigma has enjoyed tremendous success in the manufacturing sector of the domestic economy. An intensified focus in recent years on supply chain efficiency, service delivery and customer satisfaction has moreover sparked a Six Sigma movement within retail and service industries. However, managers of service companies have often found it difficult to implement Six Sigma among employees at the lower levels of their organizations, because of either (1) a misunderstanding of the purposes and practical applicability of Six Sigma, or (2) apprehension of or failure to understand the basic concepts behind Six Sigma (Patton, 2005).

"Introduction to Six Sigma" (ISS) will focus on explaining the core concepts of Six Sigma (6σ) and the practical, measurable business value of the program to service organizations-particularly those in the retail industry. Though suitable for employees at all levels and occupations, this course is especially designed for sales and service professionals with little or no working knowledge of 6σ. An examination of related literature reveals that implementing 6σ typically results in decreased costs coupled with increased customer satisfaction, and serves as a valuable skill developing, learning experience for the student. Consequently, students should be able to appreciate and apply 6σ quality methods to various processes in their respective work situations. Some students may be wary of 6σ because they are simply unfamiliar with statistics. The approach taken here will be to keep mathematical and statistical technicalities to a bare minimum, focusing instead on the basics of the methodology and the benefits attainable by using it on the job. Nonetheless, further explanation calls for just a bit of statistical language.

The "σ" in 6σ is the symbol used in statistics for standard deviation--a measure of variation from the average, or mean, of a given set of numerical data. In manufacturing and business settings, σ is used to measure process variation: A smaller σ value means a tighter, or more controlled process. Likewise, the more standard deviations that can be "packed" into a process' specifications, the lower the level of actual variation that emerges in that process. In controlled manufacturing processes, the acceptable level of variation is typically 3σ, which translates to about a 99.73% acceptable level of output. In a 6σ process, variation is reduced to the point that a "standard" deviation becomes astonishingly small--well over 99.99% of output falls within established quality parameters.

Job and Task Analyses

Job description

Because 6σ is a general quality improvement methodology rather than a job-specific set of skills or information, the job in question could be simply understood as the implementation of the 6σ method in sales/service contexts. To put it another way: 6σ is a tool used to improve the quality of output of most any service-related job, so that the specific tasks of applied 6σ fit most any job description. Any job in which work processes directly involve the consumer may be enhanced through the method to be taught here. A graduate course in "Structured Problem-Solving" offered at Virginia Tech, for example, adopts an interdisciplinary approach to 6σ, designed for statistics, engineering and business students (Anderson-Cook, et al, 2005). The ISS course described in this document will make plentiful use of real and hypothetical examples of service applications taken mainly from the retail trade industry.

Task Analysis

According to most researchers and practitioners, 6σ can be broken down into five broad but distinct phases, which will be treated in the ISS course as the main duties of the 6σ learner in any job context. These phases or duties are known as Define, Measure, Analyze, Improve, and Control (also known by the acronym DMAIC). Students should be instructed to keep the service business context (retail, health care, etc.) in mind while selecting the processes and problems to address with the DMAIC methodology. Also it should be noted that whereas descriptions of DMAIC vary in depth and detail among researchers, the ISS course has been designed as an introduction and therefore will take a more basic, "nuts and bolts" approach.

Define. In the Define phase, the 6σ practitioner performs the following tasks, referred to variously as elements of the "charter" or defining "tollgates."

State the business case.
Create problem and goal statements.
Identify project constraints and scope
Identify the players. In the define phase especially, 6σ practitioners must continually consider the five elements of suppliers, inputs, process, output, and customers (SIPOC) in order to maintain a proper quality focus throughout the project (Eckes, 2003).

Measure. The measure phase is one of the points of departure from traditional problem-solving techniques, which often rely on instincts more than facts. Measuring involves two major tollgates which follow logically on the heels of the define phase:

Collect data relevant to the process problem at hand. Although any given process by definition entails inputs, internal processes, and outputs, output data should be examined first. Output "baseline" data translates customer complaints and defined problems into quantifiable, measurable terms.
Target likely input data sources to locate potential causes of the problem. Again, the suspected process cause should be documented through the collection of data.

Analyze. At this point, the 6σ project team gets to work looking over the data and making decisions as to its importance or relevance to the quality problem. As noted by Pande and Holpp (2002), problem causes are best categorized as methods, machines, materials, measures, Mother Nature, and people. They are found by use of the Analyze Cycle, as follows in basic form:

Verify the quality (or the level of variation) of the process by calculating Sigma. Important sub-tasks in calculating Sigma are, in order, the following:
Define a process in quantifiable terms.
Determine the defects per opportunity (DPO) pertaining to the process.
Measure the number of defects against the total number of defect opportunities.
Calculate yield.
Look up Sigma level in a standard Process Sigma table.
Evaluate significance of the problem based on existing quality standards.
Form an initial hypothesis explaining the cause of the problem.
Reexamine the situation and revise or confirm the hypothesis.

Improve. In keeping with the larger philosophy of total quality, anyone properly using 6σ will continually search further for problems to solve. This amounts to restarting the 6σ methodology from Step One.

Control. A couple of practical methods for controlling the improved process are:

Devise a monitoring process. This could include a maintenance schedule, periodic refresher training courses, and the same statistical analysis used previously.
Consider rewriting old operating standards and procedures as necessary, then retraining employees accordingly.

Philosophy of the Course

This course will adopt the Home Depot's stated core philosophical objective, "Improving Everything We Touch," as a starting point for using 6σ in retail and service contexts. A decades-long leader in the home improvement industry, Home Depot now boasts leadership in the successful use of 6σ among home improvement retailers. As noted previously, TQM involves continuous improvement of processes--and 6σ is one of the more successful, more empirically reliable TQM tools available (Goetsch & Davis, 2006). Ideally, the ISS course will strike an effective balance between a general appreciation for quality improvement and an understanding of technical and statistical methods used to achieve it. The philosophy of this course could then be encapsulated in the words, "Improving Service Quality with Proven Six Sigma Methods."

Target Population Analysis

The target population for a typical ISS course would be described as follows:

Population size and location. Fifteen to thirty students would make up the class, consisting of sales and service workers.
Current skill/knowledge levels. Though none have any appreciable experience with 6σ, students are employees in a service firm with at least six months of work experience.
General attitudes toward the subject. Sentiments could be expected to vary widely. A common misperception is that 6σ has no place in a service environment.
Education levels. All students have either a high school diploma or a GED equivalent. Most have an associate's degree or at least some college or technical school training. A handful have bachelor's degrees, and almost none have advanced degrees.
Age and gender. Student ages range from late teens/early twenties to past retirement age, with numbers of males and females roughly equal.
Familiarity with instructional delivery. The majority would be most familiar with traditional classroom methods, but all would have taken at least a few e-learning courses.
Motivational factors. Students in service industries are accustomed to a fast-paced, demanding work environment, and tend to lose interest quickly if the course material is not personally challenging or relevant to their department's performance.
Social-cultural factors. With many years of accumulated experience interacting with the public, students would be highly adept at verbal communication skills such as listening and establishing rapport. They will generally learn new concepts quickly, but have little interest in jargon or academic treatments. More than anything they want to know how this course can help them satisfy their customers.

Instructional Objectives

Drawing from the DMAIC model, the successful ISS student will be able to:

Define a viable, practically workable 6σ project for a retail store.
Interpret the Voice of the Customer (VOC).
Specify a business case/justification for the project.
Create problem and goal statements.
Identify project constraints and scope.
Identify key players involved.
Collect data pertinent to the process in question.
Target input data sources as potential problem causes.
Verify process variation of existing processes by calculating Sigma.
Form cause-effect hypotheses, and test accordingly.
Revise or confirm hypotheses based on test results.
Apply critical thinking skills to continually select and improve processes.
Devise controls for monitoring and maintaining improved processes.

Instructional Units

Unit 1: Introduction to 6σ

Length: 8 hours.

Unit Goal: Students will develop an understanding of 6σ as a practically useful total quality tool, and a process improvement methodology applicable in a retail service environment.

Student Learning Objectives:

Become conversant in the history and language of "Six Sigma Quality."

Be able to provide specific success stories of 6σ in manufacturing and retail.

Be able to explain the methodology of 6σ as part of a larger Total Quality Management effort in sales and service industries.

Be able to explain the sequential "DMAIC" process improvement methodology.

Unit 2: Define the Problem

Length: 8 hours.

Unit Goal: Students will use 6σ tools and methods to define a process improvement project for a retail store.

Student Learning Objectives - to Be Able to:

Define a viable, practically workable 6σ project for a retail store.

Understand the Voice of the Customer.

Specify a business case for the project.

Create problem and goal statements.

Identify project restraints and scope.

Identify key players involved.

Unit 3: Measure the Process

Length: 8 hours.

Unit Goal: Students will use reports and basic math skills as tools to convert perceived problems into data available for analysis.

Student Learning Objectives - to Know How to:

Use retail merchandising and productivity reports as objective data sources.

Collect data pertinent to the process in question.

Target input data sources as potential problem causes.

Unit 4: Analyze the Data

Length: 8 hours.

Unit Goal: Students will be able to evaluate the statistical significance of data obtained, and make further decisions accordingly.

Student Learning Objectives - to Demonstrate an Ability to:

Verify variation levels in existing processes by calculating Sigma.

Form hypotheses and test accordingly.

Revise or confirm hypotheses based on test results.

Unit 5: Improve and Control the Process

Length: 8 hours.

Unit Goal: Students will know how to repeat the DMAIC cycle in order to continually improve existing processes.

Student Learning Objectives - to Be Able to:

Select more processes or sub-processes for improvement.

Devise controls for monitoring and maintaining the improved processes.

Plan of Instruction

Module One: Informational Lesson Plan

I. Subject: The Define Phase

II. Objective: The student will be able to define a viable, practically workable 6σ project for a retail store, by interpreting the Voice of the Customer, specifying a business case for the project, creating problem statements, identifying project constraints and scope, and identifying key players.

III. Student Preparation and Instructional Presentation

Topic A. Introduction to Six Sigma (6σ)

1. Instructor will ask students and discuss: Who's ever heard of Six Sigma? Can anyone describe it for us?

2. Instructor will explain the brief history and current popularity of 6σ.

3. With use of dry-erase board, instructor will graph a 3σ process and compare it with a 6σ process, and explain why statistical concepts can enhance quality.

4. Instructor will explain DMAIC methodology and when it is appropriate for use, with use of poster graphic and easel.

Topic B. Interpreting the Voice of the Customer

1. Instructor will hand out samples of online VOC data taken from Home Depot store reports, and ask students to come up with related problem statements.

2. Instructor and students will compare notes, draw conclusions.

Topic C. Specifying a Business Case

1. Instructor will explain the purpose of 6σ in a business and total quality management context.

2. Instructor will discuss with students examples of a business case for a number of hypothetical projects.

Topic D. Creating Problem and Goal Statements

1. Instructor will solicit examples of problems encountered by students on the sales floor, and write all the suggestions on dry-erase board.

2. Instructor will convert two of these into goal statement, then instructor and students will do the same with remaining problem statements and write these results on an adjacent board.

3. Exercise: Students will write down problem and goal statements for a given process scenario, for example shipments arriving late consistently from certain vendors. Instructor and students will assess answers collectively.

Topic E. Identify Project Constraints and Scope

1. Instructor will ask and discuss: What are examples of project restrictions?

2. Instructor will explain the "Five W's" as reference guides to definition.

Topic F. Identify Key Players Involved

1. Discuss importance of teamwork and "boundary spanning" communication.

2. Explain the role of leadership ("Project Champion").

3. Exercise: Instructor will announce that the class is going to have to pick a Project Champion for the remainder of the course, and give the class ten minutes to decide on the new leader. When the dust settles, instructor will ask students what they learned about leadership.

IV. Sample Test Items. Because 6σ is a general methodology rather than an observable manipulative process or procedure, test items will be delivered in a written format.

Multiple Choice. Place a check mark next to the best answer.

1. Which of the following is the best example of a 6σ project?

__ A. Employees and customers are complaining that the store is too hot. With your 6σ team, you set out to determine what the problem is and fix it before the end of the day.

__ B. A manager discovers that a number of newer employees have not been through the company orientation, and suspects that service is lagging as a result. You and your team are appointed to tackle the issue using the 6σ methodology.

__ C. Customers have expressed in surveys that wait times at the registers are longer than what they experience in most stores. You and the 6σ team are selected to see what can be done about it.

__ D. A manager cannot make sense of numerical financial data requiring statistical expertise. He asks you and the 6σ team to interpret the data in everyday language.

(Answer: C)

2. What does DMAIC stand for?

__ A. Define, Measure, Adjust, Implement, Check

__ B. Define, Measure, Analyze, Improve, Control

__ C. Define, Modify, Adjust, Improve, Control

__ D. Define, Modify, Adjust, Implement, Check

(Answer: B)

3. Which of the following best describes a business case?

__ A. A defensible rationale for undertaking a 6σ project.

__ B. A justification for legal actions related to questionable DMAIC procedures.

__ C. A leather attaché featuring two handles and side pockets.

__ D. A complete summation of the goals, objectives and strategies of a business.

(Answer: A)

4. Processes are measured in terms of:

__ A. Consistency, Variation, Standard Deviation

__ B. 2-Delta, 4-Gamma, 6-Sigma

__ C. Tolerances, Specifications, Parameters

__ D. Inputs, Processes, Outputs

(Answer: D)

True/False. Circle the best answer.

5. T F 6σ was popularized by the Motorola company in the mid eighties.

6. T F 6σ can be best described as a business strategy.

7. T F The main purpose of 6σ is to improve quality in processes.

8. T F A project champion is one who completes a 6σ project ahead of schedule.

9. T F The Voice of the Customer is another name for the customer service or complaint-resolution department.

10. T F Project restraints are often psychological in nature.

(Answers to 5-10: T, F, T, F, F, F)

Essay. In your own words, define a 6σ project for your store. Use a customer complaint experience as an example of the Voice of the Customer, then specify a business case for the project, create problem and goal statements, identify potential project constraints and select your key players.

_______________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________ _______________________________________________________________________________

Module II: Manipulative Lesson Plan

I. Subject: The Analyze Phase

II. Objective: Students will be able to verify variation levels of existing processes in a retail environment by calculating Sigma, form and test cause-effect hypotheses, and revise or confirm hypotheses based on test results.

III. Student Preparation and Instructional Presentation

Topic A: Calculating Sigma

1. Discuss: Can anyone explain what the "Sigma" (σ) represents in 6σ?

2. Explain 6σ as a quality management tool, not a strategy or a new theory of "management by statistics."

3. Present PowerPoint slide demonstrating the six steps in calculating Sigma.

Topic B: Designing and Testing Hypotheses

1. Review/discuss PowerPoint graphic explaining 6σ as a cyclical research process (in which the problem statement leads to hypothesis formulation, then to supporting data, then to modifying the hypothesis accordingly).

2. Ask for student hypotheses to explain a sample process defect, for example a high level of "SKU checks," or manually recorded item identification numbers, at the outside garden cash register during the spring months. (Typical suggestions: a bad scan gun, a poorly trained or poor performing cashier.)

3. Using an overhead slide, compare SKU check data from garden register with the other registers. Students will soon notice that a considerable majority of SKU checks requested at the outside garden register involve a single SKU, pre-cut sod. Then explain that pre-cut sod does not come with a bar code attached, unlike most items in the store, and new cashiers are hired and placed directly into the garden area regularly during the spring months.

4. Ask for revised hypotheses to explain the high rate of SKU checks at the garden area during the spring. (Most students will recognize that the problem is likely neither the cashier's performance nor the register equipment, but a simple failure to communicate to new cashiers that sod is a high selling seasonal item with no bar code attached.)

IV. Test Items

Matching. Match each phase of calculating Sigma with the correct sequence number, by writing the number in the blank next to the corresponding phase.

1. __ Determine the defects per opportunity (DPO) in the process.

2. __ Look up Sigma level in a standard Process Sigma table.

3. __ Define a process in quantifiable terms.

4. __ Calculate yield.

5. __ Measure the number of defects against the number of defect opportunities.

(Answers, from top to bottom: 2, 5, 1, 4, 3)

Multiple Choice. Place a check mark next to the best answer.

1. Why is it important to establish the level of statistical variation in business processes?

__ A. In the information age, firms must understand and apply statistical knowledge of their process variations in order to compete globally.

__ B. Without establishing statistical variation in its processes, the business may not pass the rigorous accounting standards of the Internal Revenue Service.

__ C. Determining the level of statistical variation in processes is the first step toward improving the quality of those processes.

__ D. Optimizing requires accepting and adjusting to a certain level of statistical variation in all processes.

__ E. Both A and D.

(Answer: C)

2. In the language of total quality and 6σ, solutions to problems are always advanced as hypotheses rather than simple statements of fact. Why?

__ A. Hypotheses invoke cause-effect explanations, which are necessarily hypothetical.

__ B. Hypotheses are scientific, whereas statements of fact are dogmatic.

__ C. Hypotheses can be tested, and thereby can become laws of science.

__ D. Hypotheses suggest the possibility of modification, or continuous improvement.

__ E. Both A and D.

(Answer: E)

Essay.

1. Explain why a higher σ value assigned to a process represents a lower degree of process variation.

2. As a member of a crack 6σ team, you have been assigned to improve sales of three different SKUs of ceramic floor tile, each of which has performed poorly in comparison with similar SKUs in the store. You research related records and find that sales have slowly dropped ever since these SKUS were switched to "automatic replenishment" (in which orders to suppliers are placed by computer based on average sales per week, rather than by store personnel). You also notice floor tile sales are typically "spiked," or in large quantities at a time followed by periods of relative inactivity. Devise an hypothesis to explain the problem.

_______________________________________________________________________________

Instructional Units Development

Delivery System Selection

Review of Existing Materials. Using the available materials at Home Depot as an example, students may (or may not) be already familiar with an online e-learning class, Introduction to Six Sigma. Because so few employees have actually taken the existing class, and because the existing class mainly addresses the more technical, statistical aspects of 6σ , this ISS course will serve as an alternative introduction to the subject.

Classroom Instruction. The traditional classroom format has been chosen for delivery, for the following reasons:

This course has been designed to familiarize retail workers with 6σ, a moderately technical subject which will likely require a high level of student-instructor interaction.

Because 6σ is more general and theoretical than "hands on," students will need printed materials to keep and periodically review.

Classroom instruction is the best choice for complying with company training standards, manager expectations, and employee schedule demands.

Equipment: Includes the following:

A training room reserved 8-5, Monday through Friday for a full week of instruction. Reservations and schedule changes are both made through the store HR manager.

Four large dry-erase boards on easels, for ideas/suggestions and display purposes.

A poster/graphic presenting a step-by-step explanation for calculating Sigma.

Another poster/graphic showing the DMAIC process.

Fifteen to thirty binders, with paper for taking notes and pockets for handouts.

Handouts, including a "Sigma Table" and "How to Calculate Sigma."

Course Validation and Evaluation

Focus Group Validation

A focus group consisting of the course designer, the area field trainer, the store HR manager, and a store salesperson will conduct an initial review. Each party will be free to suggest improvements to the existing course, and the course designer will note the recommendations on validation reports and make necessary adjustments. This process will be repeated biannually and indefinitely, as long as a need for quality improvement exists.

Implementation Plan

Before the first class session begins, the instructor will:

Confirm that the training room is reserved for the dates and times scheduled.

Confirm that all students have been scheduled by the HR manager.

Confirm that a sufficient number of seats, binders and handouts are available.

Prepare graphic displays and arrange on their easels.

References

Cook, M. A., Patterson, A., & Hoerl, R. (2005). A structured problem-solving course for graduate students: Exposing students to six sigma as part of their university training. Quality and Reliability Engineering International, 21, 249-256. Retrieved February 9, 2006 from Wiley Interscience database.

Eckes, G. (2003). Six sigma for everyone. Hoboken, NJ: John Wiley & Sons.

Goetsch, D. L., & Davis, S. B. (2006). Quality Management: Introduction to Total Quality Management for Production, Processing, and Services (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Pande, P., & Holpp, L. (2002). What is six sigma? Boston: McGraw-Hill.

Patton, F. (2005). Does six sigma work in service industries? Quality Progress, 38, 9, 55-61. Retrieved February 9, 2006 from Proquest database.

Walters, L. (2005). Six sigma: Is it really different? Quality and Reliability Engineering International, 21, 221-224. Retrieved February 9, 2006 from Wiley Interscience database.

Appendix A: Goals and Objectives Worksheet

INTRODUCTION TO SIX SIGMA FOR RETAIL EMPLOYEES:

LESSONS, GOALS AND OBJECTIVES WORKSHEET

Unit 1: Introduction to Six Sigma

Unit Goal:

Students will develop an understanding of Six Sigma as a practically useful total quality tool, and a business improvement method applicable to a retail service environment.

Student Learning Objectives:

Become conversant in the history and language of "Six Sigma quality"

Be able to provide specific success stories of Six Sigma within both the manufacturing and retail industries
Be able to explain the methodology of Six Sigma as part of a total quality management effort in retail trade
Demonstrate and give a rationale for the sequential "DMAIC" process improvement Methodology

Unit 2: Define the Problem

Unit Goal:

Students will use Six Sigma tools and methods to define a process improvement project for a retail store.

Student Learning Objectives - Be able to:

Define a viable, practically workable Six Sigma project for a retail store
Understand and interpret the Voice of the Customer
Specify a business case/justification for a Six Sigma project
Create problem and goal statements
Identify project constraints and scope
Identify key players involved

Unit 3: Measure the Process

Unit Goal:

Students will demonstrate the use of reports and basic math skills as tools in order to convert perceived problems into data available for analysis.

Student Learning Objectives - Know how to:

Use retail merchandising reports as objective data sources
Collect data pertinent to the process in question
Target input data sources as potential problem causes

Unit 4: Analyze the Data

Unit Goal:

Students will be able to evaluate the statistical significance of data obtained, and make further decisions accordingly

Student Learning Objectives - Demonstrate ability to:

Verify variation levels in existing processes by calculating Sigma
Form hypotheses and test accordingly
Revise or confirm hypotheses based on test results

Unit 5: Improve and Control the New Process

Unit Goal:

Students will know how to repeat the DMAIC cycle in order to continually improve existing processes

Student Learning Objectives - Be able to:

Select more processes or sub-processes for improvement
Devise controls for monitoring and maintaining the improved processes

Appendix B: Calculating Sigma

According to Pande & Holpp (2002, p. 37), the following steps can be used to calculate sigma for most service processes:

1. Define the "unit," or item to be purchased by the customer.

2. Define the conditions that create either high or low quality for the customer.

3. Determine the number of such conditions (defect opportunities) for each unit.

4. Divide total number of defects by total number of units multiplied by number of defect opportunities per unit, then multiply the resulting figure by one million.

5. From a Process Sigma table, look up the sigma level that corresponds to that number.

Example: Pizza Delivery

After collecting data on 500 delivered pizzas, a 6σ team discovers that 25 were late, 10 were too cold, 8 were burned and 15 had the wrong ingredients.

One pizza equals one unit.

Quality conditions: Right ingredients, hot and fresh, on time, undamaged.

Four quality conditions per unit equals four defect opportunities.

Figure defects per opportunity (DPO) and defects per million opportunities (DPMO):

(25 + 10 + 8 + 15) ÷ (500 · 4) =

58 ÷ 2000, or 0.029 = DPO

DPMO = 29,000

In a standard Process Sigma table, look up the sigma level that corresponds to 29,000 DPMO = 3.4 sigma.

Appendix C: Process Sigma Table

Reference

Chan, C. (2004) Achieving Process Excellence at Intuit: Improving the Reporting Process with a Green Belt Project. Retrieved April 23, 2006 from http://monet.ecom.arizona.edu/msr/PROJECTS/20041/MP-02-04.doc.

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