VIETNAM NATIONAL UNIVERSITY – HO CHI MINH CITY
INTERNATIONAL UNIVERSITY
SCHOOL OF BUSINESS
APPLY SIX SIGMA TO IMPROVE QUALITY
Quality Management (BA018IU)
FINAL REPORT
Student’s Name: NGUYEN NGOC PHUONG TRINH (BABAIU19346)
Lecturer: MR. DUONG VO NHI ANH
Ho Chi Minh City, Vietnam
2023
TABLE OF CONTENTS
I.
INTRODUCTION ..............................................................................................................................................5
II.
WHAT IS SIX SIGMA? ....................................................................................................................................5
III.
CHARACTERISTICS .......................................................................................................................................5
IV.
THE STATISTICAL BASIC OF 3.4 DPMO....................................................................................................6
V.
IMPLEMENTING SIX SIGMA .......................................................................................................................7
1.
WHAT ARE CALLED PROBLEMS IN SIX SIGMA? .............................................................................................7
2.
PROJECT MANAGEMENT AND ORGANIZATION ..............................................................................................8
3.
SELECTING SIX SIGMA PROJECTS .................................................................................................................9
VI.
THE DMAIC IMPROVEMENT CYCLE ..................................................................................................... 11
1.
DEFINE .......................................................................................................................................................... 11
2.
MEASURE ...................................................................................................................................................... 15
3.
ANALYZE ....................................................................................................................................................... 16
4.
IMPROVE ....................................................................................................................................................... 18
5.
CONTROL ...................................................................................................................................................... 19
VII.
CASE OF AMAZON ................................................................................................................................... 20
VIII.
CONCLUSION ............................................................................................................................................ 23
IX.
REFERENCES ................................................................................................................................................. 24
TABLE OF FIGURES
Figure 1. Defects per Million for ±3𝜎 vs. ±6𝜎
Figure 2. Theoretical Basis for Six Sigma
Figure 3. Quality and Profitability
Figure 4. Pareto Analysis of Computer Services Center
Figure 5. Use of Pareto Diagrams for Progressive Analysis
Figure 6. Example of CTQ tree
Figure 7. Example of Cheet Sheet
Figure 8. Example of Cause-and-Effect Diagrams
Figure 9. Example of Control Chart
Figure 10. Annual Net Revenue of Amazon from 2004 to 2020
TABLES
Table 1. Tabulation of DPMO for Different Sigma Levels
Table 2. Several types of individuals in Project
Table 3. Problems and Causes in Computer Service Center
I.
Introduction
Six Sigma is a methodology for process improvement developed by a scientist at Motorola in the
1980s. Six Sigma practitioners use statistics, financial analysis, and project management to achieve
improved business functionality and better quality control by identifying and then correcting
mistakes or defects in existing processes. Companies often use the Six Sigma model to increase
efficiency and boost profits. The five phases of the Six Sigma method, known as DMAIC, are
defining, measuring, analyzing, improving, and controlling.
II. What is Six Sigma?
Six Sigma is a process for developing and delivering virtually perfect products and services. The
main idea behind Six Sigma is that if the number of “defects” in a process can be measured, then
it can be systematically determined how to eliminate them and get as close to zero defects as
possible. In Six Sigma, “as close to zero defects as possible” translates into a statistically based
numerical goal of 3.4 defects per million opportunities (DPMO) or 99.99966% high-quality, which
is the near elimination of defects from a process, product, or service. This is a goal far beyond the
quality level at which most companies have traditionally operated. Through the reduction of
variation in all processes (i.e., achieving the Six Sigma goal), the overall performance of the
company will be improved and significant overall cost savings will be realized.
Figure 1. Defects per Million for ±3𝜎 vs. ±6𝜎
For example, if 1 million passengers pass through the St. Louis Airport with checked baggage each
month, a Six Sigma program for baggage handling will result in only 3.4 passengers with
misplaced luggage.
III. Characteristics
The second TQM definition of Six Sigma is a program designed to reduce defects to help lower
costs, save time, and improve customer satisfaction. Six Sigma is a comprehensive system— a
strategy, a discipline, and a set of tools—for achieving and sustaining business success:
(a) It focuses on total customer satisfaction. Six Sigma is a customer­focused, results­oriented
approach to business improvement that integrates many traditional quality improvement
tools and techniques that have been tested and validated over the years. Since Six Sigma is
all about pleasing the customer, a very straightforward customer-oriented definition of
quality can be employed—the ability to satisfy customer expectations. Six Sigma can be
described as a business improvement approach that seeks to find and eliminate causes of
defects and errors in manufacturing and service processes by focusing on outputs that are
critical to customers and a clear financial return for the organization.
(b) It is a discipline because it follows the formal Six Sigma Improvement Model known as
DMAIC. This five-step process improvement model.
(c) It is a set of seven tools: check sheets, scatter diagrams, cause-and-effect diagrams, Pareto
charts, flowcharts, histograms, and statistical process control.
IV. The statistical Basic of 3.4 DPMO
Figure 2. Theoretical Basis for Six Sigma
The etymology is based on the Greek symbol "sigma" or "σ," a statistical term for measuring
process deviation from the process mean or target. Field failure data analyzed by Motorola
discovered that Motorola’s processes drifted by an average of 1.5 standard deviations under normal
control. Many common statistical process control plans use sample sizes that only allow detection
of shifts of about two standard deviations. Thus, it would not be unusual for a process to drift this
much and not be noticed. The allowance of a shift in the distribution is important because no
process can be maintained in perfect control.
The shaded distribution represents the natural variation of the process output. It is assumed to be
normally distributed and centered on the nominal (target) specification. Recall that nearly 100
percent of the area under a normal distribution is within three standard deviations on either side of
the mean. We also assume that the design tolerance has a 12-standard deviation spread so that the
process capability index for the shaded distribution is Cp = 2.0, which represents excellent
capability.
A “six-sigma quality level” corresponds to a process variation equal to half of the design tolerance
while allowing the mean to shift as much as 1.5 standard deviations from the target.
Table 1. Tabulation of DPMO for Different Sigma Levels
If the process has six Sigmas, three above and three below the mean, the defect rate is classified
as "extremely low." Because if we calculate the tail area of one of the shifted curves beyond the
specification limit (which is six standard deviations from the target—the basis for the name “six
sigma”), we obtain 0.0000034, or 3.4 parts per million.
V. Implementing Six Sigma
1.
What are called Problems in Six Sigma?
The first step in using Six Sigma is to select an appropriate problem; however, not every problem
can be addressed using Six Sigma methodology. According to Kepner and Tregoe, a problem is a
deviation between what should be happening and what actually is happening that is important
enough to make someone think the deviation ought to be corrected. Research using more than a
thousand applicable published cases suggests that virtually every instance of quality problemsolving falls into one of five categories. Each of these categories of problems requires different
approaches and methodologies. Six Sigma methods are most applicable to conformance problems
because the processes that create the problems can be easily identified, measured, analyzed, and
changed. For efficiency problems, lean tools, are generally used. Unstructured performance
problems require more creative approaches to solving them. For product design problems, special
tools and methods are available. Process design problems may require a combination of many of
these approaches.
2.
Project Management and Organization
Projects are the vehicles that are used to organize and to implement Six Sigma. Although projects
are set up as temporary organization structures, their flexibility allows cross-functional teams to
complete significant work in minimum time, if well managed. One of the challenges of
implementing Six Sigma projects is to coordinate them with normal work activities. Some slack
time, as well as physical and financial resources, must be allocated to project teams in order for
them to achieve their objectives. Team members and project leaders cannot be expected to carry a
full load of routine work and still participate fully and effectively on Six Sigma project teams.
Projects fail for a variety of reasons, including not adhering to schedules, poor planning, and
“scope creep” when the nature of the project gradually loses its focus and becomes unwieldy,
mismatching of skills, and insufficient knowledge transfer. Being able to manage a large portfolio
of projects, as would be found in Six Sigma environments, is vital to organizational success.
Teams are vital to Six Sigma projects because of the interdisciplinary nature of such projects. Six
Sigma projects require a diversity of skills that range from technical analysis, creative solution
development, and implementation. Thus, Six Sigma teams not only address immediate problems,
but also provide an environment for individual learning, management development, and career
advancement. Six Sigma teams are comprised of several types of individuals:
TYPES
DESCRIPTION
Champions
Senior-level managers who promote and lead the deployment of Six Sigma
in a significant area of the business. Champions understand the philosophy
of Six Sigma, select projects, set objectives, allocate resources, and select
and mentor teams. Champions own Six Sigma projects and are responsible
for their completion and results; typically they also own the process that the
project is focused on improving. More importantly, champions work
toward removing barriers—organizational, financial, personal—that might
inhibit the successful implementation of a Six Sigma project.
Master Black
Belts
Full-time Six Sigma experts who are responsible for Six Sigma strategy,
training, mentoring, deployment, and results. Master Black Belts are highly
trained in how to use Six Sigma tools and methods and provide advanced
technical expertise. They work across the organization to develop and
coach teams, conduct training, and lead change, but are typically not
members of Six Sigma project teams.
Black Belt
Fully trained Six Sigma experts with extensive technical training who
perform much of the technical analysis required in Six Sigma projects,
usually on a full-time basis. They have advanced knowledge of tools and
DMAIC methods, and often act as project team leaders. They also mentor
and develop Green Belts. Thus, Black Belts need good leadership and
communication skills. As such, Black Belts are often targeted by the
organization as future business leaders.
Green Belts
Functional employees who are trained in introductory Six Sigma tools and
methodology and work on projects on a part-time basis, assisting Black
Belts while developing their own knowledge and expertise. Typically, one
of the requirements for receiving a Green Belt designation is to successfully
complete a Six Sigma project. Successful Green Belts are often promoted
to Black Belts.
Yellow Belt
Individuals from various functional areas who support specific projects.
Basic understanding of the Six Sigma methodology and the tools within the
DMAIC problem-solving process. Role is to be an effective team member
on process improvement project teams.
Table 2. Several types of individuals in Project
3.
Selecting Six Sigma Projects
There are two ways for an organization to generate Six Sigma projects:
(a) Top-down. Top-down projects generally are tied to business strategy and are aligned with
customer needs. Their major weakness is that they are often too broad in scope to be
completed in a timely manner. In addition, top managers may underestimate the cost and
overestimate the capabilities of the team or teams to which the project is assigned.
(b) Bottom-up. In a bottom-up approach, Black Belts (or Master Black Belts) choose the
projects that are well-suited to the capabilities of teams. However, a major drawback of
this approach is that the projects may not be tied closely to strategic concerns of top
management, thus receiving little support and low recognition from the top.
Perhaps the best way to ensure success is for executive champions, who understand the impact of
projects from a strategic perspective, to work closely with the technical experts in choosing the
most relevant projects that fit within the capabilities of Six Sigma teams. A Six Sigma project
might span an entire division or be as narrow as a single production operation. Factors that should
be considered when selecting Six Sigma projects include the following:
(a) Financial impact, as measured by cost savings, increased revenues, or return on
investment. The financial value of a successful project can be difficult to quantify. Lower
costs associated with poor quality, such as scrap, rework, excessive cycle times, delays,
and lost customers, add to the bottom line. Traditionally, measuring reductions in qualityrelated costs through cost of quality analysis was the principal method of documenting the
benefits of improvement initiatives. However, this approach only focused on internal
benefits. Six Sigma has placed more attention on external benefits related to increases in
revenues associated with improved quality and customer satisfaction. The foundation for
the approach stems from the model shown in Figure 1.3 relating quality and profitability,
which proposes that quality improvement leads to financial returns through improvements
in customer satisfaction and loyalty.
Figure 3. Quality and Profitability
(b) Impacts on customers and organizational effectiveness. Six Sigma projects should lead to
improved customer satisfaction and organizational performance. Such improvements can
lead directly to higher sales or market share, thus providing financial justification for
selecting a project.
(c) Probability of success. At the outset of a Six Sigma initiative, it is beneficial to pick the
projects that are easy to accomplish, or even can be completed by a single individual in
order to show early successes. This visible success helps to build momentum and support
for future projects.
(d) Impact on employees. Six Sigma projects should fit within the capabilities of the people
and teams that work on them. Many indirect benefits accrue. The training received as Green
or Black Belts improves employee and organizational knowledge, and participating in Six
Sigma projects improves team and leadership skills. Six Sigma can motivate employees to
innovate and improve their work environment, and ultimately their satisfaction on the job
and personal self-esteem. Many projects offer opportunities to reduce frustration with
inadequate work processes or to provide increased value to customers; these types of
projects are certainly important candidates for selection.
(e) Fit to strategy and competitive advantage. It becomes important to be able to differentiate
between, and to estimate fairly accurately, the differences in resources required to bring a
difference project to a successful conclusion.
VI. The DMAIC Improvement Cycle
The five-step DMAIC improvement cycle is an important element of Six Sigma, listing the
sequence of steps necessary to drive process improvement and through continuously using,
systematically determined how to eliminate them and get as close to zero defects as possible. The
cycle can be applied to any process or project, both in services and manufacturing firms. Using the
DMAIC improvement cycle allows the firm to continuously monitor and improve processes that
are keys to customer satisfaction. By concentrating on these key processes and the critical-toquality (CTQ) characteristics, firms can make large and radical improvements in processes,
products, and customer satisfaction. Each of the steps is described below:
1.
Define
The problem is defined, including who the customers are and what they want, to determine what
needs to improve. It is important to know which quality attributes are most important to the
customer, what the defects are, and what the improved process can deliver.
There are many tools to use in Define phase such as: Project Charter, Cost of Quality Analysis,
Pareto Analysis, High-Level Process Mapping, SIPOC, Operational Definition, Voice of
Customers, Critical to Satisfactions, etc. For example, one useful tool to help identify the most
important issue among a mess of symptoms is Pareto analysis. Pareto analysis clearly separates
the vital few from the trivial many and provides direction for selecting projects for improvement
because a Pareto distribution is one in which the characteristics observed are ordered from largest
frequency to smallest.
Imaging, Jack has taken over a failing computer service center, with a host of problems that need
resolving. His objective is to increase overall customer satisfaction. He decides to carry out a
Pareto Analysis to assess and prioritize the biggest issues facing the center. He starts by listing
these (see the Problem column in the table, below). He then identifies the underlying causes behind
each (see the Causes column). Finally, he scores each item by the number of customer complaints
that each has received (see the Score column).
Items
Problem
Cause
Score
1
Phones aren't answered quickly Too few customer
enough.
service staff.
15
2
Staff seem distracted and under Too few customer
pressure.
service staff.
6
3
Engineers aren't well organized
Poor organization and
and often need to book second
preparation.
visits to bring extra parts.
4
4
Engineers don't know what time
they'll arrive. This means that Poor organization and
customers may have to be in all preparation.
day for an engineer to visit.
2
5
Customer service staff don't
always seem to know what Lack of training.
they're doing.
30
6
Customers are often booked in
for an appointment with an
engineer, only to discover that the Lack of training.
issue could have been solved on
the phone.
21
Table 3. Problems and Causes in Computer Service Center
Jack uses his analysis to group problems together by cause, then adds up the scores for each group
identified. He is now able to order the main causes affecting the center, starting with the one that
has attracted the highest number of customer complaints:
 Lack of training (items 5 and 6) – 51 complaints.
 Too few service center staff (items 1 and 2) – 21 complaints.
 Poor organization and preparation (items 3 and 4) – 6 complaints.
Figure 4. Pareto Analysis of Computer Services Center
Thus, the business will benefit most from giving staff more training, so Jack should tackle this
first. He could also look to increase the number of staff in the call center. However, it's possible
that this won't be necessary – the provision of further training may help to reduce customer
complaints and increase staff productivity. Jack's Pareto Analysis has enabled him to quickly
identify the areas of the business that face the biggest challenges, so he can focus his efforts where
they are needed most and prioritize issues that will provide the biggest payoff to the business. This
will likely save him a great deal of time and money that he might otherwise have spent trying to
fix a range of different issues, some of which may have provided very little benefit.
Moreover, Pareto diagrams help analysts to progressively focus in on the most appropriate
problems. At each step, the Pareto diagram stratifies the data to more detailed levels, eventually
isolating the most significant issues.
Figure 5. Use of Pareto Diagrams for Progressive Analysis
2.
Measure
In Measure phase, it prepare a data-collection plan from current process to understand and quantify
the baseline performance of the process. Determine what to measure for each process gap and how
to measure it.
The measure phase of the DMAIC process focuses on understanding process performance and
collecting the data necessary for analysis. Six Sigma uses the notion of a function in mathematics
to portray the relationship between process performance and customer value: 𝑌 = 𝑓(𝑋), where Y
is the set of CTQs and X represents the set of critical input variables that influence Y.
Understanding these relationships also helps in defining the experiments that need to be conducted
to confirm how input variables affect response variables. In addition, it sets the stage for the
Control phase by defining those factors that requiring monitoring and control.
One example of CTQ tree, a grocery store collected customer feedback to identify business
improvement opportunities. From the data, they have realized that most customers are looking for
an online option to place an order without being at the store to buy the groceries. Use the CTQ
Tree method to translate customer needs into specific, measurable, and actionable performance
requirements.
Figure 6. Example of CTQ tree
One must first ask some basic questions related to measurement:
(a)
(b)
(c)
(d)
(e)
What questions are we trying to answer?
What type of data will we need to answer the question?
Where can we find the data?
Who can provide the data?
How can we collect the data with minimum effort and with minimum chance of
error?
In addition, measurement system analysis is vital to ensure that manufacturing-based data used in
a Six Sigma project is valid and reliable. Some tools are used in Measure phase such as Data
Collection Plan, Normallity Test, Run Charts, Check Sheets, Descriptive Statistics, Measurement
System Evaluation, Process Capability Analysis, Benchmarking, etc.
Example shows that calls made to wrong number are highest cause of telephone interruptions in
radiology department. Check sheets are special types of data collection forms in which the
results may be interpreted on the form directly without additional processing.
Figure 7. Example of Cheet Sheet
3.
Analyze
In Analyze phase, it perform a process analysis using the performance data collected. The data are
analyzed in order to identify potential causes of the problem and validate them to obtain the root
causes.
The Analyze phase of DMAIC focuses on why defects, errors, or excessive variation occur, which
often result from one or more of the following:
(a) A lack of knowledge about how a process works, which is particularly critical if
different people perform the process. Such lack of knowledge results in inconsistency
and increased variation in outputs.
(b) A lack of knowledge about how a process should work, including understanding
customer expectations and the goal of the process
(c) A lack of control of materials and equipment used in a process
(d) Inadvertent errors in performing work
(e) Waste and complexity, which manifest themselves in many ways, such as
unnecessary steps in a process and excess inventories
(f) Hasty design and production of parts and assemblies; poor design specifications;
inadequate testing of incoming materials and prototypes
(g) Failure to understand the capability of a process to meet specifications
(h) Lack of training
(i) Poor instrument calibration and testing
(j) Inadequate environmental characteristics such as light, temperature, and noise
Common tools are use in Analysis phase such as Scatter Diagrams, Detailed Process Mapping,
Statistical Inference, Cause-and-Effect Diagrams, Failure Mode and Effects Analysis, Root Cause
Analysis, Gemba Investigation, Hypothesis Test etc. The following graphic is an example of a
fishbone diagram with the problem "Shorted Motor Coils Causing 23% Failure Rate on Cycle
Destruct Test." A cause-and-effect diagram is a simple graphical method for presenting a chain of
causes and effects and for sorting out causes and organizing relationships between variables.
Cause-and-effect diagrams are useful in assisting teams to generate ideas for problem causes and,
in turn, serves as a basis for identify solutions. At the end of the horizontal line, a problem is listed.
Each branch pointing into the main stem represents a possible cause. Branches pointing to the
causes are contributors to those causes. Cause-and-effect diagrams are constructed in a brainstorming type of atmosphere. Everyone can get involved and feel they are an important part of the
problem-solving process. Usually small groups drawn from operations or management work with
a trained and experienced facilitator. The facilitator guides attention to discussion of the problem
and its causes, not opinions. As a group technique, the cause-and-effect method requires significant
interaction between group members. The facilitator who listens carefully to the participants can
capture the important ideas. A group can often be more effective by thinking of the problem
broadly and considering environmental factors, political factors, employee issues, and even
government policies, if appropriate.
Figure 8. Example of Cause-and-Effect Diagrams
4.
Improve
In Improve phase, it generate solutions and formulate an implementation roadmap based on the
identified solution which design an improvement plan, then remove the causes of process variation
by implementing the improvement plan. This will require modifying, redesigning, or reengineering
the process. Document the improvement and confirm that process gaps have been significantly
reduced or eliminated.
Checklists are often used as a guide for generating ideas. Osborn proposed about 75 fundamental
questions based on the following principles to spawn new ideas:
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
Put to other uses
Adapt
Modify
Magnify
Minify
Substitute
Rearrange
Reverse
Combine
Therefore, improving may be use Design of Experiments, Mistake Proofind, Lean Production,
Deming cycle, or Seven Management and Planning Tools, Prioritisation matrix, Implementation
Roadmap, Action Steps, etc., to improve process.
Moreover, problem solutions often entail technical or organizational changes. Often some sort of
decision or scoring model is used to assess possible solutions against important criteria such as
cost, time, quality improvement potential, resources required, effects on supervisors and workers,
and barriers to implementation such as resistance to change or organizational culture. To
implement a solution effectively, responsibility must be assigned to a person or a group who will
follow through on what must be done as well as where, when, and how it will be done.
One example of How to Improve Sales for a Company by applying PDCA. PDCA can be
implemented in the following ways for checking and improving sales of a company:




5.
Plan – Identify the whys as to sales being down and how to improve the same.
Do – Implement solutions in a small way.
Check – Set benchmarks to check improvements in new processes against the old.
Act – Choose the right solution and implement worldwide.
Control
If the process is operating at the desired level of performance, it is monitored to make sure the
improvement is sustained and no unexpected and undesirable changes occur. Design and use
statistical process control charts to continuously monitor, control and sustain the improvement
changes. Controls might be as simple as using checklists or periodic status reviews to ensure that
proper procedures are followed, or employing a control chart or a run chart (a line chart of time
series data without control limits) or standard operating procedures, poka-yoke to monitor the
performance of key measures. When performance gaps are once again identified, repeat steps 1–
5.
For example, Suppose Arena Electronics Ltd. is a company that manufactures televisions. Sam,
the quality control manager in the company, wanted to track the number of dead pixels on 55-inch
LCD screens. The technicians in the company recorded the number of dead pixels for each screen.
Each subgroup comprises a different number of screens. John used a chart to track the average
number of dead pixels per screen. This is an example of a control chart.
Figure 9. Example of Control Chart
VII.Case of Amazon
Amazon is such a shining example of six sigma, in fact, Amazon uses lean six sigma, but in this
case, to emphasize the applicability of DMAIC, only refers to the six sigma strategy in general
that the company would certainly serve well as an inspiration for your own business. Six sigma is
rarely mentioned by name in Amazon’s annual reports and press releases, yet the methodology is
entrenched in the culture of company. Beginning in 1994 as a retailer selling one particular product
line, it gradually morphed into a product line, an entertainment hub and a symbol whose sum is
greater than its respective parts. When Amazon.com was first launched on July 5,1994 by Jeff
Bezos, it was an online bookstore which others thought doomed to fail. Many critics thought Jeff
Bezos crazy when stocked his online bookshop with one million book titles. The e-business has
since expanded to sell music, electronics, videos, pharmaceuticals, pet supplies, home
improvement products and groceries. Not to mention its evolution as a market place for Third party
sellers, A supply chain management expert for business customers and Amazon Web Services
(AWS) for networking infrastructure. Over the 2000-2010 decade, Amazon has developed a
customer base of around 30 million people. Ever since beginning life as an online bookstore,
Amazon.com has drastically expanded its product range. They have even implemented innovative
practices like same-day delivery, set to reach new heights for efficiency with automated drone
delivery. Yet that sum needs instrumentation in order to operate efficiently. That instrumentation
needs to understand how those constituent parts interact fully and comprehensively. And those
constituent parts need to understand just how their respective roles affect the greater whole of that
sum. That instrumentation is the key to understanding Amazon's metrics. It's called the DMAIC
model and it's part of a well established business philosophy also known as Six Sigma. It's a
strategy that's driven by data. And it's responsible in no small part for Amazon's orchestrated
disruption.
Six sigma methodology is in the culture of company. Six sigma is part of the operational excellence
program that began in 1999 when Jeff Wilke joined Amazon as VP of operations. He came from
Allied signal and his background in six sigma made him the perfect choice to drive efficiencies in
operations because in 1999 Annual Report of Amazon.com, Amazon stated that “Operational
excellence: To us, operational excellence implies two things: delivery continuous improvement in
customer experience and driving productivity, margin, efficiency, and asset velocity across all over
businesses.”
1.
Define
The business model of a flywheel isn't necessarily exclusive to Amazon. But they perfected it to
such a degree that it's become one of the most referenced examples of how retail growth maintains
its own momentum. In Amazon's case, growth is generated by six specific factors: lower cost
structure, lower prices, customer experience, traffic, sellers and selection. Amazon identifies areas
within its operations or processes that require improvement. These areas could be related to order
fulfillment, inventory management, logistics, customer service, or any other critical aspect of their
business. The goals are defined, and specific metrics are established to measure the current
performance. The concept of six sigma was developed as a way to cut costs in business
manufacturing processes. While each influences one another, customer experience is the sustaining
momentum of that flywheel. And customer-centricity is the very foundation of Amazon's success.
Amazon defines itself and its own growth by the hallmark of customer experience.
2.
Measure
Data is collected and analyzed to quantify the performance of the identified processes. Amazon
uses various performance metrics and KPIs to evaluate the efficiency and effectiveness of their
operations. They may use customer feedback, order processing times, defect rates, and other
relevant data to gain insights into the current state of their processes.
3.
Analyze
The collected data is thoroughly analyzed to identify the root causes of any inefficiencies or issues.
Amazon employs statistical tools and techniques to understand the patterns and relationships
between variables impacting their processes. By using six sigma methods, Amazon was able to
reduce variation by actively seeking it out using DMAIC, Root Cause Analysis, and similar tools.
They reduced waste by cutting spending, eliminating non-value- adding process stages, and
cultivating a Kaizen-based company culture. The analysis helps them pinpoint the primary drivers
of problems and areas that require improvement.
4.
Improve
Based on the analysis, Amazon devises and implements improvement strategies. They introduce
process changes, operational enhancements, or technology solutions to address the root causes
identified in the previous step. The improvements are carefully tested and validated before being
fully integrated into their operations. Amazon's retail model subsequently changed the game for
good. They adapted to a new and virtually unexplored environment and came up with an entirely
unique business proposition: customer-centricity.
5.
Control
In this final step, Amazon sets up controls and monitoring mechanisms to ensure that the
improvements are sustained over time. They establish processes to track ongoing performance and
regularly review the results to identify any signs of deterioration. By maintaining a focus on
continuous improvement, Amazon can sustain the benefits achieved through the DMAIC process.
Figure 10. Annual Net Revenue of Amazon from 2004 to 2020
Using Six Sigma they have made rapid progress in becoming a global online retailer. With a culture
focused on continuous improvement and greatest efficiency possible, Amazon has taken over the
world. In doing so; the impact of Six Sigma on Amazon.com can be seen through the statistical
representation.
Six Sigma is more than just a methodology for improving an organization’s quality. Most people
don’t understand the nuances and complexities of Six Sigma beyond its well-known uses. Those
who aren’t quite au fait on the subject may see Six Sigma as a simple improvement strategy. But
they often don’t question how it improves businesses or what it needs to function. In truth, data
drives Six Sigma’s success. Without sufficient data, you simply cannot make decisions without
data to support and justify them. Six Sigma’s data-driven nature derives from the six standard
deviations practitioners use to keep defects in check. Like Six Sigma, data drives everything for
Amazon. From the types of purchases, customers make online to how people use their technology.
Moreover, Amazon uses various metrics to constantly harvest data that shed light on areas for
improvement and opportunities for expansion. For Amazon, data isn’t just a means to improve
customer experience. It’s a way of life.
Amazon has always been researching, innovating, and implementing bold supply chains strategies.
In 2004, Amazon’s annual revenue was just under $7 billion. According to Statista, by 2018, its
annual revenue reached almost $233 billion. Amazon is the fastest company to reach $100 billion
in sales revenue, taking only 20 years. From its inception, Amazon has grown approximately 20%
per year. It grew from 30% from 2018 to 2019. Currently, it enjoys more than 13% of gross global
e-commerce sales.
In short, Amazon is devoted to excellent customer service and experience. Before they revamped
their business operations at the start of the millennium, they were indistinguishable from any other
online bookstore. Using Six Sigma they have made rapid progress in becoming a global online
retailer. With a culture focused on continuous improvement and greatest efficiency possible,
Amazon has taken over the world. In doing so, they have emerged as a technology giant to stand
alongside the likes of Apple or Microsoft.
VIII. Conclusion
In conclusion, Six Sigma can be a powerful and strategic methodology to consistently measure
results, which can then become a new baseline for improved performance, ultimately getting you
closer and closer to operational excellence. By utilizing Six Sigma, the project management
organization uses a disciplined, data-driven approach to minimize or eliminate defects in any
process. This process can be used inmanufacturing, engineering, leadership, and any role where
there is a specific process. Those organizations that can embrace this philosophy across their
enterprise can effectively transform their manufacturing operations into a world class, unstoppable
leader.
IX. References
Burghate, Mukul. (2021). Lean
10.6084/m9.figshare.14253281.
Six
Sigma
(6)
Case
Study:
Amazon.com.
Sharma, P. (2017). Six sigma-a case study of amazon. Com. International Journal of Research in
Management, Economics and Commerce, 7(8), 131-135.