Introduction to Six Sigma
15 October 2004
Note: This report is a general introduction to Six Sigma intended for Vietnamese companies
and is for guidance purposes only. The assistance that Mekong Capital provides to companies
in which the Mekong Enterprise Fund invests includes assisting companies to strengthen
their capacity for ongoing process improvement. Mekong Capital employs Six Sigma Black
Belts who are responsible for assisting companies in this area.
1. What is Six Sigma?
Six Sigma is a statistically-based process improvement methodology that aims to reduce defects to a
rate of 3.4 defects per million defect opportunities by identifying and eliminating causes of variation in
business processes. In defining defects, Six Sigma focuses on developing a very clear understanding of
customer requirements and is therefore very customer focused.
The Six Sigma methodology is based on a concept called DMAIC: Define, Measure, Analyze, Improve,
and Control. For more on this, please see section 3 of this report on DMAIC.
Six Sigma is not a quality management system, such as ISO-9001, or a quality certification system.
Instead it is a methodology for reducing defects based on process improvement. For many Vietnamese
companies this means that instead of focusing quality initiatives primarily on checking products for
defects, the focus is shifted towards improving the production process so that defects don’t occur.
1.2 Key themes in Six Sigma
Some of the key themes of Six Sigma can be summarized as follows:
o Continuous focus on the customer’s requirements;
o Using measurements and statistics to identify and measure variation in the production process and
other business processes;
o Identifying the root causes of problems;
o Emphasis on process improvement to remove variation from the production process or other
business processes and therefore lower defects and improve customer satisfaction;
o Pro-active management focusing on problem prevention, continuous improvement and constant
striving for perfection;
o Cross-functional collaboration within the organization; and
o Setting very high targets.
1.3 Six Sigma levels
“Sigma” means standard deviation and therefore Six Sigma means six standard deviations.
Sigma Level Defects per Million Defects as Percent
One Sigma 690,000.0 69.0000%
Two Sigma 308,000.0 30.8000%
Three Sigma 66,800.0 6.6800%
Four Sigma 6,210.0 0.6210%
Five Sigma 230.0 0.0230%
Six Sigma 3.4 0.0003%
The objective of Six Sigma is only 3.4 defects (or errors) out of every million defect opportunities. This
translates into 99.99966% perfection.
Since most private manufacturing companies in Vietnam are currently around Three Sigma or even
lower in some cases, a process improvement project using Six Sigma principles may initially aim at
Four Sigma or Five Sigma, which would nonetheless result in significant defect reduction.
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An important clarification is that Six Sigma measures defect opportunities and not defective products.
The more complex a product, the more defect opportunities it has. For example, there are more defect
opportunities in an automobile compared to a paper clip.
Below is an example of counting the number of defect opportunities in the production of wooden chairs:
Company A is producing 5 orders for customer, each order has one wooden chair item (5 units).
Opportunity per wooden chair item is clarified as follows:
o The chair was made by correct material? (1 opportunity)
o Moisture content of wood is within the standard (1 opportunity)
o The chair was made in correct size? (1 opportunity)
o The chair has no damage? (1 opportunity)
o Correct finishing is applied (1 opportunity)
o Correct packaging method is applied (1 opportunity)
Total number of defect opportunities = Units x Opportunities = 5 x 6 = 30 opportunities
1.4 Focus on Causes of Variation
From the Six Sigma view, a business process is normally represented in terms of Y=f(X’s), in which the
Outputs (Y) are determined by some Input variables (X’s). If we suspect that there is a relationship
between an outcome (Y) and potential causes (X’s), we must collect and analyze data by using some
Six Sigma testing tools and techniques to prove our hypothesis. If we want to change the outcome, we
need to focus on identifying and controlling the causes rather than checking the outcomes. When we
know enough and have good control of the X’s we can accurately predict Y. Otherwise, we have to
focus our effort on Non Value-Added Activities like inspection, testing and reworking.
1.5 Process Improvement
Six Sigma aims for processes to be improved so that problems don’t recur instead of just finding short
term solutions to the problems. Only when the cause of the variation, as defined in the previous
section, has been identified, can the process be improved so that the variation doesn’t recur in the
For example, if a wood product manufacturer in Vietnam is experiencing slow cycle time at the semi
finishing assembly quality checking station because they are getting defective parts from sanding and
grinding workshops and have to rework them:
• Typical Solution: Rebalance the line by allocating more workers to do checking and reprocessing.
• Six Sigma Solution: Investigate and control key inputs to prevent defects from occurring in the
first place. This may include unclear machine calibration procedures, unclear sanding-grinding
quality working instructions, insufficient supervision skills of team leaders, lack of wood quality
checking process at the cutting workshop, etc.
In another example, if a plastics company is producing products that don’t consistently meet the
customers’ specifications on the color of the product:
• Typical Solution: Adjust the color mixing formulas in use by using a trial-and-error effort.
• Six Sigma Solution: Determine mixing process inputs which result in incorrect colors in finished
products and then control those. These inputs might include raw material supplier, clarity of the
formula instructions, system for generating and testing the mixing formulas, calibration of mixing
equipment, ability of operators to follow instructions, etc.
1.6 Measurements and Statistics
Building new measurement systems (metrics) and then asking new questions is an integral part of Six
Sigma methodology. To improve results, a company needs to identify ways to measure variation in
business processes, generate statistics based on those measurements and then use those statistics to
ask new questions about the sources of quality problems relating to its products, services, and
1.7 Six Sigma is not just about manufacturing
Although Six Sigma is most commonly used to reduce defects in the manufacturing process, the same
methodology can be used to improve other business process. For example, it can be used to
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o identify ways to increase production capacities of equipment;
o improve on-time-delivery;
o reduce cycle time for hiring and training new employees;
o improve sales forecasting ability;
o reduce quality or delivery problems with suppliers;
o improve logistics;
o improve quality of customer service; etc.
1.8 Worldwide use of Six Sigma
Six Sigma invented by Motorola in the 1986 and popularized by General Electric (GE) in the 1990’s.
Organizations including Honeywell, Citigroup, Motorola, Starwood Hotels, DuPont, Dow Chemical,
American Standard, Kodak, Sony, IBM, Ford have implemented Six Sigma programs across diverse
business operations ranging from highly industrial or high-tech manufacturing to service and financial
operations. Although not yet widespread in Vietnam, several foreign invested manufactutring
companies in Vietnam such as American Standard, Ford, LG and Samsung in Vietnam have introduced
Six Sigma programs.
In a recent survey conducted by DynCorp1:
o Around 22% of the companies surveyed in the U.S. have a Six Sigma program in place;
o 38.2% of companies with Six Sigma programs were service companies, 49.3% were manufacturing
companies and 12.5% were other companies;
o Six Sigma was rated significantly more highly than other quality management systems and process
improvement tools in terms of achieving the greatest results (however, Six Sigma also includes
some of the tools which are listed separately in the survey).
Which quality management systems process improvement
tools have yielded the greatest results?
Six Sigma 53.6%
Process mapping 35.3%
Root cause analysis 33.5%
Cause-and-effect analysis 31.3%
Lean thinking/manufacturing 26.3%
Problem solving 23.2%
ISO 9001 21.0%
Process capability 20.1%
Statistical process control 20.1%
Performance metrics 19.2%
Control charts 19.2%
Process management 18.8%
Project management 17.9%
Customer-driven processes 17.9%
Design of experiments 17.4%
Failure mode and effects analysis 17.4%
Process reengineering 16.1%
Change management 14.7%
Total Quality Management (TQM) 10.3%
Variation measurement 10.3%
Malcolm Baldridge criteria 9.8%
Workflow analysis 9.8%
Decision making 8.9%
Trend analysis 8.0%
Management by fact 6.7%
Setup reduction 6.7%
Knowledge management 5.8%
Work breakdown structure 3.1%
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2. Benefits of Six Sigma
2.1 Reduced production costs
By significantly lowering defect rates, the company can eliminate wastage of materials and inefficient
use of labor which is associated with defects. This will reduce the cost of goods sold for each unit of
output and therefore add significantly to the company’s gross margin or allow the company to sell its
products at a lower price in order to generate higher revenues.
For example, if a company has a non-reprocessable defect rate of 6%, raw materials costs at 60% of
revenues, labor costs equal to 10% of revenues, and a gross profit margin of 20%, a simple analysis
shows significant improvements to the gross profit margin resulting from defect reduction as follows:
Current Situation Some Improvement Significant
Defect rate 6% 3% 0%
Raw materials / revenue 60% 58.3% 56.6%
Labor / revenues 10% 8% 6%
Depreciation2 / revenues () 10% 9% 8%
Gross margin 20% 26.7% 29.4%
2.2 Reduced overhead costs
By significantly lowering defect rates, and implementing process improvements so that similar defects
don’t recur, the company can reduce the amount of time that senior management and middle
management spends resolving problems associated with high levels of defects. This also frees up
management to focus on more value-added activities.
2.3 Improved Customer Satisfaction
Many private companies in Vietnam have had recurring problems associated with shipping products to
customers which didn’t meet customer specifications and therefore caused the customer to be unhappy
and sometimes even cancel orders. By significantly lowering defect rates, the company will be able to
consistently ship products to customers which strictly meet the customer’s specifications and therefore
increase customer satisfaction.
Increased customer satisfaction reduces the likelihood of losing orders from customers while increasing
the likelihood that the customer will place larger orders with the company. This can mean significantly
higher revenues for the company.
Furthermore, the cost of acquiring new customers is high so companies those have lower customer
turnover will have lower sales and marketing expenses as a percent of total revenue.
2.4 Reduced Cycle Times
The longer it takes for inventory to move through the production process, the higher the production
costs since slow moving inventory must be moved, stored, counted, retrieved and faces greater risk of
becoming damaged or not meeting specifications. However, with Six Sigma, fewer problems arise
during a manufacturing process, which means that the process can consistently be completed more
quickly and therefore production costs, especially labor costs per unit produced, are lower. In addition
to reducing production costs, quicker turnaround times are often a selling point for many customers
who want the product delivered as soon as possible.
A common problem for many private Vietnamese manufacturing companies is a high rate of delayed
shipments or deliveries to customers. The variations which can be eliminated in a Six Sigma project can
The reduction in depreciation as a percent of revenues is a result of a higher volume of production from the existing
equipment and facilities due to lower defects and reprocessing, as well as reduced machine downtime.
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include variations in delivery time. Therefore, Six Sigma can be used to help ensure consistent on-time-
2.6 Greater ease of expansion
A company with a significant emphasis on process improvement and elimination of the sources of
defects will have a deep understanding of the potential causes of problems in expansion projects, as
well as systems in place for measuring and identifying the sources of those problems. Therefore
problems are less likely to occur as the company expands its production, and if they do occur, they are
likely to be resolved more quickly.
2.7 Higher expectations
By aiming for 3.4 defects per million defect opportunities, it allows the company to set high
expectations. Higher expectations themselves can lead to higher performance since they reduce the
risk of complacency. Furthermore, Six Sigma programs introduce many new measurements which help
to discover and monitor recurring problems and therefore create more of a sense of urgency to get
those problems resolved.
2.8 Positive Changes to Corporate Culture
Six Sigma is as much about people excellence as it is about technical excellence. Employees often
wonder how they are going to solve a difficult problem, but when they are given the tools to ask the
right questions, measure the right things, correlate a problem with a solution and plan a course of
action, they can find solutions to the problem more easily. Therefore, with Six Sigma, the company’s
corporate culture shifts to one that includes a systematic approach to problem solving and a pro-active
attitude among employees. Successful Six Sigma programs also contribute to the overall sense of pride
of the company’s employees.
Six Sigma transforms the way a company thinks and works on major business issues:
o Process design: Designing production processes to have the best and most consistent outcomes
from the beginning.
o Variable investigation: conducting studies to identify what the variables cause variation and how
they interact with each other.
o Analysis and reasoning: using facts and data to find the root causes of variations, instead of
educated guesses or intuition.
o Focus on process improvement: focusing on process improvement as key to excellence in quality.
o Pro-activeness: Encouraging people to be pro-active about preventing potential problems instead of
waiting for problems to occur.
o Broad participation in problem solving: getting more people involved in finding causes and solutions
o Knowledge sharing: learning and sharing new knowledge in terms of best practices to speed up
o Goal setting: aiming at stretch goals, instead of “good enough” targets, so that the company is
constantly striving for improvement.
o Suppliers: cost is not the only criteria for vendor evaluation, but relative capability to consistently
provide quality materials with the shortest lead time.
o Data-based decision making: Decisions are made based on critical analysis of facts and data.
However, this does NOT mean it will negatively impact to a company’s ability to make quick
decisions. In contrast, by smoothly applying the DMAIC principles, the decision makers are more
likely to have the data they need in order to make well informed decisions.
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3. DMAIC Roadmap
The DMAIC methodology is central to Six Sigma process improvement projects. The following phases
provide a problem-solving process in which specific tools are employed to turn a practical problem into
a statistical problem, generate a statistical solution and then convert that back into a practical solution.
3.1 Define (D)
The purpose of the Define phase is to clearly identify the problem, the requirements of the project and
the objectives of the project. The objectives of the project should focus on critical issues which are
aligned with the company’s business strategy and the customer’s requirements. The Define phase
o define customer requirements as they relate to this project. Explicit customer requirements are
called Critical-to-Quality (CTQ) characteristics;
o develop defect definitions as precisely as possible;
o perform a baseline study (a general measure of the level of performance before the improvement
o create a team charter and Champion;
o estimate the financial impact of the problem; and
o obtain senior management approval of the project
o What matters to the customers?
o What Defect are we trying to reduce?
o By how much?
o By when?
o What is the current Cost of defects?
o Who will be in the project team?
o Who will support us to implement this project?
The most applicable tools at this phase are the following:
o Project Charter - this document is intended to clearly describe problems, defect definitions, team
information and deliverables for a proposed project and to obtain agreement from key stakeholders.
o Trend Chart - to see (visually) the trend of defect occurrence over a period of time.
o Pareto Chart - to see (visually) how critical each input is in contributing negatively or positively to
total output or defects.
o Process Flow Chart - to understand how the current process functions and the flow of steps in
3.2 Measure (M)
The purpose of the Measure phase is to fully understand the current performance by identifying how to
best measure current performance and to start measuring it. The measurements used should be useful
and relevant to identifying and measuring the source of variation. This phase includes:
o identify the specific performance requirements of relevant Critical-to-Quality (CTQ) characteristics;
o map relevant processes with identified Inputs and Outputs so that at each process step, the relevant
Outputs and all the potential Inputs (X) that might impact each Output are connected to each other;
o generate list of potential measurements
o analyze measurement system capability and establish process capability baseline;
o identify where errors in measurements can occur;
o start measuring the inputs, processes and outputs and collecting the data;
o validate that the problem exists based on the measurements;
o refine the problem or objective (from the Analysis phase)
o What is the Process? How does it function?
o Which Outputs affect CTQ’s most?
o Which Inputs affect Outputs (CTQ’s) most?
o Is our ability to measure/detect sufficient?
o How is our current process performing?
o What is the best that the process was designed to do?
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The most applicable tools at this phase include the following:
o Fishbone Diagram – to demonstrate the relationships between inputs and outputs
o Process Mapping - to understand the current processes and enable the team to define the hidden
causes of waste.
o Cause & Effect Matrix - to quantify how significant each input is for causing variation of outputs.
o preliminary Failure Mode & Effect Analysis (FMEA) - using this in the Measure phase helps to
identify and implement obvious fixes in order to reduce defects and save costs as soon as possible.
o Gauge Repeatability & Reproducibility (GR&R) - used to analyze the variation of components of
measurement systems so minimize any unreliability in the measurement systems.
3.3 Analyze (A)
In the Analyze phase, the measurements collected in the Measure phase are analyzed so that
hypotheses about the root causes of variations in the measurements can be generated and the
hypothesis subsequently validated. It is at this stage that practical business problems are turned into
statistical problems and analyzed as statistical problems. This includes:
o generate hypotheses about possible root causes of variation and potential critical Inputs (X’s);
o identify the vital few root causes and critical inputs that have the most significant impact; and
o validate these hypotheses by performing Multivariate analysis.
o Which Inputs actually affect our CTQ’s most (based on actual data)?
o By how much?
o Do combinations of variables affect outputs?
o If an input is changed, does the output really change in the desired way?
o How many observations are required to draw conclusions?
o What is the level of confidence?
The Analyze phase offers specific statistical methods and tools to isolate the key factors that are critical
for a comprehensive understanding of the causes of defects:
o Five Why’s - use this tool to understand the root causes of defects in a process or product, and to
penetrate through incorrect assumptions about causes.
o Tests for normality (Descriptive Statistics, Histograms) – this is used to determine if the
collected data is normal or abnormal so as to be properly analyzed by other tools.
o Correlation/Regression Analysis - to identify the relationship between process inputs and
outputs or the correlation between two different sets of variables.
o Analysis of Variances (ANOVA) - this is an inferential statistical technique designed to test for
significance of the differences among two or more sample means.
o FMEA (Failure Mode and Effect Analysis) - applying this tool on current processes enables
identification of sufficient improvement actions to prevent defects from occurring.
o Hypothesis testing methods - these are series of tests in order to identify sources of variability
using historical or current data and to provide objective solutions to questions which are traditionally
3.4 Improve (I)
The Improve phase focuses on developing ideas to remove root causes of variation, testing and
standardizing those solutions. This involves:
o identify ways to remove causes of variation;
o verify critical Inputs;
o discover relationships between variables;
o establish operating tolerances which are the upper and lower specification limits (the engineering or
customer requirement) of a process for judging acceptability of a particular characteristic, and if
strictly followed will result in defect-free products or services;
o optimize critical Inputs or reconfigure the relevant process.
o Once we know for sure which inputs most affect our outputs, how do we control them?
o How many trials do we need to run to find and confirm the optimal setting/procedure of these key
o Who should the old process be improved and what is the new process?
o How much have Defects Per Millions Opportunities (DPMO) decreased?
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The most applicable tools at this phase are:
o Process Mapping - this tool helps to represent the new process subsequent to the improvements.
o Process Capability Analysis (CPK) - in order to test the capability of process after improvement
actions have been implemented to ensure we have obtained a real improvement in preventing
o DOE (Design of Experiment) - This is a planned set of tests to define the optimum settings to
obtain the desired output and validate improvements.
3.5 Control (C)
The Control phase aims to establish standard measures to maintain performance and to correct
problems as needed, including problems with the measurement system. This includes:
o validate measurement systems;
o verify process long-term capability;
o implement process control with control plan to ensure that the same problems don’t reoccur by
continually monitoring the processes that create the products or services.
o Once defects have been reduced, how do we ensure that the improvement is sustained?
o What systems need to be in place to check that the improved procedures stay implemented?
o What do we set up to keep it going even when things change?
o How can improvements be shared with other relevant people in the company?
Most applicable tools at the Control phase include:
o Control Plans -t his is a single document or set of documents that documents the actions, including
schedules and responsibilities, that are needed to control the key process inputs variables at the
o Operating Flow Chart(s) with Control Points - this is a single chart or series of charts that
visually display the new operating processes.
o Statistical Process Control (SPC) charts - these are charts that help to track processes by
plotting data over time between lower and upper specification limits with a center line.
o Check Sheets - this tool enables systematic recording and compilation of data from historical
sources, or observations as they happen, so that patterns and trends can be clearly detected and
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4. Six Sigma vs. Other Quality Systems
Six Sigma builds upon many of the successful elements of the previous quality improvement strategies
and incorporates unique methods of its own. Compared to other quality management and improvement
systems, Six Sigma stands out as a methodology for identifying the causes of specific quality problems
and solving those problems. Six Sigma can often be used to complement other quality management or
4.1 ISO 9001
4.1.1 ISO 9001 objectives
ISO 9001 is a Quality Management System, which includes specialized quality management standards
for specific industries. A Quality Management System is a system of clearly defined organizational
structures, processes, responsibilities and resources used to assure minimum standards of quality and
can be used to evaluate an organizations overall quality management efforts. An ISO 9001 certification
assures a company’s customers that minimum acceptable systems and procedures are in place in the
company to guarantee that minimum quality standards can be met.
4.1.2 Comparison with Six Sigma
ISO 9001 and Six Sigma serve two different purposes. ISO 9001 is a quality management system while
Six Sigma is a strategy and methodology for business performance improvement.
ISO 9001, with guidelines for problem solving and decision making, requires a continuous improvement
process in place but does not indicate what the process should look like while Six Sigma can provide
the needed improvement process. Meanwhile, Six Sigma does not provide a template for evaluating an
organization’s overall quality management efforts whereas ISO9001 does.
4.1.3 Combining Six Sigma with ISO
Six Sigma provides a methodology for delivering certain objectives set by ISO such as:
o prevention of defects at all stages from design through servicing;
o statistical techniques required for establishing, controlling and verifying process capability and
o investigation of the cause of defects relating to product, process and quality system;
o continuous improvement of the quality of products and services.
Six Sigma supports ISO and helps an organization satisfying the ISO requirements. Further, ISO is an
excellent vehicle for documenting and maintaining the process management system involving Six
Sigma. Besides, extensive training is required by both systems for successful deployment.
4.2 Total Quality Management (TQM)
4.2.1 TQM objectives
Total Quality Management (TQM) is a structured system for satisfying internal and external customers
and suppliers by integrating the business environment, continuous improvement, and breakthroughs
with development, improvement, and maintenance cycles while changing organizational culture. TQM
aims for quality principles to be applied broadly throughout an organization or set of business
4.2.2 Comparison with Six Sigma
TQM and Six Sigma have a number of similarities including the following:
o A customer orientation and focus
o A process view of work
o A continuous improvement mindset
o A goal of improving all aspects and functions of the organizations
o Data-based decision making
o Benefits depend highly on effective implementation
A key difference between TQM and Six Sigma is that Six Sigma focuses on prioritizing and solving
specific problems which are selected based on the strategic priorities of the company and the problems
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which are causing the most defects whereas TQM employs a more broad based application of quality
measures to all of the company’s business processes.
Another difference is that TQM tends to apply quality initiatives within specific departments whereas Six
Sigma is cross functional meaning that in penetrates every department which is involved in a particular
business process that is subject to a Six Sigma project.
Another difference TQM provides less methodology in terms of the deployment process whereas Six
Sigma’s DMAIC framework provides a stronger platform for deployment and execution. For example,
Six Sigma has a much stronger focus on measurement and statistics which helps the company define
and achieve specific objectives.
4.2.3 Combining TQM with Six Sigma
Six Sigma is complementary to TQM because it can help to prioritize issues within a broader TQM
program and provides the DMAIC framework which can be used to meet TQM objectives.
4.3 Six Sigma and Lean Manufacturing
4.3.1 Lean Manufacturing objectives
Lean Manufacturing, also called Lean Production, is a set of tools and methodologies that aims for the
continuous elimination of all waste in the production process. The main benefits of this are lower
production costs, increased output and shorter production lead times. More specifically, some of the
1. Defects and wastage - Reduce defects and unnecessary physical wastage, including excess use of
raw material inputs, preventable defects, costs associated with reprocessing defective items, and
unnecessary product characteristics which are not required by customers;
2. Cycle Times - Reduce manufacturing lead times and production cycle times by reducing waiting
times between processing stages, as well as process preparation times and product/model
3. Inventory levels - Minimize inventory levels at all stages of production, particularly works-in-
progress between production stages. Lower inventories also mean lower working capital
4. Labor productivity - Improve labor productivity, both by reducing the idle time of workers and
ensuring that when workers are working, they are using their effort as productively as possible
(including not doing unnecessary tasks or unnecessary motions);
5. Utilization of equipment and space - Use equipment and manufacturing space more efficiently
by eliminating bottlenecks and maximizing the rate of production though existing equipment, while
minimizing machine downtime;
6. Flexibility - Have the ability to produce a more flexible range of products with minimum
changeover costs and changeover time.
7. Output – Insofar as reduced cycle times, increased labor productivity and elimination of
bottlenecks and machine downtime can be achieved, companies can generally significantly
increased output from their existing facilities.
Most of these benefits lead to lower unit production costs – for example, more effective use of
equipment and space leads to lower depreciation costs per unit produced, more effective use of labor
results in lower labor costs per unit produced and lower defects lead to lower cost of goods sold.
4.3.2 Comparison with Six Sigma
Both Six Sigma and Lean Manufacturing have unique strengths and they integrate well.
Lean is more broad in nature since it sets the broad objective of eliminating all waste, and recommends
certain processes for achieving that. When the objective is process design, factory layout, waste
reduction and the way to accomplish the objectives is known, Lean tools and approaches are
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Six Sigma is more focused in nature since it a set of tools for achieving clearly defined improvements,
which are likely to help make the company more lean. Six Sigma provides a richer infrastructure and
toolset for problem solving especially with unknown causes and solutions.
4.3.3 Combining Lean Manufacturing with Six Sigma
It is quite common for companies to combine Lean Manufacturing with Six Sigma in what is sometimes
called Lean Six Sigma. The two are quite complementary since Six Sigma is a useful tool for helping to
make the company more lean. Likewise, some of the processes often used in lean manufacturing may
be the solutions to problems addressed in a Six Sigma project.
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5. Six Sigma Implementation
Although the result of Six Sigma projects are desirable by most companies, companies need to carefully
consider the implementation process, since Six Sigma requires a very serious commitment by the
senior management team as well as other key employees.
5.1 Steps for building Six Sigma capacity within the organization
Discover: recognize the need for Six Sigma and explore its potential impact on the company.
Decide: senior management approves the Six Sigma initiative, and then defines the purpose and scope
of Six Sigma.
Organize: establish financial targets; set time lines; train senior executive team and Deployment
Champions who are responsible for planning and mechanism building.
Initialize: create detailed deployment plans including the numbers of Six Sigma Black Belts and other
human resources needed per business unit, training requirements, proposals for Six Sigma project
opportunities with estimated cost savings, project review agendas and formats, instructions and
systems for individual project benefit tracking and overall expected Six Sigma financial impact versus
the current situation.
Deploy: train project Champions and Black Belts. Meanwhile, select and execute improvement
Sustain: train Six Sigma Green Belts and Process-Improvement Team Leaders to speed up
improvements and maintain achievements.
5.2 Critical Success Factors
5.2.1 Senior Management Commitment
Implementation of Six Sigma represents a long term commitment. The success of Six Sigma projects
depends substantially on the level of commitment by the senior management. General Electric’s
success with Six Sigma is due in large part to the role that Jack Welch (former CEO) played in
relentlessly advocating Six Sigma and integrating it into the core of the company’s strategy.
5.2.2 Initial Questions to ask before Adopting Six Sigma
o Does the company’s leadership understand and completely behind implementing Six Sigma?
o Is the company open and ready to change?
o Is the company hungry to learn?
o Is the company willing to commit resources, including people and money, to implement this
5.2.3 Selecting and Training The Right People
It is necessary to attract the best people to be involved in the company’s Six Sigma initiative and
motivate them by compensation, rewards, recognition and promotion which are linked to performance.
Training programs should focus on statistical, analytical, problem-solving skills and leadership skills
that help to remove barriers and create initial momentum.
Furthermore, getting people excited and motivated about the Six Sigma initiative should be done
through training and communication. Everyone in the company should understand how Six Sigma will
benefit themselves as well as the company.
5.2.4 Selecting Six Sigma projects
Primarily, Six Sigma projects should focus on key problem areas with strategic alignment in terms of
high customer satisfaction impact and critical to business success in terms of faster or larger financial
return (higher revenues, lower cost, etc.).
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Selecting Six Sigma projects at the beginning is very important and therefore plays a key role in the
success of Six Sigma projects. The company should carefully consider the expected impact of the
project as well as if there may be easier ways of solving the problem, other than a Six Sigma project.
5.2.5 Managing Six Sigma projects
During project execution, it is important to
o lead a focus effort in which the project Champion is responsible for conducting a project review,
uses his authority to solve cross-functional problems and allocate needed resources.
o check for real financial impact (please refer to 5.2.6);
o continuously communicate progress to executive leadership and those involved in the projects.
o implement effective control plans including such documents as Process Maps, C&E Matrix, FMEA,
Control Plan Summary and approved procedure changes to ensure that improvements are
o review the project’s effectiveness at regularly scheduled intervals;
o roles and responsibilities of relevant parties should be clearly defined;
o conduct regular Six Sigma training to reinforce the initiative throughout the company.
5.2.6 Finance Department involvement
The finance department needs to be involved from the beginning of each project to ensure that cost
savings are being tracked for each Six Sigma project and actually being reflected in the bottom line.
Project baseline and claimed improvements must be strictly verified by finance team. Improvements
are converted into dollar amount savings whenever possible and deducted if any cost arises due to the
5.3 Costs of Six Sigma Projects
Although Six Sigma projects can have many benefits and help the company to save money over the
long run, there are also costs associated with Six Sigma projects. They typically include the following:
o Direct Payroll - Payroll expenses for individuals dedicated to the Six Sigma project on a full time
o Indirect Payroll – The cost of time devoted by senior executives, team members, process owners
and others in the implementation of the Six Sigma project.
o Training and Consulting – The cost of teaching people Six Sigma skills
o Improvement Implementation Costs – The costs of improving the production process to eliminate
the sources of variation identified in the Six Sigma project. This might involve new equipment, new
software, additional personnel costs for newly formed positions, etc.
o Software – Some software such as Minitab Inc.’s Minitab statistical software or Microsoft’s Visio, for
generating flow-charts, may also be required. More advanced software tools sometimes include
Popkin’s System Architect, Proforma’s Provision or Corel’s iGrafx Process 2003 for Six Sigma.
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6. Definition of Terms
Analysis of Variances (ANOVA): A statistical test that allows for comparisons of multiple sources of
variation, or effects, to determine if any of these sources significantly affect the variability of the
outcome being studied.
Black Belt (BB): expert in leading project execution with relevant experience in one or more specific
fields; extensive training and strong background in statistics and analysis. A BB will be certified after
meeting qualifications specified by the company in term of significant cost savings achievement;
effective application of tool and philosophy, analytical skills, project management and team building
skills. BB is also responsible for training and coaching Green Belts.
Cause & Effect Matrix: A prioritization matrix or diagram that enables selection of those process input
variables (X’s) that have the greatest effect on the process output variables (Y’s). The tool is also used
to emphasize the importance of understanding the customer requirements.
Champion(s): selected senior executives and managers familiar with basic and advanced statistical
tools, who allocate resources and remove barriers for Six Sigma projects; create the vision of Six
Sigma for the company; develop training plan; select high impact projects; select potential people;
construct and improve deployment mechanism; monitor SS project review; recognize people for their
efforts and contribution.
Check Sheets: Forms or worksheets facilitating data collection and compilation. These are generally
used to count different types of defects.
Control Plan Summary: a process control document that logically describes the system for controlling
processes and maintaining improvements in order to ensure that the company consistently operates its
processes such that products meet customer requirements all the times.
Correlation Analysis: A statistical method to identify if a relationship exists between the two variables
by plotting paired values. To quantify the relationship, a regression line, which is characterized by its
slope and intercept, can be drawn through the scatter-plot of the paired data points. The tighter the
paired data points fit the line, the stronger the relationship.
Critical to Quality (CTQ): Explicit customer requirements (specifications) which if not met are
Critical Inputs: The vital few factors proven to be primarily responsible for a specified outcome (Y).
Defect: Any failure of products or services to meet one of the acceptance criteria of the company’s
customers (internal or external). A defective unit may have one or more defects. Defects should always
be considered a fail on a pass/fail scale.
Defect Opportunity: Any situation in a process which presents a reasonable possibility of causing a
defect on a unit of output which is important to the customer. A complex product such as a car has
many more defect opportunities than a simple product such as a paperclip.
Design for Six Sigma (DFSS): Describes the application of Six Sigma tools to product development
and Process Design efforts with the goal of "designing in" Six Sigma performance capability. This can
also apply to process redesign efforts at the Improve phase of a Six Sigma project.
Design of Experiment (DOE): An efficient method of experimentation which identifies, with minimum
testing, those factors and their optimum settings that affect the mean and variation of the outputs.
DMAIC: Acronym for a Process Improvement/Management System which stands for Define, Measure,
Analyze, Improve and Control.
Failure Mode & Effect Analysis (FMEA): A structured approach for preventing defects by
documenting failure events, the way in which a process can fail, estimating the risk associated with
specific causes, and prioritizing potential problems and their resolution.
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Fishbone Diagram (cause & effect diagram): Also known as a "Fishbone" or "Ishikawa Diagram", a
channeled brainstorming tool used for determining root-causes (the bones of the fish) for a specific
effect, or problem.
Five Why’s: A method used to move past symptoms and understand the true root cause of a problem.
It is said that only by asking "Why?" five times, successively, you can delve into a problem deeply
enough to understand the ultimate root cause.
Gauge Repeatability & Reproducibility (GR&R): A statistical tool that measures the amount of
variation or error in the measurement system arising from the measurement device and the people
taking the measurement.
Green Belt (GB): who current positions are associated with the problem to be solved while performing
their regular duties, familiar with basic statistical tools and less intensive in training.
Hypothesis testing (T-test, F-test): The process of using a variety of statistical tools to analyze data
and, ultimately, to accept or reject the null hypothesis. From a practical point of view, finding statistical
evidence that the null hypothesis is false allows you to reject the null hypothesis and accept the
alternate hypothesis. A null hypothesis (H0) is a stated assumption that there is no difference in
parameters (mean, variance, defects per million defect opportunities) for two or more populations. The
alternate hypothesis (Ha) is a statement that the observed difference or relationship between two
populations is real and not the result of chance or an error in sampling.
ISO-9000: Standard and guideline used to certify organizations as competent in defining and adhering
to documented processes. It is mostly associated with quality management systems, rather than
quality improvement efforts.
Lean Manufacturing: A system of tools for reducing the time from customer order to manufacturing
and delivering products by eliminating non-value added activities and waste in the production stream.
Lean Six Sigma: The combination of Lean Manufacturing with Six Sigma.
Main Effect Plot: A statistical study that samples the process as it operates, and through statistical
and graphical analysis, identifies the important variables.
Mean: The average data point value within a data set. To calculate the mean, add all of the individual
data points then divide that figure by the total number of data points.
Non-Value Added Activities: Steps/tasks in a process that do not add value to the external customer
such as rework, handoffs, inspection/control, wait/delays, etc.
Non-Value Added Waste: Byproducts of the production process which are non-value added.
Operating Flow Chart(s) with Control Points: Similar to process flow chart but also highlighting
critical areas where control measures are applied. This is a frequently updated document useful as a
process control guideline.
Pareto Chart: A tool for establishing priorities based on the Pareto principle, also know as the 80/20
rule, which is that 20% of the causes result in 80% of the impact. For example, 20% of the causes of
defect opportunities tend to cause 80% of the defect opportunities. The Pareto chart uses attribute data
with columns arranged in descending order, with highest occurrences (highest bar) shown first. It uses
a cumulative line to track percentages of each category/bar, which distinguishes the 20 percent of
items causing 80 percent of the problem. The purpose of this is to prioritize which problems should be
Process: A series of activities or steps that create a product or services.
Process capability: Ability of a process to produce a defect-free product or service in a controlled
manner of production or service environment.
Process Capability Analysis: Analysis of the degree to which a process is or is not meeting customer
Process Flow Chart: Graphical display of the process flow that shows all activities, decision points,
rework loops, and handoffs. This is different from Process Mapping.
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Process improvement: Improvement approach focused on incremental changes/solutions to
eliminate or reduce defects, costs or cycle time. It leaves basic design and assumptions of a process
Process Mapping: A step-by-step pictorial sequence of a process showing various process inputs,
process outputs and process steps which is a first step toward understanding how those inputs affect
the output. This is different from a Process Flow Chart.
Project Description: Broad statement defining area of concern or opportunity including impact/benefit
of potential improvements, or risk of not improving a process. It includes links to business strategies,
the customer, and/or company values. It is provided by senior management to an improvement team
and used to develop problem statement and Project Charter.
Project Charter: A document that clearly addresses a Six Sigma project scope, target(s), projected
financial savings, project Champion, team involved and project timeline, etc.
Process redesign: method of restructuring process flow elements eliminating handoffs, rework loops,
inspection points, and other non-value-added activities.
Quality management system (QMS): A system of clearly defined organizational structures,
processes, responsibilities and resources used to assure minimum standards of quality. ISO9000 is a
quality management system.
Regression Analysis: A statistical technique for estimating a model for the relationship among several
variables. It gives us an equation that uses one or more variables to help explain the variation in
Regression Plot: A graphical display used to evaluate the relationship between two or more variables
by determining an equation to estimate the interested outcome from knowledge of the input variables.
Sigma (σ): The Greek letter used to represent standard deviation in statistics.
Six Sigma Level: The performance level with only 3.4 defects per million defect opportunities.
Six Sigma: A statistically-based process improvement methodology that aims to reduce defects to a
rate of 3.4 defects per million defect opportunities by identifying and eliminating causes of variation in
Statistical Process Control (SPC): Use of data gathering and statistical analysis to monitor
processes, identify performance issues, measure variation and capability, and distinguish between
common and special cause. This serves as a basis for data-based decision-making for product or
service quality maintenance or improvement.
Statistical Quality Control (SQC): See Statistical Process Control.
SPC charts: Charts which track Statistical Process Control data.
Tests for normality (Descriptive Statistics, Histograms): A statistical process used to determine if
a sample or any group of data fits a standard normal distribution. Descriptive statistics and histogram
tools graphically show the shape of a set of data - where it centers, and how far it spreads out on either
Time Series Plots: A graphical display often used in process variation studies in which observations
(data points) are plotted to show the trend over time. The upper and lower control limits are also
included to evaluate the process stability.
Total Quality Management (TQM): A structured system for satisfying internal and external
customers and suppliers by integrating the business environment, continuous improvement, and
breakthroughs with development, improvement, and maintenance cycles while changing organizational
Trend Chart: A graphical display used to show trends in data over time. All processes vary, so single
point measurements can be misleading. Displaying data over time increases understanding of the real
performance of a process, particularly with regard to an established target or goal.
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Variables: refers the input factors (X’s) that causes variation of process output.
Variation: Change or fluctuation of a specific characteristic, which determines how stable or
predictable the process may be; affected by environment, people, machinery/equipment,
methods/procedures, measurements, and materials; Process Improvement aims to reduce or eliminate
For more information please contact:
Mekong Capital Ltd
Saigon Tower, 11th Floor
29 Le Duan St., District 1
HCMC, Viet Nam
Tel. (84 8) 827 3161
Fax: (84 8) 827 3162
Mekong Capital’s Introduction to Six Sigma Page 17 of 17