Online Six Sigma Training

Six Sigma is a quality management methodology that follows a data driven approach for reducing waste and improving overall quality of goods manufactured or services rendered. It makes use of statistical tools and techniques that help in identifying exactly what the customer needs and designing sustainable methods to meet those requirements. By implementing Six Sigma, any organization can hope to increase efficiency, increase productivity, and reduce manufacturing costs. By employing statistical methods, companies can look forward to create a near perfect situation wherein the number of defects is reduced to less than 3.4 per million opportunities that exists for such defects to occur. Companies the world over have implemented Six Sigma in their business processes, which has helped them in attaining optimum competence and saving millions of dollars through phenomenal reduction in the amount of waste.

Why Online Training

The success of Six Sigma initiatives depends on a number of factors, one of which is the training imparted to owners and employees. Training is necessary as it allows organizational members to understand the various concepts and implement them in a proper manner. Due to hectic schedules, companies often decide to provide online training, making it easier for employees to select an appropriate time for training based on their work schedule.

Benefits Of Online Training

Employees often find it difficult to manage work schedules and training at the same time. Online training allows them to give priority to their current work obligations and receive training in their free time. Online training helps in better absorption as employees can decide on the number of topics to be covered in a day. Employees can receive online training in the comfort of their homes, which eliminates traveling expenses and time lost while traveling. Online training allows employees to view the entire course list on the screen from where they can select any topic they want to learn. Based on their knowledge, they can skip through topics that they are already aware of and continue with the rest of the topics. This helps them to devote more time to topics that are difficult to understand.

Online training courses offer practical tips related to work issues, which employees can use for learning the practical use of Six Sigma concepts and techniques. Employees can give online tests after completing a topic for assessing their learning quotient. Test results are displayed at the click of a button, allowing employees the freedom to move on to the next topic or study the same topic again if results are unsatisfactory. Employees can take part in online discussions, which allows them to gain different perspectives towards a common problem. Online training is imparted through interactive sessions, which may include audio/video clips, multi-media slide shows, online simulations, quizzes, and tests.

Classification Of Online Training Courses

Online Six Sigma training courses can be broadly classified into four different categories; namely, courses for functional managers, for quality control managers, for senior management, and for business associates. Each training course is designed to meet the specific learning requirements of individuals who work in different positions within an organization. Online courses can also be classified based on the level of training, which may be for Six Sigma Green Belt, Six Sigma Black Belt, or Six Sigma Master Black Belt. Companies can choose any of these levels for its employees depending on organizational requirements.

Tony Jacowski is a quality analyst for The MBA Journal. Aveta Solutions - Six Sigma Online ( http://www.sixsigmaonline.org ) offers online six sigma training and certification classes for lean six sigma, black belts, green belts, and yellow belts.

1 Sigma Decisions in a Six Sigma World

Six Sigma has become the standard for product quality in our highly competitive world, but we are still wrestling with decision-making that is running at a less than one sigma success rate. Paul C. Nutt in his book, ?Why Decisions Fail? reports, ?For more than twenty years I have been studying how decisions are made, writing about what works, what doesn?t and why. The key finding is startling ? decisions fail half of the time.?

In this world of ?Continuous Improvement? it seems incomprehensible that we are still working with a decision-making process that results in a 50% success rate. Why worry about competition from off shore when decision-making with a 60%, 70% or even higher success rate would really give organizations a huge competitive advantage. The amount of time and money spent on bad decisions is incalculable and it boggles my mind to think about the cost of covering up bad decisions not to mention the blot a bad decision can be on a reputation or the personal friction it might cause.

Historically, most decision-making has been based on the ?rational model.? This involves: define the problem; state objectives; outline alternatives, estimate consequences; evaluate tradeoffs; recognize uncertainty; estimate risk tolerance; remove emotion and choose the best option. Somehow this whole process sounds negative to me. There is nothing positive about problems or estimating consequences. Evaluating tradeoffs signifies settling for something less than the optimum. Estimating risk tolerance doesn?t sound very positive either. Given that we are always faced with imperfect knowledge and the risk of unintended consequences in any decision, choosing the best option seems like a pretty risky proposition. My experience has proven to me that attitude is a huge determinant of success and if this process is negative by its very nature, it seems easy to understand why ?decisions fail half of the time.?

There is another school of thought that suggests when faced with a problem, it makes sense to create an hypothesis and then gather data to test the hypothesis. Unfortunately, this approach falls prey to some of the same problems with our traditional model. Problems equate to negatives. The symptoms of the problem may lead you to identify the wrong problem. Data gathered to support an hypothesis might provide the right decision but the wrong problem. Both the traditional and the hypothesis models are based on the ?how? of decision-making. The hypothesis approach appears to me to be an expeditious way to the same results. Since data shows that ?decisions fail half of the time,? it seems safe to say that reality is often more confused and messy than a neat model can allow for.

Peter Drucker once said, ?The best way to predict the future is to create it.? This truth also applies to decision-making. Decision-making is not a problem solving activity. It is an exercise in the construction of a preferred future. Traditional decision-making is grounded in the negative and in the past. The new way to make decisions is to establish a positive mind set, to fully appreciate the ?why? of decision-making and build from there. Since we move toward that which we define, what better way to make decisions than to utilize the Appreciative Inquiry process. Modified slightly as the Taking Aim approach, we ?marshal? our resources and think about the best of what is, our successes, the things we have done well and felt good about. This step sets up the positive attitude that is so critical to success. Next we get ?ready? by envisioning the perfect future or what might be. This desired future provides us with the answers to ?why.? ?Aim? is the next step where we actually design what should be and finally we ?Fire? or execute what will be. This is a much more positive approach and builds around the desired outcome rather than around the obstacles that may or may not exist. If in this process we can fully understand the why of what we are about to undertake, we can adapt to the vagaries along the way that can stifle a how based solution.

Appreciative inquiry is real and the supporting data is building. Paul Nutt in the book, ?Why Decisions Fail? points out that staying issue-centered is critical to good decision- making and AI is a process to stay issue-centered. Successful business users include Roadway, John Deere, Green Mountain Coffee and others.

We all agree that our customers deserve six sigma products. If our organizations are to survive; our customers to have an ongoing supply of our products; our owners are to earn a return on their investment and our associates are to have secure well paying jobs; don?t they deserve a better success rate on decisions than 50%. If that rate could be increased to 60% or 70% what kind of competitive advantage would you gain in your industry? Isn?t it time you thought about a new approach to decision-making?

Copyright Bob Cannon/The Cannon Advantage, 2003. All rights reserved.

 

Six Sigma And The Small Or Home Based Business

Although Six Sigma was originally devised as a quality improvement technique for the manufacturing industry, it is now increasingly being adopted by the services industry as well. The basic Six Sigma concepts and methodologies are more or less the same in the services sector where they are applied to both operational and non-operational processes.

Defining Six Sigma

Motorola was the first company to develop and implement Six Sigma concepts in its business processes. The main aim of the company was to reduce manufacturing defects and to achieve near perfect production processes that would help in production maximization. Six Sigma implementation projects aim at bringing the number of defects to not more than 3.4 per million opportunities that exist for such defects to occur.

This standard is applicable for both manufacturing industries as well as the services sector. Six Sigma implementations start with the assessment of current quality levels, which are termed as 1 sigma, 2 sigma, and so on. The aim is continuous quality improvements until Six Sigma quality levels are achieved.

Six Sigma In Small Businesses

Six Sigma can be effectively employed in small businesses irrespective of whether the business is a manufacturing unit or is servicing a customer base. Even in small businesses, Six Sigma aims at perfecting existing business processes and assessing the real costs of the business such as COPQ (Cost of Poor Quality). At first glance, it may seem that Six Sigma is suitable only for large businesses because of multimillion-dollar savings and huge reduction in the number of defects. However, this not mean that Six Sigma will not be cost-effective in small businesses as standard concepts and methodologies can always be tweaked to suit small scale process requirements and for reducing implementation costs at the same time.

Most small businesses compete with large and well-established businesses and this is why they always need to be on their toes in order to reduce costs and offer quality products and services to customers. Six Sigma helps because it provides a level playing field to small businesses, allowing them to concentrate on increasing the customer base by offering better quality products and services. For ensuring the success of Six Sigma initiatives, small business owners can hire the services of professional Six Sigma professionals such as Black Belts and Master Black Belts. They also have the option of training their existing employees.

The conclusion is that Six Sigma concepts and methodologies can be tailored to suit any business that has a ready customer base. It is also applicable in an online business where it is all the more important to have satisfied customers because news travels faster on the internet, especially when it is something to do with bad quality products or services. By employing Six Sigma, small businesses can ensure the quality of their products or services, which in turn will allow them to garner positive publicity through customer feedbacks and reviews. Such businesses are most likely to witness rapid growth because satisfied customers are the real assets of any business, whether big or small.

Tony Jacowski is a quality analyst for The MBA Journal. Aveta Solutions - Six Sigma Online ( http://www.sixsigmaonline.org ) offers online six sigma training and certification classes for lean six sigma, black belts, green belts, and yellow belts.

 

1 Sigma Decisions in a Six Sigma World

Six Sigma has become the standard for product quality in our highly competitive world, but we are still wrestling with decision-making that is running at a less than one sigma success rate. Paul C. Nutt in his book, ?Why Decisions Fail? reports, ?For more than twenty years I have been studying how decisions are made, writing about what works, what doesn?t and why. The key finding is startling ? decisions fail half of the time.?

In this world of ?Continuous Improvement? it seems incomprehensible that we are still working with a decision-making process that results in a 50% success rate. Why worry about competition from off shore when decision-making with a 60%, 70% or even higher success rate would really give organizations a huge competitive advantage. The amount of time and money spent on bad decisions is incalculable and it boggles my mind to think about the cost of covering up bad decisions not to mention the blot a bad decision can be on a reputation or the personal friction it might cause.

Historically, most decision-making has been based on the ?rational model.? This involves: define the problem; state objectives; outline alternatives, estimate consequences; evaluate tradeoffs; recognize uncertainty; estimate risk tolerance; remove emotion and choose the best option. Somehow this whole process sounds negative to me. There is nothing positive about problems or estimating consequences. Evaluating tradeoffs signifies settling for something less than the optimum. Estimating risk tolerance doesn?t sound very positive either. Given that we are always faced with imperfect knowledge and the risk of unintended consequences in any decision, choosing the best option seems like a pretty risky proposition. My experience has proven to me that attitude is a huge determinant of success and if this process is negative by its very nature, it seems easy to understand why ?decisions fail half of the time.?

There is another school of thought that suggests when faced with a problem, it makes sense to create an hypothesis and then gather data to test the hypothesis. Unfortunately, this approach falls prey to some of the same problems with our traditional model. Problems equate to negatives. The symptoms of the problem may lead you to identify the wrong problem. Data gathered to support an hypothesis might provide the right decision but the wrong problem. Both the traditional and the hypothesis models are based on the ?how? of decision-making. The hypothesis approach appears to me to be an expeditious way to the same results. Since data shows that ?decisions fail half of the time,? it seems safe to say that reality is often more confused and messy than a neat model can allow for.

Peter Drucker once said, ?The best way to predict the future is to create it.? This truth also applies to decision-making. Decision-making is not a problem solving activity. It is an exercise in the construction of a preferred future. Traditional decision-making is grounded in the negative and in the past. The new way to make decisions is to establish a positive mind set, to fully appreciate the ?why? of decision-making and build from there. Since we move toward that which we define, what better way to make decisions than to utilize the Appreciative Inquiry process. Modified slightly as the Taking Aim approach, we ?marshal? our resources and think about the best of what is, our successes, the things we have done well and felt good about. This step sets up the positive attitude that is so critical to success. Next we get ?ready? by envisioning the perfect future or what might be. This desired future provides us with the answers to ?why.? ?Aim? is the next step where we actually design what should be and finally we ?Fire? or execute what will be. This is a much more positive approach and builds around the desired outcome rather than around the obstacles that may or may not exist. If in this process we can fully understand the why of what we are about to undertake, we can adapt to the vagaries along the way that can stifle a how based solution.

Appreciative inquiry is real and the supporting data is building. Paul Nutt in the book, ?Why Decisions Fail? points out that staying issue-centered is critical to good decision- making and AI is a process to stay issue-centered. Successful business users include Roadway, John Deere, Green Mountain Coffee and others.

We all agree that our customers deserve six sigma products. If our organizations are to survive; our customers to have an ongoing supply of our products; our owners are to earn a return on their investment and our associates are to have secure well paying jobs; don?t they deserve a better success rate on decisions than 50%. If that rate could be increased to 60% or 70% what kind of competitive advantage would you gain in your industry? Isn?t it time you thought about a new approach to decision-making?

Copyright Bob Cannon/The Cannon Advantage, 2003. All rights reserved.

Bob Cannon helps visionary leaders improve performance and profitability. He is the author of the new book ?Taking Aim for Better Decision-Making?, available at http://www.cannonadvantage.com. Bob can be reached at (216) 408-9495 or mailto: bob@cannonadvantage.com

This article courtesy of http://www.cannonadvantage.com

Six Sigma and Its Benefits

Six Sigma is a business improvement methodology, originally developed by Motorola to systematically improve processes by eliminating defects. Defects are defined as units that are not members of the intended population. The objective of Six Sigma is to deliver high performance, reliability, and value to the end customer. Since it was originally developed, Six Sigma has enjoyed wide popularity as an important element of many Total Quality Management (TQM) initiatives.

Methodologies:
Six Sigma has two key methodologies: DMAIC and DMADV. DMAIC is used to improve an existing business process. DMADV is used to create new product designs or process designs in such a way that it results in a more predictable, mature and defect free performance.

DMAIC:
Basic methodology consists of the following five steps:

* Define the process improvement goals that are consistent with customer demands and enterprise strategy.

* Measure the current process and collect relevant data for future comparison.

* Analyze to verify relationship and causality of factors. Determine what the relationship is, and attempt to ensure that all factors have been considered.

* Improve or optimize the process based upon the analysis using techniques like Design of Experiments.

* Control to ensure that any variances are corrected before they result in defects. Set up pilot runs to establish process capability, transition to production and thereafter continuously measure the process and institute control mechanisms.

DMADV:
Basic methodology consists of the following five steps:

* Define the goals of the design activity that are consistent with customer demands and enterprise strategy.

* Measure and identify CTQs (critical to qualities), product capabilities, production process capability, and risk assessments.

* Analyze to develop and design alternatives, create high-level design and evaluate design capability to select the best design.

* Design details, optimize the design, and plan for design verification. This phase may require simulations.

* Verify the design, set up pilot runs, implement production process and handover to process owners.

Benefits of Six Sigma:
Those organisations that implement Six Sigma correctly achieve significant benefits that contribute to competitive advantage and to changing the culture in an organisation from reactive problem solving to proactive problem prevention. Specifically the proven benefits include:

Benefits For the organization:

* Bottom line cost savings (5%-20% of turnover per annum)
* Improved quality of product or service as perceived by the customer (internal and external customers)
* Reduction in process cycle times
* Development of staff skills
* Common language throughout the organization
* World class standard

Benefits For the individual:
* Improved knowledge and skills
* Ability to use a wide range of tools and techniques
* A status that is recognised world wide

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Six Sigma In The Insurance Industry

6 Sigma concepts and philosophies were originally developed for improving the overall quality of business processes in the manufacturing sector. Companies like Motorola and GE were among the first few that successfully introduced Six Sigma concepts in their business processes. However, with the development of newer tools and techniques, 6 Sigma is now deemed appropriate for the services sector as well. The usability of Six Sigma in the services sector is easily evident from the increasing number of finance and insurance companies that are opting for 6 Sigma.

Consumers are increasingly becoming aware of the quality of services being offered to them, making it essential for the services industry to implement quality improvement techniques like Six Sigma for conforming to customer expectations. This is especially true for the insurance industry where the relationship between the insurer and the insured is still largely governed by sustained personal contact. By implementing 6 Sigma programs, insurance companies have been able to offer quality services at affordable rates to their customers.

Identifies Key Business Processes

Unlike other quality management practices such as Total Quality Management (TQM) whose effectiveness is difficult to measure, Six Sigma based improvement programs make use of statistical tools, which can measure the effect of changes being made in a very short time. 6 Sigma focuses on process orientation, enabling organizations to identify key business processes that are necessary for improving customer satisfaction. This helps managers in understanding the exact requirements of their customers and in altering business processes to suit customer needs and expectation.

Follows A Disciplined Approach

Six Sigma has helped insurance companies in improving quality as well as reducing costs of services offered. It has enabled insurance companies to follow a disciplined approach, which has helped in preventing errors, minimizing hand-offs, and eliminating rework and workarounds. It has also helped in increasing the speed of business processes used in the insurance industry.

Helps In Making Informed Decisions

6 Sigma has enabled managers in taking informed decisions based on statistical data. With the use of Six Sigma tools and techniques, managers no longer have to rely on their perceptions or gut feelings for rendering the level of services promised to policyholders, clients, and prospects.

Helps In Building Customer Loyalty

6 Sigma emphasizes on understanding the needs of the customers before making any changes to business processes. This helps insurance companies in building customer loyalty among their policyholders, which is necessary for the long-term success of any business organization. Insurance companies can also hope to increase their market share, as satisfied customers are most likely to recommend a company that offers quality services while advising a friend, relative or business associate. Helps In Reducing Costs

Six Sigma tools and techniques aim at streamlining business processes in such a way that helps in reducing costs. This helps insurance companies to improve their savings and avoid drastic cost-saving measures such as downsizing, which can have a negative effect on employee morale. It can also create doubts in the mind of policyholders and prospects as downsizing usually attracts a lot of negative publicity.

6 Sigma has helped the insurance industry in bridging the gap between planned strategies and actual operations by providing analytical and in-process performance measurement tools. These tools are used for comparing planned goals and objectives with actual outcomes and for finding the reasons as to why a particular business process is not giving the desired results. Once the exact problem has been pinpointed, managers can make the necessary changes that will help in improving overall quality of services rendered to policyholders and prospects.

Tony Jacowski is a quality analyst for The MBA Journal. Aveta Solution's Six Sigma Online offers online six sigma training and certification classes for lean six sigma, black belts, green belts, and yellow belts.

The Road to Six Sigma: Cause-Effect and Scatter Diagrams

Part 2 of a 4 part series

Last week we talked about using Pareto analysis for organizing, simplifying, and prioritizing problem solving. This week, we're going to introduce two simple tools which can be used together to improve the performance of business systems. In improving any process, there are problems to be overcome. Most of these problems come to our attention due to their symptoms and effects. In order to solve these problems, we must find the root cause of each problem and eliminate that cause.

One of the most useful tools in problem solving is the Cause-Effect Diagram. Cause-effect diagrams were invented in Japan in 1943 by Kaoru Ishikawa as an aid to explaining how various factors in a complex process can be sorted out and related. Cause-effect diagrams are often referred to as fishbone diagrams because of their shape or Ishikawa diagrams after their inventor.

Cause-effect diagrams are extremely useful for organizing input from a brainstorming session. Brainstorming, to be effective, should be freewheeling and without judgments. Data is developed without regard to order, relationships or relevance. Once the data is captured, however, we need to sort it out and show the various relationships. Let's use as a simple example:

<p align="center"><img src="http://www.bizmanualz.com/articles/images/cause_effect.jpg" width="387" height="44" />

Now let's say that all the people affected by this situation have been gathered for a brainstorming session and have produced the following possible causes for variations in temperature:

• Heating plant
• Controls
• Insulation
• Dimensions of room
• Outside temperature
• Supply of energy
• Design of room (windows, doors, etc.)
• Person adjusting the controls

Note that the discomfort could have been caused by variations in humidity, noise, lighting or other factors, but in this case, it is a simple problem of incorrect and/or varying temperature. Because this is true, we can focus our efforts only on the possible causes of temperature variation. To help organize the information, we will group our data into four categories; People, Equipment, Process, and Environment.

<div style="float:left;margin-right:5px;"> <div align="center"><img src="http://www.bizmanualz.com/articles/images/cause_effect2-small.jpg" width="175" height="110" border="0" />
Cause-Effect Fig. 1</div> </div>

This is shown in the first cause-effect diagram (<strong>Cause-Effect Fig. 1</strong>).

We could have labeled our categories anything, but we used labels that work for the situation. Sometimes more than four groups are identified. No problem!

<div style="float:right;margin-left:5px;"> <div align="center"><img src="http://www.bizmanualz.com/articles/images/cause_effect3-small.jpg" width="175" height="108" border="0" />
Cause-Effect Fig. 2</div> </div> Now let's see where our possible causes can be logically placed (Cause-Effect Fig. 2).

Once we have arranged the data in this fashion, we can investigate each factor and determine if it is in control. In our example, the problem is that the occupants of the room are cold. We know the problem is not due to environmental factors because the design of the room has not changed, and the outside temperature is warmer than it was yesterday, when we were comfortable.

The person who adjusts the controls says that he has set the temperature at 80F, but the room is still cold.

Therefore, the problem must have something to do with the equipment. A careful examination reveals that the heating plant and controls are in good shape, but the gauge on the fuel oil tank registers zero. A call to the fuel oil distributor brings his truck in short order and soon we are achieving our <strong>desired output</strong>, comfortable occupants. (Sure -- They are comfortable! They don't have to pay for the heating oil.)

Now this is an absurdly simple example, but suppose our analysis of the cause-effect diagram did not reveal the <strong>root cause</strong>. Usually this means that we have not been sufficiently thorough in our analysis. We began with the premise that temperature was the source of the discomfort. But if that were not the case, we could easily miss important factors in the analysis. This points out the need for careful <strong>problem definition</strong>.

It also happens that the analysis reveals several possible causes, and it is not clear if there is one or more of these causes that need to be addresses in order to solve the problem. This brings us to our second handy tool, the <strong>scatter diagram</strong>.

<div style="float:right; margin:0px 0px 5px 5px;"> <div align="center"><img src="http://www.bizmanualz.com/articles/images/scatter-pos_small.jpg" width="175" height="106" border="0" />
<strong>Fig. 3: Example
Scatter Diagram</strong></div> </div>

Scatter diagrams, like the ones shown on<strong> Fig. 3</strong>, are a special type of cause-effect diagram developed from historical or experimental data. Scatter diagrams, will reveal the relationship, if any, between variations in one variable and variations in another.

Scatter diagrams do not identify which variable is the cause of changes in the other variable. Sometimes, both variables are changing as a result of changes in a third, unidentified variable. Therefore it is usually best to develop and analyze the cause-effect diagram first. We know from our simple example that changes in occupant comfort do not cause changes in room temperature, (at least not until someone adjusts the controls).

As an example, let's say that we are investigating why particulate emissions are high and varying in a random fashion. From a cause-effect analysis we have identified variable fan speed as a possible cause. Fortunately, we have daily data from the last fifty days on both indicated fan speed and lab sample particulate counts from the filter exhaust. The data and resulting scatter diagram show the situation more clearly.

<div style="float:left;margin:0px 5px 5px 0px;"> <div align="center"><img src="http://www.bizmanualz.com/articles/images/scatter1-small.jpg" border="0"/>
<strong>Fig. 4 </strong></div> </div>

What can we say about fan speed as a possible cause for variability in particulate levels? From the scatter diagram <strong>(Fig. 4)</strong>, it is unclear what the precise nature of this relationship is. It appears as a general rule that as fan speed rises, particulate counts rise. Because of the dispersion of the data, however, fan speed is probably not the only cause of this problem. We should keep looking.

So far we have discussed setting priorities for process improvement and looked at ways of finding and quantifying cause. Once we have our process in control, we need a tool for keeping the process in control and assessing opportunities to improve its performance. That's for next week when we will discuss <strong>control charts</strong>.

Learn more about developing policies, procedures and processes, or about improving your organization by attending the next Implementing Lean Thinking, How to Create Well Defined Procedures and Processes or Statistical Process Control classes. TO address other training needs, please visit the Bizmanualz Training Website.
Chris Anderson is the founder and CEO of Bizmanualz, Inc. Since 1995, Bizmanualz has specialized in empowering organizations to continuously improve compliance, control and customer satisfaction using effective and well-defined management

Statistical Software in Six Sigma

Six Sigma is about numbers. Six Sigma produces a flood of data about your process that are critical to your success. If you don't measure it and understand what you are measuring, you can't manage it. Six Sigma's clear strength is a data-driven analysis and decision-making process -- not someone's opinion or gut feeling.

The value of statistical analysis cannot be underestimated. Through an analysis of all of that data, you begin to understand your process and develop methodologies to identify and implement the right solutions to improve your process. Statistical evaluation of the data identifies key areas which can have an adverse effect on product quality if not controlled. Once you have identified these key areas you can focus your process improvement efforts

Given the importance of intelligently handling all of this data, you need to find an efficient and powerful method of crunching the numbers. Naturally, you want to avoid the drudgery of manual calculations and save a whole lot of time by using a statistical software application. You may be tempted to use Excel or another spreadsheet application as a calculator and database to store your statistical process control data. However, you will quickly find out that a basic spreadsheet is too cumbersome to handle the volume and sophistication of the data keeping and analysis you need to perform in a Six Sigma project.

Advanced statistical software such as Minitab (http://www.minitab.com/) or Statgraphics (http://statgraphics.com), are very useful if not essential for gathering, categorizing, evaluating, and analyzing the data collected throughout a Six Sigma project. Both Minitab and Statgraphics are powerful full standalone statistical process control software applications for performing statistical analysis. Both are highly recommended for Six Sigma use as they are tools that can help you utilize one of Six Sigma's biggest advantages: the ability to make better decisions based upon data. They will work with the DMAIC Define-Measure-Analyze-Improve-Control methodology and Lean Six Sigma.

Both Minitab and Statgraphics are designed to support the Six Sigma philosophy offering a range of tools for graphical analyses, collecting powerful statistics, quality analyses with potential for a range of custom designed uses.

• Statistical Process Control Charts
  
• Analysis of Variance and Regression Analysis
  
• Design of Experiments
  
• Factorial and Matrix Plots
  
• Relationships between variables
  
• Life Data Analysis and Reliability
  
• Process Capability Analysis
  
• Hypothesis Testing
  
• Correlation and regression
  
• Time Series Analysis and Forecasting
  
• Measurement Systems Analysis
  
• Regression Analysis
  
• Multi-variation analysis
  
• ANOVA tools and techniques
  
• Six Sigma Quality Assessment

Both applications provide you with nearly real time statistical data, enabling you to respond quickly to prevent further defects. Statistical evaluation of the data identifies key areas to focus process improvement efforts on, which can have an adverse effect on product quality if not controlled.

However, while it is easy to purchase a statistical software application, it is harder to use it effectively. It is <EM>smart </EM>analysis of the data that create real change. All too often, Six Sigma/DMAIC teams collect and load data into Minitab or Statgraphics only to find themselves overwhelmed by the prospect of where to start and how to use their new tool to successfully analyze their data that comes up with, not just any answers, but meaningful and useful answers. As a result, Six Sigma/DMAIC projects often fall far short of the productivity expectations associated with statistical software.

Training in use of Minitab is often offered integrated with Six Sigma training. Minitab training will focus on solving practical problems with Minitab. This includes learning the practical aspects of major statistical tools like Control Charts, Capability Analysis, Regression Analysis, and ANOVA. There is a strong emphasis on learning how to get data into Minitab, learning how to manipulate data once in Minitab and learning how to display graphically major findings from the data. Proper training will teach you how to drive Minitab like a pro and thus bring greater statistical power to your Six Sigma projects.

Peter Peterka is President of Six Sigma us. For additional information on Six Sigma Master Black Belt or Minitab Training programs contact Peter Peterka

Six Sigma Employee Assessment

A typical business environment would like all processes to be assessed for improvement possibilities. The competitive business world demands that all business processes be at their peak performance levels at all times to meet challenges. These challenges, as defined by the ‘Voice of Customer’ and the projections of ROI, are not fixed but moving targets.

For business success, organizations have to realize the contribution of employee assessment. Employee assessment results in measurable metrics called ‘Employee Ratings’. Business organizations embarking upon an employee rating exercise, use internal and cross organizational surveys which assess ‘as is’ conditions with regard to perceptions of employees about their work environment.

The survey may be divided into two parts; one preliminary and the other comprehensive. A representative sample of employees may be taken into confidence for conducting what can be called a preliminary interview. The interview has to be invariably conducted in a formal environment for the feedback to be as real as possible. The purpose of this employee assessment exercise is to find out the present situation so that the metrics can be compared with the goal, point by point.

Preliminary Assessment Guidelines

Some researchers have identified 15 such aspects that affect organizations’ working environments. Employees may be interviewed for, for example on:

• Whether Six Sigma implementation reduced their workload
• Whether Six Sigma implementation improved their work climate
• Whether Six Sigma implementation helped reduce process time in their perception
• Whether Six Sigma implementation helped eliminate process variation
• Has it come to their notice that reduced defects reduced wasteful reworking
• Whether Six Sigma improved the position of the organization, in their view

The findings of the preliminary survey may be representative sample feedback and further assessment is strongly advised. The feedback may reveal two different things. The obvious one being the assessment of employees and the other important one is employee perception of the project itself. Although the latter is only relative, it serves as a wakeup call.

Before embarking on a comprehensive survey, the feedback from the initial survey must be analyzed in view of theoretically expected results, which were set at the time of project implementation. All possible deviations must be scrutinized with a view toward concluding whether there has been positive impact on employee performance. The analytical results lead the way for the final, comprehensive employee survey.

A Brief On The Comprehensive Employee Survey

For conducting the final survey, the team must consist of at least a couple of Master Black Belts, one from the HR department and the other being from another respective department for obvious reasons.

Having equipped itself with the preliminary feedback, the survey team need not take indirect paths to extract results. Further, the survey must include all employees, obviously for individual assessment, unlike the preliminary interview. The feedback is recorded on spreadsheets and charts are drawn.

Employee assessment is not necessarily for downsizing staff, as is the common misconception. For the future success of Six Sigma, the team must approach the assessment without being biased.

Tony Jacowski is a quality analyst for The MBA Journal. Aveta Solutions – Six Sigma Online ( http://www.sixsigmaonline.org ) offers online six sigma training and certification classes for lean six sigma, black belts, green belts, and yellow belts.