Programs

Green Belt - Commercial

Program Description

The Green Belt role is usually part-time in nature, although some organizations might choose to make it a full-time position. By design, the role of a Green Belt is played out at the process level of a business enterprise and is focused on making improvements within the scope and reach of Green Belts normal work-related line-of-sight. Such localized improvements are generally made by a Green Belt in one of two ways. First, the Green Belt can support a Black Belt project, to effectively extend the scope and reach of a Black Belt. This could involve facilitating the execution of routine activities such as data collection and basic diagnostics in addition to executing small-scale experiments and implementing process controls. Second, a Green Belt can be assigned a highly focused improvement project that has been pre-selected and operationally scaled to fit their unique skill-set and normal job duties.

This program provides the training to use the powerful Six Sigma process for realizing breakthrough - Define, Measure, Analyze, Improve, and Control, or simply DMAIC. Participants learn fundamental problem solving, the most commonly used Six Sigma tools and techniques, and how to best apply the supporting tools of Six Sigma. Candidates will be exposed to specific tools for the commercial environment such as Survey Methods, and how to apply the tools of Six Sigma for short-cycle, high-yield improvements.

By nature, the difference between an Industrial and Commercial Green Belt lies in the type of data they are likely to encounter, thus altering the array of tools and analytical approaches. For example, the commercially oriented Green Belt will often work with discrete data and frequencies that naturally emanates from such things as customer satisfaction surveys, transactional defect counts, and binary outcomes, just to mention a few. Participants will also work a Training Project that will allow them to exercise all the tools taught during training as well as understand the methodology and steps needed to carry out an on-site organizational project.

Successful Commercial Green Belt candidates will be able to increase their job-related or product-related output quality and quantity in less time and at a lower total cost, thereby creating additional value. Naturally, this translates to greater effectiveness and efficiency of job execution and the realization of business imperatives, regardless of the organization’s type or size. Total instructional time for this program is approximately 80 hours.


      Downloadable Program Syllabus

Training Project

Project Introduction - Understand the steps to deploy a Training Project

Recognize Phase - Understand the tools used during the Recognize Phase

Define Phase - Execute the steps needed during the Define Phase

Measure Phase - Understand the tools needed during the Measure Phase

Analyze Phase - Become familiar with the tools used during the Analyze Phase

Control Phase - Recognize the usage of tools needed for Process Control

Survey Analysis - Execute the techniques to analyze Survey data

Training Orientation

Excel Orientation - Explore the Excel software package

Minitab Orientation - Explore the Minitab software package

Simulator Orientation - Explore the Process Simulator

Breakthrough Vision

Content Overview - Understand the nature, purpose, and drivers of Six Sigma

Driving Need - Identify the needs that underlie a Six Sigma initiative

Customer Focus - Explain why focusing on the customer is essential to business success

Core Beliefs - Contrast the core beliefs of Six Sigma to conventional practices

Deterministic Reasoning - Describe a basic cause-and-effect relationship in terms of Y=f(X)

Leverage Principle - Relate the principle of leverage to an improvement project

Tool Selection - Identify the primary family of analytical tools used in Six Sigma work

Performance Breakthrough - Describe the underlying logic of the DMAIC improvement process

Business Principles

Quality Definition - Articulate the idea of quality in terms of value entitlement

Underpinning Economics - Describe the relationship between quality and cost

Process Management

Performance Yield - Explain why final yield is often higher than first-time yield

Hidden Processes - Describe the non-value added component of a process

Measurement Power - Describe the role of measurement in an improvement initiative

Establishing Baselines - Explain why performance baselines are essential to realizing improvement

Performance Benchmarks - Explain how a benchmarking chart can be used to assess quality performance

Defect Opportunity - Understand the nature of a defect opportunity and its role in metrics reporting

Process Models - Define the key features of a Six Sigma performance model

Process Capability - Identify the primary indices of process capability

Design Complexity - Describe the impact of complexity on product and service quality

Installation Guidelines

Champion Role - Define the operational role of a Six Sigma Champion and highlight key attributes

Black Belt Role - Define the operational role of a Six Sigma Black Belt and highlight key attributes

Green Belt Role - Define the operational role of a Six Sigma Green Belt and highlight key attributes

White Belt Role - Define the operational role of a Six Sigma White Belt and highlight key attributes

Application Projects - Describe the purpose of Six Sigma Application Projects and how such projects are executed

Application Projects

Project Description - Understand how to fully define a Six Sigma application project

Project Overview - Provide an overview of the key elements that characterizes an application project

Project Guidelines - Explain how to establish project selection guidelines

Project Scope - Explain how to properly scope an application project

Project Leadership - Recognize the actions that must occur to ensure successful project leadership

Project Teams - Form a project team that is capable of supporting Six Sigma applications

Project Financials - Understand the role of project financials in supporting deployment success

Project Management - Explain how application projects are best managed to achieve maximum results

Project Payback - Understand the driving need for establishing project paybacks

Project Milestones - Identify the primary milestones associated with a successful Six Sigma deployment

Project Charters - Understand the role of project charters and how they are used to guide implementation

Value Focus

Recognize Needs - Recognize the power of need fulfillment and how it links to value creation

Define Opportunities - Understand how to define opportunities that lead to the creation of value

Measure Conditions - Identify and evaluate the conditions that underlies improvement opportunity

Analyze Forces - Explain how the underlying forces are identified and leveraged to create beneficial change

Improve Settings - Establish optimal settings for each of the key forces that underpins beneficial change

Control Variations - Discuss how unwanted variations can mask the pathway to breakthrough

Standardize Factors - Understand the role and importance of standardized success factors

Integrate Lessons - Explain how key lessons learned can be merged into a set of best practices

Application Example - Understand how the breakthrough process can be applied to everyday life

Lean Practices

Lean Thinking - Comprehend the underlying logic of lean thinking

PokaYoke System - Understand how PokaYoke systems can lead to quality improvement

6S System - Explain how the 6S system can contribute to process efficiency

7W Approach - Describe how the 7W approach can be used to solve problems

6M Approach - Explain how the 6M approach is used to identify sources of causation

Quality Tools

Variable Classifications - Define the various types of variables commonly encountered during quality improvement

Measurement Scales - Describe each of the four primary scales of measure and their relative power

Problem Definition - Characterize the nature of a sound problem statement

Focused Brainstorming - Explain how focused brainstorming is used to facilitate improvement efforts

Process Mapping - Understand how to define the flow of a process and map its operations

SIPOC Diagram - Describe the nature and purpose of an SIPOC diagram

Force-Field Analysis - Utilize force field analysis to solve problems

Matrix Analysis - Understand how matrices are created and used to facilitate problem solving

C&E Analysis - Explain how C&E matrices can be used to solve quality problems

Performance Sampling - Explain how to design and implement a sampling plan

Check Sheets - Understand how check sheets can be used for purposes of data collection

Analytical Charts - Identify the general range of analytical charts that can be used to assess performance

Pareto Charts - Explain how Pareto charts can be used to isolate improvement leverage

Run Charts - Utilize run charts to assess and characterize time-based process data

Multi-Vari Charts - Define the major families of variation and how they can be graphed

Correlation Charts - Utilize a correlation chart to illustrate the association between two variables

Frequency Tables - Explain how to construct and interpret a frequency table

Performance Histograms - Construct and interpret a histogram and describe several purposes

Basic Probability - Understand basic probability theory and how it relates to process improvement

Control Charts - Explain the purpose of statistical process control charts and the logic of their operation

Concept Integration - Understand how to sequence a given selection of quality tools to better solve problems

Basic Statistics

Performance Variables - Identify and describe the types of variables typically encountered in field work

Statistical Notation - Recognize and interpret the conventional forms of statistical notation

Performance Variation - Explain the basic nature of variation and how it can adversely impact quality

Normal Distribution - Describe the features and properties that are characteristic of a normal distribution

Distribution Analysis - Explain how to test the assumption that a set of data is normally distributed

Location Indices - Identify, compute, and interpret the mean, median, and mode

Dispersion Indices - Identify, compute, and interpret the range, variance, and standard deviation

Deviation Freedom - Explain the concept of degrees-of-freedom and how it is used in statistical work

Standard Transform - Describe how to transform a set of raw data into standard normal deviates

Standard Z-Probability - Describe how to convert a standard normal deviate into its corresponding probability

Central Limit - Understand that the distribution of sampling averages follows a normal distribution

Standard Error - Recognize that the dispersion of sampling averages is described by the standard error

Student's Distribution - Understand that the T distribution applies when sampling is less than infinite

Standard T-Probability - Describe how to convert a T value into its corresponding probability

Statistics Simulation - Employ basic statistics to analyze data generated by the process simulator

Continuous Capability

Performance Specifications - Explain the basic nature and purpose of performance specification limits

Cp Index - Compute and interpret Cp

Cpk Index - Compute and interpret Cpk

Pp Index - Compute and interpret Pp

Ppk Index - Compute and interpret Ppk

Discrete Capability

Defect Metrics - Identify and describe the defect metrics commonly used in Six Sigma work

Defect Opportunities - Understand the nature and purpose of defect opportunities in terms of quality reporting

Binomial Distribution - Describe the features and properties that are characteristic of a binomial distribution

Poisson Distribution - Describe the features and properties that are characteristic of the Poisson distribution

Throughput Yield - Compute and interpret throughput yield in the context of Six Sigma work

Rolled Yield - Compute and interpret rolled-throughput yield in the context of Six Sigma work

Hypothesis Testing

Statistical Inferences - Explain the concept of a statistical inference and its primary benefits

Statistical Questions - Explain the nature and purpose of a statistical question

Statistical Problems - Understand why practical problems must be translated into statistical problems

Null Hypotheses - Define the nature and role of null hypotheses when making process improvements

Alternate Hypotheses - Define the nature and role of alternate hypotheses when making process improvements

Statistical Significance - Explain the concept of statistical significance versus practical significance

Alpha Risk - Explain the concept of alpha risk in terms of the alternate hypothesis

Confidence Intervals

Mean Distribution - Comprehend and characterize the distribution of sampling averages

Mean Interval - Compute and interpret the confidence interval of a mean

Variance Distribution - Comprehend and characterize the distribution of sampling variances

Variance Interval - Compute and interpret the confidence interval of a variance

Proportion Distribution - Comprehend and characterize the distribution of sampling proportions

Proportion Interval - Compute and interpret the confidence interval of a proportion

Control Methods

Statistical Control - Explain the meaning of statistical control in terms of random variation

Control Logic - Explain the logic that underpins the application of a control chart

Control Limits - Reconcile the difference between specification limits and control limits

Chart Selection - Explain how to rationally select a control chart

Chart Interpretation - Interpret an SPC chart in terms of its control limits

Variables Chart - Characterize the role and purpose of a variables chart

Attribute Chart - Characterize the role and purpose of an attribute chart

Individuals Chart - Construct and interpret an individuals control chart

Proportion Chart - Construct and interpret a control chart for sampling proportions

Defect Chart - Construct and interpret a control chart for defect occurrences

Parametric Methods

Mean Differences - Determine if two means are statistically different from each other

Variance Differences - Determine if two variances are statistically different from each other

Chi-Square Methods

Statistical Definition - Describe how to translate a practical problem into a statistical problem

Model Fitting - Explain what is meant by the term "Model Fitting" and discuss its practical role in Six Sigma work

Testing Independence - Explain how a test of independence can be related to the idea of correlation

Contingency Coefficients - Understand how a contingency coefficient relates to a cross-tabulation table

Yates Correction - Describe the role of Yates correction in terms of the chi-square statistic

Testing Proportions - Test the significance of two proportions using the Chi-square statistic

Survey Methods

Research Design - Explain how the idea of research design fit with the idea of problem Solving

Information Sources - Explain how the idea of research design fit with the idea of problem Solving

Questionnaire Construction - Describe the role of survey demographics when analyzing closed-form survey data

Formulating Questions - Identify several things that should be avoided when developing survey questions

Question Quality - Explain what is meant by the term "question quality" and how this idea relates to data analysis

Sampling Plans - Describe several different types of sampling plans commonly used in survey research

Data Analysis - Explain how categorical survey data can be analyzed to establish strength of association

Nonparametric Methods

Nonparametric Concepts - Explain the difference between parametric and nonparametric methods

Median Test - Execute a median test on two groups and then determine if the difference is statistically significant

Runs Test - Conduct a runs test to determine if a time series pattern is random