Green Belt

Six Sigma Green Belt Workshop

  • Free Six Sigma Green Belt practice test paper
  • Access to online study material
  CERTIFICATE Six Sigma Green Belt
  DURATION 2 or 3 Days
  COURSE DELIVERY Classroom, Live Virtual Classroom
  LANGUAGE English

Course Description

The notion of ‘project’ is central to the whole Lean Six Sigma approach. Unlike other quality and improvement models providing essentially a catalogue of best practices, Lean Six Sigma is a pragmatic approach that emphasizes the importance of the Business Case for INVESTING in quality and process improvement.
A true Return On INVESTMENT can only be demonstrated through successful projects, aiming at reducing the cost of poor quality, increasing process capability, minimizing process cycle time, removing waste and ultimately resulting in increased customer satisfaction.

Lean Six Sigma Green Bely provides the Project Management skills necessary to successfully complete DMAIC projects, including basic knowledge of planning and estimation techniques, Business Case development, team problem solving methods and improvement strategies.

The training combines lectures with interactive group exercises and hands-on work on examples related to the services industry.

There are no prerequisites for this course except a willingness to participate and an open mind.

Course Outline


  •  Objectives of the training and reminder of the DMAIC cycle Define
  •  Problem Definition
  •  Voice of the Customer and Voice of the Process
  •  Lean Six Sigma Project Management
  •  Project Selection
  •  Project roles and responsibilities
  •  Lean Six Sigma and Project Management
  •  notes on Integration
  •  Lean Six Sigma Business Case
  •  Overview of Probabilistic approaches (Planning and Business Case)

The Define Phase

  •  The Business Case
  •  Project financial indicators (ROI, NPV)
  •  The Business Case
  •  Probabilistic Models (Crystal Ball exercises)
  •  Probability
  •  introduction
  •  Probability models (and their use for process improvement and design)


  •  Measurement Information Model
  •  Selecting the right metrics
  •  Sampling
  •  basic concepts
  •  Yield and Defects
  •  Process capability measures
  •  Developing a Process Baseline
  •  The Measure phase
  •  Reminder (measurement framework and metrics identification)
  •  Descriptive statistics
  •  MINITAB Exercises (Creating a process baseline)
  •  graphical tools
  •  Z transformation


  •  Process Value analysis
  •  Value stream mapping
  •  Root Cause Analysis
  •  process decomposition
  •  Cause and Effect Matrices
  •  Exploratory Data Analysis (EDA)
  •  Inferential Statistics for Root Cause Analysis (overview)

The Analyze Phase

    •  Root Cause Analysis (reminder)
    •  Estimation (point estimation and confidence intervals)
    •  The Central Limit Theorem (CLT)
    •  Hypothesis Testing
    •  Introduction
    •  Hypothesis Testing Examples and MINITAB Exercises


  •  Hypothesis Testing on Continuous Normal Data (Z and T tests, tests for variances..)
  •  ANOVA
  •  Analysis of Variance
  •  Non Parametric Tests
  •  Tests for discrete variables (proportions, ChiSquare)
  •  Correlation Analysis and Correlation indexes (Pearson, Spearman)
  •  Regression Analysis overview and exercises
  •  Measurement System Analysis (MSA / Gage R&R)

Improve Phase

  •  Generating Solution Ideas
  •  Brainstorming (Six Thinking Hats)
  •  Process Improvement strategies
  •  Lean Principles
  •  Selecting Solutions
  •  Risk Management
  •  Pilot Projects
  •  Improvement qualification (quantifying improvements)

The Improve Phase

  •  Reminder
  •  Improvement Qualification
  •  Change Management in the Improve phase
  •  The role of Green Belts

Control Phase

  •  Sustaining improvement
  •  Statistical Process Control (SPC)
  •  Control charts
  •  Statistical Process Control
  •  SPC applicability and interpretation
  •  Conclusions and Next Steps

Course Objective

  •  Problem solving and process improvement methods (Integrate knowledge gained with the LSSYB)
  •  Plan and manage a real Lean Six Sigma DMAIC project
  •  Identify the elements of Cost of Poor quality and waste in a process and develop a realistic Business Case for their projects
  •  Understand basic concepts of Project Risk Management (including probabilistic approaches)
  •  Structure a measurement system and identify the appropriate metrics to support quantitative process improvement efforts
  •  Root cause analysis and value analysis methods
  •  Process Improvement strategies
  •  Communicate with key stakeholders and drive change in the organization
  •  Quantitative methods for process improvement
  •  Application of statistical tools to support root Cause Analysis
  •  Descriptive and Inferential Statistics techniques
  •  Data Analysis (graphical and formal)
  •  DMAIC Projects
  •  Financial Indicators
  •  Basics of Probability theory (and practical applications to estimation

Please contact us to know more about the exam.