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Lean Six Sigma Green Belt
- Description
- Objective
- Outline
| CERTIFICATE | Lean Six Sigma Yellow Belt |
| DURATION | 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.
Prerequisites
- Together with the content of the 2 day Lean Six Sigma Yellow Belt module, the main focus of the full five days is on the application of Lean Six Sigma DMAIC methods to real life improvement projects within the delegate's own organization. While the Yellow Belt training is intended to provide an overview of the methodology sufficient to participate as Project Contributors, Green Belts are required to lead at least one project, as part of the certification requirements.
- Support will be provided during the course to help delegates identify a suitable Lean Six Sigma project, however delegates are invited to discuss internally (with a potential Project Champion) and assess in advance project opportunities.
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 problems)
Target Audience
Senior Managers (with more than 4 years of Program management and 4 years of Project Management experience) - seeking to obtain the PgMP® Certification.
These Managers typically manage Programs containing complex activities spanning functions, organizations, clients and geographic regions. As a part of their Program Management, they would also typically possess advanced skills in finance, leadership, cross-cultural communications, negotiations and conflict resolutions
Course Outline
Introduction
- 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)
Measure
- 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
Analyze
- 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, Chi
- Square)
- 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
