Lean Six Sigma Green Belt Training Course

Lesson 1 • History and Evolution of Lean Six Sigma

Traces Lean roots in Toyota Production System and Six Sigma origins at Motorola. Provides context for why the methodologies merged into a unified improvement system.

Lesson 2 • Core Philosophies and Principles

Defines waste elimination, variation reduction, and customer focus as the three pillars. Connects each principle to measurable business outcomes.

Lesson 3 • DMAIC Framework Overview

Introduces the five-phase Define-Measure-Analyze-Improve-Control roadmap as the Green Belt's primary problem-solving structure. Each phase is mapped to deliverables.

Lesson 4 • Business Case and Project Charter

Teaches how to quantify improvement opportunities and document them in a project charter. A strong charter aligns stakeholders before work begins.

Lesson 1 • Define Phase Gate Review

Consolidates charter, VOC, CTQs, and SIPOC into a phase-gate presentation for sponsor approval. Teaches criteria for a passing Define review.

Lesson 2 • Stakeholder Analysis and Communication

Identifies stakeholders by influence and interest, then builds a targeted communication plan. Early alignment reduces resistance during later phases.

Lesson 3 • Voice of the Customer Techniques

Covers surveys, interviews, focus groups, and complaint analysis to capture customer requirements. Outputs feed directly into Critical-to-Quality trees.

Lesson 4 • Critical-to-Quality Trees

Converts broad customer needs into specific, measurable CTQ characteristics. CTQs become the performance targets for the entire project.

Lesson 1 • Descriptive Statistics and Distributions

Covers mean, median, mode, variance, and standard deviation as tools for summarising process data. Graphical displays reveal patterns invisible in raw numbers.

Lesson 2 • Comparing Means and Variances

Applies t-tests, ANOVA, and F-tests to determine whether group differences are statistically significant. Results guide root-cause prioritisation in the Analyse phase.

Lesson 3 • Probability Concepts for Green Belts

Introduces probability rules, the Central Limit Theorem, and confidence intervals at a practical level. These concepts underpin every inferential test used in DMAIC.

Lesson 4 • Non-Parametric and Proportion Tests

Covers chi-square, Mann-Whitney, and proportion tests for non-normal or attribute data. Expands the analyst's toolkit beyond normal-distribution assumptions.

Lesson 1 • Baseline Performance and Sigma Level

Calculates current process sigma level using defect data and capability indices. The baseline anchors the improvement goal stated in the project charter.

Lesson 2 • Data Collection Planning

Builds structured data collection plans that define what, where, when, and how data are gathered. Proper planning eliminates sampling bias and gaps.

Lesson 3 • Measurement System Analysis

Gage R&R studies quantify repeatability and reproducibility of measurement systems. Unreliable measurement invalidates all subsequent analysis.

Lesson 4 • Process Capability Fundamentals

Introduces Cp, Cpk, Pp, and Ppk indices to quantify how well a process meets specifications. Capability indices become the baseline for improvement targets.

Lesson 1 • Pareto Analysis and Prioritisation

Pareto charts apply the 80/20 principle to rank causes by frequency or impact. Prioritisation focuses improvement effort on the highest-leverage problems.

Lesson 2 • Cause-and-Effect Analysis Tools

Fishbone diagrams and the 5 Whys structure brainstorming to surface potential root causes systematically. These tools prevent teams from jumping to solutions prematurely.

Lesson 3 • Process Analysis and Value Stream Mapping

Detailed process maps and value stream maps expose waste, delays, and handoff failures. Visual analysis reveals where defects and variation originate.

Lesson 4 • Correlation and Regression Analysis

Scatter plots, correlation coefficients, and simple linear regression quantify relationships between variables. Regression models distinguish signal from noise in process data.

Lesson 1 • Solution Generation and Creativity Tools

Brainstorming, benchmarking, and TRIZ-inspired thinking generate a broad solution set before narrowing. Divergent thinking prevents premature commitment to suboptimal fixes.

Lesson 2 • Implementation Planning and Change Management

Action plans, resource allocation, and stakeholder engagement translate pilot success into full-scale rollout. Change management prevents solution rejection by the workforce.

Lesson 3 • Pilot Planning and Risk Assessment

Pilots test solutions at small scale before full deployment, reducing implementation risk. Failure Mode and Effects Analysis quantifies and mitigates residual risks.

Lesson 4 • Introduction to Design of Experiments

Full factorial and fractional factorial designs identify optimal factor settings with minimal runs. DOE replaces one-factor-at-a-time testing with efficient multi-factor analysis.

Lesson 1 • Control Plan Development

A control plan documents what to measure, how often, and what action to take when limits are breached. It is the primary handoff document from the project team to day-to-day managerial operations.

Lesson 2 • Project Closure and Knowledge Transfer

Formal closure confirms financial benefits, documents lessons learned, and transfers ownership. Structured handoff ensures the organisation retains improvement gains long-term.

Lesson 3 • Statistical Process Control Charts

Control charts distinguish common-cause variation from special-cause signals in real time. Selecting the correct chart type depends on data type and subgroup structure.

Lesson 4 • Standard Operating Procedures and Training

Updated SOPs and targeted training embed new process behaviours into daily day-to-day managerial operations. Without documented standards, improvements erode within weeks.

Lesson 1 • Final Presentation and Certification Readiness

Students present the full project to a panel using a structured storyboard format. Feedback targets gaps before formal Green Belt certification assessment.

Lesson 2 • Executing Measure and Analyse Phases

Students collect real or simulated data, validate the measurement system, and identify root causes. Phase outputs are reviewed against Green Belt competency standards.

Lesson 3 • Designing and Piloting Solutions

Teams design Lean or DOE-based solutions, complete an FMEA, and run a structured pilot. Pilot data are analysed to confirm solution effectiveness before full rollout.

Lesson 4 • Project Selection and Charter Development

Applies selection criteria to choose a high-impact project and drafts a complete charter. This section activates Define-phase skills in a realistic business scenario.