Lean Six Sigma Course

Lesson 1 • Roles, Belts, and Organisational Structure

Explains the belt hierarchy from White to Master Black Belt and sponsor roles. Clarifies accountability at each level within a deployment.

Lesson 2 • Business Case and Return on Investment

Demonstrates how to quantify the financial impact of a Lean Six Sigma initiative. Connects project selection to strategic organisational goals.

Lesson 3 • Core Philosophy and Guiding Principles

Defines value, waste, and variation as the three central problems Lean Six Sigma addresses. Links philosophy to measurable business outcomes.

Lesson 4 • Origins and Evolution of the Methodology

Traces Lean's roots in Toyota Production System and Six Sigma's origin at Motorola. Provides context for why the two were integrated.

Lesson 1 • Crafting the Project Charter

Covers all charter elements: problem statement, goal statement, scope, and timeline. A well-written charter prevents scope creep and aligns sponsors.

Lesson 2 • Voice of the Customer Collection

Teaches methods for gathering customer needs through surveys, interviews, and observation. Converts raw feedback into actionable requirements.

Lesson 3 • SIPOC and High-Level Process Mapping

Builds a Suppliers-Inputs-Process-Outputs-Customers diagram to frame the process under study. Establishes shared understanding before detailed mapping begins.

Lesson 4 • Critical to Quality Tree Development

Translates customer needs into measurable Critical to Quality characteristics. Bridges qualitative voice of the customer data to quantitative metrics.

Lesson 1 • Data Types and Measurement Scales

Distinguishes continuous, discrete, nominal, and ordinal data and their implications for tool selection. Prevents analytical errors caused by misclassified data.

Lesson 2 • Measurement System Analysis

Applies Gage R&R studies to assess measurement system accuracy and repeatability. Ensures data collected is trustworthy before drawing conclusions.

Lesson 3 • Process Capability Analysis

Calculates Cp, Cpk, Pp, and Ppk indices to quantify how well a process meets specifications. Establishes the performance baseline for the Analyse phase.

Lesson 4 • Baseline Data Collection and Sampling

Designs statistically valid sampling plans to capture representative process data. Balances cost and precision to support reliable baseline estimates.

Lesson 1 • Regression and Correlation Analysis

Builds simple and multiple linear regression models to quantify input-output relationships. Enables prediction of process output from controllable input variables.

Lesson 2 • Graphical Analysis and Exploratory Tools

Uses histograms, box plots, scatter plots, and run charts to reveal patterns in data. Builds intuition before applying formal statistical tests.

Lesson 3 • Cause-and-Effect Analysis Methods

Applies fishbone diagrams and the Five Whys technique to structure root cause investigation. Prevents teams from jumping to solutions before causes are confirmed.

Lesson 4 • Hypothesis Testing Fundamentals

Introduces null and alternative hypotheses, p-values, and Type I and II errors. Provides the statistical foundation for confirming root causes with data.

Lesson 1 • Flow and Pull System Design

Designs continuous flow and kanban-based pull systems to match production to demand. Reduces inventory, overproduction, and waiting waste.

Lesson 2 • Lean Waste Elimination Techniques

Applies the eight wastes framework and 5S methodology to remove non-value-added activities. Directly reduces lead time and operating cost.

Lesson 3 • Piloting and Rapid Experimentation

Designs small-scale pilots and Plan-Do-Check-Act cycles to test solutions before full rollout. Reduces implementation risk and builds evidence for scaling.

Lesson 4 • Design of Experiments for Optimisation

Introduces full factorial and fractional factorial designs to optimise multiple input factors simultaneously. Identifies optimal settings with minimal experimental runs.

Lesson 1 • Standard Operating Procedure Creation

Documents improved processes in clear, auditable standard operating procedures. Embeds new methods into daily operations to prevent knowledge loss.

Lesson 2 • Training and Knowledge Transfer

Designs training plans to upskill process operators on new procedures and control methods. Ensures competency before the project team disengages.

Lesson 3 • Project Closure and Benefits Realisation

Formalises project closure with financial validation, lessons learned, and handoff documentation. Confirms that projected savings are realised and recorded.

Lesson 4 • Control Plan Development

Builds a comprehensive control plan linking CTQs, measurement methods, and reaction plans. Ensures process owners know what to monitor and how to respond.

Lesson 1 • Multivariate Analysis Techniques

Applies principal component analysis and cluster analysis to reduce dimensionality in complex datasets. Reveals hidden structure when many variables interact simultaneously.

Lesson 2 • Logistic Regression for Binary Outcomes

Models the probability of a binary outcome as a function of continuous or categorical predictors. Extends regression capability to pass-fail and defect-present data.

Lesson 3 • Reliability and Failure Analysis

Applies Weibull analysis and failure mode and effects analysis to predict and prevent failures. Connects statistical reliability to product and process design decisions.

Lesson 4 • Advanced Control Chart Methods

Introduces CUSUM, EWMA, and multivariate T-squared charts for detecting small process shifts. Enhances monitoring sensitivity beyond standard Shewhart charts.

Lesson 1 • Change Management for Large-Scale Deployment

Applies Kotter's eight-step model and ADKAR framework to drive cultural adoption of Lean Six Sigma. Addresses resistance at individual, team, and organisational levels.

Lesson 2 • Strategic Alignment and Project Selection

Links the project portfolio to strategic objectives using hoshin kanri and portfolio matrices. Ensures improvement resources target the highest-value opportunities.

Lesson 3 • Scaling and Sustaining a Lean Culture

Embeds continuous improvement into daily management systems, leader standard work, and hiring practices. Transitions from project-based improvement to a self-sustaining culture.

Lesson 4 • Measuring Deployment Effectiveness

Defines deployment-level metrics including savings realised, projects completed, and belt utilisation. Enables leadership to assess programme health and course-correct.