Introduction to Lean Six Sigma and Project Identification Methods

Lesson 1 • Lean Concepts and the Eight Wastes

Introduces the eight categories of waste (DOWNTIME) with real-world examples. Provides the vocabulary needed for waste identification in later chapters.

Lesson 2 • Core Philosophies and Principles

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

Lesson 3 • LSS Roles and Organizational Structure

Defines Belt levels, Champion, and Sponsor roles and their responsibilities within an LSS program. Clarifies how organizational hierarchy supports project execution.

Lesson 4 • Six Sigma Concepts and Variation

Explains sigma levels, defects per million opportunities, and process capability as Six Sigma fundamentals. Grounds statistical thinking before formal tools are introduced.

Lesson 1 • DMAIC as a Problem-Solving Roadmap

Positions DMAIC within the broader LSS methodology and contrasts it with DMADV and Kaizen. Establishes why a structured roadmap prevents premature solution jumping.

Lesson 2 • Define Phase Essentials

Covers project charter creation, problem statement writing, and scope setting as Define outputs. Links Define rigor to downstream project success.

Lesson 3 • Phase-Gate Reviews and Tollgates

Explains tollgate criteria, review formats, and stakeholder sign-off requirements at each DMAIC transition. Reinforces disciplined progression through the framework.

Lesson 4 • Measure Phase Essentials

Introduces baseline data collection, measurement system validation, and current-state process mapping. Shows how Measure outputs feed directly into Analyze.

Lesson 1 • Prioritization Tools and Matrices

Applies effort-impact matrices, weighted scoring, and Pareto analysis to rank competing project candidates. Builds decision-making rigor into the selection process.

Lesson 2 • Sources of Improvement Opportunities

Identifies internal and external sources—customer complaints, process audits, financial data, and benchmarking—as project inputs. Teaches systematic opportunity scanning.

Lesson 3 • Linking Projects to Strategic Goals

Explains hoshin kanri and strategy deployment to ensure projects support organizational priorities. Prevents resource waste on low-impact initiatives.

Lesson 4 • Project Scoping and Feasibility

Covers scope definition, resource estimation, and feasibility assessment to ensure projects are actionable. Introduces the concept of a well-scoped vs. over-scoped project.

Lesson 1 • Completing and Validating the Project Charter

Assembles all Define outputs into a complete charter and validates it against tollgate criteria. Prepares students to present and defend the charter to sponsors.

Lesson 2 • Setting Goals and Business Case

Guides students in setting measurable improvement targets and calculating a compelling financial business case. Connects goal-setting to stakeholder buy-in.

Lesson 3 • Crafting Effective Problem Statements

Teaches the IS/IS-NOT framework and SMART criteria to write focused, evidence-based problem statements. Avoids solution bias and scope ambiguity from the start.

Lesson 4 • SIPOC Mapping

Builds high-level SIPOC diagrams to define process boundaries and key stakeholders before detailed mapping. Anchors the project scope within the Define phase.

Lesson 1 • Process Mapping and Value Stream Analysis

Teaches detailed process flow mapping and value stream mapping to visualize current-state performance. Identifies value-added vs. non-value-added steps for later analysis.

Lesson 2 • Measurement System Analysis

Introduces Gage R&R studies and attribute agreement analysis to validate measurement system reliability. Ensures baseline data accurately reflects true process performance.

Lesson 3 • Data Collection Planning

Designs structured data collection plans specifying what, where, when, and how data is gathered. Reduces sampling bias and ensures data integrity.

Lesson 4 • Establishing Baseline Performance

Calculates process capability indices (Cp, Cpk) and baseline sigma level from validated data. Provides the quantitative starting point for improvement targets.

Lesson 1 • Hypothesis Testing Fundamentals

Introduces null and alternative hypotheses, p-values, and test selection logic for validating root causes. Provides statistical rigor without requiring advanced mathematics.

Lesson 2 • Graphical Analysis Tools

Uses histograms, box plots, run charts, and scatter diagrams to reveal patterns and relationships in data. Builds visual analysis skills before statistical methods are introduced.

Lesson 3 • Cause-and-Effect Analysis

Applies fishbone diagrams and the 5 Whys technique to systematically explore potential root causes. Structures team brainstorming to prevent overlooking key cause categories.

Lesson 4 • Pareto Analysis and Vital Few

Uses Pareto charts to separate the vital few causes from the trivial many, focusing improvement effort. Reinforces data-driven prioritization over intuition.

Lesson 1 • Piloting and Testing Solutions

Designs and executes a controlled pilot to validate solution effectiveness before full deployment. Establishes criteria for pilot success and scale-up decisions.

Lesson 2 • Lean Improvement Techniques

Applies 5S, standard work, visual management, and flow design to eliminate waste in the improved process. Connects Lean tools directly to root causes identified in Analyze.

Lesson 3 • Solution Evaluation and Selection

Uses solution matrices, Pugh concept selection, and risk assessment to choose the best solution. Ensures selection is objective and aligned with project goals.

Lesson 4 • Creative Solution Generation

Applies brainstorming, benchmarking, and TRIZ-inspired thinking to generate a broad solution set. Encourages divergent thinking before convergent evaluation.

Lesson 1 • Building a Comprehensive Control Plan

Assembles a control plan specifying what to monitor, how often, who is responsible, and what to do when out of control. Formalizes the handoff from project team to process owner.

Lesson 2 • Mistake-Proofing and Error Prevention

Applies poka-yoke principles to design processes that prevent defects from occurring or escaping. Reduces reliance on inspection as the primary quality mechanism.

Lesson 3 • Project Closure and Benefits Realization

Conducts a formal project closure including lessons learned, financial benefit validation, and recognition. Transfers accountability and closes the DMAIC cycle completely.

Lesson 4 • Statistical Process Control Fundamentals

Introduces control charts, control limits, and special vs. common cause variation for ongoing monitoring. Provides the statistical foundation for the control plan.