This module explores advanced decision-making and process mapping tools used in the Define and Measure phases. Learners practice applying frameworks such as Pugh Matrix, Affinity Diagrams, Pareto Charts, and SIPOC mapping. The module also introduces foundational measurement concepts including data types, populations, and samples to prepare learners for statistical analysis in later phases.

This module develops statistical literacy for Lean Six Sigma projects, focusing on descriptive statistics and measurement tools. Learners explore measures of central tendency, spread, and distribution shapes to understand process performance. Case studies, data collection planning, and MSA (Measurement System Analysis) provide real-world applications. The module concludes with an introduction to the Analyze phase, linking measurement insights to root cause identification.

This module focuses on the Analyze and Improve phases of DMAIC. Learners validate root causes with statistical tools and prioritize the most critical factors. In the Improve phase, learners design, test, and refine solutions through methods such as DOE (Design of Experiments) and pilot studies. Emphasis is placed on iterative refinement, customer validation, and preparing improvements for long-term sustainability.

This module covers the final DMAIC stage (Control), ensuring improvements are sustained through monitoring and standardization. Learners explore the Recognize phase for identifying new project opportunities, and study Lean Management principles for efficiency. The module introduces DFSS (Design for Six Sigma) with the DMADV methodology and concludes with Change Management strategies to embed continuous improvement into organizational culture.