Motorola didn't invent Six Sigma because the idea sounded good on paper — it built the methodology because reducing defects by even a fraction of a percent was translating into millions of dollars saved. Companies like General Electric, Sony, and Ford later proved the same result at their own scale, which is why Six Sigma remains one of the most tested approaches to improving quality in services, products, and processes.

This course introduces participants to the DMAIC framework — Define, Measure, Analyze, Improve, Control — as the backbone of Six Sigma problem-solving, along with the statistical tools and Lean principles that support it. Through practical exercises and real cases, participants learn to move from spotting a process inefficiency to actually fixing it, with results that can be measured and sustained.

Who Should Attend?

• Quality control and quality assurance professionals.
• Operations and production managers seeking process optimization.
• Project managers and business analysts.
• Team leaders and supervisors driving quality improvement initiatives.

What You Will Gain

• Understand the origins and core logic of Six Sigma as a quality methodology.
• Apply the DMAIC framework to real process-improvement problems.
• Use root-cause analysis tools to find what's actually driving defects.
• Convert reactive problem-solving into proactive planning that prevents issues before they happen.
• Set performance standards and know how to measure whether improvements worked.
• Understand the Six Sigma belt system and how teams are organized around projects.

Module 1: Six Sigma Fundamentals

• Origins and evolution of Six Sigma, and why quality matters this much.
• Key concepts: the 1.5 sigma shift, variation, and standard deviation.
• Core principles: Voice of the Customer, reducing variation, and data-driven decisions.

Module 2: Define and Measure

• Defining project objectives, scope, and problem statements.
• Identifying critical-to-quality (CTQ) characteristics and using SIPOC diagrams.
• Collecting baseline data and process mapping.

Module 3: Analyze and Improve

• Root cause tools: fishbone diagrams, 5 Whys, and FMEA.
• Hypothesis testing and regression for identifying quality drivers.
• Developing, testing, and piloting solutions, with an introduction to design of experiments (DOE).

Module 4: Control and Sustain

• Control charts and statistical process control (SPC).
• Standard operating procedures and documentation.
• Monitoring process stability over time.

Module 5: Lean Six Sigma in Practice

• Six Sigma belts: roles, responsibilities, and team structure.
• Where Lean and Six Sigma overlap, and applying Lean tools for waste reduction.
• Case studies and a group project plan.