Green Belt Lean Six Sigma
Complex problem solving - Standard performance level
Develop the skills to improve operational performance and solve complex problems using Lean, LSSx.0, DMAIC, and statistical analysis.
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Next: 1 Oct 2026 · 31 dates
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7Daysor52.5Hours
Pricing
€3 495excl. VATOpen Enrollment Remote
€3 990excl. VATOpen Enrollment In-Person
On RequestRequest A QuoteIn-Company
Small group sessions (maximum 12 participants).
Interactive learning approach with exercises, case studies, and serious games.
Complete training kit included (manuals and materials).
Session recordings available for remote participants for review and reinforcement.
Official LSSx.0 reference books included.
Recognized LSSx.0™ Lean Six Sigma Green Belt certification.
Target Audience
All sectors — industry and services
This Green Belt training course is designed for:
Project managers and consultants (internal or external) involved in organization, quality, continuous improvement, or operational excellence
Operations and production managers
Supply chain and logistics managers
Quality managers and process improvement specialists
Prerequisites: No specific prerequisites.
Learning Objectives
Lean Practitioner Module (Days 1-2)
Module 01
01
Understand the philosophy, tools, and principles of Lean Management
02
Assess operational performance, capacity, and resource losses
03
Create and analyze process maps based on field observations
04
Improve operational processes using Lean problem-solving methods
05
Develop performance management routines and lead improvement workshops
Six Sigma Yellow Belt Module (Days 3-4)
Module 02
01
Understand the foundations of Lean Six Sigma and the DMAIC framework
02
Identify the type of operational problem using the LSSx.0 typology and select the appropriate improvement trajectory
03
Define relevant quality criteria based on customer expectations
04
Identify root causes and evaluate potential improvement solutions
05
Lead a DMAIC project addressing a simple operational problem
Six Sigma Green Belt Module (Days 5-7)
Module 03
01
Define project metrics and structure robust data collection plans
02
Validate measurement systems to ensure reliable data
03
Identify and quantify root causes through statistical analysis
04
Develop statistical process monitoring systems
05
Lead a DMAIC project addressing complex operational problems
Training Program
Lean Practitioner Module (Days 1-2)
Module 01
Lean Foundations
Principles and positioning of Lean Management
Continuous improvement and Kaizen approach
Process and Flow Analysis
Process and flow analysis (cycle time, takt time, bottlenecks)
Value Stream Mapping (VSM) and rhythm diagrams
Operational Improvement
Waste elimination and value-added analysis
Flow optimization and line balancing
Pull systems and production control (kanban, continuous flow)
Lean Practices and Performance
Visual management and Lean practices (5S, poka-yoke, SMED)
Operational performance and efficiency indicators (OPE, FPY, RTY)
Six Sigma Yellow Belt Module (Days 3-4)
Module 02
Lean Six Sigma Foundations
Principles and positioning of Lean Six Sigma
LSSx.0 problem typology and selection of the appropriate improvement trajectory
Problem Structuring
Project definition and SIPOC process mapping
Voice of the Customer and Critical-to-Satisfaction
Problem Analysis
Problem metrics and measurement planning
Root cause analysis using Pareto and Five Whys
Solution & Performance Management
Solution identification and evaluation
Performance monitoring and response plan
Six Sigma Green Belt Module (Days 5-7)
Module 03
Statistical Problem Solving
Application of the MAIC method to solve complex statistical problems
Project metrics definition and structured data collection
Measurement System & Process Analysis
Measurement system validation (Gauge R&R, linearity, bias)
Process capability analysis and Voice of the Process
Statistical Analysis
Process analysis using Y = f(X) logic and Ishikawa diagram
Graphical data analysis, correlation, and confidence intervals
Improvement Validation & Control
Statistical validation of improvements
Statistical Process Control (SPC) and control charts
Learning Experience
Experiential and Inductive Pedagogy
Kaizen-based role-playing simulation of a cross-functional business process (order reception, production, invoicing, shipping)
DMAIC case study guiding participants throughout the training
Statistical problem-solving applied to real service-level improvement cases
Interactive Learning Environment
Small groups (maximum 12 participants)
Active participation, collaboration, and peer learning
Assessment
Self-assessment tests at the end of each module
Self-assessment tests at the end of each module
Tools & Materials
Statistical software: JASP and Statoscopex
Excel-based analytical models and calculators
Training materials available in PDF and printed formats
Reference books :
LSSx.0 – 1. Flow Problems and Lean Management
LSSx.0 – 2. Discernible Problems and Methodological Foundation
LSSx.0 – 3. The Statoscope: Resolving Indiscernible and Related Statistical Problems
LSSx.0 – 1. Flow Problems and Lean Management
LSSx.0 – 2. Discernible Problems and Methodological Foundation
LSSx.0 – 3. The Statoscope: Resolving Indiscernible and Related Statistical Problems
Certification
The Lean Six Sigma Green Belt certification (LSSx.0™) is awarded upon successful completion of two separate examinations: Lean Practitioner Examination and Six Sigma Green Belt Examination.
Both exams validate knowledge aligned with the LSSx.0™ body of knowledge, ensuring participants can independently lead DMAIC projects and resolve complex quality challenges.
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Upcoming availabilities
See all datesExamination Format
Online, closed-book exams with remote video monitoring
Lean Practitioner Examination : 25 multiple-choice questions – 50 minutes
Six Sigma Green Belt Examination : 35 multiple-choice questions – 70 minutes
Available in French or English
Exams must be completed within six months of training
Passing Criteria
Minimum score: 60% per exam
One retake per exam included in case of failure
Additional attempts available upon purchase of a new exam
