Module 1. Six Sigma and the Green Belt at Work

• What Six Sigma is and the problems it solves
• Variation, defects and the sigma scale
• Y = f(x): how outputs depend on process inputs
• DMAIC roadmap and tollgates; DMADV and when DMAIC is the wrong tool (awareness)
• Roles in an improvement programme and where the Green Belt fits
• Green Belt jobs in India and globally: manufacturing, BFSI, IT services, GCCs, healthcare, logistics, e-commerce
• Practical lab

Module 2. Process Thinking and the Cost of Poor Quality

• Processes, inputs, outputs and customers
• Lean basics every Green Belt needs: value, the eight wastes, flow and pull
• Cost of Poor Quality (COPQ): prevention, appraisal, internal and external failure costs
• The hidden factory
• Connecting improvement to business KPIs and strategy
• Practical lab: Waste walk and COPQ estimate for a selected process

Module 3. Selecting and Justifying the Right Project

• Where projects come from: KPIs, complaints, audits, COPQ, management priorities
• Project prioritisation matrix
• Choosing the approach: quick fix, Kaizen event or full DMAIC
• Hard and soft savings; building the business case
• Common reasons Green Belt projects fail
• Practical lab: Score a project shortlist and build a one-page business case

Module 4. Understanding the Customer: VOC to CTQ

• Voice of the customer, voice of the business and voice of the employee
• Collecting customer data: surveys, interviews, Gemba visits, complaint data, NPS, CSAT, CES
• Using digital feedback and text analysis
• Affinity diagrams and the Kano model
• CTQ tree; converting needs into measurable specifications
• House of Quality (practical core)
• Practical lab: Build a CTQ tree from a raw customer-feedback dataset

Module 5. The Project Charter, SIPOC and Project Plan

• Writing SMART problem and goal statements
• Charter elements and sponsor sign-off
• SIPOC and scope boundaries
• Primary, secondary and consequential metrics
• Project plan: work breakdown, Gantt chart, critical path
• Risk register; RACI matrix
• Tollgate review preparation
• Practical lab: Complete a project charter, SIPOC and 12-week project plan

Module 6. Leading the Project Team and Stakeholders

• Building and leading cross-functional and hybrid teams
• Running effective meetings and facilitation tools: brainstorming, nominal group technique, multivoting
• Stakeholder analysis and communication planning
• Handling resistance, conflict and low engagement
• Influencing without authority
• Practical lab: Stakeholder map and communication plan for the case project

Module 7. Process Mapping and Data Collection Planning

• Process maps, swimlane maps and value stream maps
• Identifying input, process and output variables
• Operational definitions
• Data types; sampling methods and sample size
• Data collection plans and check sheets
• Pulling data from business systems: ERP/CRM records, timestamps, logs
• Data cleaning and data privacy obligations (India’s DPDP Act and global norms)
• Practical lab: Swimlane map plus data collection plan, and cleaning a raw system extract

Module 8. Statistics for Green Belts

• Descriptive statistics: centre, spread and shape
• Graphs that answer questions: histogram, box plot, Pareto, run chart, scatter plot
• Probability essentials
• Normal, binomial and Poisson distributions; t, chi-square and F distributions (working level)
• Central Limit Theorem and standard error
• Normality testing and data transformation
• Practical lab: Statistical summary and graphical analysis

Module 9. Measurement System Analysis

• Why measurement error matters
• Accuracy: bias, linearity, stability
• Precision: repeatability and reproducibility
• Gage R&R study design and interpretation: %Study Variation, %Tolerance, ndc
• Attribute agreement analysis and kappa
• MSA for transactional and system data
• What to do when the measurement system fails
• Practical lab: Run and interpret a Gage R&R and an attribute agreement study

Module 10. Baseline Performance and Process Capability

• DPU, DPMO, yield, first-pass yield, rolled throughput yield and sigma level
• Process stability before capability
• Cp, Cpk, Pp and Ppk
• Short-term vs long-term performance
• Capability for non-normal and attribute data
• Lead time, process cycle efficiency and OEE as baseline measures
• Practical lab: Baseline report with capability analysis and a refined project goal

Module 11. Root Cause Analysis

• Fishbone diagram, 5 Whys and Pareto analysis
• Cause-and-effect matrix; interrelationship digraph
• Multi-vari studies
• Value-added and bottleneck analysis
• Process FMEA: severity, occurrence, detection, RPN and action priority
• Turning suspected causes into testable hypotheses
• Practical lab: Root cause workshop output and a process FMEA

Module 12. Hypothesis Testing: Concepts and Test Selection

• Null and alternative hypotheses
• Type I and II errors; alpha, beta and power
• p-values and confidence intervals
• Sample size
• Statistical vs practical significance
• Test selection roadmap by data type and question
• Practical lab: Choose the correct test for ten workplace scenarios

Module 13. Comparing Groups: Tests for Means, Variances and Proportions

• One-sample, two-sample and paired t-tests
• Tests for equal variances
• One- and two-proportion tests; chi-square test of independence
• One-way ANOVA and Tukey comparisons
• Nonparametric tests: Mann-Whitney, Kruskal-Wallis, Mood’s median
• Reporting results to non-statistical managers
• Practical lab: Validate three suspected root causes with the appropriate tests

Module 14. Relationships in Data: Correlation and Regression

• Correlation and the correlation coefficient
• Correlation vs causation
• Simple linear regression, R² and residual checks
• Prediction vs confidence intervals
• Multiple regression and logistic regression (introduction)
• Practical lab: Build and interpret a regression model of a key output

Module 15. Generating and Selecting Solutions

• Idea generation techniques; benchmarking good practice
• Lean solutions in practice: 5S, standard work, flow, pull, kanban, SMED, Kaizen events
• Mistake-proofing (poka-yoke)
• Automation, RPA and AI as solutions — when they help and when they don’t
• Solution selection matrix and Pugh matrix
• Cost-benefit analysis; solution FMEA
• Practical lab: Solution selection matrix with a cost-benefit case

Module 16. Design of Experiments

• Factors, levels and responses
• Randomisation, replication and blocking
• Why one-factor-at-a-time testing misleads
• 2^k full factorial designs
• Main effects and interactions; analysing results
• Fractional factorials (awareness); confirmation runs
• Practical lab: Design, analyse and interpret a 2³ experiment

Module 17. Piloting and Implementing Improvements

• Planning a pilot and defining success criteria
• Before/after statistical comparison
• Implementation plan, training and SOP updates
• Rollout communication; managing implementation risk
• Practical lab: Pilot plan and pilot results analysis

Module 18. Statistical Process Control

• Common vs special cause variation
• Rational subgrouping
• Choosing the right chart: I-MR, X̄-R, X̄-S, p, np, c and u
• Control limits vs specification limits
• Run rules and out-of-control signals
• Reaction plans
• SPC in service processes and live dashboards
• Practical lab: Select, build and interpret control charts for three datasets

Module 19. Control Plans, Sustainment and Project Closure

• Control plan and response plan
• Standard work, visual management and mistake-proofing for sustainment
• Process audits; handover to the process owner
• Validating financial benefits with finance
• Lessons learned; replicating results in other areas
• Closure report and final tollgate
• Practical lab: Full control plan and project closure report

Module 20. Capstone Project and Green Belt Career Launch

• End-to-end DMAIC capstone on a new case dataset
• A3 and project storyboard
• Presenting results to leadership: storytelling with data
• Using the digital toolkit on live projects
• Green Belt job roles: Process Excellence Analyst
• Building a project portfolio from the module labs
• Resume, LinkedIn profile and interview preparation (technical and case questions)
• Your first 90 days as a Green Belt; path to Black Belt-level responsibilities
• Practical lab: Capstone storyboard presentation

Apply for Certification

https://www.vskills.in/certification/quality/certified-six-sigma-green-belt-professional