Lean Six Sigma Green Belt Training Course

Participants can create a project charter with clear scope, goals, stakeholders and customer requirements.

• Problem statements distinguishing symptoms, causes, scope and quantified impact
• SMART goal statements linked to baseline and target performance
• Project charters defining boundaries, milestones, roles and anticipated benefits
• Voice of Customer collection through interviews, complaints and service data
• CTQ trees converting customer needs into measurable performance requirements
• Stakeholder analysis identifying sponsors, process owners, users and resisters

Participants can describe a process boundary, sequence, ownership and customer outputs.

• SIPOC diagrams establishing suppliers, inputs, process, outputs and customers
• High-level process maps showing major steps and decision points
• Swimlane flowcharts clarifying handoffs, ownership and approval delays
• Gemba observation techniques for recording actual work and exceptions
• Rework loops, queues and failure points identified on process maps
• Process walk-through questions testing documented procedures against reality

Participants can identify non-value-added work and analyse process flow using Lean principles.

• Eight wastes: defects, overproduction, waiting, non-utilised talent and transport
• Inventory, motion, extra-processing and their service-process equivalents
• Value-added analysis using customer value, business value and waste categories
• Current-state value stream maps showing touch time, wait time and queues
• Takt time, cycle time and lead time distinguished clearly
• Constraint identification using capacity, demand and bottleneck evidence

Participants can build a defensible plan for collecting relevant and consistent process data.

• Measurement plans specifying metrics, sources, owners, timing and sampling
• Operational definitions removing ambiguity from defect and timing measures
• Data types: nominal, ordinal, discrete and continuous measures
• Sampling approaches using random, systematic and stratified selection
• Data collection forms designed for complete, usable process evidence
• Data integrity checks for missing values, duplicates and inconsistent codes

Participants can assess whether measurement systems are suitable for project decisions.

• Accuracy, precision, bias, linearity and stability in measurement systems
• Attribute agreement analysis for categorical inspection and review decisions
• Repeatability and reproducibility concepts for variable measurement studies
• Calibration records and traceability requirements for critical measurement equipment
• Inter-rater reliability risks in audits, quality checks and case reviews
• Measurement system findings incorporated into the project measurement plan

Participants can summarise process data and establish a meaningful performance baseline.

• Mean, median and mode selected for appropriate data distributions
• Range, variance and standard deviation describing process variation
• Histograms revealing distribution shape, spread, gaps and unusual values
• Box plots comparing groups, outliers and central tendency
• Baseline dashboards combining volume, defects, timing and cost measures
• Stratification by product, channel, team, supplier or customer segment

Participants can calculate defect-based metrics and interpret process capability against requirements.

• Defects, defectives, units and opportunities defined for project metrics
• First-pass yield and rolled throughput yield calculations
• DPU, DPMO and sigma level calculations from process data
• Specification limits distinguished from control limits and customer requirements
• Cp and Cpk interpreted for stable, capable processes
• Capability analysis limitations when data are unstable or non-normal

Participants can select and interpret charts that reveal variation, trends and special causes.

• Pareto charts ranking defect categories by frequency and impact
• Run charts detecting shifts, trends and non-random patterns
• Time plots revealing seasonality, batching and workload-related variation
• Scatter plots examining associations between process variables
• Individuals and moving range charts for continuous process data
• Attribute control charts selected for proportions, counts and defects

Participants can develop, organise and test plausible causes of process performance problems.

• Fishbone diagrams structuring potential causes by people, process and technology
• 5 Whys analysis tracing failure mechanisms beyond immediate symptoms
• Cause-and-effect matrices linking inputs to critical output requirements
• Affinity diagrams grouping observation, complaint and workshop evidence
• Process segmentation locating variation by time, source or transaction type
• Root-cause hypotheses stated as testable relationships between variables

Participants can use basic hypothesis tests to validate whether observed differences are meaningful.

• Null and alternative hypotheses framed around process improvement questions
• P-values, confidence intervals and practical significance interpreted together
• One-sample tests comparing baseline performance against target requirements
• Two-sample tests comparing teams, suppliers, channels or process methods
• Paired tests assessing before-and-after changes on matched cases
• Chi-square tests examining associations within categorical defect data

Participants can investigate relationships among variables and assess failure risks systematically.

• Correlation coefficients interpreted without claiming unsupported causal relationships
• Simple regression models estimating relationships between input and output variables
• Residual plots checking model fit, patterns and unusual observations
• FMEA scoring severity, occurrence and detection for failure modes
• Risk priority numbers used cautiously alongside management judgement
• Cause validation combining data analysis, observation and subject-matter expertise

Participants can generate, assess and select improvements that address validated root causes.

• Brainstorming rules producing diverse countermeasures without premature evaluation
• Benchmarking internal best practices against the current process
• Solution selection matrices comparing impact, effort, cost and risk
• Impact-effort grids prioritising quick wins and strategic improvements
• Future-state process maps showing redesigned flow and control points
• Assumption logs recording dependencies, constraints and unresolved decisions

Participants can apply Lean methods to reduce waste, improve flow and prevent errors.

• 5S workplace organisation for visual order, access and standardisation
• Visual management making status, priorities and abnormalities immediately visible
• Standard work defining sequence, timing and expected quality criteria
• Poka-yoke controls preventing errors or detecting them immediately
• Kanban signals controlling work release and limiting work in progress
• Pull systems matching upstream activity to downstream demand

Participants can plan, run and evaluate a controlled improvement pilot.

• Pilot charters defining scope, duration, measures, owners and success criteria
• PDCA cycles testing changes through planned observation and adjustment
• Implementation plans sequencing actions, resources, dependencies and approvals
• Change impact assessments identifying affected roles, systems and procedures
• Communication plans addressing sponsors, frontline teams and process users
• Pilot results compared against baseline using agreed performance measures

Participants can design controls that sustain improved performance after project closure.

• Control plans specifying measures, limits, frequency, ownership and response actions
• Standard operating procedures updated to reflect approved process changes
• Reaction plans defining escalation when performance breaches agreed thresholds
• Control charts used for ongoing monitoring of critical measures
• Training plans transferring revised work methods to process users
• Benefits tracking confirming financial, service and risk outcomes

Participants can manage Green Belt project reporting, stakeholder decisions and benefit claims.

• DMAIC tollgate reviews preparing evidence for sponsor decisions
• Project dashboards reporting scope, milestones, risks, metrics and benefits
• Benefit calculations separating hard savings, cost avoidance and capacity release
• RACI matrices assigning accountability for actions and control activities
• Executive summaries presenting findings, options, decisions and expected impact
• Storyboards structuring project evidence from problem through sustained results

Participants can build, review and present a complete DMAIC project pack for a defined operational problem.

• Project charter refined with sponsor, customer and financial requirements
• Current-state map and baseline metrics assembled into project evidence
• Root-cause analysis supported by stratification, charts and validated hypotheses
• Improvement options evaluated through risk, impact and implementation criteria
• Control plan linking measures, owners, limits and response actions
• Project presentation reviewed against DMAIC tollgates and decision requirements