This curriculum spans the design and governance of performance evaluation systems in complex organisations, comparable in scope to a multi-phase continuous improvement program integrating Lean and Six Sigma methodologies across operational, analytical, and cultural dimensions.
Module 1: Defining Performance Metrics Aligned with Lean and Six Sigma Objectives
- Selecting lead versus lag indicators based on process maturity and stakeholder reporting requirements
- Mapping critical-to-quality (CTQ) characteristics to operational metrics in cross-functional processes
- Resolving conflicts between throughput metrics (e.g., cycle time) and quality metrics (e.g., defect rate) in production environments
- Establishing baseline performance using historical data while accounting for seasonality and outlier events
- Designing scorecards that integrate Lean waste categories with Six Sigma capability indices (e.g., Cp, Cpk)
- Validating metric ownership and data collection responsibility across departmental boundaries
Module 2: Data Collection and Measurement System Integrity
- Conducting Gage R&R studies for attribute and variable data in mixed manual-digital workflows
- Choosing between automated system logging and manual data entry based on error rates and cost
- Implementing calibration schedules for measurement tools used in both shop floor and office settings
- Addressing data silos by defining standardized data fields across ERP, MES, and QMS platforms
- Designing sampling plans that balance statistical validity with operational disruption
- Documenting data lineage and transformation rules to support audit readiness
Module 3: Process Baseline Establishment and Capability Analysis
- Applying non-normal data transformations when process data fails normality tests in capability analysis
- Determining appropriate subgroup sizes for control charts in low-volume, high-variability processes
- Interpreting process performance indices (Pp, Ppk) versus process capability indices (Cp, Cpk) in unstable processes
- Handling missing data points in time-series analysis without introducing bias
- Setting specification limits when customer requirements are ambiguous or internal
- Using process maps to validate that measured steps reflect actual process flow, not idealized versions
Module 4: Root Cause Analysis and Performance Gap Diagnosis
- Selecting between Fishbone diagrams, 5 Whys, and Pareto analysis based on problem complexity and data availability
- Facilitating cross-functional root cause sessions without allowing dominant stakeholders to skew findings
- Validating root causes through designed experiments or controlled pilot interventions
- Managing resistance when root cause points to systemic issues in management practices
- Quantifying the impact of identified root causes on key performance indicators
- Documenting assumptions and limitations in root cause conclusions for regulatory and audit purposes
Module 5: Implementing Improvement Interventions with Measurable Outcomes
- Phasing pilot implementations to isolate variables and measure individual impact on performance metrics
- Configuring control plans to sustain improvements in processes with high staff turnover
- Negotiating resource allocation for improvement initiatives without disrupting core operations
- Integrating standardized work documents into existing training and onboarding systems
- Deploying visual management tools in multi-lingual or low-literacy work environments
- Adjusting performance targets dynamically when external factors (e.g., supply chain delays) affect outcomes
Module 6: Control Systems and Sustaining Performance Gains
- Designing control charts with appropriate rules (e.g., Western Electric) based on process sensitivity
- Assigning escalation protocols for out-of-control signals in 24/7 operations
- Updating standard operating procedures after process changes and ensuring version control
- Integrating process alerts into existing enterprise monitoring dashboards
- Conducting periodic process audits to verify adherence to improved workflows
- Managing change freeze exceptions during system upgrades or organizational restructuring
Module 7: Organizational Integration and Continuous Improvement Culture
- Aligning Lean Six Sigma project selection with strategic business objectives during annual planning
- Structuring cross-departmental improvement teams to avoid duplication and ensure knowledge transfer
- Linking individual performance reviews to process ownership and improvement participation
- Managing executive sponsorship transitions when leaders change roles
- Scaling improvement practices across global sites with regulatory and cultural differences
- Archiving project documentation to maintain institutional knowledge during staff turnover
Module 8: Advanced Analytics and Performance Forecasting
- Applying regression models to predict process performance under varying input conditions
- Using Monte Carlo simulation to assess risk in processes with high variability
- Integrating predictive analytics into control plans for proactive intervention
- Validating model assumptions with real-time process data to prevent drift
- Communicating forecast uncertainty to decision-makers without undermining confidence in insights
- Ensuring data privacy and compliance when using operational data for predictive modeling
