Problem Solving in Lean Management, Six Sigma, Continuous improvement Introduction

This curriculum spans the full lifecycle of organisational improvement work, equivalent to a multi-phase continuous improvement program, from problem identification and data-driven analysis to solution implementation, control, and cultural sustainment across teams and processes.

Module 1: Defining and Scoping Improvement Initiatives

• Selecting projects based on strategic alignment, measurable impact, and stakeholder buy-in while avoiding initiatives with unclear ownership or undefined metrics.
• Conducting voice-of-customer (VOC) interviews to translate qualitative feedback into specific, prioritized problem statements.
• Developing a project charter that includes problem definition, scope boundaries, baseline metrics, and expected outcomes approved by process owners.
• Mapping stakeholder influence and resistance levels to design an effective engagement plan for cross-functional support.
• Determining whether to pursue a quick-win kaizen event or a long-term DMAIC project based on problem complexity and data availability.
• Establishing tollgates for project progression, including criteria for moving from Define to Measure phase.

Module 2: Process Mapping and Value Stream Analysis

• Conducting current-state value stream mapping with frontline operators to capture accurate cycle times, batch sizes, and wait times.
• Distinguishing between value-added, non-value-added, and necessary non-value-added steps using standardized time-motion observations.
• Identifying handoffs, rework loops, and bottlenecks in cross-departmental workflows using swimlane diagrams.
• Quantifying lead time and process cycle efficiency to establish baseline performance for improvement targets.
• Validating process maps with data from ERP or MES systems to avoid reliance on anecdotal process descriptions.
• Designing future-state value stream maps with realistic constraints such as capital budgets, labor agreements, and system dependencies.

Module 3: Data Collection and Measurement System Analysis

• Developing a data collection plan that specifies what to measure, how often, by whom, and using which tools or templates.
• Conducting Gage R&R studies for continuous and attribute data to assess measurement system reliability before collecting baseline data.
• Selecting appropriate metrics (e.g., defect rate, cycle time, throughput) based on process type and customer requirements.
• Addressing data gaps by implementing temporary tracking methods when automated systems lack required granularity.
• Standardizing operational definitions across teams to ensure consistent data interpretation and reduce ambiguity.
• Using control charts during data collection to detect instability or special causes that could invalidate baseline assumptions.

Module 4: Root Cause Analysis and Problem Validation

• Applying the 5 Whys technique in team workshops while guarding against superficial answers or blame-oriented discussions.
• Constructing fishbone diagrams with cross-functional input to categorize potential causes across people, process, equipment, and environment.
• Using Pareto analysis to prioritize root causes based on frequency, cost, or impact on customer CTQs.
• Designing and executing hypothesis tests (e.g., t-tests, ANOVA) to statistically validate suspected root causes.
• Employing failure mode and effects analysis (FMEA) to assess risk priority numbers and guide preventive actions.
• Verifying root causes through controlled pilot changes before full-scale implementation.

Module 5: Solution Development and Pilot Testing

• Generating countermeasures using structured ideation techniques such as brainwriting or SCAMPER, followed by impact/effort prioritization.
• Designing small-scale pilots with defined success criteria, duration, and rollback procedures to minimize operational disruption.
• Implementing visual management tools (e.g., Andon, Kanban) in pilot areas to test sustainability and user adoption.
• Adjusting staffing, scheduling, or workflow sequences in pilot zones to validate throughput improvements.
• Documenting deviations from expected results and conducting mid-pilot reviews to refine solution design.
• Using pre- and post-pilot data comparisons with appropriate statistical tests to confirm performance gains.

Module 6: Standardization and Control Implementation

• Developing updated standard operating procedures (SOPs) with input from operators to ensure practicality and compliance.
• Integrating control mechanisms such as mistake-proofing (poka-yoke) devices or automated alerts into production systems.
• Establishing control charts or dashboards to monitor critical process parameters and detect early signs of drift.
• Assigning ownership for ongoing monitoring and response to out-of-control conditions in process control plans.
• Training supervisors and team leaders on response plans for common process deviations.
• Embedding audit schedules into existing management review cycles to sustain adherence to new standards.

Module 7: Sustaining Gains and Scaling Improvements

• Conducting post-implementation audits at 30, 60, and 90 days to verify that improvements are maintained.
• Integrating key performance indicators from completed projects into operational scorecards for ongoing visibility.
• Transferring ownership of improved processes from project teams to line management with documented handover criteria.
• Identifying replication opportunities across similar processes or sites using process commonality analysis.
• Updating training materials and onboarding programs to include new methods and standards.
• Managing resistance to change during scale-up by addressing role impacts and reinforcing accountability through performance metrics.

Module 8: Leadership Engagement and Continuous Improvement Culture

• Designing leader standard work that includes gemba walks, audit checklists, and review of improvement backlogs.
• Aligning performance management systems to reward problem-solving behaviors, not just outcome metrics.
• Facilitating improvement boards to prioritize, track, and escalate improvement initiatives across departments.
• Establishing tiered performance meetings that connect shop-floor issues to strategic objectives.
• Managing resource allocation between daily operations and improvement project workloads to prevent burnout.
• Using coaching cycles to develop team members’ problem-solving skills rather than providing direct solutions.