This curriculum spans the technical and organisational challenges typical of a multi-workshop process improvement initiative, addressing the same depth of operational decision-making found in internal capability programs for lean manufacturing and continuous improvement.
Module 1: Process Mapping and Baseline Assessment
- Selecting between value stream mapping and SIPOC diagrams based on process complexity and stakeholder familiarity with lean tools.
- Validating process start and end points with operations leads to prevent scope creep during baseline data collection.
- Deciding whether to use direct observation or system log data for cycle time measurement in high-volume transaction environments.
- Resolving discrepancies between documented procedures and actual operator behavior during process walkthroughs.
- Establishing thresholds for acceptable data completeness when historical performance records are fragmented across departments.
- Coordinating cross-functional workshops to align on process ownership when responsibilities are informally distributed.
Module 2: Data Collection and Performance Metrics
- Designing sampling strategies for manual processes where 100% data capture is operationally disruptive.
- Choosing between lead time, cycle time, and takt time as the primary KPI based on production pacing and customer demand patterns.
- Implementing data validation rules in spreadsheets or databases to prevent manual entry errors during time studies.
- Addressing resistance from frontline staff when introducing stopwatch timing or digital logging tools.
- Determining whether to normalize performance data for shift, crew, or equipment differences when comparing lines.
- Setting thresholds for statistical significance when evaluating small-sample performance improvements.
Module 3: Root Cause Analysis and Bottleneck Identification
- Selecting between fishbone diagrams and 5 Whys based on team expertise and time constraints during incident reviews.
- Using Pareto analysis to prioritize which process defects to investigate when multiple failure modes exist.
- Deploying time-loss tracking sheets to distinguish between planned downtime and emergent bottlenecks.
- Interpreting control charts to determine whether variation is common-cause or special-cause before initiating changes.
- Mapping work-in-progress (WIP) accumulation points to identify hidden capacity constraints in batch processes.
- Calibrating team consensus on root cause validity when data is incomplete or contradictory.
Module 4: Lean and Six Sigma Intervention Design
- Choosing between Kaizen events and longer-term DMAIC projects based on problem scope and resource availability.
- Designing standardized work instructions that balance prescriptive detail with operator discretion in variable tasks.
- Implementing 5S in shared workspaces where multiple teams use the same equipment and storage areas.
- Calculating takt time adjustments when customer demand fluctuates seasonally or due to supply chain disruptions.
- Integrating poka-yoke devices into existing machinery without requiring full-line shutdowns.
- Defining operational definitions for defect classification to ensure consistent measurement across shifts.
Module 5: Technology Integration and Automation
- Evaluating whether to automate manual data entry using RPA or restructure the process to eliminate the need for entry.
- Configuring SCADA or MES systems to trigger real-time alerts for out-of-spec process parameters.
- Integrating IoT sensors into legacy equipment where communication protocols are proprietary or undocumented.
- Designing user interfaces for shop floor tablets that minimize cognitive load during high-interruption workflows.
- Establishing data retention policies for process logs when storage costs conflict with audit requirements.
- Validating accuracy of automated cycle time tracking against manual observations during pilot phases.
Module 6: Change Management and Operational Adoption
- Sequencing rollout of process changes across shifts to allow for feedback incorporation without halting production.
- Developing visual management boards that reflect real-time status without overwhelming operators with metrics.
- Addressing union concerns when new performance metrics could be perceived as precursors to staffing reductions.
- Training super-users from each shift to sustain knowledge transfer when consultants exit the project.
- Reconciling conflicting incentives between maintenance and production teams during uptime improvement initiatives.
- Updating standard operating procedures in parallel with change implementation to prevent documentation lag.
Module 7: Continuous Improvement Governance
- Establishing cadence and attendance requirements for process performance review meetings across departments.
- Deciding which improvement ideas to fund when multiple teams submit proposals with overlapping benefits.
- Designing feedback loops from quality control data back into process adjustment protocols.
- Auditing adherence to new workflows three months post-implementation to detect regression.
- Balancing investment in incremental improvements versus major redesigns within annual planning cycles.
- Archiving project documentation in a searchable repository accessible to operations and engineering teams.
Module 8: Scalability and Cross-Functional Integration
- Adapting a successful line-level optimization for rollout across multiple facilities with different equipment vintages.
- Aligning process KPIs between procurement, production, and logistics to prevent sub-optimization.
- Integrating process capability data into supplier scorecards for raw material consistency.
- Managing handoffs between departments when end-to-end process ownership is split across managers.
- Standardizing data models across plants to enable centralized benchmarking and best practice sharing.
- Updating control plans when new regulatory requirements affect process validation or documentation.
