This curriculum spans the technical and operational complexity of a multi-phase inventory optimisation programme, comparable to an internal capability build for global service parts planning, covering forecasting, network design, and data governance across product lifecycles.
Module 1: Demand Forecasting for Intermittent Parts
- Select between Croston’s method and Teunter-Syntetos models based on historical demand sparsity and obsolescence risk.
- Adjust forecast parameters when new product introductions disrupt legacy part usage patterns.
- Integrate engineering change notifications into forecasting logic to preempt demand drops for superseded parts.
- Decide whether to pool demand across regions when service networks have asymmetric failure rates.
- Handle zero-demand periods during equipment warranty phases without over-suppressing future forecast signals.
- Validate forecast accuracy using holdout samples that reflect actual service technician dispatch patterns.
Module 2: Inventory Stratification and Criticality Classification
- Define ABC-XYZ classifications using both movement velocity and downtime cost per hour, not just sales volume.
- Reclassify parts when equipment criticality changes due to shifts in production scheduling or regulatory requirements.
- Override automated stratification rules for parts with long lead times and high supplier risk exposure.
- Assign dual classifications to parts used in both preventive maintenance and emergency repairs.
- Exclude trial or prototype parts from standard inventory policies until deployment scales.
- Align classification thresholds with service level agreements (SLAs) for different customer tiers.
Module 3: Replenishment Policy Design and Parameter Tuning
- Set reorder points using probabilistic models that account for lead time variability from overseas suppliers.
- Determine order-up-to levels for repairable parts considering asset return timelines and cannibalization rates.
- Adjust safety stock multipliers when operating under constrained warehouse capacity or budget ceilings.
- Implement min/max policies with dynamic bands for parts affected by seasonal field failure trends.
- Balance cycle service level targets against fill rate objectives when stocking high-cost, low-turn items.
- Introduce order pacing rules to prevent system nervousness from demand spikes due to one-time campaigns.
Module 4: Supplier and Lead Time Risk Management
- Qualify alternate suppliers for single-source parts based on technical certification timelines and MOQ constraints.
- Negotiate consignment or vendor-managed inventory (VMI) agreements for parts with volatile demand profiles.
- Trigger proactive expediting protocols when supplier performance metrics breach predefined thresholds.
- Model lead time uncertainty using historical inbound shipment data, not supplier-provided estimates.
- Allocate safety stock across echelons when dual sourcing involves regional distribution centers and field depots.
- Enforce supplier scorecard reviews that include on-time delivery, quality defect rates, and responsiveness to urgent requests.
Module 5: Obsolescence and Lifecycle Transition Planning
- Initiate last-time buy decisions using end-of-life forecasts and remaining installed base counts.
- Flag parts for phase-out when OEMs announce end-of-support for specific equipment models.
- Coordinate with engineering teams to map cross-reference tables for backward-compatible replacements.
- Dispose of excess stock through controlled channels to avoid gray market leakage and warranty conflicts.
- Retain strategic stock for legacy systems still in operation beyond standard depreciation schedules.
- Update master data attributes to reflect obsolescence status and prevent inadvertent reordering.
Module 6: Network Design and Multi-Echelon Optimization
- Determine optimal stocking locations using total cost-to-serve, including transportation and technician wait time.
- Implement push-pull boundaries at regional distribution centers based on regional failure density.
- Simulate the impact of consolidating depots on service levels and emergency shipment costs.
- Assign repairable parts to centralized vs. decentralized recovery centers based on repair cycle duration.
- Adjust transshipment rules to prevent unauthorized part borrowing between customer territories.
- Model the cost of downtime at the work order level to prioritize stocking decisions in the network.
Module 7: Data Governance and Master Data Integrity
- Enforce part number rationalization to eliminate duplicates arising from M&A integration or ERP migrations.
- Define ownership roles for maintaining lead time, unit cost, and supplier data across procurement and logistics teams.
- Implement change control workflows for modifying criticality codes or stocking policies.
- Validate demand history by filtering out data anomalies from system conversions or bulk corrections.
- Map field-replaceable unit (FRU) hierarchies to ensure spare parts are linked to correct assemblies.
- Monitor data completeness metrics before running inventory optimization cycles to avoid flawed outputs.
Module 8: Performance Monitoring and Continuous Improvement
- Track stockout frequency per part by root cause: forecasting error, supply disruption, or policy violation.
- Measure inventory health using aged stock ratios segmented by criticality and obsolescence risk.
- Conduct root cause analysis on emergency air shipments to identify systemic replenishment gaps.
- Align KPIs across procurement, planning, and field service to prevent local optimization.
- Review inventory turns quarterly with finance to validate capital allocation efficiency.
- Run periodic policy audits to detect deviations from approved stocking logic in ERP execution.