Description

This curriculum spans the design and execution of service parts inventory systems with the depth and structure of a multi-workshop operational improvement program, addressing technical, organizational, and system integration challenges found in global service supply chains.

Module 1: Defining Service Parts Inventory Structure and Classification

Selecting between multi-echelon and single-echelon inventory models based on network complexity and service response requirements.
Implementing ABC/XYZ classification by combining part value (A-B-C) and demand variability (X-Y-Z) to prioritize inventory control efforts.
Determining appropriate part numbering conventions that support integration across ERP, MRO, and logistics systems.
Deciding whether to group repairable, rotable, and consumable parts in the same inventory system or manage them separately.
Establishing criteria for defining part criticality, including downtime cost, safety impact, and regulatory compliance.
Resolving conflicts between engineering-driven part definitions and supply chain requirements for aggregation and substitution.

Module 2: Demand Forecasting for Intermittent and Lumpy Service Parts

Choosing between Croston’s method, SBA, and TSB models for forecasting low-turnover parts with sporadic demand patterns.
Adjusting baseline forecasts for known future events such as product end-of-life, fleet expansions, or regulatory changes.
Integrating technician feedback and field failure reports into forecasting models to improve accuracy for high-impact parts.
Handling obsolescence risk by identifying parts with declining demand trends and triggering phase-out procedures.
Validating forecast accuracy using holdout samples and tracking forecast bias across part categories.
Managing forecast inputs when historical data is limited due to new equipment introductions or system migrations.

Module 3: Setting Inventory Policies and Stocking Parameters

Calculating optimal reorder points and safety stock levels using service level targets (e.g., 95% fill rate) and lead time variability.
Adjusting stock levels for parts with asymmetric downtime costs, even if demand volume is low.
Implementing min/max policies with dynamic adjustments based on supplier performance and seasonal fluctuations.
Defining different inventory policies for forward stocking locations versus central depots based on replenishment cycles.
Deciding when to use consignment inventory or vendor-managed inventory (VMI) for high-cost, low-usage parts.
Aligning stocking decisions with warranty obligations and service level agreements (SLAs) for different customer tiers.

Module 4: Multi-Echelon Inventory Optimization (MEIO)

Mapping the physical and logical structure of the supply network to define echelons (e.g., central warehouse, regional hubs, field depots).
Allocating inventory across echelons using METRIC or similar models to balance holding costs and expected backorder costs.
Integrating lateral transshipment rules into MEIO to allow peer-to-peer transfers between depots under predefined conditions.
Simulating the impact of lead time reductions at different echelons on overall system performance and stock requirements.
Managing data synchronization challenges between echelons when inventory visibility is delayed or incomplete.
Rebalancing stock distribution after major operational changes such as warehouse closures or service territory realignments.

Module 5: Supplier and Procurement Integration

Negotiating supplier lead time commitments and penalties to reduce safety stock requirements for long-lead parts.
Implementing blanket purchase orders with consumption reporting to streamline procurement for high-frequency parts.
Managing dual sourcing strategies for critical parts to mitigate supply disruption risks.
Integrating supplier delivery performance data into inventory policy reviews and safety stock calculations.
Establishing return material authorization (RMA) processes for defective parts that affect inventory accuracy and replenishment.
Coordinating with suppliers on end-of-life (EOL) notifications and last-time buy decisions for obsolete components.

Module 6: Performance Monitoring and Inventory Health Management

Tracking inventory aging by identifying parts with no demand over 12, 24, or 36 months and triggering review processes.
Calculating and reporting inventory turns separately for rotables, repairables, and consumables to avoid misleading averages.
Using stockout frequency and backorder duration metrics to assess service level compliance at operational locations.
Conducting regular inventory reconciliation between system records and physical counts to maintain data integrity.
Identifying excess stock through variance analysis between planned and actual consumption rates.
Implementing automated alerts for parts approaching obsolescence, overstock thresholds, or minimum service levels.

Module 7: Technology Enablement and System Configuration

Selecting between standalone service parts management systems and ERP modules based on scalability and integration needs.
Configuring reorder point and safety stock algorithms within inventory management software to reflect actual lead time distributions.
Designing data interfaces between inventory systems, field service management (FSM), and enterprise asset management (EAM) platforms.
Validating system-generated replenishment recommendations against planner judgment and adjusting algorithm parameters.
Implementing role-based access controls to prevent unauthorized changes to stocking parameters and min/max levels.
Managing master data governance for part attributes, lead times, and supplier information across global operations.

Module 8: Governance, Continuous Improvement, and Change Management

Establishing a service parts review board to approve changes to critical part stocking strategies and obsolescence plans.
Defining ownership of inventory KPIs across supply chain, service operations, and finance functions.
Conducting post-incident reviews after major stockouts to identify systemic gaps in forecasting or policy design.
Updating inventory policies in response to changes in service contracts, product mix, or support geography.
Training planners on system tools and decision frameworks to reduce reliance on manual overrides and spreadsheets.
Aligning inventory investment decisions with total cost of ownership (TCO) models that include downtime and repair costs.