Description

This curriculum spans the design, execution, and governance of service parts networks with the same technical and operational granularity found in multi-workshop supply chain transformation programs for global after-sales service operations.

Module 1: Strategic Network Design for Service Parts

Selecting the optimal number and geographic placement of distribution centers based on mean time to repair (MTTR) targets and regional service level agreements.
Evaluating centralized vs. decentralized inventory models for high-cost, low-turnover parts considering capital constraints and obsolescence risk.
Integrating service network design with product lifecycle stages, especially end-of-service and legacy support transitions.
Assessing the trade-off between network responsiveness and transportation costs when determining echelon levels.
Aligning service parts network strategy with OEM warranty obligations and third-party service contract requirements.
Modeling demand variability across regions to determine safety stock placement and buffer locations within the network.

Module 2: Inventory Positioning and Stocking Logic

Implementing multi-echelon inventory optimization (MEIO) to determine stocking policies at each node in the network.
Classifying parts using demand frequency, criticality, and lead time to assign appropriate stocking rules (e.g., push vs. pull).
Defining stocking thresholds for repairable vs. disposable parts, including return lead time and repair yield assumptions.
Adjusting base stock levels dynamically based on forecast accuracy and service level performance deviations.
Managing consignment inventory at customer sites while maintaining ownership and financial accountability.
Handling cross-location substitutions and managing inventory visibility across heterogeneous systems.

Module 3: Demand Forecasting and Planning

Choosing between time-series, regression, and machine learning models for intermittent demand forecasting of service parts.
Incorporating product retirement schedules and field failure trends into demand planning cycles.
Handling zero-demand periods and sporadic usage patterns without overreacting to noise in forecasts.
Validating forecast accuracy using holdout samples and adjusting model parameters based on forecast error tracking.
Integrating field technician feedback and warranty claims data into demand signal refinement processes.
Coordinating demand planning across multiple business units with shared parts but different service contracts.

Module 4: Spare Parts Supply Chain Execution

Designing replenishment workflows that synchronize procurement lead times with service dispatch requirements.
Managing supplier performance for long-lead or obsolete parts using contractual service level agreements.
Implementing vendor-managed inventory (VMI) for high-usage parts while retaining control over critical stock.
Configuring warehouse management systems to support kitting, staging, and expedited shipping for emergency orders.
Executing dynamic order splitting across warehouses based on real-time availability and delivery urgency.
Handling reverse logistics for defective parts including inspection, disposition, and credit processing.

Module 5: Service Level Management and Performance Monitoring

Defining and measuring service levels using fill rate, cycle time, and on-time delivery metrics across customer tiers.
Allocating inventory during shortages based on customer priority, contract value, and equipment criticality.
Reporting service performance by part category, region, and service channel to identify systemic bottlenecks.
Conducting root cause analysis on stockouts and service delays to adjust planning parameters.
Balancing inventory investment against service level commitments in multi-year service agreements.
Using service level deviation reports to trigger network reconfiguration or supplier escalation.

Module 6: Technology Integration and Data Architecture

Selecting enterprise systems (ERP, SCM, EAM) that support multi-location inventory visibility and repair tracking.
Mapping part master data across systems to ensure consistent identification and classification.
Designing data integration workflows between service dispatch systems and inventory management platforms.
Implementing data quality controls to prevent stock record inaccuracies due to misreporting or system latency.
Configuring APIs for real-time inventory checks across distributed warehouses during service dispatch.
Establishing data governance policies for part classification, demand history retention, and forecast versioning.

Module 7: Network Optimization and Continuous Improvement

Running network simulation models to evaluate the impact of adding or closing distribution nodes.
Conducting total cost of ownership (TCO) analysis for alternative transportation modes and fulfillment paths.
Optimizing repair network flows by evaluating in-house vs. outsourced repair capacity and turnaround time.
Rebalancing inventory across locations based on seasonal demand shifts and service contract renewals.
Implementing periodic network health checks to identify underperforming nodes and excess inventory.
Integrating sustainability goals into network decisions, such as reducing transportation emissions through regional consolidation.

Module 8: Governance, Risk, and Compliance

Establishing inventory audit protocols to ensure compliance with financial reporting standards (e.g., SOX).
Managing regulatory requirements for hazardous or controlled parts across international borders.
Defining ownership and liability for parts in transit, at customer sites, or in third-party repair shops.
Implementing controls to prevent unauthorized disposal or diversion of high-value service parts.
Assessing supply chain risk for single-source or long-lead parts and developing mitigation plans.
Documenting network change management procedures for system updates, warehouse closures, or supplier transitions.