Description

This curriculum spans the technical and operational complexity of a multi-workshop service parts optimisation programme, addressing the same granular decision-making required in enterprise-wide inventory transformations and cross-functional supply chain advisory projects.

Module 1: Demand Forecasting for Service Parts

Selecting between intermittent demand models (Croston, SBA, TSB) based on part obsolescence patterns and historical transaction sparsity.
Adjusting forecast parameters dynamically when dealing with parts experiencing sudden failure spikes due to design flaws or environmental factors.
Integrating field failure reports and warranty data into forecasting algorithms to improve accuracy for critical failure-prone components.
Handling zero-demand periods for legacy equipment parts while avoiding premature discontinuation of low-turn items.
Calibrating forecast error tolerance bands for high-cost parts where overstocking carries significant financial risk.
Coordinating forecast inputs across regions when service networks operate under different maintenance cycles and equipment ages.

Module 2: Inventory Stratification and Classification

Defining service-level targets per part class (A/B/C) based on equipment criticality and downtime cost, not just velocity.
Rebalancing ABC classifications quarterly to reflect changes in installed base and repair procedures.
Applying multi-attribute classification that includes repairability, lead time, and substitution options beyond turnover rate.
Managing exceptions for low-velocity, high-criticality parts that defy traditional classification logic but require high availability.
Aligning inventory classification with procurement strategies—e.g., consignment vs. stock-to-stock—for different part tiers.
Documenting classification rules to ensure consistency across global warehouses and third-party logistics providers.

Module 3: Replenishment Strategy Design

Choosing between min/max, reorder point, and periodic review systems based on supplier reliability and inbound shipment frequency.
Setting safety stock levels that account for both demand variability and supplier quality incidents affecting usable receipt quantities.
Implementing dynamic reorder points that adjust for known upcoming maintenance campaigns or fleet modifications.
Managing replenishment for repairable parts by integrating return forecasts and repair cycle times into net demand calculations.
Coordinating push vs. pull strategies for regional distribution centers serving different service response time commitments.
Adjusting replenishment parameters during supplier transitions or component end-of-life phases to avoid overbuying.

Module 4: Network Design and Multi-Echelon Optimization

Determining optimal stocking locations for slow-moving parts across a multi-tier network (central warehouse, regional depots, field vans).
Calculating transshipment feasibility between sites based on response time SLAs and transportation cost thresholds.
Allocating repair capacity within the network to minimize total turnaround time for high-impact components.
Modeling the impact of localized stocking on total cost of ownership, including inventory, transportation, and downtime.
Establishing rules for emergency bypass shipments that override standard echelon logic during critical outages.
Integrating third-party service centers into the network model with visibility into their spare part holdings and usage patterns.

Module 5: Obsolescence and Lifecycle Management

Triggering last-time buy decisions based on OEM phase-out notices and projected remaining service life of installed equipment.
Assessing the financial impact of holding excess stock for parts supporting end-of-service-life systems.
Coordinating with engineering teams to identify form-fit-function replacements before discontinuation occurs.
Managing cannibalization programs for retired equipment to recover usable parts without disrupting active service operations.
Updating planning parameters for parts in phase-out mode to suppress automatic replenishment recommendations.
Documenting obsolescence risk in service contracts to allocate responsibility between provider and customer.

Module 6: Supplier and Procurement Integration

Negotiating consignment or vendor-managed inventory agreements for high-cost, low-turn parts to reduce working capital.
Validating supplier lead time reliability through performance scorecards and adjusting safety stock accordingly.
Managing dual sourcing strategies for critical parts where single-source risk exceeds acceptable thresholds.
Integrating supplier quality data into procurement decisions—e.g., rejecting orders with high historical defect rates.
Aligning purchase order timing with inbound logistics capacity to avoid dock congestion and receiving delays.
Handling counterfeit part risk by restricting procurement channels and requiring certification for high-risk components.

Module 7: Performance Measurement and Continuous Improvement

Defining and tracking fill rate metrics at the part-location level, not just aggregate warehouse performance.
Conducting root cause analysis on stockouts to distinguish between forecasting error, supply disruption, and demand surge.
Using inventory aging reports to identify obsolete or stagnant stock requiring disposition action.
Conducting periodic plan accuracy audits to validate that system parameters reflect current operational reality.
Measuring the cost of expediting versus planned replenishment to justify investment in forecasting improvements.
Aligning KPIs across planning, procurement, and field service teams to prevent conflicting incentives.

Module 8: Technology and System Configuration

Configuring ERP or EAM systems to differentiate between service, project, and production spare part demand streams.
Mapping part master data attributes to planning rules—e.g., repairable flag, shelf life, hazardous material status.
Enabling system alerts for parts approaching expiration or requiring re-certification after storage.
Integrating IoT and predictive maintenance data into planning systems to anticipate component failures.
Designing user roles and approval workflows for manual overrides to automated planning recommendations.
Validating system-generated recommendations against planner judgment in a structured exception review process.