Spare Parts Planning and Forecasting Training Course

Participants can segment spare parts and identify master-data conditions needed for reliable planning.

• Item master data fields governing planning, replenishment, traceability and obsolescence control
• ABC analysis using annual usage value and Pareto concentration
• XYZ classification from demand variability and forecastability measures
• ABC-XYZ matrix assigning differentiated review, service and stocking policies
• FSN analysis identifying fast-moving, slow-moving and non-moving inventory
• Data cleansing rules for duplicates, units, lead times and supersessions

Participants can select and assess forecasting methods for spare parts with irregular demand.

• Demand-pattern diagnosis using average demand interval and squared coefficient variation
• Intermittent-demand characteristics distinguished from lumpy, erratic and smooth consumption
• Croston's method separating demand size from inter-demand interval estimation
• Syntetos-Boylan Approximation correcting Croston bias for intermittent demand
• Moving averages and exponential smoothing for stable, non-intermittent demand
• Forecast error measures: MAD, MAPE, bias and tracking signal
• Forecast value added assessed against naïve and planner-adjusted forecasts

Participants can combine historical consumption with maintenance and engineering information to improve demand plans.

• Maintenance plans converted into time-phased planned spare-part requirements
• Work-order history analysed for failure codes, quantities and replacement intervals
• Installed-base changes incorporated into demand rates and stocking assumptions
• Engineering change notices controlled through effectivity dates and supersession chains
• Project shutdowns and turnarounds separated from recurring maintenance demand
• Planner overrides documented with reason codes, assumptions and expiry dates

Participants can model supply uncertainty and incorporate supplier and repair performance into planning parameters.

• End-to-end replenishment lead time mapped from requisition through goods receipt
• Lead-time distributions measured using purchase-order history rather than supplier promises
• Supplier performance tracked through on-time delivery, completeness and quality measures
• Repair-loop turnaround time modelled for rotable and repairable components
• Minimum order quantities, pack sizes and transport constraints factored into plans
• Supply-risk segmentation combining single-source exposure, geography and substitute availability

Participants can calculate and select replenishment parameters suited to part characteristics and service requirements.

• Continuous-review reorder points calculated from demand, lead time and safety stock
• Periodic-review order-up-to levels set for scheduled purchasing cycles
• Safety stock derived from service targets and demand-lead-time variability
• Cycle service level distinguished from fill rate and equipment availability
• EOQ applied where ordering, holding and demand assumptions remain valid
• Min-max settings aligned with criticality, review frequency and replenishment constraints
• Insurance spares justified through consequence analysis rather than usage frequency

Participants can determine where inventory should be held and assess alternatives to local stocking.

• Multi-echelon stocking roles assigned across central, regional and site warehouses
• Pooling benefits assessed for low-demand parts across multiple operating locations
• Transshipment rules defined for urgent demand, ownership and replenishment responsibility
• Consignment, vendor-managed inventory and framework agreements evaluated for critical items
• Repairable exchange pools balanced against repair capacity and turnaround time
• Stocking-location decisions tested against response time, freight and downtime costs

Participants can manage planning-system exceptions and maintain inventory records that support reliable replenishment.

• MRP parameters aligned with independent demand, dependent demand and maintenance schedules
• Planning exceptions reviewed for shortages, excess stock, reschedule messages and late orders
• Purchase requisitions released using approved planning rules and authority limits
• Cycle-count programmes targeted through ABC class, record accuracy and risk
• Inventory record accuracy investigated using root-cause codes and corrective actions
• Warehouse replenishment signals connected to bin locations, reservations and issue transactions

Participants can identify lifecycle risks and make evidence-based decisions on excess and obsolete spares.

• Obsolescence risk identified from supplier notices, technology changes and declining usage
• Last-time-buy quantities evaluated against forecast horizon, alternatives and carrying cost
• Supersession chains maintained to prevent duplicate buying and unusable residual stock
• Excess and dormant stock segmented by recoverability, return options and disposal
• Disposition decisions compare redeployment, repair, resale, scrapping and controlled retention
• Inventory write-off proposals supported by evidence, approvals and financial impact

Participants can establish performance controls and a prioritised plan for improving spare-parts planning.

• Spare-parts KPI hierarchy linking availability, service, inventory investment and obsolescence
• Dashboard measures defined for forecast accuracy, fill rate, turns and stockouts
• Monthly planning cadence assigns inputs, decisions, escalation routes and owners
• Parameter-review triggers set for demand shifts, lead-time changes and criticality revisions
• RACI matrix clarifies planner, maintenance, engineering, procurement and warehouse accountabilities
• 90-day improvement plan prioritises data, policy and supplier actions