Inventory Management and Optimisation Training Course

Participants can assess inventory data quality and establish a reliable performance baseline.

• Required fields: SKU, location, unit, lead time, cost, and status
• Master-data errors causing false replenishment signals and inaccurate inventory valuation
• Data cleansing rules for duplicate SKUs, inactive codes, and unit conversions
• Baseline stock profile built from value, volume, movement, and ageing
• Exception reports identifying negative balances, blocked stock, and open orders
• Root-cause analysis using five whys and process walk-throughs

Participants can segment stock portfolios and assign control policies suited to item behaviour.

• ABC analysis using annual usage value and cumulative percentage thresholds
• XYZ classification based on demand variability and forecastability measures
• ABC-XYZ matrix translated into review frequency, service, and replenishment rules
• FSN analysis distinguishing fast, slow, and non-moving stock
• Criticality ranking for safety, regulatory, operational, and customer-impact items
• Policy matrix assigning planners, review cycles, and escalation triggers

Participants can select and calculate suitable forecasts for common inventory demand patterns.

• Demand patterns: level, trend, seasonality, intermittency, and lifecycle change
• Moving averages selected using demand stability and planning horizon
• Exponential smoothing with alpha values matched to demand responsiveness
• Seasonal indices calculated from historical demand and calendar periods
• Croston’s method applied to intermittent spare-parts demand
• Forecast bias, MAD, MAPE, and tracking signal interpreted correctly

Participants can quantify lead-time exposure and incorporate supply uncertainty into inventory decisions.

• End-to-end lead time mapped from requisition through receipt and put-away
• Lead-time components separated into supplier, transport, customs, and receiving delays
• Average and variable lead time calculated from purchase-order history
• Supplier OTIF performance linked to replenishment parameter reviews
• Risk register covering single sourcing, disruption, quality, and geopolitical exposure
• Lead-time reduction opportunities prioritised using process and supplier evidence

Participants can calculate safety stock using demand, lead-time variability and defined service targets.

• Cycle service level distinguished from fill rate and availability
• Safety stock calculated for variable demand with constant lead time
• Combined demand and lead-time variability incorporated into safety-stock calculations
• Z-values selected from service-level targets and normal distribution tables
• Service differentiation applied across ABC-XYZ and criticality segments
• Safety-stock review triggered by forecast error, lead-time, or policy changes

Participants can set and maintain reorder points for continuously reviewed inventory items.

• Reorder point calculated from expected lead-time demand plus safety stock
• Continuous-review logic applied to high-value and high-criticality SKUs
• Demand during lead time estimated from daily, weekly, or monthly data
• Order triggers checked against open orders, reservations, and usable stock
• Reorder-point exceptions investigated through demand, supply, and record analysis
• Parameter governance assigns approval limits, review dates, and audit trails

Participants can select order quantity rules that balance transaction cost, holding cost and constraints.

• Economic order quantity calculated from demand, ordering cost, and holding cost
• EOQ assumptions tested against discounts, capacity, shelf life, and minimums
• Min-max parameters set from demand, review period, and service policy
• Periodic-review order-up-to levels calculated for scheduled replenishment cycles
• Fixed-order quantities compared with lot-for-lot and economic batch rules
• Supplier minimum order quantities challenged using total-cost analysis

Participants can connect inventory policies with production schedules, bills of materials and MRP signals.

• Dependent demand distinguished from independent demand in planning systems
• Bill-of-materials accuracy checked before MRP parameter changes
• MRP netting considers on-hand stock, scheduled receipts, and allocations
• Lot-sizing rules assessed for setup cost, capacity, and schedule stability
• Safety time compared with safety stock for production-material protection
• Work-in-progress controls linked to bottlenecks, queues, and throughput

Participants can use inventory information to support cross-functional planning and decision making.

• S&OP cycle connects demand plans, supply plans, inventory, and finance
• Inventory projections calculated from opening stock, supply, and demand
• Capacity constraints exposed through projected shortages and inventory buildup
• Scenario planning tests demand uplift, supply delay, and service changes
• Consensus assumptions documented with owners, dates, and decision thresholds
• Executive inventory dashboard highlights risks requiring cross-functional action

Participants can allocate inventory across central, regional and local stocking locations.

• Echelon inventory defined across supplier, central warehouse, and field locations
• Centralisation trade-offs assessed using demand pooling and response-time requirements
• Deployment rules allocate stock by priority, demand, and transport constraints
• Lateral transshipments evaluated against cost, urgency, and service commitments
• Decoupling points located between forecast-driven and order-driven operations
• Network stock targets reconciled with warehouse capacity and handling capability

Participants can design warehouse controls that improve stock-record accuracy and traceability.

• Inventory record accuracy measured through count variance and location accuracy
• Cycle-counting frequencies assigned using ABC value and operational risk
• Blind counts, recounts, and tolerance rules strengthen count integrity
• Root causes classified across receiving, put-away, picking, adjustments, and returns
• Barcode and RFID controls compared for identification and transaction capture
• Inventory adjustments governed through authorisation, evidence, and variance reporting

Participants can assess how storage design and handling practices affect inventory availability and cost.

• Slotting analysis uses velocity, cube, weight, and pick-frequency data
• Fixed, random, and class-based storage compared for control requirements
• Location capacity calculated using pallet positions, cube utilisation, and constraints
• FIFO, FEFO, and serial tracking selected by product characteristics
• Put-away rules protect segregation, compatibility, and temperature requirements
• Picking errors reduced through location labelling, verification, and replenishment discipline

Participants can apply specialised controls to inventory with expiry, traceability and availability requirements.

• FEFO controls applied to expiry-dated pharmaceuticals, food, and laboratory materials
• Batch, lot, and serial traceability maintained through receipt-to-issue records
• Cold-chain exceptions investigated using temperature logs and quarantine procedures
• Shelf-life risk quantified from expiry profiles and projected consumption
• Controlled-item access rules separate custody, authorisation, and reconciliation duties
• Critical-spares policies balance equipment downtime risk against carrying cost

Participants can identify, value and reduce inventory that no longer supports expected demand.

• Ageing buckets designed around movement history, shelf life, and policy
• Excess stock calculated against forecast, consumption, and target inventory
• Obsolescence indicators include supersession, project closure, and demand cessation
• Disposition routes compare redeployment, return, repair, sale, donation, and disposal
• Provisioning evidence prepared using accounting policy and inventory condition
• Prevention actions address parameter errors, engineering changes, and purchasing discipline

Participants can measure inventory performance and communicate the financial case for improvement.

• Inventory turns calculated using cost of goods sold and average inventory
• Days on hand compared across SKU classes, sites, and product families
• GMROI links gross margin return with average inventory investment
• Stockout cost estimated from margin loss, expedite, and disruption consequences
• Inventory reduction benefits separated from one-off releases and recurring savings
• Balanced KPI set combines service, cash, accuracy, ageing, and productivity

Participants can establish controlled processes for maintaining inventory planning parameters in ERP systems.

• ERP parameter fields mapped to planning logic and replenishment behaviour
• Parameter change requests include evidence, owner, approval, and effective date
• Master-data governance defines stewardship, validation, escalation, and periodic review
• Planning-system alerts filtered by materiality, urgency, and root cause
• User access controls protect inventory adjustments and parameter maintenance
• Control calendar schedules forecast, parameter, count, and ageing reviews

Participants can plan an inventory improvement initiative with measurable benefits and sustained controls.

• Problem statement defines affected SKUs, locations, service, and financial impact
• Pareto analysis focuses improvement effort on material inventory drivers
• A3 problem-solving structure records condition, cause, countermeasures, and follow-up
• Pilot scope selected using risk, data quality, and implementation feasibility
• Benefits tracker measures baseline, target, realised value, and ownership
• Control plans embed review routines, escalation paths, and compliance checks

Participants can align supplier agreements and purchasing practices with inventory policy requirements.

• Supplier segmentation links replenishment strategy with supply risk and spend
• Framework agreements specify lead time, flexibility, MOQ, and service measures
• Vendor-managed inventory assessed for data quality, ownership, and accountability
• Consignment stock evaluated for cash impact, control, and demand visibility
• Collaborative forecasts shared through agreed horizons, versions, and exceptions
• Supplier scorecards combine OTIF, quality, responsiveness, and lead-time variability

Participants can build, review and present a complete inventory optimisation plan for a defined SKU portfolio or warehouse operation.

• Scope statement defines portfolio, sites, objectives, constraints, and stakeholders
• Baseline analysis quantifies service, inventory value, ageing, accuracy, and risks
• ABC-XYZ segmentation selects differentiated control and replenishment policies
• Forecast, safety-stock, reorder-point, and order-quantity assumptions documented
• Improvement roadmap assigns actions, owners, milestones, benefits, and controls
• Peer review challenges financial logic, service impacts, data, and implementation risks