Supply Chain Analysis Training Course

Participants can map supply chain processes and locate performance gaps using SCOR.

• SCOR Plan, Source, Make, Deliver, Return and Enable processes applied
• Swimlane maps expose handoffs, approvals, queues and information delays
• Value stream maps quantify processing time, waiting time and rework
• Process boundaries set from demand signal through customer delivery
• Bottlenecks identified using throughput, utilisation and cycle-time evidence
• Control points assigned to prevent recurring process failures

Participants can prepare operational data sets for reliable supply chain analysis.

• Data dictionaries define fields, units, owners and refresh frequencies
• Master-data errors identified across products, suppliers, locations and lead times
• Transaction records reconciled against purchase orders, receipts and invoices
• Outliers tested before calculating averages, trends and performance measures
• Missing values treated using documented assumptions and exception flags
• Time-series data aligned across fiscal calendars, weeks and reporting periods

Participants can design performance measures that connect operations to financial outcomes.

• Perfect order rate calculated from complete, on-time and damage-free deliveries
• OTIF measures separated by customer, product, lane and root cause
• Cash-to-cash cycle linked to inventory, receivables and payables
• Inventory turns interpreted alongside service levels and demand volatility
• Balanced scorecards combine reliability, responsiveness, cost, asset and sustainability measures
• Metric trees connect executive targets with controllable operational drivers

Participants can classify demand patterns and select suitable forecasting inputs.

• Demand histories segmented by volume, variability, seasonality and lifecycle stage
• ABC-XYZ analysis classifies items by value and demand predictability
• Promotional, seasonal and event-driven demand effects isolated from baseline demand
• Intermittent demand distinguished from stable and erratic consumption patterns
• Forecastability assessed using coefficient of variation and demand history
• Data cleansing rules remove stockout distortion and exceptional orders

Participants can build and compare baseline forecasts using standard forecasting methods.

• Moving averages calculated for stable demand with selectable periods
• Exponential smoothing models weighted toward recent demand observations
• Seasonal indices applied to recurring monthly or quarterly patterns
• Forecast bias measured using cumulative error and tracking signal
• MAPE, MAD and RMSE compared for forecast accuracy assessment
• Consensus forecasts reconciled with sales, finance and supply assumptions

Participants can set inventory policies using demand, lead-time and service-level data.

• Reorder points calculated from expected demand during replenishment lead time
• Safety stock sized for demand variability, lead-time variability and service targets
• Economic order quantity tested against ordering, holding and purchase costs
• Min-max policies matched to consumption patterns and review frequency
• Service levels translated into fill rate and stockout risk
• Slow-moving and obsolete inventory identified through ageing and movement analysis

Participants can quantify the cash and profitability effects of inventory decisions.

• Inventory carrying costs include capital, storage, insurance and obsolescence
• Working-capital impacts calculated from stock, receivables and supplier terms
• Stock reduction opportunities tested against service and expediter cost
• SKU rationalisation evaluates margin, demand, complexity and replacement risk
• Excess inventory classified by cause, ownership and disposal options
• Cash conversion scenarios compare policy changes and expected benefits

Participants can analyse supplier performance and prioritise supplier-management actions.

• Supplier scorecards weight quality, delivery, cost, responsiveness and compliance
• Kraljic matrix positions categories by profit impact and supply risk
• Delivery performance separated into quantity, timing, quality and documentation failures
• Supplier concentration measured by spend share and source dependency
• Corrective action requests linked to verified performance failure patterns
• Quarterly business reviews structured around commitments, trends and actions

Participants can evaluate procurement options using spend, cost and supplier data.

• Spend cubes analyse expenditure by category, supplier, location and buyer
• Total cost of ownership includes acquisition, operation, failure and disposal
• Should-cost models separate material, labour, overhead and supplier margin
• Price variance traced to specifications, volumes, currencies and index movements
• Make-or-buy analysis compares relevant costs, capacity and strategic control
• Sourcing scenarios evaluate competition, resilience, compliance and transition costs

Participants can analyse transport costs, service outcomes and distribution alternatives.

• Cost-to-serve models allocate transport, handling and delivery costs
• Freight spend analysed by mode, lane, carrier, weight and urgency
• Route performance measured through distance, stops, utilisation and on-time delivery
• Load consolidation opportunities tested against delivery frequency and service commitments
• Incoterms 2020 responsibilities mapped to cost, risk and control points
• Carrier scorecards compare claims, capacity, cost and service reliability

Participants can diagnose warehouse productivity, space and order-fulfilment performance.

• Warehouse process maps trace receiving, put-away, picking, packing and dispatch
• Slotting analysis positions fast-moving items near efficient pick faces
• Pick productivity measured through lines, units, travel time and errors
• Storage utilisation assessed by cube, location occupancy and accessibility
• Order accuracy analysed through mispicks, damages, shortages and returns
• Labour standards compare planned hours, actual hours and output volumes

Participants can compare network and capacity options using demand, cost and service evidence.

• Network maps locate suppliers, plants, warehouses, customers and transport links
• Capacity models compare available hours, utilisation, constraints and demand
• Fixed and variable costs separated for location and capacity decisions
• Centre-of-gravity analysis estimates candidate distribution facility locations
• Scenario analysis tests volume shifts, closures, disruptions and growth
• Service-radius analysis compares delivery lead times and transport costs

Participants can support S&OP decisions with balanced demand, supply and financial analysis.

• S&OP cycle links demand review, supply review and executive decisions
• Demand-supply gaps quantified by period, product family and location
• Capacity alternatives compare overtime, subcontracting, inventory and backlog
• Financial reconciliation converts volume plans into revenue, margin and cash
• Scenario assumptions documented with owners, triggers and decision dates
• Exception reports focus meetings on material variances and unresolved constraints

Participants can assess supply chain risks and define proportionate continuity actions.

• Risk registers capture events, causes, impacts, owners and controls
• FMEA scores failure modes using severity, occurrence and detection
• Supplier risk profiles assess financial, geographic, operational and compliance exposure
• Single-source dependencies quantified by alternatives, lead times and qualification status
• Business continuity plans define triggers, response actions and recovery priorities
• Risk heat maps distinguish high-impact exposures from routine operational issues

Participants can incorporate environmental and social measures into supply chain analysis.

• GHG Protocol Scope 3 categories linked to purchased goods and transport
• Transport emissions estimated from distance, mode, weight and emission factors
• Supplier assessments review labour, safety, environmental and ethical requirements
• Packaging analysis compares material use, damage rates and disposal costs
• Circular flows assess returns, refurbishment, reuse and recovery opportunities
• Sustainability measures balanced against service, cost and supply continuity

Participants can specify practical data, dashboard and governance requirements for supply chain analytics.

• Dashboard requirements begin with decisions, users, thresholds and actions
• Leading indicators distinguish emerging risk from confirmed performance failure
• Control towers combine order, inventory, shipment and exception data
• Data governance assigns ownership, validation rules and access permissions
• Predictive analytics use cases assessed for data quality and decision value
• Automation candidates selected through volume, repeatability, controls and exception rates

Participants can convert analysis findings into prioritised and measurable improvement actions.

• Five Whys analysis tests causal chains behind recurring operational failures
• Fishbone diagrams organise people, process, technology, material and measurement causes
• Pareto analysis identifies high-frequency or high-cost problem categories
• Impact-effort matrices rank initiatives by value, feasibility and urgency
• Benefits cases quantify cost, cash, service, risk and implementation requirements
• Improvement charters assign scope, milestones, owners, measures and governance

Participants can present supply chain analysis clearly to operational and executive stakeholders.

• Executive summaries state decision, evidence, recommendation, benefit and required approval
• Waterfall charts explain cost, inventory and service performance movements
• Scenario comparisons show assumptions, trade-offs, sensitivities and decision implications
• Management presentations separate facts, interpretations, risks and recommended actions
• Data visualisations use appropriate scales, labels, sources and exception markers
• Challenge questions anticipated through evidence trails and documented assumptions

Participants can build, review and present a complete supply chain diagnostic and improvement roadmap.

• Analysis brief defines business problem, scope, stakeholders and decision required
• Process map identifies flow constraints, handoffs and control weaknesses
• Performance dashboard presents service, cost, inventory, cash and risk evidence
• Root-cause findings connect data patterns with validated operational causes
• Improvement roadmap prioritises actions, benefits, owners, milestones and measures
• Management presentation defends recommendations, assumptions, trade-offs and implementation sequence