CSCM cheat sheet

Supply chain scope: plan, source, make, deliver, return (and enable) processes spanning tier-2 suppliers through end customers.

Bullwhip effect: order variability amplifies upstream; causes include demand forecast updating, order batching, price fluctuation, rationing/gaming. Countermeasures: EDI/CPFR, everyday low pricing, vendor-managed inventory, shorter lead times.

Strategic fit: competitive strategy (cost vs. responsiveness) must align with supply chain strategy; zone of strategic fit is where responsiveness matches implied demand uncertainty.

Push/pull boundary: push processes operate on forecast; pull processes respond to actual demand. Postponement moves the boundary downstream to reduce forecast risk.

Lean vs. agile: lean suits functional products with low demand uncertainty; agile suits innovative products with high uncertainty (Fisher's framework).

Total landed cost includes unit price + freight + duties/tariffs + insurance + handling + inventory carrying cost + quality/risk cost; use for sourcing decisions, not unit price alone.

SCOR model levels: Level 1 (process types: Plan, Source, Make, Deliver, Return, Enable), Level 2 (process categories), Level 3 (process elements).

Cash-to-cash cycle = days inventory outstanding + days sales outstanding − days payables outstanding; lower is better for working capital.

Make vs. buy drivers: volume, capability, IP protection, capacity, total cost, strategic control; outsourcing shifts fixed cost to variable but adds coordination risk.

Moving average: forecast = average of last n periods; larger n smooths more but reacts slower to trend.

Exponential smoothing: F(t+1) = α·A(t) + (1−α)·F(t); higher α weights recent demand more.

Holt's method adds trend: level L(t) = α·A(t) + (1−α)(L(t−1)+T(t−1)); trend T(t) = β(L(t)−L(t−1)) + (1−β)T(t−1).

Winter's method adds seasonality: multiply by seasonal index S(t) updated with γ; use when seasonal pattern repeats.

Forecast error metrics: MAD = Σ|A−F|/n; MSE = Σ(A−F)²/n; MAPE = (100/n)Σ|A−F|/A (undefined when A=0); bias = Σ(A−F)/n (should be near zero).

Tracking signal = running sum of forecast errors / MAD; |TS| > 4–6 signals forecast model out of control.

Forecast hierarchy: aggregate then disaggregate; top-down vs. bottom-up; reconcile to avoid inconsistent plans.

Qualitative methods: Delphi (anonymous iterative expert consensus), market research, sales force composite, panel consensus; use when little history or new product.

Forecast accuracy improves with shorter lead times and demand sensing; forecast is always wrong - plan safety stock for error, not just average demand.

Procurement cycle: requisition → supplier selection → PO/contract → receipt → invoice match (3-way match: PO, receipt, invoice) → payment.

Supplier selection criteria: quality, cost, delivery, service, financial stability, capacity, geographic risk; use weighted scorecard.

Kraljic matrix: leverage (high spend, low risk) → competitive bidding; strategic (high spend, high risk) → partnership; bottleneck (low spend, high risk) → secure supply/dual source; non-critical → simplify.

Supplier relationship spectrum: transactional → preferred → strategic partnership → alliance; governance intensity rises with strategic importance.

Total cost of ownership (TCO) includes acquisition, operating, maintenance, disposal, and risk costs; use for capital and long-term contracts.

Contract types: fixed-price (supplier bears cost risk), cost-plus (buyer bears cost risk), incentive contracts share risk; choose by cost uncertainty.

Supplier scorecard metrics: on-time delivery (OTD), defect rate (PPM), lead time, responsiveness, cost reduction, compliance.

Single vs. dual sourcing: single source lowers cost and simplifies coordination but raises disruption risk; dual sourcing adds volume split and coordination cost.

Ethical sourcing: audit labor practices, conflict minerals, environmental compliance; traceability to tier-2 and tier-3 suppliers.

S&OP cycle: demand review → supply review → reconciliation → executive review → implementation; monthly cadence, 18–24 month horizon.

Aggregate planning strategies: level (constant output, inventory absorbs demand), chase (output matches demand, hiring/firing), hybrid (overtime, subcontract, backorder).

MRP inputs: MPS, BOM, inventory records; outputs: planned orders, order releases, rescheduling notices. MRP II adds capacity and financial planning.

MRP lot-sizing: lot-for-lot (no leftover), EOQ (minimizes order + holding cost), fixed-period, Wagner-Whitin (dynamic programming optimum).

Capacity planning: RCCP (rough-cut, checks key resources against MPS), CRP (detailed capacity vs. MRP), finite vs. infinite loading.

Scheduling rules: EDD (earliest due date) minimizes maximum lateness; SPT (shortest processing time) minimizes average flow time; FCFS is fair but often inefficient.

Theory of Constraints: identify bottleneck → exploit → subordinate → elevate → repeat; throughput constrained by bottleneck.

Lean tools: 5S, kanban (pull signal), value stream mapping, SMED (setup reduction), poka-yoke (error proofing), JIT.

OEE = availability × performance × quality; measures equipment effectiveness.

EOQ = √(2DS / H), where D = annual demand, S = order cost, H = annual holding cost per unit; minimizes total order + holding cost.

Reorder point (ROP) = demand during lead time + safety stock (for continuous review).

Safety stock = z × σ_LT, where z is service-level factor (e.g., 95% → 1.65, 99% → 2.33) and σ_LT is demand std dev over lead time.

Periodic review order quantity = target level − inventory position; target = demand over (review period + lead time) + safety stock.

Inventory carrying cost typically 20–30% of unit value per year (capital, storage, obsolescence, insurance, taxes).

ABC classification: A items ~80% of value, ~20% of SKUs; B ~15%/30%; C ~5%/50%; tighter control for A.

Inventory turnover = COGS / average inventory; days of supply = 365 / turnover.

Newsvendor critical ratio = Cu / (Cu + Co), where Cu = underage cost, Co = overage cost; optimal service level for single-period inventory.

Inventory types: cycle stock, safety stock, in-transit, seasonal, speculative, MRO; each has different drivers.

Transportation modes: truck (flexible, moderate cost), rail (bulk, low cost, long haul), air (fast, expensive), water (slowest, cheapest for bulk), pipeline (liquids/gas).

Cost trade-offs: transportation cost vs. inventory cost vs. customer service; faster transport reduces inventory but raises freight.

Incoterms define risk/cost transfer: EXW (buyer bears all), FOB (risk transfers at ship), CIF (seller pays insurance/freight to destination), DDP (seller bears all including duty).

Freight terms: FOB origin (buyer pays freight, owns in transit) vs. FOB destination (seller pays, owns until delivery).

Consolidation: combine shipments to reduce cost; break-bulk: split large shipments for delivery.

Cross-docking: flow goods from inbound to outbound with minimal storage; requires synchronized schedules and accurate labeling.

Last-mile delivery is often 30–50% of total logistics cost; route optimization and lockers reduce cost.

Distribution network: centralized (lower inventory, longer lead time) vs. decentralized (faster service, more inventory).

Landed cost = freight + duty + insurance + handling + inventory carrying cost; use for mode/route decisions.

Warehouse functions: receiving, put-away, storage, picking, packing, shipping, returns; each has KPIs.

Storage types: pallet racking (selective, high density), drive-in (LIFO), push-back (LIFO), flow rack (FIFO), cantilever, mezzanine.

Slotting: place high-velocity items in golden zone (waist-to-shoulder height) near shipping to reduce pick travel.

Picking methods: discrete (one order at a time), batch (multiple orders), zone (pick by area), wave (scheduled release); choose by order profile.

ABC velocity slotting: A items nearest pick faces; C items in reserve or high locations.

Materials handling equipment: forklifts, pallet jacks, conveyors, AS/RS (automated storage and retrieval), AGVs; match to throughput and SKU profile.

Warehouse KPIs: lines picked per hour, order accuracy, dock-to-stock time, inventory accuracy, space utilization, cost per order.

Safety: OSHA forklift training, rack inspections, load capacity limits, aisle width for equipment.

Cross-docking and flow-through reduce storage dwell time; requires supplier compliance and labeling accuracy.

Order-to-cash cycle: order capture → credit check → fulfillment → invoicing → payment; measure cycle time and perfect order rate.

Perfect order = complete, on time, damage-free, correct documentation; perfect order rate = (perfect orders / total orders) × 100.

Customer segmentation: RFM (recency, frequency, monetary value) or ABC by profitability; service levels should reflect segment value.

Order promising: ATP (available to promise) uses current inventory; CTP (capable to promise) uses capacity; AATP (allocation ATP) reserves supply by priority.

CRM functions: sales force automation, customer service, marketing automation, analytics; data quality is critical.

Service level metrics: fill rate, on-time delivery, order accuracy, response time, first-contact resolution.

Customer lifetime value (CLV) = average order value × purchase frequency × retention duration × margin; guides retention investment.

Returns management (reverse logistics): authorize, receive, inspect, disposition (restock, refurbish, recycle, scrap); track return rate and reason codes.

Omnichannel: consistent inventory visibility and fulfillment across channels (BOPIS, ship-from-store).

Risk categories: supply (supplier failure, quality), demand (volatility, forecast error), operational (IT, labor, equipment), financial (currency, credit), geopolitical, natural disasters.

Risk management cycle: identify → assess (probability × impact) → mitigate → monitor → respond.

Mitigation: dual sourcing, safety stock, buffer capacity, flexible contracts, nearshoring, visibility tools, business continuity plans.

Resilience capabilities: visibility, redundancy, flexibility, collaboration, agility; time-to-recover (TTR) and time-to-survive (TTS) metrics.

Supply chain mapping: identify tier-2/tier-3 dependencies and single points of failure; sub-tier visibility reduces hidden risk.

Sustainability: triple bottom line (people, planet, profit); ESG reporting; carbon footprint (Scope 1, 2, 3 emissions).

Circular supply chain: design for reuse/recycling, take-back programs, reverse logistics; reduces waste and resource dependence.

Regulatory: conflict minerals, REACH/RoHS, modern slavery acts, carbon disclosure; compliance requires supplier data.

Risk quantification: probability-impact matrix, Monte Carlo simulation, scenario planning; use to prioritize mitigation spend.