SLLC Intermediate cheat sheet

Supply chain surplus = customer value − total supply chain cost; strategy is aligned when all functional policies maximize this surplus.

Strategic fit requires two alignments: competitive strategy with supply chain strategy, and supply chain strategy with all functional strategies (sourcing, production, distribution).

Responsiveness spectrum: efficient supply chains win on cost for predictable, low-margin demand; responsive supply chains absorb uncertainty for high-margin, volatile demand.

Facility location decision rule: place facilities where the sum of inbound and outbound transport cost plus fixed and variable operating cost is minimized over the planning horizon.

Center-of-gravity approximation: x* = Σ(wᵢ·xᵢ)/Σwᵢ and y* = Σ(wᵢ·yᵢ)/Σwᵢ, where wᵢ is volume and (xᵢ, yᵢ) demand coordinates.

Total landed cost includes unit price, freight, duties and tariffs, insurance, inventory carrying cost, and quality or risk cost - not purchase price alone.

Postponement (delayed differentiation) moves product differentiation downstream, reducing safety inventory of finished goods while raising component commonality.

Bullwhip effect causes: demand signal processing, order batching, price fluctuation, rationing and shortage gaming; sharing POS data and EDI reduces amplification.

Moving average of order n: Fₜ₊₁ = (Dₜ + Dₜ₋₁ + … + Dₜ₋ₙ₊₁)/n; larger n smooths noise but lags trend.

Simple exponential smoothing: Fₜ₊₁ = αDₜ + (1 − α)Fₜ; α near 1 reacts fast, α near 0 is stable.

Holt's method adds trend: level Lₜ = αDₜ + (1 − α)(Lₜ₋₁ + Tₜ₋₁); trend Tₜ = β(Lₜ − Lₜ₋₁) + (1 − β)Tₜ₋₁.

Winter's method adds seasonality with seasonal index Sₜ = γ(Dₜ/Lₜ) + (1 − γ)Sₜ₋ₚ for period length p.

Forecast error measures: MAD = Σ|Dₜ − Fₜ|/n; MSE = Σ(Dₜ − Fₜ)²/n; MAPE = (100/n)Σ|Dₜ − Fₜ|/Dₜ.

Bias = Σ(Dₜ − Fₜ)/n; a tracking signal = running forecast error / MAD flags persistent bias when it exceeds a control limit (commonly ±4).

Forecast hierarchy: aggregate plans use long-horizon, low-variance forecasts; SKU-level forecasts are disaggregated and inherently noisier.

Qualitative methods (Delphi, sales force composite, market research) apply when history is absent or discontinuous; quantitative methods need stable historical patterns.

Kraljic matrix axes: profit impact (purchase value) and supply risk; quadrants are leverage, strategic, non-critical, and bottleneck items.

Leverage items: many suppliers, high spend - use competitive bidding and volume consolidation; bottleneck items: few sources - secure supply and seek substitutes.

Supplier scorecard dimensions: quality (PPM defects), delivery (on-time-in-full), cost, responsiveness, and sustainability or compliance performance.

Total cost of ownership for a supplier bid = price + freight + inventory carrying + inspection + defect and rework + switching and risk cost.

Early supplier involvement in design reduces downstream engineering change cost; roughly 70–80% of product cost is committed at the design stage.

Single sourcing lowers unit cost and improves coordination but raises concentration risk; dual sourcing trades price for continuity.

Purchase order terms to verify: Incoterms rule, payment terms, delivery date, quantity tolerance, inspection rights, and warranty.

e-Procurement levers: catalog-based requisitioning, punch-out to supplier sites, automated three-way match (PO, receipt, invoice), and spend analytics.

Economic order quantity: EOQ = √(2DS/H), where D = annual demand, S = order cost, H = annual holding cost per unit.

At EOQ, annual ordering cost equals annual holding cost; total relevant cost = √(2DSH).

Reorder point with demand and lead-time variability: ROP = d̄·L + z·σDL, where z is the service-level factor (z = 1.65 for 95%).

Safety stock = z·σDL; it rises with the square root of lead time and with the target service level.

Newsvendor critical ratio: optimal service level = Cu/(Cu + Co), where Cu = underage cost and Co = overage cost.

Aggregate planning strategies: level (constant workforce, inventory buffers), chase (match capacity to demand), and mixed; choose by lowest total of hiring, layoff, inventory, and stockout cost.

MRP record: gross requirements − scheduled receipts − on-hand + safety stock = net requirements; planned order release = planned order receipt offset by lead time.

ABC classification: class A is roughly 10–20% of SKUs and 70–80% of annual value; counts and controls tighten with class.

Warehouse activity sequence: receiving, put-away, storage, replenishment, order picking, packing, and shipping.

Order picking is typically 50–60% of warehouse operating labor; batching, zone picking, and slotting are the main levers to cut it.

Slotting rule: assign high pick-frequency, low-cube SKUs to golden-zone locations near dispatch to minimize travel time.

Cube utilization = occupied storage volume / available storage volume; space utilization = occupied locations / total locations.

Throughput capacity of a picker or station = 1 / (travel time + pick time + handling time) per unit.

Cross-docking bypasses storage: goods flow from receiving to outbound trailers; it requires tight inbound-outbound synchronization and accurate labeling.

Selective rack gives direct access to every pallet; drive-in and push-back racks raise density but reduce selectivity.

Cycle counting validates inventory records continuously by counting a subset of SKUs on a rotating schedule rather than on an annual shutdown.

Mode selection trade-off: cost per ton-mile, speed, reliability, and accessibility; rail and water are cheapest per ton-mile, air and parcel fastest.

Freight class and rate = weight × rate per unit, with minimum charges and fuel surcharges applied on top of the base rate.

Incoterms allocate cost, risk, and responsibility: EXW (buyer takes most risk), FOB (risk transfers at the ship's rail), CIF (seller pays freight and insurance), DDP (seller delivers duty paid).

Consolidation lowers cost per shipment by combining LTL loads into truckload quantities or by pooling shipments across buyers.

Vehicle routing problem: minimize total distance or cost while satisfying capacity, time windows, and driver-hour constraints.

Milk-run routing collects from multiple suppliers on one tour; savings depend on geographic density and pickup windows.

Cost per mile = (fixed vehicle cost / annual miles) + variable cost per mile; decision rule compares private fleet cost to common carrier rates.

Last-mile delivery is the highest cost per unit in the parcel chain because of low drop density and repeated failed attempts.

Order cycle time = order receipt to delivery; it is decomposed into order entry, processing, picking, packing, and transit time.

Perfect order rate = (orders delivered complete × on time × damage free × correct documentation) / total orders.

Fill rate measures units shipped against units ordered; order fill rate measures complete orders against orders received.

OTIF (on time in full) is the standard retail service metric; it combines delivery timing and order completeness in one ratio.

Customer service segmentation: apply the highest service level and shortest cycle time to A customers and key accounts, not uniformly to all.

Service recovery rule: the cost of a failure grows with detection delay; front-line authority to resolve complaints reduces escalation cost.

Cost-to-serve = allocated order handling, transport, returns, and inventory cost per customer or channel; it often reveals unprofitable small-order accounts.

Reverse logistics flows (returns, repairs, recalls) require separate process design; return rates above 20% in e-commerce make it a core process.

System hierarchy: ERP (transactions and finance), APS (planning and optimization), WMS (warehouse execution), TMS (transport execution).

EDI replaces paper documents with standardized messages: 850 purchase order, 856 advance ship notice, 810 invoice, 940 warehouse shipping order.

RFID enables non-line-of-sight, bulk reads; barcode scanning is cheaper and more reliable for item-level accuracy where line of sight exists.

Control tower visibility depends on data latency: batch EDI gives hours of delay, API or streaming integration gives near real time.

Descriptive, diagnostic, predictive, and prescriptive analytics form an ascending ladder; most supply chain value today sits in predictive and prescriptive use.

Data quality rule: inventory and forecast accuracy are bounded by master data accuracy (item, location, supplier, and unit of measure).

KPI dashboards should pair a service metric (OTIF, fill rate) with a cost metric (cost per order, inventory turns) to avoid suboptimization.

Blockchain or distributed ledger is useful where multiple parties need a shared, tamper-evident record of custody, not as a general database.

Risk exposure = probability of disruption × financial impact; mitigation is justified when expected loss exceeds mitigation cost.

Risk response options: avoid, mitigate (buffer stock, dual sourcing), transfer (insurance, contracts), and accept.

Time to recover and time to survive: resilience requires recovery time shorter than the time the business can operate without the node.

Concentration risk: a single-source or single-site dependency on a high-revenue product is a top-tier risk regardless of spend size.

Scope 1 (direct emissions), Scope 2 (purchased energy), and Scope 3 (upstream and downstream value chain) are the GHG Protocol categories.

Sustainability levers with measurable effect: load consolidation, mode shift to rail, backhaul utilization, packaging reduction, and reverse flows.

Customs compliance elements: correct HS tariff classification, country-of-origin rules, valuation, and restricted-party screening.

Regulatory drivers to know: conflict minerals due diligence, product take-back and extended producer responsibility, and modern slavery disclosure.