Supply chain cases optimize landed cost, working capital, and service together. The cheap factory is often the expensive network.
Last full pass: 24 August 2026.
Kearney, McKinsey Ops, BCG, Bain, and operations boutiques will give you a network, a dual-source, or a service-level prompt because candidates still compare ex-works unit cost and call it a day. This is not a generic operations plant-OEE case (though OEE can show up). It is not a restructuring 13-week cash case, unless the chain is already breaking vendors. It is the flow of goods, cash, and risk from supplier to customer.
What you are deciding
- Where to make / buy (landed cost + lead time + tariff + risk).
- How much inventory (days, not “lean” as a slogan) for a service target.
- Network: number of DCs, postponement, make-to-stock vs make-to-order.
- Resilience: dual source vs single source with a larger buffer.
Clarify the service metric (OTIF, fill rate, lead time). Clarify Incoterms (who pays freight). Clarify whether “savings” are P&L or just a standard-cost illusion. Ask if demand is steady or spiky — a 58-day ocean pipeline is a different risk than a 18-day truck lane even at the same annual volume. Ask who owns expedites in the budget (often they sit in “other,” which is how China still looks cheap).
Open with: (1) service target, (2) landed cost build, (3) pipeline and safety stock, (4) dual-source / disruption, (5) SKU policy (A vs C). Do not start with a plant-OEE tree unless the bottleneck is clearly inside the four walls.
Exhibits you should expect
| Exhibit | Trap |
|---|---|
| Unit cost by country | Missing freight, duty, inventory, quality, and expedites. |
| Lead time and variability | Safety stock lives on variability, not on the mean. |
| Fill rate vs inventory days | 99% vs 96% is not “3 points of niceness”; it is a cost curve. |
| Supplier scorecard | Single-source 8% cheaper until a 6-week shutdown. |
| Demand by SKU (ABC) | One policy for all SKUs is a fail. |
Units that trip people
Total landed cost = product + freight + duty + packaging + quality yield + carrying cost of pipeline inventory.
Inventory days / turns. Carrying cost ≈ inventory × WACC (or a stated 15–20% case rate).
Service: fill rate, OTIF, backorder days. Pick one and hold it constant when you compare networks.
MOQ and container utilization. A cheap unit cost at 40% cube is not cheap.
Practice a supply-chain landed-cost case
Run a scored case where ex-works cost and landed cost disagree.
Worked mini-case: $4.20 China vs $5.10 Mexico
Prompt. A consumer-hardware client buys a component ex-works China $4.20 vs Mexico $5.10 (case inputs). China: freight $1.40, tariff 12% of ex-works, pipeline 58 days. Mexico: freight $0.45, tariff 0, pipeline 18 days. Carrying cost 18%/year. Quality yield both 99% (so ignore scrap). Which source wins on landed cost? Volume is steady.
Math. China product+freight+tariff = 4.20 + 1.40 + 0.12×4.20 = $6.104. Pipeline carrying = 6.104 × 58/365 × 0.18 ≈ $0.175. Landed ≈ $6.28.
Mexico = 5.10 + 0.45 + 0 = $5.55. Carrying = 5.55 × 18/365 × 0.18 ≈ $0.049. Landed ≈ $5.60.
Mexico wins by ~$0.68/unit (about 11%) despite a higher sticker. If the procurement slide only showed $4.20 vs $5.10, they would have picked China and added 40 days of risk.
Recommendation. Move the steady volume to Mexico; keep a qualified China dual source for surge (pay the higher landed cost on the overflow, not on the base). Do not 100% single-source Mexico until the plant has a second tool. For SKUs with spiky demand, the 58-day pipeline is a service problem, not just a carrying-cost line. Next exhibit: demand CV by SKU and expedite $ last year (often the hidden China cost).
What a generic profitability tree misses here
- COGS is not the PO price. Landed + quality + expedite + inventory.
- Time is inventory and lost sales. A 4-week miss is a revenue case, not only a cost case.
- Service is a constraint, like a hospital’s readmission cap — you cannot “save” your way to 92% fill if the contract is 98%.
- Risk is a cost (dual source, insurance, buffers) even if it does not hit this month’s P&L.
- Network effects: one cheap plant can congest a DC or a port.
If you treat this like a retail comps case, you will talk stores. If you treat it like energy, you will talk MW. The units here are $/landed unit, days, and fill rate.
See where you stand on a supply-chain case
Practice landed cost and the inventory–service tradeoff.
Related guides
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