Nearshoring Inventory and Lead Time Savings Calculator
Moving supply from Asia to Mexico shortens the pipeline, reduces safety stock and lets you order in smaller lots. This calculator puts a dollar value on that inventory release and shows how much of a price premium it can pay for.
Your numbers
Annual spend on the parts you could move to Mexico, at current prices.
How much higher the Mexican unit price is versus the current price.
Include production, ocean transit, port, customs and drayage.
Ocean freight often varies more than road freight; keep the same value to be conservative.
Container and consolidation cadence.
Capital, storage, insurance, obsolescence and shrink.
Your results
Inventory models are simplified. This tool covers pipeline, cycle and safety stock only. Add freight, duties, tariffs, exchange rates, quality cost, tooling and the cost of the transition using your own data and a landed cost comparison.
Annual effect vs Mexico price premium
Sweeps Mexico price premium from 0 to 30, holding your other inputs fixed.
Lead time analysis from ERP data
Optional: we can scope an analysis of actual lead times and demand variability from your ERP history.
Optional. The tool and every export work without this. No spam.
How to use the calculator
Enter the annual spend for the parts you would move, the lead times of both options and your demand variability. The model estimates average inventory in three components for each source, then multiplies the difference by your carrying cost rate. Change the Mexico price premium to see the net effect and read the break-even premium from the results. The chart sweeps the premium from zero to thirty percent.
The method behind it
Pipeline inventory is spend per day times lead time, relevant when you own goods in transit. Cycle stock is half the order quantity, estimated as average weekly spend times the order interval divided by two. Safety stock is Z times the standard deviation of demand over lead time, combining demand variability and lead time variability: Z times the square root of lead time in weeks times the weekly demand variance, plus the squared weekly demand times the squared lead time deviation in weeks.
- Pipeline: daily spend times lead time
- Cycle: weekly spend times interval divided by two
- Safety: Z times demand-over-lead-time deviation
- Carrying saving: inventory difference times carrying rate
Reading the result
A positive net annual effect means that inventory savings cover the price premium on their own. Even when the net is negative, the released working capital is a one-time cash benefit and the lower safety stock reduces stockout and obsolescence risk. Compare the net effect with the freight, duty and tariff difference in a landed cost model. Under USMCA, qualifying goods can enter the US duty-free, but you must hold origin documentation.
Common mistakes
People often count the pipeline inventory even when the supplier owns goods until delivery under their terms, which overstates savings. Check your Incoterms. Others use the same order interval for both sources or ignore that a faster supplier needs a smaller interval to realize the benefit. Finally, remember that the Mexico lead time depends on whether the supplier holds materials locally or imports them from Asia itself.
Frequently Asked Questions
Does the model include freight and duty?
No. It isolates the inventory effect. Use a landed cost calculator for freight, duties and tariffs, then combine the two to compare total cost between sources.
What carrying cost rate should I use?
Use your finance team's number. Typical ranges include cost of capital plus storage, insurance, shrink and obsolescence, often in the high teens to high twenties percent per year depending on the business.
Why does lead time variability matter?
Safety stock must cover both demand variation and the uncertainty of when parts arrive. Ocean freight can vary by weeks, which is a large driver of safety stock for Asian supply.
Is the break-even premium exact?
It is an approximation. The Mexican inventory itself costs more at a higher price, so the exact break-even is slightly lower. Use the chart for the precise crossing point.
If you want these numbers from your actual ERP data, such as real lead time distributions and demand variability by part, we can build a read-only analysis over your history.
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