Should-Cost Analysis

A buyer receives a quote for custom packaging and, rather than demanding a flat discount, models material use, production time, setup, delivery and a supplier margin, which creates questions about the quote. McKinsey describes should-cost as a bottom-up estimate of design, manufacture and delivery plus reasonable profit, and its warning is that assumptions drive the result.

For owners, the analysis helps distinguish a pricing problem from a design or process problem. Define the item first, because specifications, quality level, order size and delivery terms must match the quote, and comparing different products produces a fake gap.

Then map materials, estimating quantities, scrap and input prices, since a small error in a costly material can dominate the model, and map labour with realistic cycle times, wage rates and staffing rather than mixing the best labour rate from one region with another supplier's actual location. Map equipment as well, because machine time, setup, depreciation and maintenance can matter, and a model that ignores capital costs may be impossible for a supplier to meet.

Include overhead such as quality, supervision, rent and utilities, which are real costs even if not visible in each unit, and logistics such as packaging, freight, duties and delivery frequency, matched to the contractual delivery point. Include risk and margin too, because suppliers need a return and may bear demand or inventory risk, so a zero-margin model is not a fair target.

Check volume as well, since unit cost changes with batch size and capacity use, and a quote for 1,000 units should not be benchmarked to a million-unit line. Review specifications, because tolerances, finish and packaging may add cost without helping customers, and engineering and procurement can simplify requirements.

Some savings need changes before production starts, since once tooling is fixed immediate options may be limited. Understand payment terms, because long payment delays can raise financing cost and a cheaper headline price may have a different cash profile, and use current inputs, since commodity prices and exchange rates move, by dating the assumptions and refreshing them before negotiation.

Compare the model with the quote by calculating the gap, then explore which assumptions differ, because the supplier may use a different machine or have higher scrap for a valid reason and it is better to learn before declaring overpricing. Test sensitivity by changing material cost, yield or batch size to see which assumptions matter, and validate the highest-impact assumptions first, because a precise-looking spreadsheet can conceal weak inputs.

Consider alternate suppliers, since a market quote can validate or challenge the model but a lower quote may come with different quality or risk, and avoid squeezing safety, because a target that assumes unsafe staffing or noncompliance is not a legitimate efficiency gain. Coordinate teams, because finance, operations, engineering and procurement each own parts of the estimate and one team alone may miss critical costs.

Document sources such as price lists, engineering estimates and assumptions, since a number without provenance cannot be defended, and respect confidentiality by using any sensitive cost details a supplier shares, under agreed terms, only for the intended negotiation. After changing design or supplier, track actual outcomes against the model and learn from misses, because the best use is improving value rather than merely forcing a target number, and the estimate should improve with each real supplier discussion.