Insight · Sourcing

Should-cost modelling: a practical guide for buyers

A should-cost model estimates what a component, product or service should cost to produce and deliver - materials, labour, overhead, logistics and a fair margin. Done well, it changes the shape of a negotiation. Done badly, it hands the supplier a script. The stakes are real: energy and material costs alone account for 35-55% of manufacturing production costs in Germany and 20-60% across sectors in the Netherlands - roughly 49% of total costs for Dutch industrial firms overall [1] - so getting the material line wrong in a should-cost model undermines the whole negotiation.

By Matt Buckley

When should-cost is worth the effort

  • High-volume, high-spend components where a few percent moves the number
  • Bespoke items with no market benchmark
  • Categories with a small supplier base and limited competitive tension
  • Any sole-source or single-source renegotiation
  • New product introduction where target costing is required

The cost driver tree

Every should-cost model breaks price into five buckets:

  • Direct material - specification, grade, yield, scrap and indexed input prices.
  • Direct labour - cycle time, labour rate for the geography, indirect labour ratio. EU hourly labour costs range from around EUR 11 to EUR 55 depending on the country, with wages and salaries making up roughly three-quarters of total labour cost [2], so geography is a first-order variable, not a rounding error.
  • Machine / process - machine rate, setup time, tooling amortisation.
  • Overhead - factory overhead, SG&A, freight, packaging, duty.
  • Margin - a defensible profit assumption for the supplier's segment.

Where the data comes from

Those PBL and Eurostat ranges are also the reason a should-cost model has to be built bottom-up per category: input-cost structure varies far too much across geographies and sectors to apply a single benchmark [1, 2].

  • Public commodity indices (LME, ICIS, Argus, Eurostat) for raw materials
  • Regional labour rate databases and manufacturing benchmarks
  • Reverse-engineered bills of materials and teardown analysis
  • Supplier RFI data, filed accounts and analyst reports
  • Internal engineering estimates - the most under-used source

From model to lower price

The model does not negotiate for you. Three moves make it pay:

  • Anchor - open with a target price grounded in the model, not the current price minus 5%.
  • Decompose - discuss line items (material, labour, overhead) not the total. It changes what "reasonable" looks like.
  • Index - agree pass-through mechanics tied to public indices so future moves are automatic, not negotiated.

Common failure modes

  • Model built once, never refreshed as indices move
  • Engineering builds the model, procurement does not use it in the room
  • Margin assumption too aggressive - supplier walks or quality slips
  • No fallback if the supplier refuses to open the books

Related reading

Should-cost is one lever in a wider set. See the seven-lever cost reduction playbook and the sequenced strategy guide for how to combine it with demand and specification work.

We apply should-cost models inside our cost reduction consulting and procurement consultancy work, using classified data from a spend analytics baseline and applying the same logic to sourced goods under product sourcing.

What is should-cost modelling?

Should-cost modelling estimates what a product, component or service should cost to produce and deliver - built up from material, labour, machine, overhead and a fair margin - so buyers can negotiate against a fact base rather than last year's price.

When is should-cost worth the effort?

Any sole- or single-source renegotiation, high-volume components where a few percent moves the number, bespoke items with no market benchmark, and new product introductions where target costing is required.

How accurate does the model need to be?

Directional. A model within 10-15% of actual cost is enough to change the shape of a negotiation. Chasing the last 2% of accuracy usually costs more in engineering time than it recovers in savings.

What data sources feed a should-cost model?

Public commodity indices (LME, ICIS, Argus), regional labour rate benchmarks, teardown analysis, supplier RFI data, filed accounts and - most under-used - internal engineering estimates for cycle time and material use.

References

Every figure cited above is drawn from the independent sources below. Numbers in square brackets in the text link to the matching source.

  1. Share of raw material costs in total production costsPBL Netherlands Environmental Assessment Agency
  2. Labour cost structural statisticsEurostat

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