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June 25, 2026

What Is Should-Cost Modeling? A Primer for Procurement Teams

Dalinea

Four white cards on a copper background labeled Price Paid, Landed Cost, Manufacturing Cost, and Savings Potential, each with a dollar sign — illustrating the layered cost outputs a should-cost model produces.

Every buyer has been here.

You open your email to find a “Next Quarter Price Increase” notification from a supplier. They cite “rising input costs” as the reason, and…that's it.

You're left with two options: push back or accept it. Except, if you push back, what legitimate reasoning do you have? Unfortunately, most procurement teams aren't given the tools they need to get real numbers to counter with quickly. You typically just have last year's invoice and a vague sense of the current market.

The number you need comes from should-cost modeling.

Commodity markets now move faster than annual contract cycles. Tariffs shift without warning. And the consequences of not having a defensible cost model have gone up significantly. For any team buying direct materials, should-cost modeling is one of the most vital and actionable tools you can have.

In this blog, we'll break down:

What Is Should-Cost Modeling?

Should-cost modeling is a bottoms-up analytical method that estimates what a product, component, or material should cost based on its actual material, labor, overhead, and margin inputs under current market conditions. Independent from any supplier quote, it gives buyers evidence-based price data to strengthen supplier negotiations and cost validations.

While this method has been around for decades in certain spaces, the thing that has changed is the speed at which input costs now move and the tools that are available to keep models current.

In stable markets, historical spend data used to be enough to determine fair pricing. Numbers moved slowly enough that last year's invoice was a defensible starting point.

However, that world barely exists anymore.

Commodity markets move on time scales that outpace procurement cycles. Tariff schedules change with geopolitical events that no one predicted 12 weeks ago. Sub-tier cost pressures ripple through supply chains at the Tier 2 and Tier 3 levels before your Tier 1 supplier updates their own quotes.

Should-cost modeling enables the shift from historical negotiation to evidence-based negotiation. You stop asking “Is this a fair price?” and proactively start supplier negotiations with “Here's a fair price, and here's the gap we need to discuss.”

To get there, you need to plug a few figures into the equation.

What Are the Basics That Go Into a Should-Cost Model?

  1. Materials
  2. Labor
  3. Overhead and manufacturing
  4. SG&A and supplier margins
  5. Tariffs, freight, and landed cost adjustments

Every should-cost model is built from the same fundamental cost categories. The accuracy and timing of each one is the difference between getting a credible model or going into negotiations with assumed numbers you added up on the nearest Post-It note.

1. Materials

These are the raw inputs that go into a product: the metals, resins, chemicals, fabrics, and electronic components that make up the bill of materials. Typically, this is the largest single cost driver in a manufactured product (but not always).

A should-cost model will use the live commodity price and apply it to the specific grade and quantity of material your product requires.

For example, if you're sourcing parts for a precision-machined housing that requires 6061-T6 aluminum, the model will factor inputs like the specific weight at a specific market price, with a yield factor for machining waste, not just “aluminum.”

The best should-cost modeling tools will also be able to factor in how direct material costs are impacted by wider Tier 2 and Tier 3 commodities. Ignoring these inputs means you're working off incomplete cost data.

2. Labor

Labor costs in a should-cost model combine three variables: the hourly wage rate, productivity assumptions, and the manufacturing region.

This input can hold the widest range because labor rates vary wildly based on region. The same operation looks different on a cost model when one facility pays staff $28 an hour and another pays $6. Applying the wrong regional input to your model can produce figures that don't hold up to suppliers.

That's why should-cost models need to take numerous sources into account, such as ILO (International Labour Organization) wage data, regional manufacturing labor surveys, government statistics, industry association reports, and specialized cost databases for specific industries.

3. Overhead and Manufacturing

These figures cover the indirect cost of operating a manufacturing facility. Typically expressed as a burden rate, it includes inputs like utilities, equipment depreciation, tooling and amortization, maintenance, quality and inspection, and production management.

The struggle here is that this category is one of the most commonly oversimplified ones in a should-cost model. It's also the same one with the most supplier-manipulated line items. There's obviously a big difference between a 200% overhead burden rate on a more manual line and a 60% rate on a highly automated one.

For that reason, your should-cost model needs to reflect the actual production process, not just a generic assumption.

4. SG&A and Supplier Margins

SG&A covers your supplier's selling, general, and administrative expenses, while their margin is the profit they need to stay in business and scale.

Several factors can go into a supplier's margin like:

While there are genuine reasons that a supplier's margin could be higher, there's also the chance that a supplier is padding those margins simply because they can—they know you don't have the cost visibility to push back.

The goal of including this in your should-cost model is not to drive your supplier's margin to zero via negotiations, but rather to model a fair margin based on realistic factors.

5. Tariffs, Freight, and Landed Cost Adjustments

These inputs can include:

Depending on constantly changing tariff impositions and geopolitical events, these inputs can make your total landed cost significantly higher than the original purchase price.

Not only does factoring these figures into your should-cost model help determine if a purchase works for your supply chain, but you can also model what the purchase looks like if you change freight modes, shipping routes, or the like.

Once you have these inputs, you have plenty of opportunities to put them to good use.

When Are Should-Cost Models Most Valuable?

  1. Before and after supplier negotiations
  2. During financial forecasting and planning
  3. When commodity markets shift drastically

Some procurement operations call for should-cost models a bit louder than others. Here are the situations where they consistently deliver the most value.

1. Before and After Supplier Negotiations

Should-cost models allow you to turn supplier negotiations from a price discussion into a cost-structure discussion.

When you approach suppliers with cost intelligence based on actual price drivers, you have:

2. During Financial Forecasting and Planning

Supply chain costs are one of the biggest variables in any bottom-line forecast. Should-cost modeling is one of the most underused tools for getting them right.

Rather than projecting forward based on what you paid last quarter, should-cost models give finance teams an independent, market-grounded baseline for what direct material costs should look like—and what they'll look like if commodity markets keep moving.

That means tighter cost forecasts, fewer surprise variances, and a cleaner story for the CFO when margins compress.

3. When Commodity Markets Shift Drastically

When cost inputs within your supply chain change every other news cycle, should-cost modeling becomes a real-time diagnostic exercise.

When a material rises 14% on global markets, having a should-cost model based on live commodity data tells you:

Without these models, you can only react to procurement problems (accept the change or spend weeks pulling together your own analysis) instead of actively addressing them with an answer the same day.

With so many benefits that come from should-cost modeling, you may be tempted to rush into pulling together your own analyses. But doing so might mean you get caught up in a few all-too-common mistakes.

Six Common Mistakes Teams Make When Building Should-Cost Models

  1. Using static commodity inputs
  2. Ignoring the manufacturing location in labor and overhead
  3. Over-relying on supplier-provided data
  4. Stopping at Tier 1 costs
  5. Treating the model output as a price demand
  6. Trying to build models yourself

1. Using Static Commodity Inputs

Don't think you can build a model once and still trust the results six months later. Using static inputs means that your models tell you outdated data that not only inhibits effective cost strategy decisions, but puts you in a poor position for supplier negotiations.

Especially for high-spend, commodity-intensive categories, you need to update material inputs within your models as they change in real life.

2. Ignoring the Manufacturing Location in Labor and Overhead

Manufacturing labor costs vary enormously depending on local market conditions, unionized rates, and cost of living. Using a generalized or wrong region's labor rate produces a model that has structural errors before you even open negotiations.

For a model based on real cost data, you have to use region and industry-specific benchmarks, not national averages.

3. Over-Relying on Supplier-Provided Data

We're not calling your suppliers liars, but asking them to provide you with data on their specific cost structures doesn't really make for an objectively accurate model.

While a supplier's willingness to provide a cost breakdown is a sign of a strong relationship, your should-cost models need to be built on independent, third-party commodity indices within an engineering-backed process.

4. Stopping at Tier 1 Costs

A model that only accounts for cost visibility from direct spend misses the upstream cost drivers that actually determine what Tier 1 suppliers have to charge. That's because by the time a price increase shows up on your invoice, it has already been lingering at the Tier 2 or Tier 3 level for weeks.

True bottoms-up modeling traces inputs back to raw materials through multiple tiers of your supply chain.

5. Treating the Model Output as a Price Demand

A should-cost model gives you a target range for what you should justifiably be paying. You shouldn't see it as a take-it-or-leave-it number with no room for dialogue with suppliers.

There will be supplier costs that your model won't fully capture, such as long-term sub-supplier relationships that add quality, reliability, or investments in tooling or staff, that represent real value and can increase costs.

At the end of the day, your should-cost model is a transparency enabler that gives you a good starting point.

6. Trying to Build Models Yourself

This one isn't necessarily a mistake…as long as you have a few dedicated weeks to gather all the necessary data and analyze it all to build a model. And that's per product or material.

With everything that procurement is asked to do—cost savings, risk mitigation, etc.—every hour spent building should-costs by hand is an hour you lose from other strategic initiatives. Not to mention, there's a lot of room for human error.

Should-cost modeling is too valuable to skip and too time-consuming to do manually at scale. Especially when you consider the role it plays in informing your larger cost strategy.

How Should-Cost Modeling Fits Into a Broader Cost Intelligence Strategy

Should-cost modeling is a powerful individual tool, but it's most effective when you treat it as part of a connected cost intelligence system.

Here's how it all fits together.

Should-Cost Is the Start

A standalone should-cost model answers one question: what should this product cost? Simple enough.

When you build that model within a cost intelligence platform, you can answer:

Having that intelligence layer makes your model actionable in real time and keeps you from having to rebuild it every time markets shift or tariffs go into effect.

Should-Cost Should Connect to Commodity Volatility

Speaking of making manual updates, when your should-cost model is connected to live commodity data, you experience a fundamentally different tool than one built using static inputs.

Pulling these models within a cost-intelligence platform ensures they update across every affected SKU as markets move, so you know the downstream dollar impact of your specific purchases before a revised supplier quote arrives.

Should-Cost Models Inform Scenario Planning

When you have data into what something should cost, you can use those numbers to extend scenario planning from a point-in-time estimate to a strategic planning tool.

Suddenly, you have answers to the questions your CPOs and CFOs are already asking—ones you can answer with engineering-backed data instead of guesswork, such as:

Procurement has earned its seat at the table, and having these answers with specific dollar figures attached ensures you keep that seat.

Should-Cost Is Prime Negotiation Leverage

A credible should-cost model is the most defensible tool you can bring into a supplier negotiation.

When you can present real cost data of a supplier's own material costs pulled from cost indices, regional labor benchmarks, fair overhead burden, and reasonable margins, negotiations become transparent processes based on trust.

From Model to Intelligence: How Dalinea Takes Should-Cost Further

Should-cost models are only as good as the data feeding them, and in a market where commodity prices move daily and tariff schedules change with policy decisions, that data goes stale fast.

Dalinea uses live commodity data and engineering-backed cost intelligence to run 1,000+ simulations and build bottom-up, multi-tier, SKU-level should-cost models that tell you what you should pay right now, not six months from now.

With dollar figures attached to your models, you can scenario plan and stress-test ranges against tariff shifts, supplier changes, and material price movements to base sourcing, risk, and financial decisions on trustworthy cost data.

Don't just take your supplier's word for it. Know what it should-cost with Dalinea.