Imagine you receive a quote that is 30% higher than expected, but you have no breakdown, no benchmark, and no leverage. That is a common challenge—but it doesn’t have to be your reality. When built correctly, a should-cost model gives you a fact-based cost estimate grounded in materials, labor, overhead, and market data—not supplier assumptions. Combined with purchasing software, it helps you negotiate better prices.
In this article, we’ll walk you through how to build your model to calculate should-cost and where the model adds value—and where it may not.
What is the Should-Cost Model?
A should-cost model is an analytical tool that calculates the fair price of a product or service. It adds up raw materials, labor, overhead, logistics, and profit to create a clear cost estimate. This model helps procurement and finance teams spot inflated prices and negotiate smarter contracts.
Key Components of a Should-Cost Model
An effective should-cost model breaks down the following critical parts:
- Direct Materials: The cost of raw materials or purchased components, reflecting market prices, quality specifications, and sourcing conditions.
- Direct Labor: Labor costs associated with producing the item or delivering the service, based on time required and wage rates.
- Manufacturing Overhead: Indirect costs such as utilities, maintenance, quality control, equipment depreciation, and administration are allocated per unit.
- Logistics and Supply Chain: Packaging, transportation, warehousing, and handling fees.
- Reasonable Profit Margin: Fair compensation for the supplier’s investment, risk, and business sustainability.
Note!
It can take some time to settle on the right profit margin. To decide on an appropriate markup, analyze industry standards and the supplier’s pricing history.
Building a Should-Cost Model: Step by Step
Follow these steps to build a should-cost model that uncovers real costs and savings.
Step 1. Define objectives & Scope
Determine why you’re building the model (e.g., negotiate prices, validate bids) and clearly define product or service scope and level of detail.
Step 2. Collect accurate data
Gather data from internal systems (ERP, bills of materials, spend history) and external sources (industry benchmarks, market price databases, supplier disclosures).
Step 3. Identify cost drivers
Analyze the main contributors to cost—materials, labor efficiency, overhead allocation, logistics, and others—and understand their impact.
Step 4. Construct the model framework
Use spreadsheets or dedicated software to input formulas calculating each cost component based on your data and assumptions—document assumptions for transparency.
Step 5. Validate & Refine
Compare model results with historical supplier quotes or benchmark data. Perform sensitivity analyses to understand cost variability and adjust accordingly.
Step 6. Regular updates
Costs fluctuate with market dynamics, so routinely update your model to maintain accuracy and relevance.
Should-Cost Calculations Explained
To calculate a should-cost model, you break down the product or service into its main cost drivers and sum all relevant cost components. The standard formula is:
Should-Cost = Material Cost + Labor Cost + Manufacturing Overhead + Other Costs
The more details you put in, the better you can check if the prices you pay make sense based on real facts—not just guesses. After you find the should-cost, add a reasonable profit margin to get your target selling price. Then compare that to the supplier’s quote to see if it’s fair.
For example, say you want to find the should-cost of a custom part:
- Materials: $30 per part
- Labor: 1.5 hours at $28/hour → $42
- Overhead (machines, electricity, inspection): $15 per part
- Add it up: 30 + 42 + 15 = $87
So, the should-cost is $87. If the supplier charges more, you can consider negotiating or looking elsewhere.
To make a 25% profit, the selling price should be:
$87 ÷ (1 – 0.25) = $116
This way, you base your price talks on real costs plus a fair profit—no guessing!
Benefits of Should-Cost Modeling
Discover how should-cost modeling can improve cost control and negotiation outcomes across your supply chain.
- Stronger negotiation position: Backed by transparent cost data, you can push for fair prices and eliminate unnecessary costs.
- Greater cost transparency: Reveals where inefficiencies or inflated margins exist and highlights targets for cost reduction.
- Supports value engineering: Identifies potential design or process changes that reduce costs without compromising quality.
- Improves budgeting & Forecasting: Provides realistic cost estimates for more accurate financial planning.
- Enhances supplier collaboration: Builds trust through transparency and encourages joint efforts to optimize costs.
Challenges of the Should-Cost Model
A should-cost model is a powerful tool, but it’s not without its hurdles. To be effective, it must overcome these challenges:
- Data is hard to get.
The model requires a vast amount of highly specific and accurate data to function effectively. Finding that information, especially from suppliers who may be reluctant to share, is often the biggest obstacle.
- Expertise is a must.
You can’t just plug numbers into a spreadsheet. Building and managing the model requires a skilled expert who understands both cost analysis and the real-world production processes.
- It requires constant updates.
This isn’t a one-time project. Market prices, labor costs, and supplier capabilities are constantly changing, so the model needs regular updates to stay accurate and relevant.
- Some products are too complex.
For items that are highly customized or completely new, the costs can be unpredictable. This can limit how precise and useful the model’s results will be.
Tools to Support Should-Cost Modeling
Though Excel remains a standard tool for should-cost modeling, advanced software solutions improve both accuracy and workflow efficiency.
Excel add-ins like Crystal Ball and @RISK add powerful risk and scenario analysis capabilities. Software like aPriori models production costs using simulation technology. GEP NEXXE applies AI to streamline procurement cost insights, and Galorath SEER offers detailed cost estimation for complex projects.
With these tools at hand, you can improve data integration, testing, and teamwork across procurement teams and stakeholders.
Wrapping Up
A reliable should-cost model demands time, skill, and regular maintenance. Although it does not offer quick wins, the payoff—lower costs, accurate forecasts, and wiser sourcing—is valuable. Firms that use this technique earn a competitive edge through informed, data-based decisions in a cost-conscious environment.
For those new to the process, start with the primary cost drivers and build the model gradually. Over time, this tool will prove indispensable for procurement teams seeking fact-based decisions.
