Should‑Cost Analysis for Procurement

Turn gut reactions into data‑driven negotiation power. Build defensible should‑cost models that cut supplier spend and improve procurement outcomes.

Why should‑cost analysis matters

Ever felt a supplier quote was “off” but couldn’t prove it? Should‑cost analysis turns that feeling into a data‑backed advantage. Instead of debating a single number, break the product or service into core cost drivers — materials, labor, overhead, logistics, and profit — and build a transparent benchmark.

That shift does more than save money. Procurement moves from price haggling to value creation. You stop arguing totals and start collaborating on discrete cost drivers where both buyer and supplier can find improvements. Many procurement teams capture significant savings when they adopt structured should‑cost methods¹.

Core benefits

• Stronger negotiation leverage by asking targeted questions about materials, machine hours, or labor instead of debating the final number
• New cost savings from alternative materials, process changes, or design tweaks that preserve quality
• Better supplier relationships, since transparent, fact‑based conversations build trust and shared solutions
• More accurate budgeting, because a bottom‑up model reduces surprises from market shifts and supplier variability

Key components of a should‑cost model

A useful model is granular. Core components include:

• Direct materials (raw materials and components)
• Direct labor (fully burdened labor rates)
• Manufacturing overhead (utilities, depreciation, tooling amortization)
• SG&A (sales, general and administrative expenses)
• Logistics and freight (shipping, customs, warehousing)
• Supplier profit margin (industry benchmarked)

Understanding each element is the foundation of credible negotiations.

The three pillars: materials, labor, overhead and profit

Materials

Material cost is more than a catalog price. Account for grade, scrap, yield (parts per raw sheet), and market volatility. For example, machining aluminum often needs a scrap allowance of 5–10% and current commodity pricing — missing either skews your estimate.

Labor

Use fully burdened labor rates, not just base wages. Include benefits, payroll taxes, insurance, and premiums for specialized skills. Labor varies widely by region, so accurate local data matters.

Overhead and profit

Estimate indirect factory costs such as utilities, depreciation, SG&A, tooling amortization, and maintenance. Then add a reasonable supplier margin, often between 8% and 20% depending on complexity and competition.

A practical 5‑step should‑cost framework

Use this repeatable approach to build defensible cost models.

Step 1 — Deconstruct the product and define scope

Create a detailed BOM and process map: material specs, dimensions, surface finish, machine operations (CNC, drilling, deburring), secondary processes (anodizing, heat treat), and inspection steps.

Internal resources: BOM template and Cost model templates.

Step 2 — Gather intelligence on key cost drivers

Collect current market prices for materials, regional fully burdened labor rates, machine cycle and setup times, and freight costs. Don’t rely only on old ERP data — supplement with market sources and supplier interviews.

Suggested tools for live data and validation:

• Manufacturing Production Time Estimator for production time and process estimates
• Construction Material Cost Predictor for material pricing and inputs
• Logistics Shipping Cost Predictor for shipping and freight validation

Step 3 — Build the model bottom‑up

Calculate each element:

1. Material cost, including scrap allowance
2. Labor cost, as time × fully burdened rate
3. Machine cost, as run time × machine hourly rate, plus setup
4. Overhead allocation, applied to labor and machine costs
5. Supplier profit margin

A simple spreadsheet can work for one‑off jobs. For repeatable projects, scale to a validated tool.

Step 4 — Validate against market quotes

Compare your should‑cost to three or more supplier quotes. Small gaps (5–10%) are normal. Large gaps signal incorrect assumptions such as material grade, process complexity, or missed steps. With good inputs, should‑cost estimates commonly come within a close range of actual supplier costs².

If your model says $50 and quotes are $80, drill into differences rather than assuming suppliers are cheating.

Step 5 — Use insights in negotiations

Lead with specific data: “Our model estimates material cost at $15 per unit based on current market rates — can you walk me through your material choice?” This reframes the conversation into problem solving rather than price haggling.

Add context by assessing supplier stability with the Business Valuation Estimator.

Using technology to sharpen analysis

Manual models are slow and fragile. Modern tools provide live data, validated calculation engines, and fast scenario testing.

Benefits of using tools:

• Instant access to up‑to‑date material and labor data
• Pre‑built calculation templates to reduce spreadsheet errors
• Fast what‑if scenario runs (change material grade, region, or process)
• Centralized collaboration to prevent version control issues

Representative tools:

• Manufacturing Production Time Estimator
• Construction Material Cost Predictor
• Logistics Shipping Cost Predictor
• Energy Utility Bill Forecaster
• Automotive Repair Estimator

“Using live data is essential. Commodity prices change quickly, and an estimate from last quarter can cost you significantly in a negotiation.”

Manual analysis versus tool approach

Scaling should‑cost to complex systems and TCO

For large systems such as industrial machinery, fleet purchases, or long‑term service contracts, focus on Total Cost of Ownership rather than just purchase price. Account for:

• Maintenance, parts, and repairs
• Energy and fuel consumption
• Consumables and licenses
• Support, training, and service contracts
• Downtime costs and decommissioning

Practical example: a logistics manager evaluating trucks should model fuel, insurance, maintenance, and downtime, not just sticker price. For repair and maintenance modeling, consider the Automotive Repair Estimator.

In many systems, purchase price may be only 20–30% of lifetime cost; operating costs dominate the rest³.

Common questions

How accurate is should‑cost analysis?

Accuracy depends on data quality. With detailed, current data, you can often get within 5–10% of a supplier’s actual cost. The goal is a defensible benchmark to guide negotiations, not a perfect prediction to the penny².

Can you use this for services?

Yes. Replace material elements with labor hours, tool and software costs, subcontractor margins, and overhead. Focus on time allocation and fully burdened rates.

What’s the biggest initial mistake?

Using high‑level averages or stale internal data. Get specific: exact material grades, regionally accurate labor rates, up‑to‑date freight costs, and realistic scrap and yield assumptions.

Practical next steps

1. Start with a single SKU or service and build a bottom‑up model.
2. Validate against multiple supplier quotes.
3. Use a tool to automate live data pulls and speed scenario runs, for example the Manufacturing Production Time Estimator.
4. Turn the model into a negotiation script — focus questions on specific drivers.

• BOM and scope checklist
• Procurement negotiation playbook
• Downloadable cost model spreadsheets

Q&A — Quick answers to common concerns

Q: How do I get started without a big team?

A: Pick one SKU, map the BOM, gather live material and labor rates, and build a simple spreadsheet model. Validate with two to three quotes.

Q: What if suppliers refuse to share cost details?

A: Use your should‑cost model to ask targeted, non‑accusatory questions about specific drivers like material grades or process steps. That usually prompts constructive discussion.

Q: When should I use a tool instead of spreadsheets?

A: Move to a tool when you need live data, repeatable scenario testing, or collaboration across teams. Tools reduce version errors and speed validation.

Conclusion

Should‑cost analysis converts intuition into measurable leverage. By breaking costs into materials, labor, overhead, logistics, and profit, you create a repeatable process that improves negotiations, reveals cost‑reduction opportunities, and strengthens supplier relationships. Start small, validate your model, and use modern tools to keep estimates current and scalable.

Ready to speed up your analysis? Try a production and process estimator to get live, actionable inputs: Manufacturing Production Time Estimator

Author: (same as original) — Published: (same as original)

Quick Q&A (concise)

Q: What is should‑cost analysis in one line? A: A bottom‑up cost model that benchmarks supplier quotes and exposes specific savings opportunities.

Q: What’s the fastest way to see value? A: Build a model for one SKU, validate with 2–3 quotes, and use those findings in your next negotiation.

Q: When do I need a tool? A: Use a tool when you need live data, repeatable what‑if scenarios, or team collaboration.