The Pricing Problem in Long-Cycle Contracts

Pricing an ETO contract means making predictions about costs that will materialize months, often years, after the contract is signed. In that interval, almost everything can change: raw material costs, subcontractor availability, exchange rates, logistics conditions, energy prices.

Yet in most ETO companies, the quotation process still relies on static estimates built on aggregated historical costs, with few mechanisms to incorporate future uncertainty. The result is a systematic erosion of margin between bid and contract close.

Where the Margin Goes: The Main Sources of Deviation

Analyses of European ETO company samples identify three main categories of deviation between expected and realized margins:

The first is raw material volatility. Steel, aluminum, copper, rare earths, technical polymers: these materials can experience price swings of 20–40% over a 12–18 month period. For a contract with a complex BOM, even a 15% increase in raw material costs can wipe out the expected margin.

The second is the underestimation of processing and subcontracting costs. Standard costs used at the bid stage often don't reflect actual market conditions at execution time, especially during periods of high demand or supply chain bottlenecks.

The third is unanticipated technical complexity: requirements partially interpreted at the bid stage that emerge in full only during execution, generating unplanned additional costs.

Raw Material Volatility: A Structural Factor

Over the past five years, raw material volatility relevant to the ETO sector has reached historically unusual levels. Steel saw price swings exceeding 100% between 2020 and 2022. Copper hit record highs in 2024. Rare earth metals, critical for defense and aerospace electronics, are subject to geographic supply concentration that amplifies volatility.

For companies signing multi-year fixed-price contracts, this scenario is structurally challenging. Price revision clauses are not always available or granular enough to cover the real exposure. The response cannot be purely contractual: it must also be analytical.

From Standard Costs to Scenario Simulation

The difference between a company that quotes well and one that doesn't isn't the quality of its engineers: it's the information structure on which the bid is built. The most advanced companies are moving away from static standard costs toward scenario simulation approaches.

In practice: for each relevant BOM component, a pricing model is built that incorporates historical trends, recent volatility, and available market forecasts. On this basis, margin is simulated across three scenarios (base, optimistic, pessimistic)  and a quotation is defined that remains defensible even under the adverse scenario.

The Role of Internal Data: Historical Records as an Asset

One of the most underutilized resources in ETO pricing is the historical record of past contracts. Every won or lost bid contains valuable information: actual vs. estimated costs per category, variances by component type, and supplier performance. This data exists in almost every ETO company,  but is rarely structured in a way that enables systematic interrogation.

When historical records are structured and made queryable, it becomes possible to build pricing models that don't rely on generic estimates, but on actual cost distributions calibrated to the company's specific experience. Quotations become more accurate, margins more stable, and bid/no-bid decisions more informed.

Discover BidderAI, Vedrai Joint Venture with Erre Quadro to support ETO pricing optimization