Germany’s manufacturing sector ended 2024 in a downturn that was difficult to ignore. The HCOB Manufacturing PMI dropped to 42.5 in December, a level that not only confirmed contraction but marked the 18th straight month of decline, according to Reuters. Across key industries, factories were producing less, backlogs were shrinking, and the outlook remained bleak. At the same time, European energy markets stayed volatile, with electricity and gas prices rising unpredictably, while global commodity costs continued to shift week by week. In this environment, cost engineers need new ways to deliver reliable estimates earlier in the process, even when key data points are still missing. Specialized product costing software can offer a structured approach to modeling cost under uncertainty, thereby helping teams move forward faster without sacrificing calculation accuracy.
The Traditional Process No Longer Fits the Pace of Change
The disruptions across the industry are not only affecting day-to-day operations but also changing how companies make product and sourcing decisions. According to KPMG’s 2024 Global Procurement Outlook, 83% of procurement leaders cite inflation and commodity price volatility as their top external concern. These conditions make it harder than ever to base cost estimates on stable, confirmed inputs.
Timelines are tightening, and design iterations are accelerating. In sectors like automotive and industrial equipment, products are often developed in parallel with sourcing and quoting. A recent McKinsey study found that more than 60% of product cost decisions are now made before specifications or suppliers have been finalized. As a result, cost engineers are pulled into the process earlier than before, but they are often working with only partial knowledge of the final design, production setup, or the supply chain.
This creates a disconnect that traditional costing methods cannot resolve. Engineers are expected to support early decisions with numbers that hold up in later negotiations, even when the underlying data is incomplete or in flux. Without the right tools, the risk of rework, misalignment and supplier challenges grows.
To close this gap, more and more manufacturers are turning to simulation-based costing. These tools allow models to evolve over time while maintaining a clear structure and audit trail, thereby ensuring that even early estimates can support real-world decisions.
From “Best Guess” to Structured Simulation
The key question is no longer whether engineers should wait for perfect data, but whether they can make confident, structured comparisons based on what they have today. This is exactly where product costing software brings value. It enables teams to build cost models on realistic assumptions, then refine those models as better inputs become available, preserving consistency from concept through sourcing.
According to Tset experts, users often begin calculating even when only 60 to 70 percent of the input data is available. This figure may sound low, but it reflects the new pace of decision-making. Business cases need to be evaluated, sourcing strategies need direction, and product concepts need feedback – irrelevant if all the details have been confirmed.
What does that 60 to 70 percent actually mean? Typically, early inputs might include:
- Preliminary geometry
- Expected volume
- General technology process group (e.g., casting, machining)
But final data, such as supplier rates, detailed logistics, or tooling specifics, is still missing.
To make progress, teams use product costing software to begin with a “greenfield” estimate. This represents an ideal production scenario using best-practice cost and CO₂ data. Once internal constraints or supplier limitations are known, the estimate then evolves into a “brownfield” model, which reflects real-world production conditions.
