Cost Engineering & BOM Optimization

Problem it solves: Your product costs more than it should, but you cannot identify which components are over-specified and which are under-negotiated. The BOM was assembled incrementally — a material chosen here, a specification inherited there — and no one has evaluated the full cost structure against what the product actually needs to deliver at the performance level your brand requires.

Home Methods Cost Engineering & BOM Optimization

Engineering Process

How It Works

We deconstruct the BOM into its engineering and commercial components and evaluate each against two questions: does this component need to be at this specification level, and is this the best cost position for the required specification?

Component-level teardown: every material weighed, identified, and costed against market alternatives. Where a competitor achieves similar performance with a lower-grammage ADL or a different core architecture, the cost delta is quantified.

Specification audit: which parameters are driving cost without driving perceptible performance? Over-specified components are flagged with a performance-impact assessment — what would the consumer actually notice if this specification were relaxed by 10%?

Supply chain cost mapping: material cost is only part of the picture. Minimum order quantities, tooling charges, lead time premiums, and logistics costs are mapped for each component. Sometimes the cheapest material per kilogram is the most expensive material per unit when MOQ and freight are included.

Scenario modeling: we build 2-3 BOM configurations at different cost-performance trade-off points, each with fully loaded cost estimates and a performance impact assessment. The decision is yours — but the data behind the decision is engineering, not guesswork.

Differentiation

Why Only CORIO

Cost engineering requires two things that rarely exist in the same team: deep knowledge of what materials actually cost at the factory gate (not the price on a quotation sheet), and the engineering judgment to know which cost reductions will degrade the product and which will not.

On the cost side, our manufacturing experience means we know the difference between a supplier's quoted price and their actual production cost — which tells us where negotiation leverage exists. When a supplier quotes a 20% premium for a specific nonwoven variant, we can assess whether that premium reflects genuine production complexity or margin padding, because we have run the same materials on the same types of equipment.

On the engineering side, our product development experience means we can predict which specification relaxations will be invisible to the consumer and which will generate complaints. In competitive teardowns, we routinely find that the highest-performing product in a category is not the most expensive one — because smart cost engineering removes cost from layers the consumer does not perceive while concentrating investment in the layers they do.

Deep Dive

Full Detail

BOM optimization is not cost-cutting — it is cost reallocation guided by engineering data and consumer perception.

What you receive:

Component Cost Benchmark — every material in your BOM costed against market alternatives and competitive products, with the cost delta quantified at each layer. You see exactly where you are overpaying relative to the market.

Specification Sensitivity Analysis — for each component, an assessment of how much the specification can be relaxed before the consumer perceives a difference. This identifies the “invisible cost” — money spent on specifications that deliver engineering margin but not consumer value.

Optimized BOM Scenarios — 2-3 alternative configurations at different cost-performance points, each with fully loaded unit economics including material, MOQ impact, tooling, and logistics. You choose the trade-off — the analysis provides the data.

The goal is not to make the product cheaper. It is to make every gram and every cent work harder toward the performance dimensions your consumer actually values.

Real-World Validation