How to Compare Injection Molding Quotes: Normalize the Assumptions, Not the Numbers

PrintForm’s account of a procurement failure shows the risk of reading the numbers without the context behind them: a team had three quotes for the same part, ranging from $0.58 to $0.91 per piece at 50,000 units annually. They took the lowest. Six months into production the blended cost was running at $0.74 — still under the highest quote, but 27% above what had been contracted.

The winning supplier had quoted a 22-second cycle time; production ran at 29 seconds. It had assumed 2% scrap, and production held 4.5% because of gate blush on a cosmetically sensitive surface. It had quoted four-cavity tooling and built two, to stay inside its mold-build budget. Every one of those assumptions was in the fine print — technically present, practically invisible.

The supplier did not lie; the quote was simply a model. When physical reality rejected the model’s assumptions, the buyer absorbed the variance.

Quotes are not guaranteed prices; they are mathematical models dependent on specific technical assumptions. A clean RFQ package sets the baseline, but comparing the resulting quotes requires normalizing those assumptions.

The Normalization Requirement

When three quotes for the same part exhibit a wide spread, they are rarely pricing the same manufacturing strategy. Each supplier fills the silences in the RFQ with proprietary assumptions regarding tooling architecture, process capability, and quality yield. The variance between quotes measures differences in these models, not merely differences in factory efficiency.

Comparing bottom-line numbers without normalizing the underlying assumptions guarantees a compromised decision. Evaluate quotes across five critical axes.

Cycle Time

Machine time dictates piece price. A quote built on a 22-second cycle versus a competitor’s 30-second cycle represents a fundamentally different process architecture. Buyers must identify the assumed cycle time and request the technical justification, such as a wall thickness cooling analysis or the use of conformal cooling.

Scrap and Yield

An aggressive scrap assumption (e.g., 2%) against a realistic one (e.g., 5%) creates a hidden margin tax. Buyers must verify the assumed scrap rate and clarify how cosmetic rejects on defined cosmetic surfaces are classified. Unspecified reject criteria invariably default to the supplier’s benefit.

Cavitation and Press Size

A 2-cavity quote and a 4-cavity quote represent entirely different capital and operational strategies. The tooling cost, piece price, and risk profile are not comparable until separated. Furthermore, the press size dictates the hourly rate applied to the cycle time.

Tool Class and Life

The lowest tooling quote typically procures a softer steel tool, fewer guaranteed cycles, and minimal documentation. Quotes are only comparable when the SPI tool class, guaranteed life, and ownership terms are identical. Require low bidders to requote at the specified class.

Inclusions and Exclusions

Two identical piece prices with different inclusion lists are different prices. Buyers must normalize sampling parameters, T1 trials, dimensional reporting (e.g., FAI), texturing, mold maintenance responsibilities, freight (Incoterms), resin price baselines, and revision pricing.

Normalization Worksheet

Utilize this framework to force alignment across quotes. Do not evaluate totals until all rows are populated.

QUOTE NORMALIZATION WORKSHEET        Part: ____________  EAU: ________

                                     Supplier A   Supplier B   Supplier C
PIECE PRICE (quoted)                 _________    _________    _________
Assumed cycle time (sec)             _________    _________    _________
Assumed scrap/yield (%)              _________    _________    _________
Cavities / press size                _________    _________    _________
Material grade + price basis         _________    _________    _________
Resin surcharge / adjustment terms   _________    _________    _________

TOOLING PRICE (quoted)               _________    _________    _________
SPI class / guaranteed cycles        _________    _________    _________
Tool ownership + transfer terms      _________    _________    _________
Revisions: process + cost            _________    _________    _________

INCLUDED? (Y/N each)
T1/T2 sampling + samples             _________    _________    _________
Dimensional report / FAI             _________    _________    _________
Texturing / finishing                _________    _________    _________
Mold maintenance responsibility      _________    _________    _________
Packaging / freight (Incoterms)      _________    _________    _________

Lead time: start event / end event   _________    _________    _________
Payment terms                        _________    _________    _________
Stated assumptions & exclusions      _________    _________    _________

A supplier who resists detailing these assumptions is actively concealing their margin strategy.

Interpreting the Normalized Data

A low piece price dependent on aggressive cycle times and minimal scrap is a forecast, not a guarantee. Establish commercial liability upfront: clarify who absorbs the cost if the T1 trial fails to achieve the modeled cycle.

A high initial tooling cost that includes comprehensive documentation and an SPI Class 101 guarantee is frequently the most economical choice over a program’s lifecycle. Evaluate this using a part cost breakdown to analyze amortization.

A quote that explicitly states every assumption demonstrates engineering discipline. This transparency correlates strongly with favorable supplier capability assessments.

For automated analysis of response gaps, utilize the RFQ Readiness Scorer and cost estimator. To structure the follow-up dialogue, consult the Supplier Interview Generator.

Disclaimer

PlasticsTechnologyAlliance.com is an independent buyer resource. It does not manufacture parts, quote, or verify suppliers. Quote structures and assumptions vary by supplier, confirm all terms in writing before awarding tooling or production.