RFQ scoring

RFQ comparison matrix

Paste 2 to 5 competing supplier offers across price, lead time, MOQ, payment terms. The tool runs a weighted score and ranks the suppliers. Adjust the weights to match your procurement priority. All math runs in your browser; supplier data stays here.

Last updated 2026-05-09. Math runs in your browser, no data leaves your computer.

General guidance only, not legal or professional engineering advice. Verify against the cited primary sources (IMDG, REACH, ChAFTA, RCEP, Customs Tariff Act, supplier SDS, etc.) before committing to a shipment, declaration, or contract. Sourzi assumes no liability for outcomes based on these calculators.

Default weights are the chemical-trade procurement norm: price 40%, lead time 25%, MOQ 15%, payment terms 20%. Adjust if your priorities differ.

Weights

Weights need to sum to 100; the tool normalises if they do not.

Suppliers

Scoring math

Each offer is normalised against the best (lowest for price/lead/MOQ, highest for payment-term days) on each dimension; the normalised value is 100 for the best, scaled down for worse offers. The four normalised scores are weighted by the user weights and summed. The result is a 0-to-100 composite score; closer to 100 is better.

Why normalise inverse for price? A 4% price difference on commodity against a 10-day lead-time difference is hard to compare in raw form. Normalising inside each dimension (best supplier gets 100 on that axis, worst proportional to ratio) and weighting the dimensions gives the procurement team a single composite to argue from. The composite is wrong if the weights are wrong; the weights belong to the buyer, not to the tool.

Payment terms encode working capital. The score treats days of payment terms as an asset: 0 days (T/T upfront) gets the lowest sub-score, 60 days (OA 60) gets the highest. A buyer with cheap working capital (treasury rate 4%) is less sensitive to this axis than a buyer with expensive capital (factor financing at 12%). Adjust the weight to reflect the cost-of-capital position.

Non-numeric dimensions (single-source risk, factory audit history, ESG, IP exposure, regulatory compliance) are not in the score. Use the score to short-list 2 or 3, then evaluate the qualitative dimensions on the short-list. The matrix is a filter, not a decision.

Worked example. Three caustic-soda quotes

The booking. A US distributor requests 25 tonnes of caustic soda 50% solution. Three quotes back: Supplier A 460 USD/MT, 21-day lead, MOQ 20 MT, T/T 30/70 (effective 30-day); Supplier B 445 USD/MT, 28-day lead, MOQ 25 MT, T/T 100% upfront (0-day); Supplier C 475 USD/MT, 18-day lead, MOQ 20 MT, OA 60. Default weights 40/25/15/20.

The score. Price normalised: A 96.7, B 100, C 93.7. Lead normalised: A 85.7, B 64.3, C 100. MOQ normalised: A 100, B 80, C 100. Payment normalised: A 50, B 0, C 100. Weighted: A = 96.7*0.4 + 85.7*0.25 + 100*0.15 + 50*0.2 = 38.7 + 21.4 + 15 + 10 = 85.1. B = 100*0.4 + 64.3*0.25 + 80*0.15 + 0*0.2 = 40 + 16.1 + 12 + 0 = 68.1. C = 93.7*0.4 + 100*0.25 + 100*0.15 + 100*0.2 = 37.5 + 25 + 15 + 20 = 97.5. C wins on score despite having the highest price, because lead time and OA 60 payment terms offset.

The decision. Distributor short-lists A and C. Qualitative review: C is a single-source for the buyer customer cluster, A has been a supplier for 4 years. Distributor picks A despite the lower score because the single-source risk on C is unacceptable. The matrix flagged C as worth a real conversation; the qualitative review chose A. Both better than the day-1 instinct of grabbing B for the lowest unit price.

Frequently asked

How does the matrix score competing supplier offers?

It runs a weighted score on the four dimensions buyers care about: price (40%), lead time (25%), MOQ (15%), payment terms (20%). The default weights work for commodity chemical procurement; adjust the weights in the form if your priorities differ. Each offer is normalised against the best on each dimension (lower is better for price/lead/MOQ, longer is better for payment terms), then weighted and summed.

Why include payment terms as a dimension?

Payment terms drive working capital. T/T 100% upfront is a 0-day terms; LC at sight is roughly 30 days; OA 60 is 60 days. The buyer effectively borrows from the supplier for the term length. At a 6 to 8% cost-of-capital, 60 days of OA is worth roughly 1% of the order value. The score normalises this so a slightly higher unit price with OA 60 can beat a slightly lower price with T/T upfront.

What if all offers are similar?

Tighten the weights to amplify the differences. If lead time is genuinely critical (JIT delivery into a customer line), bump lead-time weight to 50% and reduce others. If price is the only thing that matters (commodity, multiple swappable suppliers), bump price weight to 70%. The score is a tool for thinking; the right weights are yours to set.

Does this tool send my supplier offers anywhere?

No. All math runs in your browser; you can paste 5 supplier names and prices into the form and the data never leaves your computer. Useful for a procurement-confidential RFQ comparison.

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