Job Shop Quoting KPIs: Benchmark Ranges for Win Rate, Turnaround, Delivery and Margin
The metrics that tell you whether a quoting operation is healthy, how to measure each one, the levers that move it, and which figures have a cited source.
A contract manufacturing quote desk can be judged on a handful of KPIs: quote win rate, quote turnaround, on-time delivery, quote-to-actual cost variance, gross margin by work type, bottleneck utilization and estimating productivity. Use the ranges below as reference points for spotting a gap worth investigating, not as targets, and always read win rate next to margin.
Every figure shows its basis. A superscript number links to a public source in the Sources list, and the text says when a cited figure comes from outside contract manufacturing. A figure marked no cited source is kept exactly as originally published because no public source stating it was found, so treat it as illustrative.
Words in parentheses keep each figure's original framing, and Not stated means no figure was given for that column. The citations in the on-time delivery and prototype margin rows are comparison points from a U.S. plant census, an aerospace customer's rating scale and one public company, not sources for the contract manufacturing bands; their sections give each source's scope.
Method: How the figures in this guide are sourced
A figure with a superscript number is stated by the cited source, listed under Sources with its publisher, location in the document and access date. Several cited figures come from outside contract manufacturing or from a single company, and the text says so where they appear. A figure marked no cited source is kept exactly as originally published because no public source stating it was found. It is illustrative, not measured industry data. Worked examples are arithmetic, not benchmarks.
Quote win rate
Quote win rate is the headline KPI for a make-to-order shop, and context sets the target. Broad-market job shops bidding open RFQs (requests for quote) typically win 20 to 35 percent no cited source; shops with strong incumbency and repeat accounts run 40 to 60 percent no cited source.
A win rate above 70 percent usually means you are leaving margin on the table and should test higher pricing no cited source. Below 15 percent signals a pricing, capability or lead-time mismatch no cited source.
Always pair win rate with margin. A win rate that jumps after a price cut is not a win.
How to measure
Divide quotes won by quotes submitted over the same period.
Report open-market RFQs and incumbent or repeat accounts separately.
Show the margin on the won work next to the win rate.
What moves it
Quote turnaround, since buyers often award to the first credible quote.
The fit of your pricing, capability and lead time with what the buyer needs.
Quote turnaround time drives win rate more than most shops admit. On standard RFQs, world-class desks respond in under 24 hours no cited source, typical shops in 2 to 4 business days no cited source, and laggards in a week or more no cited source.
Buyers frequently award to the first credible quote, so cutting turnaround from 4 days to 1 can lift win rate 5 to 10 points with no price change no cited source.
Watch estimator load as well. When one estimator carries more than 40 to 60 open RFQs, turnaround degrades sharply no cited source.
Little's Law explains the mechanism: the average number of items in a queuing system equals their average arrival rate times the average time each spends in the system4. At a fixed quoting rate, more open RFQs means a longer average wait for each quote.
How to measure
Time each quote from RFQ receipt to quote sent.
Segment turnaround by quote complexity.
Count open RFQs per estimator every week.
What moves it
Templated pricing and saved setups for repeat work.
On-time delivery is the KPI that protects repeat business. World-class contract manufacturers hold 98 percent or better against the promised date no cited source; 92 to 96 percent is typical no cited source, and anything below 90 percent puts accounts at risk no cited source.
Published bars from outside contract manufacturing line up with the top and bottom of that range. The 2000 IndustryWeek Census of Manufacturers, run with PricewaterhouseCoopers and drawing more than 3,300 survey responses on U.S. manufacturing, defined delivery leaders as plants with at least 98 percent on-time delivery to the promised date, and about one-third of plants reached it1.
Customers grade suppliers against bands like these. Lockheed Martin's supplier scorecard rates a six-month delivery average of 98 to 100 percent Excellent, 95 to 97.99 percent Approved, 90 to 94.99 percent Conditional and below 90 percent Unsatisfactory2.
The lever is honest lead-time quoting, not heroics. Shops that quote lead times from real queue time and outside-process turnaround hit their dates far more reliably than shops that quote optimistic dates to win and then expedite internally at their own cost.
How to measure
Divide orders shipped complete by the promised date by orders shipped.
Measure against the original promised date, not a renegotiated one.
Report a six-month average, the window Lockheed Martin's scorecard uses2.
What moves it
Quoted lead times built from real queue time and outside-process turnaround.
Protected bottleneck capacity, so promised dates hold.
Fewer internal expedites, which the shop pays for itself.
Quote-to-actual cost variance tells you whether your estimating is trustworthy. World-class shops hold mean absolute variance under 5 percent no cited source; 5 to 12 percent is typical no cited source; consistently above 15 percent means you are quoting blind no cited source.
The dangerous pattern is a variance that is unfavorable more often than favorable. It points to systematic underestimation of setup or scrap.
Review the worst tenth of jobs every month and update your standards. Pulling variance from 12 percent to 5 percent often recovers 3 to 5 margin points across the board no cited source.
How to measure
Compare quoted cost with actual cost for every closed job.
Average the absolute variance, and count favorable and unfavorable jobs separately.
Break each variance into setup, run time, material and scrap.
What moves it
Setup and scrap standards updated after each monthly review.
Gross margin benchmarks depend on work type and should be tracked separately, not blended. Production runs typically hold 20 to 35 percent gross margin no cited source, prototype and low-volume work 40 to 60 percent no cited source, and pure pass-through or drop-ship work 8 to 15 percent no cited source.
The one public comparison point for prototype work is a single company. Proto Labs, which manufactures prototype and low-volume production parts, reported a gross margin of 44.5 percent of revenue in 2025 and 44.6 percent in 20243. That is one blended company margin, in the lower half of the band, not an industry benchmark.
A blended shop margin hides the fact that low-volume work carries most of the estimating and setup burden. Flag any production job clearing under 15 percent for a pricing review before you accept a reorder at the same number no cited source.
How to measure
Calculate gross margin per job, then roll it up by job class.
Keep production, prototype and pass-through work in separate buckets.
Charge estimating and setup cost to the jobs that caused them.
What moves it
Small-batch premiums that recover setup and estimating cost on low-volume work.
A pricing review before a low-margin production job reorders.
Capacity and utilization benchmarks set your pricing power. Bottleneck machine utilization of 75 to 85 percent is the healthy target no cited source; above 90 percent you cannot absorb rush work or breakdowns without missing dates no cited source, and below 60 percent you are carrying overhead the quotes are not recovering no cited source.
Two published reference points sit nearby, though neither is a bottleneck benchmark. Kaplan and Anderson's time-driven costing rule of thumb is to assume that practical full capacity is 80 to 85 percent of theoretical full capacity5. The Federal Reserve put U.S. manufacturing capacity utilization at 75.7 percent in August 2026, 2.5 points below its 1972 to 2025 average6.
Queueing theory explains the upper limit. As the arrival rate approaches the service rate, the number of jobs in process and their time in the system both rise, slowly at first and then rapidly4.
When utilization runs hot, raise standard lead times and apply expedite premiums rather than accepting every job at list. When it runs cold, the answer is more quoting throughput and a higher win rate, not price cuts that damage margin on the work you already win.
How to measure
Divide run hours by available hours on the bottleneck machine.
Measure the bottleneck itself, not the shop average.
Read it weekly next to your quoted lead times.
What moves it
Longer standard lead times and expedite premiums when load runs hot.
More quoting throughput when load runs cold.
Build a quote with an expedite premium or a longer lead time when the bottleneck is full. Job Shop Quote
Estimating productivity
Estimating productivity is an overlooked KPI with a direct cost. Cost to produce a quote commonly runs $75 to $400 depending on complexity no cited source.
At a 25 percent win rate, every won job absorbs 1 / 0.25 = 4 quotes worth of estimating labor.
World-class desks push cost per quote down with templated pricing, saved setups and configurators, targeting under 2 hours of estimator time on routine RFQs no cited source. Tracking quotes per estimator per week, typically 15 to 40 no cited source, tells you whether to add staff or automate before turnaround slips.
How to measure
Divide estimating labor and tool cost by the number of quotes sent.
Log estimator hours per quote by complexity class.
Improve these numbers as a system, not in isolation. The highest-leverage moves are faster turnaround to lift win rate, honest lead times to protect on-time delivery, and monthly variance review to tighten margin.
Set a scorecard of win rate, turnaround hours, on-time percentage, mean cost variance and segmented margin, and review it monthly against these ranges.
A shop that moves win rate to 40 percent, turnaround under 24 hours, on-time above 96 percent, and variance under 5 percent typically outperforms a lower-priced competitor no cited source. Reliability and speed win more repeat work than a discount ever will.
How to build your own baseline
Pick one KPI, write its definition down, and keep it fixed.
Log every quote and every closed job, not a sample.
Collect several months of data before you set a target.
Compare against your own trend first and published ranges second.
Record what changed in pricing or process whenever the KPI moves.
Little's Law as Viewed on Its 50th Anniversary. Operations Research, Vol. 59, No. 3, pp. 536-549 (INFORMS), J. D. C. Little, MIT Sloan; DOI 10.1287/opre.1110.0940. published 2011. Section 1 (Introduction), PDF p. 1: statement of L = λW; Section 4 (operations management), PDF p. 10: WIP = TH x CT (Hopp and Spearman); healthcare staffing discussion, PDF p. 11: queue growth as arrival rate approaches service rate. Accessed September 30, 2026.