Estimating Formulas

How to Calculate Quote Turnaround, Estimator Capacity, and No-Bid Value

A worked walkthrough of the five formulas that run an estimating desk, with real units and numbers.

An estimating and sales engineering desk runs on a handful of numbers you can compute by hand before any deal closes. This guide works through the five that matter most: quote turnaround time, estimator workload capacity, RFQ complexity score, tooling amortization, and the no-bid expected value. Each pulls from data you already log in your ERP or quote log. The MFG Calcs Quote Turnaround Time and Estimator Workload Capacity tools automate these, but knowing the arithmetic lets you sanity check every output and defend it in a pricing review.

Quote turnaround time is elapsed calendar time from RFQ receipt to quote delivered, not touch time. Break it into four stages and sum them: intake queue, engineering review, cost modeling, and approval. Say an RFQ lands and waits 1.5 days in queue, takes 4 hours of engineering review, 3 hours of cost modeling, and 1 day for margin approval. Convert touch hours at an 8 hour day: 4 hours is 0.5 day, 3 hours is 0.375 day. Total elapsed is 1.5 plus 0.5 plus 0.375 plus 1.0, or 3.375 business days. Track the queue portion separately; it is usually the largest and cheapest to cut.

Estimator workload capacity tells you how many quotes one person can produce before the backlog grows. The formula is available hours per period divided by average touch hours per quote. An estimator with 160 paid hours a month, minus 20 percent for meetings and admin, has 128 productive hours. If the average quote consumes 3.2 touch hours, capacity is 128 divided by 3.2, or 40 quotes per month. Compare that to incoming RFQ volume: 52 RFQs a month against 40 capacity means a 12 quote monthly shortfall, which the Estimator Workload Capacity tool flags as a staffing or triage gap.

RFQ complexity score converts a drawing package into a single number so you can route and prioritize. Assign weighted points to the drivers: part count, tightest tolerance, number of processes, material callouts, and new versus repeat. A simple scheme scores each factor 1 to 5, then multiplies by a weight. Example: 12 parts (4 points, weight 2, equals 8), plus or minus 0.001 inch tolerance (5 points, weight 3, equals 15), 6 processes (4, weight 2, equals 8), and an exotic alloy (5, weight 1, equals 5). The sum is 36. Scores above 30 in the RFQ Complexity Score tool signal an engineering deep dive, not a same day turn.

Tooling amortization spreads a one time tool cost across the piece price. Divide fully burdened tooling cost by the total parts it will produce over the program. A progressive die costs 48,000 dollars, estimated annual usage is 25,000 pieces, and the program runs 3 years, so lifetime volume is 75,000 parts. Tooling adds 48,000 divided by 75,000, or 0.64 dollars per part. If the customer pays the tool up front, this term drops to zero and you quote only piece price. The Tooling Quote Amortization tool also handles partial payment splits and tool life shorter than program length.

The no-bid decision is expected value math, not gut feel. Compute expected profit as win probability times margin dollars, then subtract the cost to prepare the quote. A job carries 18,000 dollars in gross margin at a 25 percent win probability, so expected gross is 4,500 dollars. If the quote takes 14 engineering hours at a 95 dollar loaded rate, preparation costs 1,330 dollars. Expected net is 4,500 minus 1,330, or 3,170 dollars positive, so you bid. Flip the win probability to 8 percent and expected gross falls to 1,440, below the 1,330 cost floor plus your hurdle. The No-Bid Threshold tool runs this each time.

Win-rate margin impact quantifies the trade between price and hit rate. Model win probability as a function of quoted margin, then find the margin that maximizes expected margin dollars, not win count. Suppose at 30 percent margin you win 20 percent of bids and at 22 percent margin you win 35 percent. On a 60,000 dollar job, option one yields 0.20 times 18,000, or 3,600 expected dollars; option two yields 0.35 times 13,200, or 4,620 expected dollars. The lower margin wins on expected value here. Run several points through the Win-Rate Margin Impact tool to map the curve for your shop and product mix.

Published 2026-07-02.