For a job shop or contract manufacturer, quote speed matters. Customers often send the same RFQ to several suppliers, and the first credible quote has an advantage. Yet the first hours of every quote are spent on work that is not estimating at all: opening the packet, reading the drawings, finding the material and tolerance requirements, noting the quantities, and searching for similar jobs you have done before.
Experienced estimators are scarce, and that preparation work consumes their time before their expertise is ever applied.
What an estimator package contains
The goal is not to have AI produce the quote. It is to hand the estimator a prepared package. A good package lists the parts and quantities, the materials and finishes, the critical tolerances and any special processes, the delivery requirements, and the terms in the RFQ that deserve attention.
It also flags what is missing. If a drawing revision does not match the one referenced in the request, or a quantity break is ambiguous, the package says so up front, before the estimator has invested an hour.
Using your own history
The most valuable part of the package is often a list of related historical jobs. Manufacturers have years of quotes and job records in their ERP and file shares, but finding a similar part usually depends on someone remembering it. Searching past jobs by material, geometry described in the drawing notes, customer, and process gives the estimator a starting point grounded in your actual costs.
Where the estimator stays in charge
Pricing, lead time commitments, and the decision to bid at all remain with the estimator and the sales team. The workflow prepares; people decide. In practice this keeps the quality of your quotes where it is while giving estimators back the time they spent on intake.
A sensible pilot metric is the time from RFQ received to estimator-ready package, alongside the time from RFQ to quote sent. Track both, because a faster package only matters if quotes go out sooner.
