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Quoting

January 13, 2026 · The Bloomfield Team

What Your Estimator Wishes the Front Office Understood

The sales manager walks into the estimating office at 10 AM. There are six RFQs in the queue. Two came in yesterday, three this morning, and one is a re-quote from a customer who changed the material spec after the first round. The sales manager asks about a specific RFQ from a new customer. Can it be done by end of day?

The estimator says they will try. What they are thinking is: I need to find historical pricing data for this alloy, check whether our Cincinnati mill can hold the profile tolerance on the drawing, get a current freight estimate for shipping to the customer's plant in Tennessee, and figure out if the heat treat vendor still has a two-week lead time or if it has stretched to four. All of that before I can even start building the cost model.

The front office sees a quote that takes too long. The estimator sees a system that makes every quote harder than it needs to be.

The Information Retrieval Problem

Most estimators in job shop manufacturing spend between 55% and 70% of their working hours on information retrieval. Finding data. Searching systems. Walking to the floor. Emailing suppliers. Calling the purchasing department to ask about lead times. Scrolling through old work orders to find a job that ran three years ago on a similar part.

The actual estimating work, the part that requires their experience and judgment, occupies the remaining 30% to 45% of their time. This is where they analyze the drawing, determine the manufacturing process, sequence the operations, calculate cycle times, set the margin, and price the quote. This is the work they were hired to do.

The front office typically has no visibility into this split. From the outside, the estimator receives an RFQ and delivers a quote some number of hours or days later. The time in between looks like a single task. In reality, it is dozens of micro-tasks, most of which have nothing to do with estimating and everything to do with hunting for information that should be at the estimator's fingertips.

Seven Things Estimators Know That the Front Office Does Not

The ERP is not a quoting tool. JobBOSS, Epicor, ProShop, Global Shop Solutions: all of them store job history. None of them are designed to surface that history in the context of a new RFQ. An estimator searching for a comparable past job has to know the right part number, the right customer, or the right date range. If the description field was not filled in consistently, and it rarely was across five years of entries from different people, the search comes up empty even when the data exists.

Material pricing is always stale. The steel, aluminum, or specialty alloy pricing the estimator needs is usually sitting in a supplier email from two to eight weeks ago. Finding the most recent quote means searching someone's inbox. If the purchasing manager is on vacation, the estimator either waits or guesses. A 6% swing in material cost on a $40,000 job is $2,400 in margin that can go either direction based on whether the estimator found the right number.

Tribal knowledge fills the gap. Every shop has two or three people on the floor who carry critical manufacturing knowledge in their heads. The estimator who needs to know whether a 32 Ra surface finish on 17-4 PH stainless can be achieved in turning or requires a grinding operation will walk to the floor and ask Mike, because Mike ran that job in 2022 and remembers what happened. When Mike is on vacation, or when Mike retires, that knowledge becomes inaccessible.

Quote accuracy depends on finding the right comparable job. An experienced estimator knows that a new RFQ for a 6" diameter 304 stainless housing with a 0.001" bore tolerance is going to run differently depending on wall thickness, length, and whether there are cross-holes. Finding a past job that matches on the right dimensions is the difference between a quote that is within 5% of actual cost and one that misses by 25%. That search takes time, and the results depend entirely on how the old jobs were documented.

Rush quotes carry hidden margin risk. When the front office pushes a quote to the top of the queue because the customer is important, the estimator compresses their research. The comparable job search gets abbreviated. The material check gets skipped. The floor consultation does not happen. The quote goes out faster, but the pricing is less accurate. We have seen shops where rush quotes, those completed in under four hours, had margins 8% to 15% lower than quotes that received a full day of estimating attention.

The quote queue never empties. In most job shops, the quoting backlog runs three to seven days. The estimator starts each morning already behind. When a new RFQ arrives, it goes to the back of the line unless sales escalates it. The result is a constant state of triage. The estimator is always deciding which quotes to work on first, which ones can wait, and which ones will expire before they get to them.

Documentation is the first casualty. When estimators are overloaded, the quotes that go out the door are the minimum viable response: a price, a lead time, maybe a few notes. The detailed assumptions, the comparable jobs used as reference, the reasoning behind the setup time estimate: none of that gets recorded. Six months later, when the customer reorders and the estimator needs to reference the original quote, there is nothing to reference. The whole research process starts over.

What This Costs the Business

A senior estimator at a mid-size job shop typically earns between $75,000 and $110,000 per year, fully loaded. If 60% of that person's time goes to information retrieval instead of actual estimating, the shop is paying $45,000 to $66,000 annually for what amounts to manual searching of its own data.

That number gets worse when you account for what the estimator could be doing with that time. More quotes per day means more bids submitted. Faster turnaround means higher win rates. Better research means more accurate pricing. Each of these improvements has a direct revenue impact that dwarfs the salary cost.

There is also the retention risk. Experienced estimators are difficult to replace. The learning curve for a new estimator in a custom manufacturing environment is 12 to 24 months. They need to learn the shop's capabilities, the customer base, the supplier network, the ERP system, and the informal knowledge that lives on the floor. When a frustrated estimator leaves because the tools and systems around them never improved, the replacement cost in lost productivity alone can run $150,000 to $250,000 over the first year.

What the Front Office Can Do

The first step is understanding the problem accurately. Sit with your estimator for a full day. Watch the workflow. Count how many times they leave their desk, switch between systems, send an email asking for information, or search the ERP for a comparable job. Track the time split between research and actual estimating. The numbers will be clarifying.

The second step is recognizing that the quoting process is an information problem, not a people problem. Most estimators are experienced, skilled professionals who know exactly how to price a job. The system around them forces them to spend the majority of their time doing something other than that.

The third step is building the system that your estimator actually needs. A custom AI tool built around your quoting workflow connects to the data sources that already exist in your operation: the ERP, the supplier quotes, the job travelers, the floor knowledge that has been documented over time. It organizes that data around each incoming RFQ and delivers it to the estimator before they start the quote.

The estimator opens the RFQ. The system has already identified the customer, pulled order history, surfaced the three most comparable past jobs with full cost breakdowns, shown current material pricing, and flagged any tolerances that caused problems on similar parts. The estimator's job shifts from detective work to decision-making.

That shift changes everything about the quoting function. Turnaround drops. Accuracy improves. Volume capacity increases. The estimator does the work they were hired to do. And the front office gets the speed it has always wanted without asking anyone to work harder.