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Amanda Elkins had a quality engineer role open for over a year. She'd seen a few candidates, all wrong fits. The salary was based on internal guesswork and nobody could say whether it was competitive. Then she pulled a labor market report, adjusted the job description and pay range based on what the data showed, and hired someone from the resulting candidate pool within two weeks.
That story came up during the first episode of The State of Industrial Hiring: Live, a webinar series from FactoryFix. Amanda (Hirsh Precision Products, a precision machine shop supporting aerospace and medical OEMs) and Ashley Vogel (Innovative Machine Specialists, a custom job shop in Marshfield, Wisconsin) joined FactoryFix's Halle Miroglotta for a 30-minute conversation about what the qualified candidate shortage actually looks like when you're the only person responsible for recruiting at your company.
They hire for machinists, welders, and technical manufacturing roles. They each operate as the sole recruiting function at their company. And both made specific changes that produced different results.
Here are the three takeaways worth sitting with.
1. Stop making hiring decisions without local market data.
Most hiring teams know their roles are hard to fill. Fewer know exactly why. Is the compensation off? Is there more local competition than they realized? Is the talent pool for a specific role shrinking faster than they thought?
Amanda described the moment labor market data changed how she operates. She initially expected it to be a simple check on whether Hirsh's pay ranges were competitive. It went further than that.
"It totally changed my mindset," Amanda said during the session. "We're not competing with fellow machine shops in the Denver metro area. We're competing with our customers because plenty of these OEMs have in-house machining."
That realization reshaped her entire approach. She started using the data to refine vague job descriptions, benchmark compensation against the right set of competitors (not just the obvious ones), and have direct conversations with leadership about where Hirsh ranked for the roles they were trying to fill. She also started using it for retention, comparing internal pay to what current employees could see on the same job boards.
The result: decision timelines compressed from four weeks to two. Amanda had the numbers. Leadership had the context. The guesswork was gone.
Ashley described a parallel experience in Marshfield, where her competitors for machinists and welders are within walking distance of her building. She used labor market data to benchmark what those companies were offering so she could show up with a competitive package before posting a role, rather than discovering the gap after candidates stopped responding.
The data also pushed her team toward longer-term pipeline thinking. When the numbers showed certain roles were unlikely to be filled through traditional posting alone, they leaned into partnerships with area high schools through a youth apprenticeship program.
What you can do with this: If you're making hiring decisions or having compensation conversations with leadership without local labor market data for the specific roles you're filling, that's the first thing to fix. National averages won't tell you what you're up against in your own market. The information changes every internal conversation you have, and it changes the offers you put in front of candidates.
If you want a labor market report for a role you're currently hiring for, Book a demo with FactoryFix, and we'll send you a complimentary report.
2. Your screening process is probably costing you candidates you don't know you're losing.
The 2026 FactoryFix Industrial Hiring Benchmark Report found that 26% of hiring teams cite excess time screening unqualified applicants as their biggest source of delay. That number should bother anyone managing a pipeline solo.
Ashley described what her process looked like before she made changes. She was using the same platforms most manufacturers rely on and getting charged for every application regardless of quality. The volume was there. The relevance was not.
"You're looking for a skilled position, and you'd have somebody who would apply that maybe had only been in the food service industry," she said. "Meanwhile, you're losing out on the candidates that you actually wanted because you had to sift through all the ones that didn't have the experience."
She rebuilt her screening process and started using AI to prioritize applicants based on the qualifications she set. The shift was significant, but what convinced her to trust it was realizing she still controlled the process.
"You're driving the bus," Ashley said. "Any feature that you want to try out, you're able to do that. And you're able to adjust from there."
Amanda took a different path to the same conclusion. She leaned into AI early and now has it handling 80-90% of initial qualification. She described a recent manufacturing engineer search where she had over 100 applicants, most of them wrong fits. AI screening let her focus on roughly 10 candidates and get them in the door within a week of applying.
"I probably don't have time to go through all of them," Amanda said. "But I feel good about moving on."
What you can do with this: Time your next hire from application to first conversation. If it's taking more than three days to get a qualified candidate on the phone, your process is the bottleneck. Figure out which part of your screening requires your judgment and which part is just sorting. The sorting is where automation earns its place.
3. Build the business case for quality before someone pushes you to move faster than the market allows.
The pressure to fill the seat is constant. But in skilled trades and technical roles, a bad hire costs more than just a salary. It costs training time, coverage gaps, and the months you spend doing it all over again when the person doesn't work out.
Nearly half of industrial hiring leaders in the benchmark survey rank improving candidate quality as their single biggest priority for 2026.
Amanda and Ashley both had to make that case inside their own organizations. Amanda described how having labor market data gave her the language to explain to leadership why a role was taking longer to fill, and what it would actually take to attract the right person. Ashley described how focusing on quality over volume changed her results. She had a payroll position where the first three hires didn't stick. When she shifted to a more deliberate process, the fourth one did.
Both of them got more deliberate up front so they stopped paying for it on the back end.
What you can do with this: Calculate what a bad hire in your hardest role actually costs. Time to rehire, overtime coverage, training investment, productivity loss while the seat is empty again. Have that number ready. The next time you're being pushed to move faster than the market allows, lead with it. It reframes the conversation from "why is this taking so long" to "here's what it costs us when we rush it."
Watch the full conversation
The full 30-minute recording is available here: Watch Episode 1
This conversation is part of a 3-part webinar series built on the findings from the 2026 FactoryFix Industrial Hiring Benchmark Report, which analyzed 1.2 million applications, 15,500 roles, and survey responses from 83 hiring leaders across 18 industrial role categories.
Episode 2 covers hiring speed: how staffing agency teams are compressing time-to-fill without sacrificing quality. Register for Episode 2 here.
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