Scaling Under Constraint: Machining Technology Investment Strategies for 2026
Many machine shops are entering 2026 with a mix of opportunity and pressure — volatile costs, lingering tariff impacts and tight labor. But there is a way to scale under constraint by connecting operations and finance and getting more from the technology you already own.
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I’m beginning 2026 — an IMTS year and a new planning cycle for many of you — having just gained an outside view on what’s changing for small and mid-sized shops. I recently sat down with a financial strategist who specializes in advising manufacturing leaders, including many of the multi-generational, family-owned businesses we often cover in Modern Machine Shop.
The advisor is Mike Sibley, a CPA and partner at James Moore & Co., and from his vantage point the outlook is mixed. Many of his clients are in decent shape. Cash flows are solid, job orders are steady and several end markets are planning for growth.
At the same time, the ground is shifting beneath their feet. Tariffs that were first thought to be temporary appear to have no end in sight. Material pricing feels chaotic. And while labor is always tight, very few of his clients can justify spending tens of millions on fully automated lines.
Their reality, Sibley says, necessitates controlling what they can and being extremely deliberate with new tech investments.
Two of Sibley’s comments stuck with me. First, the shops that are gaining ground are the ones that connect shopfloor operations and financials with real numbers. They can see cause and effect between spindle time, quoting, margins and cash. Second, “buy more technology” is not in itself a strategy. Every machine, system and software package must earn its keep inside a larger plan.
Looking at Modern Machine Shop’s first issue of 2026 through this lens, it strikes me that every feature article circles the same problem: how do you scale under constraint without starting from scratch each time?
Novo Modo, the young five-axis shop that Evan Doran writes about on page 36, is a clear example. Instead of chasing pricier hardware, founder Joseph Alonso obsessed over workholding and repeatable cells. Crimping parts and using windowed frames instead of machining dovetails may sound like a small change, but it eliminates entire operations, setups and the need for a separate “dovetail machine.” Standardized offsets and modular zero-point workholding dropped setup time from an hour to a few minutes, and a complex satellite gimbal can go from a 45-pound block to a finished, 2.5-pound part in a single operation. The Hermle matters, of course, but Novo Modo’s advantage is how its fixtures, preparation and workflow elevate that machine into a cell the shop can copy as it grows.
The AI servo tuning story in this issue (page 40) shows a different kind of leverage. What FANUC calls AI Servo Tuning is not something most machinists will ever run directly. But when servo behavior is the root cause of a surface finish flaw or contour issue, this tool lets a technician diagnose and correct it in minutes instead of days. When “identical” machines are not behaving identically, it helps bring them in line. Quietly, it turns years of servo-tuning experience into a repeatable process and helps the machine you already own behave the way it should.
Julia Hider’s piece on machining nickel-based alloys (page 50) reinforces the same theme at the cutting edge. Shops that routinely handle materials like Inconel get ahead by being intentional with end mills and cutting strategies: tool materials that balance hardness and toughness, geometries and coatings that hold a sharp edge and tool paths that manage heat. Taken together, those choices can dramatically increase metal removal rates in tough materials, and the only “new investment” necessary is better decision-making.
Hider’s story (page 44) on GTR Manufacturing looks at leverage at the business level. Wanting to add machining capabilities to its sheet metal fabrication business, GTR could have tried to stand up a machining department from scratch in an already crowded building. Instead, it acquired Sweeney Metal Fabricators, a shop where sheet metal and machining already intersected. The deal brought not just machine capacity but a mature process capability that could plug directly into GTR’s existing customer base. By standardizing around Paperless Parts for quoting, GTR now has integrated capabilities, customers and data across three facilities and thousands of jobs — all without reinventing machining from the ground up.
Even the American Precision Museum feature is, in its own way, a story about leverage (page 54). Robbins and Lawrence did not invent most of the machines in their armory. They assembled and refined a system of tools and processes that could turn out interchangeable parts in a fraction of the time. The museum’s “Innovation Station” carries that idea forward, tracing a line from handwork to line shafts to done-in-one machining, robotics and 3D printing. Capabilities advance incrementally as each generation combines more operations and reduces variation.
Finally, there is the profile of Scott Harms and MetalQuest Unlimited (page 80). His company spent years overexposed to the oil-and-gas industry, then got hammered by COVID at the exact moment it had invested in an Index multispindle that cost five times more than any machine they had ever purchased. By Harms’ own account, 24 years of work felt like it was coming apart. Their path out was a hard choice to run that equipment 24/7, open a second location and build a leadership team that could keep the company going even in his absence. It’s a personal version of the same challenge: How do you turn one risky asset and a constrained labor market into durable capacity?
All of these stories live in the environment Sibley described: solid opportunity paired with real pressure. As you think about your own plans for this year — and maybe your IMTS wish list for September — it’s worth asking where you already have the ingredients for leverage. Where are you doing work twice? Where does setup, quoting or troubleshooting quietly eat away at your margins? Where are you relying on a single “magician,” whether that’s a programmer, an estimator or a machine?
Scaling intelligently by getting more from your people, your equipment, your data and your decisions is a worthy goal for the new year. It’s also a useful way to read this issue.
