The industrial-tech CFO

The first time I signed for a piece of medical-grade equipment, I watched the deposit leave the account and thought: this machine hasn’t touched a single client yet.

No revenue. No bookings. Just a lead time, an install date, and a hole in my cash flow the size of a small car.

That’s atoms finance. And an entire generation of finance leaders has never had to do it.

The software blind spot

The best finance careers of the last two decades were built in software. ARR, net revenue retention, CAC payback. Gross margins that start with an eight. No inventory, no freight, no machines to commission. When the product breaks, someone ships a fix by Friday.

That world trained brilliant operators. It also trained a blind spot.

Because the money is moving. AI — the software era’s biggest breakthrough — runs on concrete, copper, and cooling towers. Data centers. Power contracts. Chips with months-long lead times. And around it, capital is flowing back into defense, energy, robotics, and manufacturing. Even pure software companies now sign multi-year compute commitments that behave like industrial obligations: big, fixed, and paid for long before the revenue shows up.

The finance seat is being pulled back toward physical things. And most of the people sitting in it have never priced a machine, financed one, or watched one sit idle.

I’ve spent my career in atoms

I’m a CPA, CA. I’ve held the CFO seat. And I built a seven-figure salon and medi-spa where every dollar of revenue had to pass through a physical constraint — a room, a chair, a machine, a set of trained hands.

Atoms finance isn’t theory to me. It’s Tuesday.

So here is what I’d tell any software-trained CFO stepping into the industrial-tech era. Six things to relearn:

1. Cash moves before revenue does. Software collects the annual prepay up front. Atoms businesses pay deposits on equipment with long lead times, then wait. The P&L will smooth it later. Your bank account feels it now. Build your forecast around when cash moves, not when the accounting recognizes it.
2. Capacity is the ceiling. Software revenue scales while you sleep. A machine has hours in the day. Utilization is where margin gets made or lost — I could tell you the revenue per hour of every room in my spa. Learn to say the same about your assets.
3. Growth eats cash. More orders means more inventory, more work in progress, more receivables aging while payables come due. In a physical business, a growth spurt can sink you faster than a slump. Working capital is the fight.
4. Depreciation is real money you already spent. SaaS-trained operators treat D&A as an add-back on the way to EBITDA. In an industrial business, that line is the machine wearing out underneath your revenue, and its replacement has a date on the calendar.
5. Debt belongs in the toolkit. Equipment finance, asset-backed lines, lease-versus-buy math. Venture equity was the only instrument software ever needed. Atoms get financed differently — the lender wants collateral it can touch, and the CFO who can structure that debt well has a real edge.
6. Time is physical. There is no hotfix for a machine on a boat. Lead times, commissioning, downtime, repairs. Your forecast has to respect physics, because the business will.

The part AI can’t do for you

AI will happily model all of this — depreciation schedules, utilization curves, working-capital cycles, produced in seconds.

What it can’t produce is the judgment of a CFO who has watched an expensive machine sit idle because the one person trained to run it walked out. Who knows what a two-week shipping delay does to a quarter. Who has felt the gap between a clean model and a loud, hot, physical operation.

That knowledge lives in scar tissue. And the only way to earn it is to get close to the atoms.