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PLM vs Airtable: three plays for product-driven brands

12 months ago I wrote about the hybrid approach: run Airtable alongside a PLM, with the PLM owning the tech pack and Airtable owning everything around it. That was the honest answer at the time. The story's moved on.

What changed is the ceiling of what Airtable can actually do. Custom interfaces (vibe-coded TypeScript UIs that sit on top of the base) now cover the work we used to say only a PLM could handle. Matrix BOM editing. Automated tech pack generation. Paint tools for colourways. Drag-and-drop styling. Live builds, in use right now, not concepts.

So the real question for most product-driven brands in 2026 is which of 3 plays fits where you are today.

The three plays

We've run discovery conversations with fashion, beauty, CPG, and outdoor brands over the last year. The builds cluster into 3 shapes.

1. Airtable as the PLM

For brands with high SKU complexity and a working relationship with rigid, expensive PLM software that isn't paying back what it costs. We're currently working with leading streetwear brands replacing Centric entirely, and an enterprise CPG brand rolling this out across 100+ licences to replace their existing PLM stack.

The full stack lives in one place. Design briefs, BOM, tech packs, costing, sampling, supplier portals, channel exports. Every team works from one product record. You own the system outright when it ships, no licence fee following you around for a decade.

2. Airtable around an existing PLM

For brands where a PLM (usually Centric) does the tech pack work well, but everything around it (costing, planning, supplier data, channel exports) sits in spreadsheets or disconnected tools.

We keep the PLM doing the job it's good at and build the Airtable layer around it. Product master data, launch planning, supplier collaboration, commercial ops. The existing system keeps running. The Dark Stack of spreadsheets around it gets replaced.

Passenger Clothing run a version of this. Backbone PLM for their garment workflows, Airtable for the Shopify PIM and the operational stack around it. Joe Simms, their CTO: "Nolo Apps are not another software vendor, they're part of my team."

3. Operations Stack (no PLM needed)

For brands under £50M where the back-office workflows (purchasing, supplier management, product data governance) run on spreadsheets, WhatsApp, and email. Often founder-led. Often being told they need NetSuite or Business Central as the next step.

Most of these brands will never need a PLM or an ERP. The right build for them is functionality covering the 30% of an ERP and a PLM they actually need, configured clean on Airtable. Product master, purchasing, supplier portals, variant management. We configure from a template now rather than custom from scratch, so projects that used to take 50 hours track closer to 25.

Why PLMs alone fall short

I've watched this pattern repeat too many times over the last 4 years to miss it. A brand buys a PLM, adoption drags, teams keep their spreadsheets going, the licence bill arrives regardless.

Rigid by design. Your processes evolve as you scale. PLMs push back against that. We're sitting in on a brand right now that's spending 4 months migrating from Centric v7 to v13, just to move versions. Before any actual improvement lands.

Your data sits behind a wall. Point Claude at an Airtable base and it navigates the whole thing (supplier performance, purchasing gaps, production delays, answered in seconds). Try the same with most PLMs and you're looking at months of integration work, if it's possible at all. You won't be able to trust your AI any more than you can trust that your Production Schedule is up to date.

The money sits on licences, not outcomes. £200-£300/user/month is normal. One client was spending over £100K yearly on licence fees while still relying on manual processes for most of the work. The spend wasn't coming back as operational value.

Not every brand needs a PLM from day one, or ever.

Oliver Rhodes, CEO and Co-Founder

When a PLM still makes sense

A PLM earns its place in specific scenarios.

  • Your design team is large enough that deep Adobe integration (Illustrator files, CADs, spec sheets) is the core of how they work day-to-day.
  • You need complex grading across multiple size ranges with strict version control and regulatory documentation.
  • You're operating at enterprise scale (hundreds of stylists, formal design standards, tightly governed design workflows).

For most brands under £50M, none of the above is the actual bottleneck. The actual bottleneck is product data scattered across 30+ spreadsheets. A PLM adds a 31st place to keep track of.

Airtable vs PLM: the 2026 comparison

How to decide which play fits you

The real decision is about what your product operations look like today, and what you need them to look like 12 months from now. Start here.

Where does your product data actually live? If the answer is "across a lot of spreadsheets, a few email threads, and somebody's head", you start with either an Operations Stack or full PLM in Airtable. Which one comes down to scale and complexity.

Do you already have a PLM that's doing a job well? If yes, wrap Airtable around it and let each system do what it's best at. If it's dragging adoption and costing you £100K+ in licences that aren't paying back, full replacement is on the table.

What do you need to be AI-ready for? AI works on your operational data or it sits there doing very little. The answer shapes where your master data needs to live. Brands already on Airtable can point Claude at their base and ask it anything. Brands on fragmented stacks can't.

Most teams don't know which play they need until they run discovery on the current state. These are the shapes we've seen work, pulled from hundreds of builds. The fit is situational.

Strategic Recommendations

01
Start with master data. Every play builds from one clean product record.
02
Go full PLM in Airtable if you need one. BOM, tech packs, costing: solved, live, in use.
03
Wrap Airtable around your existing PLM. Keep what's working. Build around what isn't.