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First Principles

Why Most Cannabis Brands Break at Scale

Bryan FieldsJanuary 7, 2026299 words
Branding & MarketingMSOs & Multi-State OperatorsCultivation & Extraction
Written after
The Playbook Behind Consistent Cannabis Products at Scale ft. Ryan Crandall
Ep. 284 · Ryan Crandall · Jan 2, 2026

Imagine buying a Coca-Cola in New York… then buying another one in Chicago — and it tastes different.

You wouldn't debate it.

You'd stop buying Coca-Cola.

That's what product inconsistency actually costs.

A customer switching brands and likely never returning.

Hidden from dashboards.

Just sales numbers slowly declining.

Everyone wants their brand to be known for consistency. Almost no one is willing to do the unsexy work that actually makes it possible.

Why?

It's expensive. It's not mandated. And it requires additional steps.

That gap is where most cannabis brands break.

Consistency isn't an internal slogan. It's not a flavor profile. It's not a milligram number on a label.

It's systems. It's process control.

And it's still missing across most teams in this space.

I get it.

The level of precision required adds cost. It slows things down. It impacts the bottom line.

But treating process control as a "nice to have" — or something you'll layer in later — is the exact mindset that leads to missed numbers, stalled velocity, and emergency board meetings asking why market share is slipping.

Anyone can get a customer to buy once. Real brand power shows up on the second, third, fourth, and fifth purchase.

That's why my conversation with Ryan Crandall at MariMed stood out.

Ryan breaks down how MariMed engineers consistency across states by centralizing inputs, testing at multiple points throughout production, and minimizing drift before it ever reaches the consumer.

Consistency isn't accidental — it's engineered.

This is also where the industry is headed.

Process control. Process stability. Process analytical technology.

This is where Newton fits — not as "more software," but as infrastructure. A way to surface variability in real time, understand where drift is introduced, and move consistency from a hope into something measurable and repeatable.

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    Originally published on LinkedIn.