Measure Twice, Cut Once—Before You Automate Anything

I do woodworking as a hobby. Nothing fancy—just enough to enjoy working with my hands and building things.

There’s a saying you hear a lot in woodworking: measure twice, cut once.

It sounds simple, but it exists for a reason. Once you make the cut, there’s no going back. If you get it wrong, you don’t just lose time—you waste material, and sometimes you have to start over completely.

I was reminded of this while working on a new workbench I’m building. Standing there, measuring, checking, rechecking—it struck me how much this applies to the way businesses are approaching AI right now.

Because right now, most businesses are doing the opposite.

They’re cutting first.

They jump into AI tools, automation platforms, and new systems before they’ve properly understood the processes they’re trying to improve. There’s pressure to move fast, adopt something, and not fall behind.

So they start building.

Automations get set up. Tools get connected. Workflows get stitched together.

But underneath it all, the process itself is still unclear, inconsistent, or broken.

Automation doesn’t fix bad processes—it just makes them run faster.

If your workflow is messy, automation doesn’t clean it up. It scales the mess. It creates more edge cases, more confusion, and more time spent fixing what should have been thought through at the start.

It’s the business equivalent of cutting a piece of wood before you’ve measured it properly. You might only be off by a small amount—but by the time everything comes together, nothing fits the way it should.

And now you’re either patching things together… or starting over.

Measure Twice: Mapping Before You Automate

“Measuring twice” in business isn’t about overthinking. It’s about clarity.

Before you automate anything, you need to understand what’s actually happening day to day.

A simple way to do this:

• List out the tasks you and your team do regularly.
• Track your time for a week—what takes longer than expected, what repeats, what feels manual.
• Identify where things break, slow down, or depend on specific people.

Once you have that, you can start evaluating properly.

For each task, give it two simple scores:

• Ease of automation (0–10) – How easy would it be to automate?
• Business impact (0–10) – How much would it actually improve the business?

This is where most businesses skip ahead. They jump straight to tools instead of stepping back and prioritising.

The Maverick Matrix

This is where the Maverick Matrix comes in.

Instead of guessing what to automate, you map your tasks based on impact versus effort.

• Catalysts (high impact, low effort) – Quick wins that create immediate momentum.
• Transformers (high impact, high effort) – Bigger initiatives that reshape how your business operates.
• Sparks (low impact, low effort) – Small improvements that reduce friction.
• Mirages (low impact, high effort) – Time-consuming efforts that don’t deliver meaningful value.

Most businesses spend too much time in the wrong quadrant. They get pulled into mirages—solutions that feel smart but don’t actually move the business forward.

Cut Once (Even If It’s Not Perfect)

You’re going to make mistakes. You’re going to automate things that don’t quite work the first time.

That’s part of the process.

But there’s a difference between learning through iteration—and creating avoidable problems because you rushed in without clarity.

When you take the time to map your processes first, something shifts.

• You stop chasing tools.
• You stop automating for the sake of it.
• You start making deliberate decisions.

And when you finally “cut”—when you implement automation or AI—it fits.

Not perfectly. Not immediately.

But well enough to build on.

Measure twice. Then automate.