Martin Messier

July 28, 2023

Why I only model low achievers

Many NLP students who discover modeling immediately think:

"This is fantastic! Let me find the best person in the world at *insert desired result here*, and I'm gonna model them!"

Isn't that cute? It's beautiful to watch! They're like young calves who stampede out of the stables in spring, eager to sprint across bright green pastures.

And while I can appreciate this romantic idea as much as I love the story of Jack Dawson and Rose Dewitt, I do my best to get my padawans past that as quickly as possible.

Forget high achievers. I only look for low achievers to model. And I recommend you do the same.


You heard me right.

There's two main reasons for you to forego high achievers and pick low achievers as exemplars.

The first is that you're probably not cut from the same cloth as they are. I know you want to model Elon Musk in entrepreneurship, and Warren Buffett in investments, and Serena Williams in athletics, and Tony Robbins in coaching. 

Really? You honestly think that's going to work for you? 

Are you looking to build a mega-tech business (while sleeping under your desk on the assembly floor), or manage a multi-billion dollar portfolio (while leading an insurance company), or become a #1 ranked tennis player (while sacrificing every other dimension of your life), or be on the road 320 days a year doing seminars (and not see your kids grow up)?

I doubt it.

I bet you're looking for tiny improvements in your health, fitness, income and quality of relationships.

You know what? There's a guy or gal who lives on your block who has exactly what you want. 

You have compatible lifestyles, and they're already living the piece of your life you aspire to live. That makes them much better exemplars for you, because of the ecological fit and compatibility between you.

The second reason is that you probably don't have access to mega achievers. It means that you can't put into the practice the cardinal rule of modeling.

I've seen modeling done wrong again and again over the past ten years. Most of the time, it's because the modeler violates this cardinal rule. When they do, the modeling project will not deliver, almost guaranteed.

So keep this front of mind: aim low!

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