I once presented a model with 94% accuracy to a room of eight stakeholders.
Nobody asked about the model.
They asked: “What does this mean for us next quarter?”
I didn’t have that answer ready.
That’s not a modeling problem.
That’s a communication problem.
Most data education teaches you to build correctly.
Almost none of it teaches you to explain what you built to someone who doesn’t care how it works.
So you get data scientists who can walk a peer through every decision in the model, and stumble when the room asks: “So what should we do?”
That gap is where careers stall.
Past a certain level, your technical ceiling isn’t what limits you.
Your communication ceiling is.
The model that gets presented clearly beats the model that’s slightly more accurate.
I learned this slowly.
The shift that changed things wasn’t learning more. It was starting to think about the audience before the output.
Not what did I find, but what does this person need to understand to act differently tomorrow.
That question changes what you build. What you cut. What you lead with.
Clear communication is not how you explain your work. It’s how your work survives contact with the real world.
— Josep
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