“Being able to make decisions when you know you have imperfect data is so critical. I was always taught that: A good decision now is better than a perfect decision in two days,” says James Waters, former Deputy of Scheduling at the White House.

The decision to forgo perfection for action is one example of a good decision — one that most entrepreneurs should be making.

But don’t mistake being decisive for being a good decision maker.

Nobel economics laureate and psychologist Daniel Kahneman recently revealed the secret to making good decisions at the Wharton People Analytics Conference.

Kahneman said:

“Algorithms are noise-free. People are not. When you put some data in front of an algorithm, you will always get the same response at the other end.”

Please don’t think you need a degree in computer science or statistics to start implementing Kahneman’s algorithm approach.

At ETR we use a peer-reviewed system for all our long-form sales letters called the Copy Logic. In our Copy Logic sessions, we run sales letters through what’s called the CUB check (our algorithm), which I’ll explain in a second. But first, here’s Kahneman:

“A good algorithm does not require a massive amount of data. Let’s say you are evaluating the financial stability of firms to give them a loan or insure them against financial risk. Sit down with a committee of people who are knowledgeable about the situation and make a list of five or six dimensions. More than eight is probably unnecessary. If you create good ranking scales on those dimensions, and give them equal weight, you will typically do just as well as with a very sophisticated statistical algorithm,” says Kahneman.

Kahneman first invented a prototype of this procedure when he was a young Israeli platoon commander.

Kahneman identified six dimensions that could be rated one at a time, among them punctuality, sociability, conscientiousness, “something called masculine pride” (he noted that these were interviews for combat units, 60 years ago), and others, says Wharton School of Business.

“Very important to rate things one at a time,” says Kahneman. “That way you don’t form a global impression of the person, but a differentiated impression of [each] topic. It controls what psychologists call the halo effect.”

If you’re wondering how your organization can start implementing a strategy like Kahneman’s, let me tell you how ETR uses Kahneman’s algorithm approach for writing better sales letters.

In our Copy Logic sessions at ETR, we run sales letters through what’s called the CUB check (our algorithm).

Implementing CUB provides us with data about the probable success of a sales letter.




How it Works

We typically get 4-6 people (6 is ideal) to sit down for 30 minutes with one sales letter. Everyone rates the copy in each of the CUB categories on a scale from 1.0-4.0.

1.0 is bad, would not read more
2.0 is neutral, might read more
3.0 is good, but skeptical
4.0 is excellent, with interest

We aim for a 3 to 3.5 out of 4. This process is repeated for each section of the sales letter (Headline, Lead, CTA, etc.) and the scores are totaled for a final score.

Implementing this algorithm does not guarantee winning ad copy, but it dramatically increases our chances.

Daniel Kahneman calls this “disciplined thinking” — a strategy anyone can start applying today. Stop relying on whimsical decision making, and start relying on a proven and tested algorithm.

Nick Papple
Managing Editor
Success Formula Daily


Everything We Thought We Knew About Resilience Is Wrong

We often take a militaristic, “tough” approach to resilience and grit. We imagine a Marine slogging through the mud, a boxer going one more round, or a football player picking himself up off the turf for one more play. We believe that longer we tough it out, the tougher we are, and therefore the more successful we will be. However, this entire conception is scientifically inaccurate. Click here to read more.

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Nick Papple is a regular writer for Early to Rise. He holds a Bachelor of Science degree in Human Kinetics from the University of Guelph in Canada.


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