When a patient suffering from a heart attack is admitted to a hospital, doctors need to decide whether the patient should be treated as low-risk or high-risk. If the patient’s life is threatened, he’s high-risk and needs intensive care.

Such a decision can save or cost a life. But until the early ‘90s, doctors and medical staff didn’t have the luxury to make it quickly.

At the University of California, San Diego Medical Center, for instance, they measured as many as 19 cues within the first 24 hours for each such patient. These cues included blood pressure, age, and 17 other binary covariates that were considered important indicators of the patient’s health. Once measured, they were probably ranked according to importance and run through complex statistical software to arrive at a final conclusion.

Then in 1993, Leo Breiman, a brilliant statistician and a pioneer in the field of Machine Learning, came up with a simple decision tree. It classified patients according to risk by using a maximum of three variables.

Now, a patient who has a systolic blood pressure of less than 91 is immediately classified as high risk—no further cues are needed. Otherwise, the decision moves to the next cue: age. A patient under 62.5 years is low risk; if he’s older, then the medical team checks the final cue: sinus tachycardia.

This meant the medical staff could begin life-saving treatment sooner, and it also freed up resources for them to attend to more patients.

This strategy is simple for three reasons. First, it ignores the majority of details that are not important to make a practical decision. Second, it reduces the decision to a maximum of three yes/no questions. For instance, it doesn’t care how much older or younger than 62.5 years the patient is.

Third, it’s a stepwise process that could end after the first question and doesn’t add values like weight on top of the three predictors.

The model’s simplicity raised suspicions about its accuracy, especially when compared with complex methods that process all available indicators. But it has proved to be more accurate than its complicated and fancy competing methods.

To this day, doctors use the model to identify patients at risk of having a heart attack. Imagine how many lives it has saved!

Everything that has lasted for a notable amount of time has been simple. The adoption of every technology increased when it became simple enough for the majority to use.

The best example of simplicity is evolution. As Morgan Housel wrote:

“Animals with hundreds of teeth often evolved to have a handful of specialized incisors, canines, and molars. Dozens of jawbones fuzed into two big ones. Skulls often made up of hundreds of tiny bones evolved into typically fewer than 30.

Evolution figured out its version of simplification. It (if you can imagine it talking) says, “Get all that useless crap out of the way. Just give me the few things I need and make them really effective.”

Yet, much of our lives are shrouded in complexity.

Why We Love Complexity?

Everyone craves a simple life, but many people struggle to achieve it because of mankind’s inherent bias towards action.

It’s true that all progress in the world is a result of taking action. But this conventional wisdom misses a critical point that progress is a result of the right actions, which include retaining what’s essential, flushing out the rest, and sitting tight.

The last part is where people struggle the most. Following the same routine is boring, and we dread boredom the most. Sitting tight in silence is uncomfortable; we’d rather replace it with aimless distractions to avoid our problems and stay in our emotional comfort zones.

“All of humanity’s problems stem from man’s inability to sit quietly in a room alone,” — Blaise Pascal

That’s why, regardless of how well something is going, people take more action. Such actions leaven boring routines, feel intellectually stimulating and challenging, and keep FOMO at bay. But what we fail to notice is that each new action increases a system’s complexity which has huge long-term costs.

Business leaders add unnecessary steps in processes and complicate them, leading to a loss in business efficiency. People buy and sell stocks frantically despite evidence that you actually make more money in the long term by just sitting tight with a few investments. Reading becomes a race to finish more titles instead of absorbing the wisdom from the ones that leave a lasting impact.

Complexity keeps us busy and lets us avoid FOMO. But it also makes us move in circles instead of moving forward. We lose sight of our goal and instead, chase every new shiny object.

Eventually, life becomes a meaningless, stressful journey of chasing the goals others set for us.

Simple is Beautiful

“Truth is ever to be found in simplicity, and not in multiplicity and confusion of things.” — Isaac Newton

Contrary to the popular myth, simplicity doesn’t mean dumbing things down. It means distilling a concept, task, or system to retain the essence. This essence or fundamental truth makes your life better in the following ways:

1. It sets the 80-20 Rule in motion, where 20 percent of your actions yield 80 percent of the results. You will still experience plateaus, but when you get results, they’re exponential.
2. It lets you get rid of the distractions and stick to what really matters. During a workout, for instance, this means getting the form right before you lift heavier weights. In the long term, this makes you stronger and less prone to injury.
3. You fall in love with the process, and your mind doesn’t feel overloaded with the burden of making decisions each minute. And the more you do something because you love it, the closer you get to mastering it.

No wonder da Vinci called simplicity the ultimate sophistication.

Simplicity comes not from addition, but from thoughtful subtraction. When you remove the weeds, you can see the quality of the soil and decide what to grow on it.

But Be Wary…

It’s tempting to remove something for the sake of it, or because it’s difficult, or it doesn’t align with your beliefs. Such oversimplification makes people prone to the confirmation bias, and it doesn’t get them any closer to their goals. Eventually, they start taking any action that appears easy but ends up complicating matters.

“Everything should be made as simple as possible, but no simpler,” Einstein once said. So how can you tell what to remove and what to retain?

An effective approach to simplify your life is to ask yourself, “What did I achieve by doing this?” Did you get closer to your goal? If not, did you learn? By this, I mean did the task or experience lead to an improvement in your behavior?

If the answer is yes, it’s useful to retain even if you failed because such learning is valuable feedback. If you cannot find a compelling reason for doing the task, it’s best to let it go.

Such reflection will improve the speed and quality of your decisions and help you simplify your life.

“We do not learn from experience… we learn from reflecting on experience.” — John Dewey

Complexity is like sugar: easily available and tasty, but laden with nasty side effects.

Simplicity is like a healthy lifestyle. It feels tougher in the beginning but is more beautiful and rewarding in the long term. And once you begin to enjoy its taste, you’re never going back.