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Why Systems Fail?

Why Systems Fail?


"You do not rise to the level of your goals.

You fall to the level of your systems" - James Clear.

Pick any goal, personal or professional, especially those from the recent past where you started with full enthusiasm. Let's say daily exercise for 45 mins. You start with those new running shoes, a smartwatch to count the steps & calories burnt or a new gym membership. Still, then somehow, you lost track and could not achieve the expected outcome. Why do you think you missed the goal? If there was your health management system, why did that fail?

A health management system, a productivity improvement system or any other system requires order. But what we have in the real world are constant forces to kill that order, what physicists call entropy. In simple terms, it is the measure of disorder. Entropy increases as disorder increases. For example, if you want playing cards scattered on a table, it has a very high level of entropy because there is no particular order expected in the arrangement of cards. So if you leave your room and come back after a week, or even after a month, you will still find it as it is.

On the contrary, if you build a house of cards, the level of entropy is low, and the expected order in the arrangement of cards is high. Forget leaving room for a week; even if you stand there, it will collapse in a few minutes because the forces of wind, gravity, friction, etc., are constantly working on increasing the entropy level. The same applies to any system.

There can be two ways to deal with entropy. One is to design the systems with as many paths of least resistance as possible with the help of systems design thinking. And the other is to induce energy into the system to fight entropy with what we call Kinetizers (derived from the word Kinetic energy). Maybe we can get into more details about these two approaches in some future newsletters. Let us for now identify the forces around us that work against the order in our systems. Then you can decide: 'to be or entropy'.