How to Build Systems That Don’t Break

Fabio Strässle
Oct 17, 2019 · 4 min read
Photo by Clint Adair on Unsplash

Our world is nothing but a system with countless sub-systems. A system is a group of elements or variables that interact and interrelate with one another. In our own lives and society as a whole we create systems to organize us towards defined goals. A good system makes us succeed in reaching those goals while a system fails if it leads to unintended negative consequences. Everything is a system in society, your daily routines, how your workplace is structured and how our governments are set up.

If things are not working how we want them to, what do we usually do? We add stuff, do more, increase to-dos and research more. When our health is not like we want it to be we add a new exercise routine or supplements. When a company grows it starts adding more and more rules and hierarchy. When problems arise in a state the government introduces new laws and regulations. On all levels of society we approach problems by addition and our organizational and governmental systems have grown all the more sophisticated over the years. But is this the right approach?

Complexity of social systems

This is best illustrated by the cobra effect. In a colonial Indian city the amount of snakes started to get out of hand. The government thought about ways to eliminate the snakes as efficient as possible and decided to invoke a new law. For every snake that was brought dead to the government office the citizen would receive a monetary reward. Through this incentive, the government officials thought, people all over the city would hunt snakes and the epidemic would be extinguished in a matter of days. However, they did not take into account potential second order consequences. Instead of going out to hunt snakes in the street of the city, many entrepreneurial minded poor decided to breed snakes instead. Soon the government offices were hit with bucket loads of dead snakes while the epidemic reached new heights.

The behavior of a social system to an input cannot be predicted with absolute confidence. Adding elements and hence, additional variables to such systems increases complexity by magnitudes. This in turn leads to a non-linear increase in risk of system failure. Therefore, when designing a system for ourselves or organizations we should keep in mind that we increase its fragility by addition.

“Once you get fancy, fancy gets broken.”

Morgan Spurlock

The case for simplicity

“Entities should not be multiplied unnecessarily.”

The principle goes back to the ancient Greeks and argues against unnecessary increase of complexity. If there are other options than adding new elements to a system, they should be preferred under Occam’s razor. The principle can be stated even stronger and used to argue for more simplicity overall.

“If you have two equally likely solutions to a problem, choose the simplest.”

Aiming for simplicity might not only be the easier and more straightforward solution, it might as well be the better one. Simpler solutions are more robust and can cope better with unexpected inputs.

Can we take it further? What happens if we take it to the extreme and start taking away complexity to solve problems? Meeting organizational problems through reducing rules instead of adding them is very counter-intuitive, however, it might just work.

In a German town they conducted an experiment. All traffic signs were taken away and left the town basically traffic-law-less (there were only two rules left in place to organize traffic). Now what result would you expect? Increased accidents? More loud and annoyed honking? In fact the opposite happened and accidents went way down.

Think about things in your life or organization that have grown increasingly complex. Problems you are trying to solve by buying more tools or adding more habits and try the opposite. Reduce and simplify. Not only could you safe time and money but even make the overall system more robust to unexpected inputs.

As simple as possible but not simpler

The problem is that we do not know where the breaking point is and more often than not we err on the side of complexity. I suggest to experiment with reducing elements in non-consequential situations and re-introducing them in case this has not a positive effect. Find the optimal point were things are as simple as possible but not simpler.

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Fabio Strässle

Written by

Extroverted intuitive by nature, analytical introvert by training. If something fascinates me I dive in and learn about it.

The Startup

Get smarter at building your thing. Follow to join The Startup’s +8 million monthly readers & +789K followers.

Fabio Strässle

Written by

Extroverted intuitive by nature, analytical introvert by training. If something fascinates me I dive in and learn about it.

The Startup

Get smarter at building your thing. Follow to join The Startup’s +8 million monthly readers & +789K followers.

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