The words complex and complicated are often used interchangeably. Both refer to things with lots of parts, and both can refer to things that are difficult to understand. But in Competitive Thinking we use the words differently, and the different meanings are important.
We rely on complicated systems every day, for some of our most basic needs. Think of a mechanical clock or analog wristwatch, or the engine in your fuel-efficient hybrid car, or maybe the hard disk drive in your laptop.
What makes these systems complicated is the large number of moving parts. The wristwatch has perhaps dozens of tiny gears and springs, each required for its function. The engine has hundreds, maybe thousands, of parts – fuel injectors, pistons, seals, pumps, valves – many of them moving hundreds of time per second. The modern disk drive moves at thousands of revolutions per minute, with bearings and tolerances smaller than a human hair.
All of these devices, and every other complicated system, have one thing in common – if you remove even a single part, they break. An engine may continue to run if some small part fails but it’s output will be reduced and, eventually, it will stop. Complication breaks.
Now think of a complex system – a city, an economy, an ant hill or a bee hive. Remove any individual component and the system continues. Remove multiple components and the system may slow down, but it will eventually find a way to return to full operation without the missing pieces. It will often do this even in the face of massive disruption. Complexity adapts.
There are other important differences. Complicated systems demand standardization, sameness, and inspire a quest for “the one right way.” Complex systems need diversity, fuzzyness, and greater tolerance.
Complicated systems also have a strict hierarchy, a command-and-control structure that organizes the parts from greatest authority to least which must be strictly followed. Complex systems may also have hierarchy, but the lines of authority are fuzzier.
In Competitive Thinking we are most concerned with the failure of complicated things, like computer models and analysis frameworks. Few, if any, of the computer models in use today are adaptive – at least not those within reach of the typical mid-sized enterprise. An error in input can go undetected and lead to faulty output which, in turn, can lead to faulty conclusions and misguided efforts.
In analysis the more complicated the framework the less likely it is to be used. When it is used the more time it takes to get it right.
That’s why Competitive Thinking focuses on people, because they can adapt, and frameworks that are simple but not simplistic. Competitive Thinking tools and techniques must be effective yet easy to understand and quick to apply. Complication is the enemy of Competitive Thinking.