From: jimruttshow8596
The distinction between “complex” and “complicated” is a fundamental concept in complexity science and applied complexity theory, particularly within frameworks like Cynefin, developed by Dave Snowden [00:03:43]. While often used interchangeably, these terms refer to distinct types of systems with different underlying characteristics and implications for decision-making and management.
Defining the Terms
Complicated Systems
The term “complicated” originates from the Latin root meaning “to unfold” [00:03:51]. In a complicated system, something that can be folded can also be unfolded, and it remains the same thing [00:04:01].
Key characteristics:
- Decomposability and Reassembly: Complicated systems can typically be taken apart and put back together again, maintaining their original function [00:04:59]. The logic of the system is often implicit in its static design [00:05:05].
- Predictability: Humans are generally skilled at creating complicated systems, which offers predictability [00:04:09].
- Examples: A lawnmower motor or a Boeing 777 airplane can be disassembled and reassembled while retaining its functionality [00:05:32]. An aircraft is considered complicated [00:05:57].
Complex Systems
The term “complex” derives from the Greek origin meaning “entangled” [00:03:55]. An entangled system is constantly shifting and changing [00:04:06].
Key characteristics:
- Interdependence and Entanglement: A complex system is like “bramble bushes in a thicket,” where everything is entangled with everything else [00:04:32].
- Irreversibility: You cannot take a complex system apart and put it back together in the same way, because much of the information resides in its dynamics [00:05:08].
- Non-Linear Causality: In a complex adaptive system, there is no linear material causality [00:06:07]. While modulated, a complex system does not possess causality in a meaningful sense [00:06:17]. It may exhibit easily unmappable or even deterministic chaos [00:06:25].
- Emergence: The properties of the whole system are always different from the properties of its parts [00:06:46]. This means new properties emerge from the interactions within the system [00:07:10]. Superconductors are an example: superconductivity emerges when enough electrons clump together, despite being unpredictable from individual electron behavior [00:06:48].
- Unintended Consequences: With complex systems, one can be certain that any action will lead to unintended consequences [00:04:42].
- Open Systems: Complexity thinking typically deals with systems that are open and have multiple connections, rather than defined boundaries [01:12:29]. Life, for instance, is a complex open system [01:12:22].
- Examples: A human cell cannot be taken apart into its chemicals and reassembled to work [00:05:20]. The economy cannot be stopped and restarted without changing [00:05:27]. Mayonnaise is considered complex [00:05:59].
Implications for Management and Decision-Making
A critical error occurs when a complex system is mistakenly assumed to be complicated, leading to radically wrong approaches [00:04:19]. This highlights a fundamental reductionism and complexity issue in traditional management.
Contrast with Systems Thinking
Most systems thinkers define systems by boundaries, often implying closed systems [00:08:09]. Conversely, complexity thinking addresses open systems where connectivity, rather than strict boundaries, is paramount [00:08:13].
Managing Complex vs. Complicated
- Complicated Systems: Can generally be “governed” and “contained” through fixed rules and processes [00:07:57]. Approaches like business process re-engineering and scientific management are suited for complicated systems [01:14:46].
- Complex Systems: Cannot be controlled by predicting the outcome. Instead, one must describe the current state and identify immediate next steps [00:08:43]. Management of complex systems focuses on influencing the system’s dispositionality rather than dictating specific outcomes [01:21:32].
This distinction emphasizes that different system types require different approaches, and applying methods suited for complicated systems to complex ones can lead to significant failure.