The exciting new field of Systems Thinking draws on researching mother nature’s formations to tackle business problems in an ever-increasing complex world.
Businesses and organizations can learn a lot from nature’s beautiful harmonic formations, commonly referred to as complex systems. The systems thinking approach links real-life occurrences such as bird flocks and fish schools’ formations to real-life business problems. Based on studying bird flocks and fish schools, this article will discuss how three simple rules can lead to business resilience to equip businesses with the competitive edge and the DNA they need to achieve extraordinary higher performance.
Animals, as such, are under constant threat from predators. They live in a dangerous and unpredictable ecosystem, where they must take in complex sensory information and translate it into these kinds of movements in real-time. The specific set of rules that led to this behavior is what helped these species survive millennia. Their complex nature is similar to the climate in which all businesses operate today.
To explain the extraordinary lessons learned and the potential benefits to business, first, we’ll need to cover the what, why, and how of these formations. Then, we’ll conclude by linking the findings to business and the management of organizations.
So, how do schools of fish form and birds flock in such harmony? You’ve probably already seen these complex systems in real life or in videos.
For example, during the winter months, species of birds like starlings are known to take flight altogether and render large displays of swirling patterns. But these amazing displays of synchrony that enable thousands of creatures to act as a single entity are also observed in insects, herds, and other land animals.
This kind of animal behavior could neither be studied nor explained for a long time. Intuitively, it appears impossible to achieve this phenomenon without some centralized orchestration or a leader. But, of course, we now know that this kind of behavior is possible without any leader or centralized information. We also know that the key to these complex systems is the individualized behaviors and the fact that there’s not a globally orchestrating power.
We’ll see how this complex system is made possible when individual elements within itself communicate with each other on a local level. Through this communication medium, we get groups of animals synchronizing their motions.
So, why do birds flock and fish school? There are several reasons and hypotheses. First, it makes sense to believe that predators will assume that the flock or the school is a single large organism that is possibly threatening, which will keep predators from attacking. It’s also evident that predators find it much more challenging to target individuals in a flock or a school than target single animals. The other way around is also possible: The flocks or schools are more effective at catching prey by cooperative hunting than individuals on their own.
Whatever the reason, there has been a great deal of research on this topic. One such example is the research conducted at the Max Planck Institute at the University of Konstanz in Germany. A team of researchers set out to study the behaviors of the collective and the individuals in schools of fish.
Observing schools of fish is challenging because their movements are extremely fast to the naked eye. But with high-speed videos, their movements can be carefully tracked and studied by capturing their actions in hundreds of frames-per-second cameras at very high resolutions. At the Planck Institute, they placed fish in a large tank, installed a four-camera system above it, and then tagged each fish with a tracker. Finally, the cameras were time-synchronized, and the images from the videos were stitched together in post.
By viewing the high-resolution slow-motion video footage, researchers were able to examine their behavior in detail as if they had a microscope that magnifies these complex systems in ways that weren’t possible before. Then, by combining video tech with tracking tech, they had the data they needed on the emergent collective behavior that arose from interactions among the system’s components. From this data, they could then understand how each individual behaved and processed complex sensory information and how they translated that into movement decisions in fractions of a second, for example, by simulating the existence of threats to the animals in the lab or on an iPad in the wild.
Besides observation and experimentation, another method of studying this phenomenon is asking: How can these flocks or schools come to be without any leader, knowing that each individual in the group has only a small amount of information, i.e., mainly how to interact with its neighbors?
In the 1980s, Craig Reynolds presented a very simple model of this phenomenon, known as Boid’s model. His goal was to develop realistic computer graphics of flocking or schooling behavior. As a result, he wrote a well-known paper titled: Flocks, herds, and schools: A distributed behavioral model.
In that paper, he provides a simple model in which individuals obey three rules in order of importance.
- The first rule is collision avoidance, which has only one purpose — to avoid collisions with their neighbors.
- The second rule is velocity matching, which ensures that individuals are synchronized in speed and direction by matching their velocity to their neighbors.
- The third and final rule is flock centering, a proximity rule to ensure that individuals remain close to their neighbors.
Reynolds and others who simulated this model found that these extremely simple rules produce surprisingly realistic results. It is an impressive demonstration of how complex behaviors and complex systems can be achieved from only three basic rules. Moreover, the model looks convincingly similar to real flocks except for the shape of the elements.
The code to achieve this behavior would be pretty simple and short, and it works as follows:
I am eying my mates and applying Rule #1, which is if I’m too close to my nearest neighbor, I’m going to separate from it. That means I’m going to turn away from the nearest neighbor’s heading. Otherwise, I’m going to apply rule #2 and align as closely as possible to the heading of my neighbors. And based on rule #3, I’m going to cohere, meaning move closer to my neighbors.
With the help of NetLogo software simulation, you can see that they start in random directions and move at a constant velocity. Then, gradually, flock-like formations begin to emerge. Of course, the shape and formations aren’t very realistic-looking because it’s hard mimicking the physics of flying in a simple two-dimensional computer program. However, you can still notice the flocking behavior.
Note that, from a visual perspective, the depiction here is a snapshot of a sphere or a globe visualized on a flat square surface. Think of this as a globe that wraps around the edges. Where north and south, east and west are circular.
To sum up, as you can see, a set of simple rules can create these complex systems without any central command. They’re made entirely possible by having every individual stick to the three simple rules we outlined earlier.
Researchers at the Max Planck Institute at the University of Konstanz concluded that being ignorant and uninformed can be a very positive component to the resilience and integrity of the school of fish and the survival of the group. They determined that having uninformed individuals participate in decision-making ends up democratizing group decision-making and prevents extremist individuals from having a disproportionate influence overall. This results in a more robust collective intelligence, where individuals gather evidence by themselves without the need to be told how to think. This collective intelligence is based on strategies that took millennia to evolve to what you see here; it increased the species’ resilience and enabled their survival. And if you’re familiar with the Lindy effect, you would understand how something that has stood the test of time is likely to do so for a proportional amount of time in the future.
How Can These Complex Systems Rules Apply to Human-Based Organizations and Business Strategies for Better Performance?
You may already be thinking about this question. However, being able to manage both sides of the coin is a paradox that requires carefully designed rules that do not compromise vision and specific performance goals at the cost of individualism and creativity. In other words, while collective intelligence can be achieved through decentralization and individualism, you need to balance such freedom in other areas of the enterprise to ensure that its vision and strategic objectives remain intact. Furthermore, such rules should minimize the trade-offs between influence and collective intelligence without killing the momentum of the extraordinary performance that could be achieved as a result.
To do so, a combination of isolation and experimentation — for example, through options — can be adopted, and when carefully designed, this strategy can lead to extraordinary results. For instance, one such tool developed in-house under the Emergence Thinking framework is called the Paradoxical Management Assessment System (PMAS). It helps businesses manage the paradox of leveraging collective intelligence in some areas while retaining processes and control in others that require it. It minimizes the trade-off between collective intelligence that can be achieved from individuals and the influence of group leaders, then dampens it where and when augmented intelligence is needed most. We use another common framework based on only two principles designed to address more than 70% of business challenges faced by almost every modern organization.
The idea is that simple rules lead to high results and performance and can also be leveraged to tackle most of today’s complex systems or organizations.
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