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Harish Jose
Published: Tuesday, February 5, 2019 - 13:03 The TV show The Walking Dead, about survival in a post-apocalyptic zombie world, is one of the top-rated currently. I’ve written previously about the show, but today I want to briefly look at the complex adaptive systems (CAS) in the show’s plot structure. A CAS is an open, nonlinear system with heterogeneous and autonomous agents that have the ability to adapt to their environment through interactions between themselves and the environment. The simplest example of a CAS is an ant colony. Ants are simple creatures with no leader telling each ant what to do. Each ant’s behavior is constrained by a set of behavioral rules that determine how it will interact with others and its environment. Each ant works with local information and interacts with other ants and the environment based on this information. Their tasks include patrolling, foraging, maintaining the nest, and performing midden work. The local information available to each ant comes from the pheromone scent from another ant. As a whole, their interactions result in a collective intelligence that sustains their colony, a complex and intelligent system. In response to perturbations in their environment, ants are able to switch to specific tasks to maintain their system. Each ant decides its task based on the local information, in the form of perturbation to their environment, as well as the ant’s rate of interaction with other ants performing specific tasks. In the presence of need, ants can rise through the ranks, eventually becoming foragers, a position they maintain for the rest of their lives. The ant colony supports a large amount of “reserve ants” that don’t perform any function. This reserve allows for specific task allocation as needed based on perturbations to their environment. To further illustrate the “self-organizing” or pattern-forming behavior of ants, let’s take their foraging activity as an example. Ants will set out from the colony in a random fashion, looking for food. Once an ant finds food, it will bring it back to the nest, leaving a pheromone trail on its way back. Other ants engaged in foraging will follow the pheromone trail, bring back food, and also leave their pheromone scents on the path. The scent evaporates after a short amount of time. Ants that followed the shortest path will leave a pheromone trail that stays “fresh,” while the trails on a longer path won’t remain as fresh because the pheromone has more time to evaporate. This means that the path with the strongest pheromone trail is the shortest path to the food. The shortest path is a result of positive feedback loops from more and more ants leaving pheromone at a faster rate. Here, the local information available to each ant is the rate of pheromone release from the other ants. The faster the rate, the stronger the trail. This generally corresponds to the shortest trail to the food source. Once the food source is consumed, another food source is identified, and a new short path is established. As an aside, several transportation companies have adapted this “ant colony optimization algorithm” to find the shortest delivery routes. In The Walking Dead, a similar collective behavior is shown by the zombies. They exhibit a herding behavior where a large number them will move together in search of “food.” Similar to ants, they are devoid of any intelligence, and there is no one in charge. The zombies are attracted to sound, movement, and, since they don’t attack each other, possibly an absence of “zombie smell.” In fact, in the show several characters were able to survive a zombie attack by lathering themselves in the “zombie goo.” The possible explanation for the formation of herd structures is the hardwired attribute that we all have—copying others. We tend to follow what others are doing when we are not sure what is happening. We go with the flow. We could develop a model where a few zombies are attracted by a stimulus, and they walk toward it. Other zombies simply follow them, and soon a large crowd forms due to the reinforced loops with more and more followers. This is similar to the positive reinforcing feedback of a pheromone trail laid down by ants. The show recently introduced an antagonist group called “Whisperers.” They worship the dead, adorn themselves with zombie skins, and walk among the zombies. They learned to control the herd and make it go where they want. Possibly, they are able to guide the zombies by first forming a small crowd themselves and then getting zombies to join them. Because they have the “zombie smell” on them, the zombies don’t attack them. The Whisperers, themselves a CAS, have adapted by joining the zombies. We’re not ants and certainly not zombies. But there are several lessons we can learn from understanding CAS. The underlying principle is that we live in a complex world that we can understand only in the context of our local interactions with neighbors and the environment. We all belong to a CAS, whether at work or in our communities. Every project we are involved in is new in some way; it could be the nature of the project itself, the team members, the deadlines, or the client. Every part of a project can introduce a variation that we didn’t know about. Here are some lessons from CAS that can help in project management. 1. Observe and understand patterns. 2. Understand the positive and negative feedback loops. 3. Be humble. 4. Always get multiple perspectives (reality is multidimensional and constructed). 5. Go inside and outside the system. 6. Embrace variety. 7. Aim for effectiveness, not efficiency. 8. Use heuristics, not rules. 9. Experiment frequently with safe-to-fail, small experiments. 10. Understand that complexity is always nonlinear, so keep an eye out for emerging patterns. My column has taken a simple look at CAS. There are lot more attributes to CAS that are worth pursuing and learning. Complexity Explorer from Santa Fe institute is a great place to start. I’ll finish with a quote from the retired U.S. four-star general, Stanley McChrystal, from his book, Team of Teams (Portfolio, 2015): Always keep on learning.... First published on Harish's Notebook blog. Quality Digest does not charge readers for its content. We believe that industry news is important for you to do your job, and Quality Digest supports businesses of all types. However, someone has to pay for this content. And that’s where advertising comes in. Most people consider ads a nuisance, but they do serve a useful function besides allowing media companies to stay afloat. They keep you aware of new products and services relevant to your industry. All ads in Quality Digest apply directly to products and services that most of our readers need. You won’t see automobile or health supplement ads. So please consider turning off your ad blocker for our site. Thanks, Harish Jose has more than seven years experience in the medical device field. He is a graduate of the University of Missouri-Rolla, where he obtained a master’s degree in manufacturing engineering and published two articles. Harish is an ASQ member with multiple ASQ certifications, including Quality Engineer, Six Sigma Black Belt, and Reliability Engineer. He is a subject-matter expert in lean, data science, database programming, and industrial experiments, and publishes frequently on his blog Harish’s Notebook.Herd Structures and Complex Adaptive Systems
Lessons from ants and The Walking Dead
How does understanding complex adaptive systems (CAS) help us?
CAS present patterns due to the agents’ interactions. You must observe and understand the different patterns around you. How do others interact with each other? Can you identify new patterns forming in the presence of new information—or perturbations in your environment? Improve your observation skills to understand how patterns form around you. Look and see who the “influencers” are in your team.
Observe and understand the positive and negative feedback loops that exist around you. A pattern forms based on these loops. An awareness of the positive and negative loops will help us nurture the required loops.
Complexity is all around us, and this means that we often lack understanding. We can’t foresee or predict how things will turn out every time. Complex systems are dispositional, to quote Dave Snowden. They may exhibit tendencies, but we can’t completely understand how things work in a complex system. Edicts and rules don’t always work, and they can have unintended consequences. Every event is possibly a new event, and this means that although you can have insights from your past experiences, you can’t control the outcomes. You can’t simply copy and paste because the context in the current system is different from what you have experienced in the past.
Get multiple perspectives. To quote the great American organizational theorist, Russell Ackoff, “Reality is multidimensional.” To add to this, it is also constructed. Multiple perspectives help us to understand things a little better and provide a new perspective that we were lacking. Systems are also constructed and can change how reality appears, depending on our perspective.
We can’t try to understand a system by staying outside it all of the time. Conversely, we can’t understand a system by staying inside it all the time. Go to the gemba (the actual workplace) to grasp the situation to better understand what is going on. Come away from it to reflect. We can understand a system only in the context of the environment and the interactions going on.
Similar to item four, variety is your friend in a complex system. Variety leads to better interactions that will help with developing new patterns. Our environment is not homogenous; if everybody were the same, we’d lack the requisite variety to counter the variety present in our environment.
In complex systems, we should aim for effectiveness. Here, the famous Toyota heuristic, “Go slow to go fast” is applicable. Because each event is novel, we can’t always aim for efficiency.
Heuristics are flexible while rules are rigid. Rules are based on past experiences and may lack the variety needed in a given context. Heuristics allow flexibility for agents to change tactics as needed.
As part of prodding the environment, we should engage in frequent and small, safe-to-fail experiments. This helps us improve our understanding.
Complexity is nonlinear, and this means that a small change can have an unforeseen and large outcome. Thus, we should be alert for any emerging patterns and determine our next steps. Move toward what we have identified as “good,” and move away from what we have deemed “bad.” Patterns always emerge bottom-up. We may not be able to design the patterns, but we may be able to recognize them as they are developed and potentially influence them.Final words
“The temptation to lead as a chess master, controlling each move of the organization, must give way to an approach as a gardener, enabling rather than directing. A gardening approach to leadership is anything but passive. The leader acts as an ‘eyes-on, hands-off’ enabler who creates and maintains an ecosystem in which the organization operates.”
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Harish Jose
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Comments
Nice!
I hadn't really thought of Zombies in the context of CAS, but it does sort of work, at least to a point. I have seldom seen them form anything like a stable system, but I suppose you could say that the enormous piles of Zombies that stayed constantly outside the prison for all those weeks might arguably represent one.
Your recommendation is excellent. Anyone who wants to understand systems, chaos and complexity at a much deeper level should visit complexity explorer. It's a free resource, with outstanding courses taught by true thought leaders in the CAS world.