Tools for Systems Thinkers: The 12 Recurring Systems Archetypes
Archetypes are recurring patterns of behavior that give insights into the structures that drive systems. They offer a way of deciphering systems dynamics across a diversity of disciplines, scenarios, or contexts. Think of these archetypes as the storylines of systems in the world. Just as you can identify the same formula for a romcom or a thriller in a Hollywood film, these archetypes help systems thinkers see behaviors and flows in more concrete terms.
Basically they offer insights into universal behaviors across different system scenarios.
I haven’t mentioned mental models in this series yet, but its important to understand the concept as these are the frames in which we view the world through and the term is used quite a bit in systems lingo.
Archetypes rely on heuristics, which are mental shortcuts that we all use to make sense of the world. We use archetypes to help shift our perspective of a problem from a mental model of blame, to one of curiosity and constant inquiry.
In Chapter 1, I defined causality, and in Chapter 2, we explored feedback loops and in chapter 3 I explained how to do some introductory systems maps. In this chapter, I have summarized the 12 main recurring systems archetypes that will help you identify feedbacks and occurrences in phenomena in the world. Many of these were identified in the 1960s and 1970s by systems pioneer Jay W. Forrester at MIT and added to over the years by other systems proponents such as Donella Meadows and Peter Senge.
But many of these depict more negative feedbacks, so I added three of my own positively framed archetypes at the end. Really, the world is a magical wonderland filled with potential, so I designed these archetypes to show the positive potential of systems dynamics.
Remember, everything is interconnected, so these are likely to overlap and play off each other in dynamic ways. I have provided a few real-world examples of each, but try to see if you can come up with others of your own as you read them. Since system dynamics is all about understanding cause and effect, any of these archetypes many of these get drawn out as feedback loops which you can find at the reference list at the end, but for now the wonderful Emma Segal has illustrated each one.
1. Limits to growth
Perhaps one of the most known systems archetype is the concept of limits to growth. Donella and Dennis Meadows wrote a pioneering book on the topic in the 1970s arguing that there are biophysical limitations to growth. This is based on the exploration of the reinforcing feedback loops of population growth where more humans increases the capacity for more humans.
Other examples of this archetype are market saturation, and housing bubbles. Equally, this is about the limitations to success that we have. Nothing can grow forever; at some point, the system will fight back and intervene to regulate exponential growth. That’s when the bubble bursts.
2. Tragedy of the commons
Commons are shared resources, and the original idea for this archetype was put forward in 1968, arguing that common resources would inevitably get exploited by agents wanting to maximize their individual gain from the shared resource. So, many people who were all sharing the same plot of land for example, would eventually deplete it of its fertility. Elinor Ostrom (who is still the only woman to have won a Nobel prize in economics) explored this further and showed that eventually, the people who live with the commons will work to protect it.
From a systems dynamics perspective, the tragedy of the commons archetype models the exploitation of shared resources and the way greedy extraction leads to more competitive extraction, which could eventually lead to the collapse of the system — this is a reinforcing feedback loop. We see that when many parties all seek to maximize their own benefits from the same common resource, the immediate result is exploitation. But there is always the possibility (like with any system archetype) that the status quo of the system can be intervened in to shift the end result.
There are many real world examples of this archetype playing out, such as fishing. Over 70% of the world’s fisheries have been exploited to the point of collapse, and many have already collapsed due to exploitation. More people means more demand, and this can pervert the motivations of agents in the system. But over time and with better management, the fisheries can be regenerated. What we learn from this is that shared resources require a custodian of sorts to maintain equity in the use of the commons. Such an intervention shifts it from a reinforcing to a balancing feedback loop.
Competition is a natural part of many systems, including human nature, but we all know things can get out of hand when the rate of “one-upping” ends up with all parties at a loss. In the case of escalation in systems dynamics, we see agents fighting for limited resources, trying to out-compete each other until the situation has escalated or snowballed out of control.
We see this with price wars in business. One example of this could be revenge in feuding families (yes, imagine the TV version of the Mafia here), where you have families killing off each other to get back the competing family until there is no one left.
4. Eroding goals
When actors in a system fail at achieving what they set out to do, they reduce the benchmark, constantly reducing the level of their goals. We see this in the battle for even cheaper consumer electronics, with the quality and functionality losing out over price reductions. Politicians are classic goal eroders as well, since they reduce their lofty goals overtime to meet common denominators.
Addiction, in the case of systems dynamics, is when agents become addicted to external forces to maintain the system. As we know, addictions alter behaviors as the seeking of external substance becomes more and more prominent, and over time, the system becomes addicted to the external resources, such as government subsidies. This is the opposite of a self-sustaining system, where the system self-regulates from internal resources to maintain its equilibrium based on what is available. Addictions can come in many forms and many products, such as home printers and new pod coffee machines, are designed to be addicted to an outside resource in order to function. This is turn makes the owner addicted to the producer of the product.
6. Seeking the wrong goal
I’m sure we can all relate to this one. We set a goal that we know is a band-aid solution to the bigger thing at play. The wrong goal makes us feel like we are achieving something when really, this behavior is masking something else. This is sadly the case with a lot of aid projects, where the need to get clear and measurable results incentivizes agents to set only immediate and achievable goals. This reinforces superficial actions in the system that can, in some cases, perpetuate the problem that the goals are trying to resolve.
7. Exponential successful
In this case, the reward of success is in turn a motivator for the actions of the agent to continue winning, even if the acts are harmful. This is a reinforcing feedback loop where the stock of ‘success’ creates a perverse motivation to continue to gain the reward. This freezes new players out of the system and can mean runaway ‘success’ for not necessarily the best players. The more success you get the easier it is to get more success and the harder it is for others to get access to success.
We see this with fast fashion, coupled with the fact that people love to buy cheap clothes. Since consumers constantly replace their existing clothes, it means that these companies are motivated to continue to produce cheap clothing at whatever cost. The reward of increased sales motivates the company to continue with business as usual.
8. Race to the bottom
It’s a sad but all too common archetype these days, where players compete to be the lowest common denominator in the system. The airline industry is a classic case of this, where quality of service and experience is dramatically cut in order to attract more customers with the offer of cheaper flights. Eventually this creates a new type of normal where the services are as cheap and dirty as they can get, but the customer suffers. The seats are too small, the food is unhealthy, and the experience is based on speed and disposability. The issues with this archetype is that the end result is no one wins, so it needs players willing to buck this downward spiral trend and rise above the rest.
Another airline example is the introduction of charging for luggage which in turn shifts the systems of behavior of the customers. As soon as you introduce a cost (a tax on luggage), people try to game the system and just have a carry-on, which in turn, means more packed cabins and longer load times. In general, people get annoyed at the inconvenience, and the byproduct of this systems change is a negative feeling by the customers.
9. Rule breaking
Rules are often set up to try to fix a problem that occurs in a system, and in many cases, rules are broken by the agents in order to maximize their goals. This is often the case with regulation. A government puts a policy in place to try to change the behavior of the agents in a system, and then the outcomes are that the agents move their polluting practices to another country or region where there is a lack of rules and government practices.
We have seen this with global attempts to regulate hazardous electronic waste. The International Basel Convention technically should encourage players to design their products to be easy to recycle and to recapture materials at the end of life in their own country, but instead, it has increased the trafficking of electronic waste to emerging economies where there are lax environmental laws. In this example, we see intersection with the shifting the burden archetype.
10. Shifting the burden
Such a common archetype of business decision makers, this is where good intentions often lead to worse outcomes unless the system is understood. If everything is interconnected and we live on a closed ecosystem, then when you make one decision, say to increase the amount of recycled material in your products, the burden of delivering that resource is shifted to another part of the system (in this case to people finding to recycled material market). This is also defined as the law of unintended consequences of our actions — the accidental outcomes that occur in dynamic systems.
11. Fixes that fix back
The easy way out often leads back in. When we try to solve a problem with the same thinking that got us there, we apply quick fixes that only seek to address the symptoms rather than the root cause of a situation.
12. Growth Paradox
This is where growth in one location leads to a decline somewhere else. It’s a basic law of physics that every action has an equal or opposing reaction. We know we live on a finite planet, and we see how the increase in wealth in one location will always come at the cost of wealth somewhere else. This can be shifted by the more equitable distribution of assets. But in most socially constructed systems, equity plays a smaller role to individual opportunity. So when we see this archetype playing out, we see that for anything to grow, something else must be taken away.
But, wait what about the positive archetypes in systems dynamics?
What I find interesting with these common systems stories is that many are identifying negative or undesirable behaviors over time, but there are also many positive systems dynamics that reinforce the effectiveness of a system’s success. Certainly, nature has much to teach us much on this front, but so do the brighter sides of humanity. Here are three positive systems archetypes I can identity:
1. Intensity to action
This occurs when agents are motivated to take action for the collective benefits due to an intensely focused experience, as was the case in Mexico City after the earthquake last week. The focused intensity of the need to act and the physical actions of many agents create a reinforcing feedback loop of contribution, all dedicated to the collective whole.
2. Regenerative relationships
This is when actors develop a positive reinforcing feedback loop that shares resources in a regenerative and collaborative way. For example, schools that support their teachers’ personal and professional development, plus offer extra resources, are likely to create a relationship between the teacher and the school that is experienced as positive and regenerative. Energy is then transferred as a regenerative relationship to the students, who, in turn, feed back a positive commitment to the school.
3. Status quo disruption
This occurs when individual acts of intervention shift the status quo of a situation so that the new operating environment is more equitable for the agents. I think this could play out both ways. If the intervention is not measured based on the other systems archetypes, it could be that the collective outcome is worse off for some players (shifting the burden) and better for some (exponential success), but equally, well-placed interventions into a system can leverage change in exponentially positive ways. FYI: this is what we teach people to do at the UnSchool.
For example, when we see an anomalous element in a system such as female leadership in corporations, we then start to create a new type of normal that in time, can reinforce more of this new element in the system. Of course there are many roadblocks set up to prevent progress, but systems are never static and are always changing. Even a loss can be made up as a gain later.
I could go on about this for days, but instead would love to hear your ideas on positive systems archetypes. We have just started a Linkedin community to connect systems change makers — here we can start to build new narratives around systems change and elevate the positive ways we can all contribute to designing a future that works better than the current status quo.
In the next chapter, I will combine all of these tools into systems interventions, identifying leverage points and modes of shifting systems dynamics. You will need to read all the chapters so far for systems interventions to really sink in.
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References for this chapter
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