Systems Thinking 101: Learning to Connect the Dots
Systems thinking can seem daunting. However, mapping systems in the community development space begins with understanding just three fundamental concepts: the iceberg model, operational thinking and feedback loops. Fair warning: Once you start seeing the world this way, you may not be able to stop.
An iceberg is often used to symbolize the systems thinking approach. Most of an iceberg is submerged, with only the tip showing above water. The smallest, visible part of an iceberg is similar to events around us; what we see or hear is simply the immediately observable. For instance, we might hear that people in our community can’t find jobs, or that they are enrolling in adult education programs. To think in systems means looking at trends. This is like plunging below the water’s surface, where the bulk of the iceberg is found. We might, for example, measure changes in unemployment rates or adult education enrollment over time. Doing so reveals patterns in the system’s behavior. Diving to the deepest part of the iceberg provides a more thorough understanding of the system’s structure—its parts and their interconnections—and how it explains the observed behavior.
In other words, systems thinking helps describe how the design of a system leads to the phenomena we see, which in turn enables us to imagine how the system can be redesigned to obtain a desired outcome.
The iceberg pictogram below illustrates how our focus influences our responses. When we focus only on events, the top part of the iceberg, we are constantly in a state of response to urgent or crisis situations. While necessary at times, this approach limits us to reactive behavior. By focusing on patterns, the middle part of the iceberg, we can anticipate future events based on past data. Understanding the underlying structure, the deepest part of the iceberg, allows us to examine why we are seeing certain patterns. This insight enables us to design systems, moving beyond mere reaction or anticipation.
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If you were asked to develop a research model of cow milk production in the U.S., which variables would you include? As Barry Richmond, a systems thinking educator reflecting on a similar question (PDF), wryly observed, “If one asks how milk is actually generated, one discovers that cows are absolutely essential to the process.” He was referring to a research paper on milk production in the U.S. that included lots of variables and complicated equations. However, the model didn’t include cows.
To think in systems, it is essential to understand how a system operates. In other words, it’s about how things work. How much time does it take to train workers? How does affordable housing get built? How do small businesses start and mature? How do people learn about affordable financial services? When we understand how things work, we can begin to examine interdependencies in the system.
To better understand operational thinking, let’s turn to a question that you may have heard before in any number of contexts: What are the ingredients for success? Now, this could refer to the success of a workforce training program, an economic development project to revive a downtown, an educational program to improve reading scores—the list goes on. When we identify the ingredients, or factors, of a program’s success, we are usually describing what influences success. It’s important to have that answer, but perhaps the real question is how other programs have achieved success in the past. The solution lies in the design of the program and the processes guiding the program’s everyday operation.
Next, we will walk through the concept of feedback loops. As you read, keep in mind that feedback loops are a great way to illustrate the design of a system. Feedback loops will also help you think operationally about a system.
We often conceptualize connections in a linear way: X impacts Y, and Y impacts Z. In reality, we are surrounded by feedback loops. Take our human bodies, for example. Homeostasis, any self-regulating processes through which systems adjust to maintain stability, helps preserve balance in our bodies. When our body senses a lack of nutrition, we start feeling hungry. Or if our body needs hydration, we start feeling thirsty. As we eat food or drink water, that feeling subsides. Can you imagine if these processes were linear? We would keep eating and never feel satiated.
Figure 1 shows a balancing feedback loop, which is denoted by the “B” in the middle. Feelings of hunger increase food intake, which then reduces hunger, leading to less eating. A plus sign on the arrow from feelings of hunger to food consumption indicates they move in the same direction—when one increases, so does the other. The arrow from food consumption to feelings of hunger has a negative sign, meaning they move oppositely—when one increases, the other decreases. Balancing feedback loops work to regulate the behavior of the system.
There is another type of feedback loop called a reinforcing loop, identified by the “R” in its center. (See Figure 2.) Compounding interest is perhaps the most common example of this kind of feedback loop. Let’s say you have some money in the bank. As you build your savings and the money in your account increases, the amount of interest you get also increases. The speed at which this increase occurs depends on your interest rate, but the system’s overall behavior is of growth.
When Fixing One Thing Breaks Another: A Systems Thinking Primer
In 1878, whalers introduced rabbits to Macquarie Island, located off the coast of Australia, as a food source. By 1968, the rabbit population had increased to 100,000, causing significant ecological concerns. Scientists introduced myxoma virus to control the rabbit population, successfully reducing it to 20,000 by 1980. However, feral cats on the island, which relied on the rabbits for food, began preying on local birds due to the rabbit population’s decline.
In 1985, scientists implemented plans to remove the cats from the island, resulting in a declining cat population. However, without their natural predator, the rabbit population began to increase again, adversely affecting the island’s vegetation. The impact was so severe that satellite images captured a noticeable difference in vegetation density. (For a more detailed explanation of what happened, see this article (PDF) from the Australian government’s Department of the Environment.)
Complex Systems Yield Multidimensional Problems
Why talk about cats and rabbits in a tool kit focused on community development? Scientists working on Macquarie Island were so fixated on trying to solve one problem that they ignored the ecosystem’s many interdependencies. Eventually, they realized they needed to look at the ecosystem as a whole and address all the elements of the problem at the same time. In other words, they needed a holistic perspective to understand how different parts of the system interacted with one another. Otherwise, solving complex problems can often feel like playing Whac-a-Mole: One problem is solved only to have another pop up. This is a common theme across complex systems.
Another reason to share this example is to dispel the frequent misconception that if we approached solving problems only from a scientific perspective, we would make more progress. In reality, the nature of complex problems is such that scientific experts with decades of knowledge can be as perplexed as anyone else.
Community development operates within complex socioeconomic systems encompassing many interdependent parts. Altering one element—intentionally or unintentionally—can influence others. For instance, a region that excels at drawing in quality employment opportunities and skilled workers may eventually grow less affordable. This shift could prevent others, such as teachers, emergency responders and hospitality staff, from living near their workplaces. As they relocate farther away, transportation expenses rise, posing challenges around access to jobs and training opportunities.
Breaking Down Silos
In complex systems, changes often take a long time to produce noticeable effects, making it more difficult to extract lessons. People and organizations within systems pursue individual objectives, each holding distinct ideas about how the system should work and what actions are necessary to reach certain goals. This can lead to siloed efforts. Unintended consequences may emerge as a result, making problem-solvers feel like they are always putting out fires.
Let’s circle back to where we started, with the pest problem on Macquarie Island that revealed just how tangled systems are. In 2007, authorities formed a $25 million, three-year plan to deal with the different problems at the same time using multiple strategies. This time it worked. A 2014 report found that no rabbits, cats or rodents had been seen since 2011, and the vegetation had recovered.
Community development already operates within complex systems. Systems thinking can be a valuable tool for the field, helping practitioners both understand the complexity and seek ways of leveraging it to prioritize solutions and allocate resources to foster economic resiliency and mobility for lower-income and underrepresented households and communities.
The Fundamentals in Practice
Once you are familiar with these fundamental concepts, take a moment to read the case study. It will provide you with an example of how systems thinking was applied in workforce development. The hope is that seeing them in practice will also further your understanding of these fundamental concepts.
Last updated: Aug. 27, 2026
