 In order to do systems change, we have to understand whatever it is we are trying to change as a system, and this requires that we actually create a systems model of it. Most of us do not see systems, we just see things, and as a consequence, we have designed our world based upon this component-based vision. We might say that we have a transport system, a health system, or a political system. However, our actual model of those is typically not a system at all. It is just a set of parts. A university is just a set of departments without any understanding of how all those parts fit together to produce a complete learning experience for the student. Health care is likewise a set of actors that interact, without much understanding of how their actions fit into the function and behavior of the whole system. We have people doing health insurance, health finance, health policy, clinicians, hospital management, etc. None of those people really understand themselves as being part of a system that is working together towards delivering a function to meet the end user's needs. The insurers are interested in insurance, the clinicians in their medical procedures, regulators are interested in laws and compliance, etc. It may sound funny, but no one is really looking at these things as systems. We have ended up in a world of sets where the whole is thought to be just a summation of its parts, and thus requires no special attention. The same is true for finance, energy, food, and other areas. We traditionally just look at these things in terms of their parts. No one is really looking at these things as systems, because that requires a different way of thinking to the one we are used to. But if you are serious about systems change, then you have to be able to model what you are dealing with as a system. Otherwise, you will simply be doing what everyone else is trying to do, which is improve the efficiency of the parts, leading at best to incremental change, before eventually you get displaced by a new paradigm. We are trying all the time to elevate our thinking about a problem, from seeing only parts to seeing the system's structure and behavior that creates those issues. To do that, we need some kind of model of the whole system, no matter how crude that overall insight might be. A system is a set of parts that are interrelated to perform some collective function. There are just two types of composite entities in the world, sets and systems. Sets are a collection of elements that are independent. Because they are independent, they cannot function together to achieve anything more than the sum of their effects in isolation. A pile of stones is just a set, because they are not organized and interrelated towards a common function. The weight of the whole pile will be equal to the sum of the weights of all the stones taken separately. To call something a system is to say that the set of elements are interdependent in affecting some joint outcome. Every kind of organization in our economies that we are interested in is a system. There is an important aspect to note here, which is this. The difference between a system and just a set of parts is the way the parts are interrelated. That means everything that we are interested in when it comes to systems is the relations, the connections and the interdependencies that give rise to the functioning of the whole. The whole that emerges and the overall functionality of the system is a product of the way the parts are interrelated. This is why in systems innovation, we are interested not in parts, but connections. We are not trying to change the parts as per the usual approach. We are trying to change the connection so that we get the emergence of new macro level structures and new whole systems functionality. A model of a system needs to capture and take account of a few key aspects. It has to define the elements within the system, the types of relations between those component parts, how those parts interrelate into a whole system that performs some function and how the whole system interacts with its environment, adapts and evolves over time. Say for example we are dealing with a local food system. We would first have to identify the different elements and their properties. The farmers, the natural resources, agribusiness, the government regulators, etc. Then identify the types of relations between them. The farmers require water, the agribusiness, lobby government regulators that provide grants to the farmers, etc. We need some understanding of how the whole food system interrelates to create a certain functional pattern. What does this food system produce at the end of the day? How does it interact with the broader environment of the economy, society, culture, political system, ecosystem, and how is this whole dynamic changing over time? All systems are composed of elements which are the basic building blocks. Elements are things like people, banks, computers, or cities. They can have properties associated with them. They can be larger or smaller. They can be part of a certain category of things like advanced economies or emerging economies. You have to identify the basic units, their essential distinctive characteristics and properties which will create the categories to give your model some structure. A systems model consists of a set of elements with relations between those elements through which they are interdependent. Relations can have many attributes but the most fundamental one is the type of synergy. Do the components interact in a fashion that is constructive or destructive? Adding value to the whole or depleting value from the whole? The relation between bees and flowering plants is an example of a positive synergy. That is to say, they work together in a constructive fashion, adding some value to the whole greater than that of the parts. The runoff pollutants from a factory in a river ecosystem interact through a negative synergy when combined they have a destructive effect on the whole environment. The overall functionality of the system will be a product of the constructive or destructive synergies between the parts. A functioning system is one that has more positive synergies than negative synergies because the parts are interrelated in a fashion that enables the emergence of overall functionality. A dysfunctional system is one that has many negative synergies so that the parts are interfering making them incapable of delivering an overall function. There is much more to the dynamics of the interrelationships between the parts in a system but we will cover this in a future module on system dynamics. All of the systems we are interested in perform some function or else we would not be interested in them. Thus, a critical part of understanding any system is to ask, what is the function of this system? The answer to that question is not always as obvious as it may seem. Many people have never really questioned what is the function of the system they operate within and have only a superficial understanding of it. What is the function of a financial system? The financial system accounts for and enables the exchange of economic value between people. What is the function of a water system? A water system performs the function of accessing and transferring water to when and where people need. What is the function of the political system? A political system performs the function of making collectively binding decisions for a community of people. What is the function of a manufacturing system? To fabricate goods and so on. An understanding of the functioning of the system gives us an answer to the question why? Why do we use or need this system? By refining that question, we can come to define some metric of what is functional and of value. And what is dysfunctional, what we might call entropy? By understanding the functioning of the system within its environment, we have some criteria for assessing it as a whole. This enables us to let go of any specific instantiation of the system. To start from the beginning by asking what is the function and what is really needed to deliver that function? Innovation does not happen without a space of possibilities. By looking at outcomes and functions, we can let go of the specific form of the current system and create an open space for innovation. By looking first at functionality, we can start by putting the outcomes to the system at the center of our vision. This is already a paradigm shift, because when we take an analytical approach, focusing on parts first, most of our talks starts to revolve around the input and internal workings of the system. And we quickly lose sight of its output and how it actually operates in its environment. Typically, we do not really ask what is the function or outcome of the system. We simply look at internal optimization of the parts. We assume that if the parts are working well, then the whole will be working, and we will get the outcomes that we desire. But this is a false assumption, as none of those things have to follow from each other. We focus on GDP, but we forget that it is really quality of life that people want. And these are two different things. The first is a measurement of how much resources are churning through the economy. And the second is an outcome. The analytical approach always focuses on the internal operations of closed systems. In so doing, it blinds us to the most important thing, which is how the system really functions within its environment, and the actual outcomes for end users. By looking at organizations as being fundamentally open, systems thinking can help us with identifying those real outcomes. Finally, we need some model for how the system exists within its environment and how it adapts to changes within that environment. How the whole system evolves over time is a consequence of the feedback interaction with its environment. In these large complex systems, no one gets to define a linear process of development. But instead, they just evolve. This evolution involves a process where new variants are produced, selected for and duplicated. Evolution is how whole societies, cultures, economies, or technology infrastructure develop over time, and we need some model to account for that. Complex systems exist on many different levels and scales. As we think about a system and try to model it, spend part of your time from a vantage point that lets you see the whole system. Not just the problem that may have drawn you to focus on the system to begin with. In our analysis, we should be zooming in and out across all the scales and levels to the system, actively focusing on specific details of importance, but also taking time to step back and passively observe the whole. This looking at the system on various scales helps to identify how the way the parts interrelate create the whole pattern, and how that macro pattern then feedbacks to shape how the parts act. This micro-macro feedback dynamic is critical to understanding the overall dynamics of the system as it changes over time.