 As we've previously discussed, the emphasis within the systems and complexity paradigm is on local interactions and how these give rise to the emergent macro level phenomena of the state of the whole system. Systems dynamics is one modeling language used in the management of large complex systems in order to try and capture and model these local causal links and how their interaction over time gives rise to long term patterns of behavior. Systems dynamics is a methodology and mathematical modeling technique for framing, understanding and discussing complex issues and problems. Originally developed in the 1950s to help managers improve their understanding of industrial processes, it is now being used throughout the public and private sector for dealing with large complex projects such as macroeconomic analysis, military interventions or environmental policy modeling. Systems dynamics is again a holistic approach in nature. In our analysis we often focus on discrete events, like watching the news every night where the presenter simply describes what happened. But of course if we really want to understand something like why a dictatorship fell or the price of biogast is going up or why a large organization like Nokia was incapable of responding to market changes, we can't simply do this by describing what happens. We need to understand the dynamics behind these events, what is really driving the system and this is what systems thinking is all about, trying to get behind events to see what is truly causing them. All of these complex organizations that we see have a typical behavior. We see reoccurring patterns like the example of Nokia failing to innovate and adapt. We see this with many large organizations that are incapable of adapting to change and eventually get disrupted. These typical reoccurring behaviors within a system are called systems archetypes. Systems archetypes are reoccurring patterns of behavior within a system. For example we might see a child playing away happily and then some small event happens and they start crying. The first time we see this happen we would think that it was the small event that caused the child to cry. But if we were the child's parent and saw this pattern of behavior happening time and time again, we would start to realize that in fact it is not so much the event itself but some underlining dynamic that is creating this behavior. Thus systems exhibit certain behavior but under this is deep systems structure a set of underlining dynamics that are really driving the system and it is these drivers that systems dynamics tries to capture. In large complex systems it is these dynamics that hold the system within a certain configuration or state. Therefore it is necessary to understand these dynamics before we can try and affect the system. If we don't understand the underlining drivers and dynamics we will likely get unintended consequences or no effect at all. For example we can think about the Iraqi war. The Iraq invasion was a direct intervention into a very complex system that of a whole social cultural and political system of a nation to which the invaders had very little understanding of the dynamics behind. By altering these dynamics that had held the system in its previous state it essentially went out of control and eventually collapsed into chaos. Just to say you can't really manage a system until you understand its dynamics and by understanding those dynamics you can find the leverage points that enable effective changes within that system. The basic idea of systems thinking is that of interdependence. For many people this is what defines the idea of a system the fact that the parts are interdependent therefore every action within the organization is seen to trigger a reaction. In systems dynamics this reaction is called feedback. In these highly interconnected systems nothing exists in a vacuum, every action feeds back to its source over time. The fuel exhaust coming out of your car engine may look like it simply disappears having no effect but this is just because you are isolating one component in a much larger system. Of course sooner or later all that exhaust feeds back to affect all of us drivers and that is the nature of managing complex systems you have to look at the whole in order to see these feedbacks that are driving him. So feedback loops describe a state of interdependency between two or more elements within a system and there are just two types of feedback. Positive feedback which is a self reinforcing loop and negative feedback which is a balancing loop. Reinforcing feedback or amplifying feedback accelerates the given trend of a process. Positive feedback also called reinforcing feedback or amplifying feedback accelerates the given trend of a process. If a trend is ascending the reinforcing positive feedback will accelerate the growth. If the trend is descending, it will accelerate the decline. For example, the falling of an avalanche is a self-reinforcing feedback process. The more material that falls, the more momentum it adds to the avalanche, thus dislodging more material, which feeds back to create greater momentum and so on. Another example might be minority group prejudice within a society. Prejudice tends to generate discrimination against the minority, which tends to limit their opportunities, which feeds into limit their achievements, which in turn feeds back to validate the majority that the minority are not as good as them, thus once again reinforcing the chain of events. This downward spiral that may be caused by self-reinforcing feedback is called a vicious circle, but we can also have virtuous circles. For example, having a good reputation as an organization means others will talk about you favorably, which will feed back to motivate your organization to live up to that expectation and excel, which again will affect people's perception favorably and so on. Balancing feedback or stabilizing feedback involves two or more elements that are counter-balancing each other. If we get more of one, this creates less of another, which feeds back to reduce the first. For example, the market mechanism that balances supply and demand is a negative feedback loop. If supply goes up, prices go down, which promotes more buying, which feeds back to reduce the stock, thus bringing it back to a balancing equilibrium. Maintaining your balance whilst riding a bicycle is another example of a negative feedback loop. The more you move off in one direction, the stronger you react by putting yourself back onto course. Thus we can see how negative feedback works as a control system to maintain and regulate the organization within a set of desired parameters, whereas positive feedback tends to lead to instability via exponential growth, oscillation or chaotic behavior. Negative feedback generally promotes stability. Negative feedback tends to promote a settling towards equilibrium and reduces the effects of perturbations. Negative feedback loops, in which just the right amount of correction is applied, with optimal timing, can be very stable, accurate and responsive. These feedback loops then create a certain reoccurring pattern to the system as it changes over time. For example, most feedback does not occur instantly, especially when we're dealing with a large organization, there is instead a time delay. If we have a system dominated by negative feedback with time delay, we get an oscillatory pattern over time as we have one effect that takes it in one direction, before the counter balancing feedback gradually dampens it down and brings it back in the other direction. We might see this dynamic in the counter cyclical physical policy by a government as it tries to counterbalance the business cycle. Inversely, positive reinforcing feedback loops can create a dynamic of rapid exponential growth or decay, when some maximum or minimum value is reached. The so-called tragedy of the commons may be an example of this archetype. Agents use common limited resources to profit individually. As the use of the common resource is not controlled, the agents would like to continuously raise their personal benefits. The resource is therefore used more and more and the revenue to the agents starts to decrease as the overall resource becomes depleted. The more an actor sees others over exploiting the resource, the more they are likely to intensify their activity, knowing that the collective resource will be gone soon. Agents intensify their exploitation until the resource is completely used up or seriously damaged leading to a collapse. By understanding these dynamics that hold the system in a particular configuration or generate a particular behavior over time, we can begin to identify points within the linkage of effects that might alter its behavior towards the desired outcome. Traditionally, we focus on changing things by changing the components within the system. If a company is doing badly, we fire the CEO, but this is the lowest point of leverage. By understanding the dynamics, we can see that it is not really the members of the organization that are creating systemic failures, it is the system itself, the way it is arranged that creates systemic failures. If you're in systemic political deadlock, electing a new president is unlikely to change things much because you're simply replacing a component in a broader system whose dynamics are set up to create the same behavior again. It is only at the systems level that you have the opportunity to really change things through leverage points. These leverage points are places within a complex system such as a corporation, an economy, a city or an ecosystem where a small shift in the connections can produce a big change in everything. The founder of Systems Dynamics talked about complex systems as being counter-intuitive and leverage points being likewise. In our traditional approach, we focus on the component parts to an organization. We think it is the president of a country that has the greatest leverage. In fact, the components are typically the lowest point of leverage within a system. The higher points of leverage are in changing the connections within that organization, changing the flow of information and most of all, changing the model that the organization uses to interpret that information. For example, let's think about trying to get people to smoke less. We could try to directly affect them by increasing the cost of cigarettes but also we can indirectly influence them by altering the feedback loops. Most people who smoke try to ignore or downplay the negative effect it has on their body, simply hoping that they don't get cancer. This is an open-loop system with negative externalities. They are consuming the cigarette and shifting the negative effects away by denying them in some way. Now when it comes to managing this system, instead of focusing on the parts, we try to alter this feedback loop. We might place a big graphic image or sign on the face of the cigarette packet that connects them with the consequences of their actions every time they smoke, thus trying to close the feedback loop to reduce their consumption. As another example of a counter-intuitive leverage point, we could cite a recent piece of research done analyzing the social network of a company in Hungary. The analysis showed that the network had one dominant node in it which had much higher levels of connectivity than all of the senior executives. But this node was not the CEO, in fact it was the external health practitioner who during his job got to travel around the different departments and make contact with almost all of the employees, thus serving as an important point of information exchange within the organization and a potential leverage point for changing behaviors. But ultimately the highest leverage point in any organization is in changing the model that they use to interpret events. Changing the paradigm can change the whole organization's understanding of itself and its function, which can ultimately result in a complete transformation. As an example we can think about the rise of the paradigm of sustainability over the past few decades. Before this change in paradigm, talking about the environment, trying to conserve nature or affect any positive environmental impact was largely a lost cause. Environmental concerns were marginalized and generally bulldozed by economic interests. But given this paradigm shift we now see sustainability moving to central stage as it becomes a part of what organizations are and do. Sustainability is now starting to be seen as part of the marketing, value proposition and competitive advantage of many organizations. This change in paradigm is then generating real outcomes that work and change the overall macro structure to this complex organization. As the saying goes, there's nothing as practical as a good theory. The paradigms and models an organization uses are by far the highest leverage point for affecting the overall state of the organization. In this module we've been giving a brief overview to systems dynamics, a systems based approach to modeling complex organizations that is focused on feedback loops and the dynamic patterns of behavior they give rise to. We talked about positive feedback as a self-reinforcing cycle of interdependency that can create virtuous or vicious cycles. A feedback that functions as a balancing mechanism to maintain stability and control within the system. We discussed leverage points as critical points within the organization where you can have a large systemic effect by altering the connections, information flow, models or paradigm used. There's plenty more to systems dynamics that we haven't had a chance to touch upon here such as stock and flow diagrams. System dynamics is quite a popular modeling language so there's plenty of resources out there on the web for you to dig further into.