 In this video, we'll be giving a high-level overview to the domain of complexity management, all of which we'll be going over in more detail in coming videos. We can understand complexity management as the application of complexity theory to the practice of management. Thus, it draws upon the key insights and ideas from complexity science and uses them to try and help us manage complex organizations. Most of these complex organizations might be cities, international politics, multinational corporations, global logistics networks or healthcare systems. These are all complex organizations due to their nature of having many parts that are highly interconnected, independent and autonomous. We can and often do go on using our traditional industrial age management approach to try and manage these organizations, but as we'll be discussing in a future module, the basic principles underlining our traditional management approach were designed for dealing with relatively simple systems, that is, organizations that have a limited number of components that interact in a simple, linear fashion at a low level of interconnectivity and where we can constrain those components. A factory would be a classical example of this and it should not be surprising that the industrial age management approach was designed to manage relatively simple closed systems like factories because that was exactly what we had to do a hundred or two hundred years ago when this approach was first formalized. But today in post-industrial economies, managing factories as important as it is is really the least of our concerns. We face much more complex challenges such as trying to get our healthcare systems working, enabling effective forms of governance or achieving collaboration between companies across large supply chains. These are all very different forms of organization that represent a different set of challenges and require a more complex approach to management that is aligned with their core attributes. And we already see lots of innovation in management theory to meet this. We've seen the rise of a new set of ideas around agile and lean organizations. Many different ideas around flipping the hierarchy upside down, creating networked organizations and lots of innovation in enabling more collaborative forms of organization. But most of these new management theories can be best understood within the context of complexity theory as they all fit within the complexity framework. And we'll use the rest of this video to outline what that framework is. That is to say the key concepts within complexity theory and how they apply to management. Although complexity theory consists of a whole zoo of new ideas, we'll structure it around a few central concepts, namely systems thinking, non-linearity, networks and adaptation and evolution. Firstly, complexity management is based on the systems thinking paradigm that we'll be discussing in a coming module. But simply systems theory or systems thinking is a holistic way of looking at the world. This paradigm posits that the parts to a system can only be properly understood and thus managed when taken in relation to the whole system. Whereas our traditional analytical approach takes a system and breaks it down, focusing on the individual parts of the organization. Systems thinking looks instead at the relationship between the parts and the context or environment within which something exists. Whereas our traditional analytical approach is very much focused on closed, well-bounded organizations, systems theory is instead looking more at open systems. That is to say organizations that have so much interaction and exchange with their environment that we cannot model them as closed systems. And this is the nature of complex organizations. They are really open networks instead of closed, well-bounded formal organizations. Think about a healthcare system. It is a complex network of many different organizations and individuals, from primary care practitioners to hospital administration to government agencies to universities and so on. All of them are interdependent in affecting the outcome to the system and the boundaries are fuzzy and even non-existent. For example, would we include the food companies in this organization? As what they produce clearly has a direct impact on people's health. Would we include the clean air lobby group as air quality would also have an effect on people's health? Another example would be global supply chains, where we have to get many independent organizations across the value network to collaborate for the whole supply chain to function effectively. This supply chain has no real boundaries to it and no one is in control of the whole organization. The same would be true for international politics and many other forms of complex organizations. This is the nature of complex organizations, there is no real boundary to them and this makes them quite different in nature to our traditional well-bounded organizations. Because they have no real boundary, it is more relevant to talk about them as systems or networks of connections. So the question is then how do we actually manage this form of open organization when we don't really have control over the members but still they are interdependent and we need to get a functioning global outcome from the system for the end user. The primary problem being that our traditional reductionist approach is predicated upon actually being able to directly itemize and control the members of the organization. Our traditional approach works by creating a boundary around the organization and a hierarchy within the organization, where top management then decide what is best for the entire organization and the members are constrained and coordinated towards that predefined outcome and in such a way we get global coordination. Suffice to say this does not work in open organizations, global macro level patterns in complex systems are emergent phenomena of local level interactions that give rise to self-organization. Thus instead of directly aligning the actions of the members towards the desired global outcome we instead create the context or platform within which the members can interact so as to coordinate locally and then out of this we will get the emergence of some global organization. For managers this means creating the context that facilitates the process of self-organization to take place. We can't directly control the outcome to the system but we can influence the initial conditions. We can do this by creating a conducive context that represents an attractor towards coordination and cooperation between the members. The big idea here is that of collaboration, we no longer have control but we can enable the context and conditions for collaboration to emerge. Next we'll talk about non-linearity and interdependency which are key concepts within systems and complexity theory. As we turn up the connectivity the parts of the organization become more interdependent and this is something we're currently witnessing around the world with the rise of IT and globalization. Interdependence creates non-linearity when we put two or more things together and they become interdependent, they can work together constructively or inversely they can counteract each other creating a combined organization that is more or less than the sum of its parts. One on one stops adding up to two and linear thinking starts to break down. It should come as no surprise to you when I say our traditional management methods are very much based upon linear thinking. We look for linear cause and effect interactions to describe events and in reality we will often go on using simple cause and effect descriptions of events even when they aren't really working simply so that we don't have to deal with the complexity behind the situation. We go on talking about GDP when we all know this is a very blunt linear metric that hides the complex set of interacting variables to a society's overall quality of life. We go on looking at maps of the world divided up into nation states when their simple linear model hides the much more complex set of networks that make up our global economy and society. Linear thinking works well in simple environments and it is a necessary competency to being an effective manager but it's not sufficed. In complex environments we need to be able to recognize that it combined us in dealing with the real dynamics to the situation and thus in such situations be prepared to switch to a more complex nonlinear form of reasoning. Complexity management would posit that most complex phenomena that we encounter are the product of a number of different variables interacting in a specific nonlinear fashion where they are amplifying or dampening each other to give us the overall emergent outcome. Because no one single thing causes the outcome we cannot simply solve the problem by affecting one input variable. We need to identify and affect the multiple relevant factors. So for example let's apply some nonlinear thinking to our current challenge of global terrorism which is clearly a very complex problem. A linear cause and effect approach would be to simply exert superior military force against the enemy and that cause would affect the desired outcome that we wish for, the eradication of terrorism. We might note that in this approach we're looking at the problem as independent from us and other things. It simply exists out there and we can just go and solve it with a single cause. Now if we treated this phenomena as complex and nonlinear we would be looking less at the actual phenomena itself and more at the network of interdependencies that are generating it including a recognition of our own interdependence with this issue. That is to say what role do our actions play in causing this problem and also remembering the events in time feedback on themselves. Current events are path dependent meaning they are typically conditioned by feedback from historical events. Using this nonlinear paradigm we would have to look at how the nexus of education interacts with religion and global culture, you would have to look at the sociopolitical dynamics in the region and of course how economics and corruption interact with poverty, food prices and so on all of which interact in a constructive or destructive fashion to produce this emergent outcome. So this should help to illustrate why it's called complexity management because really before anything it is about accepting that not all things are simple, some things are but some things are truly complex and trying to treat them as if they're not does not change the situation. You really have to roll up your sleeves and dig into all the specific interacting parts and also understand the system as a whole. This is the only way you really solve difficult problems. There is no silver bullet but on the other hand if you do actually understand how things work and you are prepared to do all the hard work then complexity theory does provide us with a framework that actually makes it possible to solve problems that otherwise would appear virtually impossible. Next, network theory is another central part of complexity science as it deals with the highly interconnected architecture of real world complex systems such as transportation networks, financial markets or ecosystems. With the rise of the internet we're seeing the birth of new forms of networked organizations and the so called access economy. Open platforms like Airbnb, the App Store, Uber and many others have shot to fame taking over or creating whole new industries. The networked platform model is proving highly scalable and they're currently disrupting many industries. With the reduction in transaction costs that IT enables these networked organizations are able to harness new value sources and access whole new markets that were previously not possible within closed formal organizations whose costs of coordination were too high to reach out to the mass of people. These networked platforms are instead able to harness the small but combined vast productive capability of the so called crowd or long tail. The mass of people that were previously not productive enough to organize formally are now able to set up their own networks of collaboration and out of this we're seeing a new mode of production within society, sometimes called peer production or mass collaboration, classical examples being Wikipedia or the Linux Foundation, a much more dynamic and swarm like form of organization. The access economy is a major paradigm shift from ownership of products to access of services in the same way that hyper connectivity is unlocking a vast amount of untapped productivity of the crowd on the long tail. It also has the potential to do the same to virtually every product around us. We can think about all the products around us as both things and the function they perform. The industrial economic model was all about ownership of things that monolithic ownership worked to lock up the functionality of the product, meaning that the function was only accessed a fraction of the time, a good example being the typical car that is used on average less than 5% of the time. With the reduction in transaction costs and the proliferation of networks, we can now think of products as services and economies not as being about the buying and selling of products but instead about the access to value. This access economy requires us to change our management approach, to think in terms of access, connectivity and networks and network theory gives us the language to do that. Finally, we'll talk about adaptation and evolution. With fast paced technology innovation, globalization and changes in our supporting ecosystem, the post-industrial world is no longer the stable predictable environments that it once might have been. It is marked by what business leaders call VUCA, which stands for volatility, uncertainty, complexity and ambiguity. Our traditional centralized organizations are normalized for stable and predictable environments and they are inept at dealing with fast paced change or non-linear radical events but fast paced change and radical events are becoming the new norm as the world becomes more interconnected and dynamic. And this is congruent with what complexity theory tells us about the capacity for non-linear systems to generate black swan events and the butterfly effect. As we see more indicators becoming exponential, we also see a shift from normal distributions to long tail distributions that generate many more events that are several standard deviations from the norm, such as financial crisis or extreme weather phenomena. We currently see a lot of creative destruction as companies in the S&P 500 are lasting shorter and shorter periods of time. The primary focus of organizations within this disruptive environment should be survival through building adaptive capacity to enable their evolution. This VUCA world requires a recalibration of many dimensions to our approach to management, a fundamental shift from resisting change to adapting to it. This requires a new set of capabilities surrounding adaptive capacity, the capacity for the organization to evolve new solutions in response to their changing environment. Adaptation involves a recognition to uncertainty, that is to say that we cannot fully know future outcomes. This idea of uncertainty runs very much contrary to our traditional management approach. In fact, it is so alien that in economics we typically call it radical uncertainty. But what we call radical uncertainty is just normal old uncertainty. It just looks radical because our standard analytical approach leads us to think that the future should be knowable. We conceive of the future in terms of some linear transformation of the past, what is called ergodicity. We take a sample from the past and use it to compute future outcome probabilities. Most of our business analysis and particularly our financial analysis is dependent upon this idea of ergodicity that the future is knowable. But when things become more non-linear and complex, ergodicity doesn't really hold. As the system evolves, we get non-linear interactions between events that have not even emerged yet. For example, try turning the clock back 20 or 30 years and predicting how the internet would unfold, how we would get the emergence of smartphones that would give rise to the app economy that would enable big data and all the future possibilities that will emerge out of that. This is not really possible because of all the non-linear interactions and the emergent evolutionary dynamics to the systems development. In such a case, our strategy needs to change from one of trying to predict the future to adapting to it as it unfolds. Adaptation means being open to uncertainty and maintaining a diversity of states in order to be able to respond to a variety of possible outcomes that are as yet unknown. It requires an evolutionary approach that involves experimenting, testing and rapid iteration. In a word, it requires business agility, agile organizations, and we're currently seeing how the idea of enterprise agility has gone from nowhere to being identified as one of the few top-level strategic enterprise capabilities and we'll be discussing agility and evolution in the final section to the course as we talk about the VUCA framework. In this module, we'll be giving a brief overview to the area of complexity management whilst also trying to weave in a discussion around the fundamental transformations taking place within our economy in order to illustrate the relevance of this alternative paradigm to the current unfolding economic context. We firstly talked about systems thinking that offers us a new approach to managing open organizations that reduces our dependency on closed hierarchical management structures by instead focusing on the process of self-organization and emerging outcomes. We looked at non-linearity as a key characteristic of complex organizations where many factors are interdependent working in a synergistic fashion. We then went on to talk about how networked organizations can harness the productive capabilities of the crowd in the growing access economy where value is no longer interpreted in terms of products but instead in terms of access to services and how our management approach has to equally shift to focus on access and connectivity. Finally, we briefly touched upon the idea of adaptation and evolution as business agility is becoming a central concern within the context of the 21st century VUCA environment.