Systems Design Articles

Networked Design

Complex systems are by many definitions highly interconnected, examples being social networks, financial networks, and transportation netw
 Think of the air transportation system. It is not so much the static properties of your location in space and how far away your destination is, but more importantly where you are located in the network. If you are beside a major hub, it can be quicker and easier to travel to another major hub on the other side of the planet as it would be to travel from one disconnected hub to another that is a fraction of the distance away. Network Theory Irrespective of whether we explicitly call them networks or just systems, networks are the true geometry of complex systems. And thus, it is very important to think about designing them from this perspective of access, connectivity, and network structure. In order to do this, we first need to understand a bit about the nature of networks, and network theory is the area of math and science that provides us with the models for analyzing networks. So let’s take a look at some of the key features to networks and how they will affect the system as a whole. Probably the most important feature of a network is its degree of connectivity, that is, how connected is the whole system? Designing for a densely populated urban environment like Hong Kong will be very different from designing for a city like Los Angeles, which is dispersed. In highly interconnected systems, the dense interconnections can require much greater layering. The components can be much more specialized and there may be a much higher level of dependencies. As a result of these, failures can quickly propagate. A small security scare in one airport, for example, can result in delays across large areas of the air transportation system within a nation. In these large, highly interconnected systems, we do not always know the dependencies. No one has complete knowledge of all the inter-linkages that regulate complex systems like large urban centers or our global supply chains. Thus, our aim should not be to design these systems to be perfect, 100% fault-tolerant, as this is not realistic. Instead, they need to be engineered so as to be robust to failure. Again, the internet is a good example, as it is called a “best effort network.” This means it tries its best, but if something goes wrong, then it is no big problem. It just drops your packet and tries again. It happens all the time, but the internet still works. The occurrence of failure should be designed into these systems and not out of them in order to achieve robustness. Centralized & Decentralized Another key consideration in the design of these networked systems is their degree of centralization versus decentralization, as this is a defining factor in the structure and makeup to networks. In centralized networks, we have a node or small set of nodes that have a strong influence on the system, and the network will be largely defined by the properties of these primary nodes. These centralized networks can leverage economies of scale and it is possible to have a high degree of control over the system through one point of access. Due to this, centralized networks can be very efficient in the short run, as well as faster and easier to manage. But they are also more vulnerable to strategic attacks, often less robust and sustainable due to their dependencies on a few centralized nodes. They can also result in a high degree of inequality and problems in load balancing. This is due to the occurrence of highly centralized peak demands for resources, with rush hour traffic jams and exaggerated properties prices in the center of cities being examples of this. The heavy use of economies of scale engendered in industrial system of organization means many of the networks that make up advanced economies are highly centralized, including our global financial system centralized around a few key nodes, many national transportation systems, and logistic networks, which are designed as a centralized hub and spoke structures. Decentralized Networks Decentralized networks are in contrary without centralized nodes. Responsibility, control, and resources lie on the local level and are dispersed amongst a large percentage of the nodes. Examples of these include peer-to-peer file sharing, sustainable agriculture systems, car sharing services, and direct democracy. Decentralized networks typically require greater user engagement, as they cannot depend on centralized batch processing and economics of scale. The nodes in the network are often more self-sufficient and less specialized, and thus it is easier to interchange and replace any node with any other, making them less susceptible to attack and more robust to fail. They also have fewer dependencies and are typically more sustainable in the long run....

Platform Technologies

Platform technologies are systems build upon a platform architecture that distributes the system out into different levels of abstraction
we are simplifying the complexity and level of engagement required. Those working on the platform level require a deep understanding of the system and have to deal with its full complexity but are relatively unconstrained. Those who engage with the system on the application and user level are constrained by what the platform providers have designed, but being enabled by this technology they will be able to do more with less input and engagement. The net result is that we should get an amplification effect as we go up the solution stack due to the increased ease of engagement. Thus, there will be many more application developers than there are operation systems developers, and there will, in turn, be many more end-users than there are application developers, and this should be the case wherever we are using this platform model to systems architecture. Importance Finally, we might ask – why should we care about platform technologies? There are a number of reasons this architecture should be of benefit to us. 
Firstly, by distributing the system across multiple layers, we can abstract away the complexity that users or producers of the service have to deal with. Everything gets its own space. Secondly, we can avoid redundancies by having the platform provide the common services required by all components. We can reduce the need for each component on the application layer to re-invent the wheel.
 Thirdly, platforms are the ideal architecture for creating user-generated systems. Thus, we can leverage the amplification effect we discussed earlier to do more with less, helping to maintain an agile core system. And lastly, the platform architecture is ideal for building flexible, adaptive, and evolutionary systems. Given its independence from fixed instances, the system can stay innovating on the application level to continue regenerating itself. 1. What is a Platform? – Definition from Techopedia. (2017). Retrieved 7 July 2017, from

Self-Organization Design

Self-organization in design refers to the process of co-creation in the development of a product or service.[1 Instead of a professional 
But part of the definition for complex systems is that the components of the system have some degree of autonomy, which means, as designers, we can only have a partial influence over the system as a whole. The degree to which we can define the system will depend on the degree of autonomy of the elements in, say, a transportation network. We can have a relatively high level of control by constraining the actions of the cars. But in designing, say, a social network, people value their autonomy highly. No one is in control of the networks that are spawned out of Facebook or Twitter. They are created out of the self-organization of the users on the local level. What we are describing then is essentially a spectrum on the one side of which we can have top-down control, allowing us to design a well-defined system that will thus be relatively orderly. On the other end, we have what we call self-organizing systems that are less designed but are instead created from the actions and interactions of their users, thus they will likely be less orderly. Our traditional design engineering approach is of course on the left-hand side of this spectrum. It is a linear model based on the assumption that the end-user is a passive recipient or consumer. Within this industrial model, end-user variation and engagement is dumbed down so as to fit in with pre-designed procedures and systems of mass production. The obvious result of this is disengagement, alienation, and a world where end-users are constrained by systems that are created by a few designs and engineers in large centralized organizations. This is a model we should all be very familiar with. Although user-generated systems have always been there on the fringes of the mainstream, the rise of I.T. and the internet has put powerful tools for self-organization and collaboration in the hands of many. Today many of the most innovative, dynamic and fast growing businesses and services are harnessing this by creating platforms for technologies and people to interact, adapt and self-organize. Co-creation Platforms Instead of the traditional divide between producer and consumer of a technology or service, co-creation harnesses the relatively untapped and potentially vast resource of end-user engagement. Although finished products are sometimes what people want, it is also true that when we give people the capacity to be part of the design and production process they feel more engaged, are more likely to value the end product, and can be a valuable source of innovation amongst other things. The question then turns to, why design these platforms of co-creation to be productive if we can’t actually control them? What happens if our company crowdsources the designs for the production of our next pair of sports shoes? How do we know they are going to be what we want? Part of giving over control is accepting the fact that one person will use a social network for saving the planet, the next for avoiding work. What we can do though is create attractor states, that is, when we build the platform we set desired default positions that users can change but will be attractors for most as they are the default. For example, when building a video sharing site, if we want the site to be open and sharing, we could set the default copyrights for an uploaded video to creative commons. They can change it, but this is an example of an attractor state. Similarly, when we are designing an urban transport system, if we build lots of greenways, cycle paths and pedestrian streets, people still have a choice as to what mode of transport they use. But, walking and cycling increasingly become attractors in the system towards which people will naturally gravitate as it becomes the course of least resistance. Attractors Thus, we can see how, for every choice we have, there is a default because it is the cheapest, nearest or easiest. Leveraging these default positions is a powerful method of design. Creating subsidies for renewable energy or open workspaces for collaboration make these desired outcomes attractors. If, at one end of our spectrum, we have our traditional fully-controlled systems, and in the middle co-creation platforms, then at the other end we have peer networks that are truly self-organizing systems, examples being Bitcoin, mesh networks, and swarm robotics. There is very little in the way of a centralized platform here. Elements in the system are almost fully autonomous. Each node contributes to providing the system’s infrastructure and maintaining the system. Thus, they require more engagement and responsibility from each node in the network but can result in exceptionally robust systems. In complex adaptive systems, there is always a dynamic between agents and structure, that is, between the elements in the system and the system itself. Understanding this dynamic and the trade-off between being able to control the system vs. harnessing the uncontrollable resources of the users is a key consideration. Formal & Informal When we impose a top-down formal design on the system, we will create barriers to entry and thus exclude elements either intentionally or unintentionally. They will then inevitably self-organize on the local level to create a two-tier parallel system, one formal the other informal. Shanty towns and favelas are good examples of this. Because the requirements to enter the formal urban system were too high for the migrants, they created an informal self-organized system. This is an undesirable state that will create chronic systems integration problems. By understanding the relationship between the formal and informal, the centralized design and the distributed self-organization, we can design a multi-layered, co-creation platform to integrate the two, with an integrated transition from informal low constraints and requirements to the more highly constrained formal level. Top-down formal systems can be very austere, abstract and impersonal. They are designed to be universal, one size fits all. Bureaucratic systems are paradigms of this. They are designed to be impersonal and standardized for all. McDonald’s is often cited as an icon of this paradigm, with the exact same procedures and processes for making a big Mac whether in Bahrain or Santiago. But there is a good reason why many large corporations who are icons of globalization have regional offices and localized offerings. If you want to really engage people, you have to engage them on their own terms, and co-creation is one of the most effective ways of achieving this. When it came to translating Facebook into French, all they had to do was open it up for the users to translate and passionate users had it completed within a few days. Thus, an impersonal system was adapted to local needs and this is what co-creation is all about – creating synergies between producers and consumers, between systems and their constituent agents. Harnessing the vast resources of the end-user through co-creation is one of the great sources of untapped potential that we are only just beginning to discover in post-industrial economies. It requires us to be aware of and better understand the dynamics of self-organization, and just as importantly, the interplay between agents within the system, that is the users and the structure of the system, the producer of the product or service. 1. Meijer, B.R. (2020). Self Organization in Design. Advances in Design, [online] pp.49–59. Available at: [Accessed 8 Sep. 2020]. ‌...

Systems Innovation

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