Most of the social problems that we face are quite complex and so they have been widely acknowledged as ‘complex problems’ since they are resistant to simple solutions. These problems are prevalent in all spheres of social life and we all face them on a regular basis: for instance, poverty, education inequality, economic inequality, high levels of pollution, poor environmental quality, racism, corruption, violence, etc. These problems cannot be easily simplified and always resist solutions. They are messy and lack one solution since the outputs are also inputs. Hence, they are not easy to understand and solve using traditional approaches. Solutions that follow linear stages are incapable of addressing the problems effectively because they tend to take a narrow focus on the problems. Hence, it is imperative that those that attempt to solve these complex problems acquire the skills to diagnose them effectively and manage them appropriately. Addressing these problems requires a shift in the world view that conventional linear approaches take. We have designed the manual to help anyone interested in understanding complex problems, diagnosing them, and designing appropriate solutions for them.

There is a lot of information on systems thinking and complexity that people can use for social change initiatives but the availability of the information alone does not accomplish much for those addressing social change issues. People can achieve social change goals only when they use the information effectively to design systemic intervention plans and carry them out. The way that the information on systems thinking and complexity has been presented makes it difficult for one to know what to do with that information; for the most part, it is usually too theoretical. People who are carrying out social change initiatives don’t just need to know the information but how to use it. When there is a need to train people on how to carry out social change there is usually a tendency to assume that the gap is information and so training initiatives focus on compiling and disseminating information.

When diagnosis of complex social problems is taught using lectures, especially in large classes, students are unlikely to learn how to use the knowledge that is given to them because they don’t have a chance to practice applying the knowledge and develop skills that will be relevant for solving complex problems. We have used insights on how to learn effectively from cognitive science to help users to become proficient in diagnosing complex problems. The activities in the manual have been designed to ensure that the procedures for diagnosing complex problems become automated in the brain so that over time a user can focus on higher level tasks when diagnosing even more complex problems. Learning the procedures may be new to some and this manual has been designed to ease the process of learning them.

This manual is designed to provide users with a valuable learning experience. What allows it to do so is that it does not merely focus on providing users with knowledge on complexity but guides users on how to do deep learning with that knowledge. From almost one year of research we found out that there is no shortage of knowledge on information. What was lacking was a resources that guides learners on how to develop their cognitive skills so that they can use that they can learn deeply. That is a gap that we fill in this manual by teaching cognitive processes along with the knowledge on complexity; the manual provides users with several opportunities to sharpen their skills on predicting outcomes of complexity, evaluate complexity, diagnose complexity, plan how to address complex issues, determine non-linear causal relations, make sound judgments, and describe complex issues. These cognitive processes can only be sharpened through a diversity of experiences with diagnosing complex problems and the manual guides users on how to do so. The goal is to make it possible for users acquire experiences that they can draw from when dealing with other complex social problems in future.

In Stage 1, students will learn the basic characteristics of a complex system and try the answer the question of what are the key characteristics of a complex system. For example, students will learn what is the difference between a system and a complex system and develop the mindset of always framing analysis from a complex system perspective. They will also know why nonlinearity is a defining feature of a complex system and how it operates in real life.

The goal of Stage 2 is for students to recognize how interactions and interconnections give rise to a network. Learning how to distinguish between the central and minor nodes, students will be able to identify central nodes in their own system and recognize the importance of collaborating or working around those agents. Additionally, this manual teaches the different kinds of ways that the nodes tie or interact with each other. Students will be able to thoroughly investigate the interactions, formally or informally between nodes. Last, the users learn the formation of a social network system based on the nodes and the ties. Network analysis requires students to first identify what is the nature of the network and define what qualifies an agent to be part of the network. Sometimes when only considering the nodes, many people fail to realize that there are other important nodes in the system who are influenced or influence the communication and interaction of the system. Scoping a network enables students to examine the patterns of communication and include every stakeholder that are in fact within this web of communication. The goal is to familiarize users with the basics of network theory, network effect, and network analysis.

Stage 3 explores the social outcomes as properties of complex systems, which are results of networks. Such outcomes include emergence, self-organization, and attractors. While the emergence is the outcome of the non-linear interactions in the previous stages, it is largely unpredictable. Nonetheless, students need to gain in-depth knowledge of the emergence for two reasons. First, prepare themselves with the potential emergent properties in their working environment. Even though they may not be able to predict the emergent property before its occurrence, their more profound knowledge of the system empowers them to grasp everything there is to know about the emergence quickly; thus, they can cope with this emergence better. Second, students should be constantly alerted that their effort may lead to an emergent property in the future. Understanding the forms or patterns of organization that emerge based on simple rules, students will appreciate the intricacy of the self-organization and adaptation of the system. For example, when students are aware the implicit sets of rules that underlie the self-organization and adaptation, they will study beyond the explicit rules that inform the human interactions (e.g. law) and delve into the non-obvious of the society, which informs better strategies.

Much as the way to intervene in the system varies from person to person and from context to context, Stage 4 provides the key knowledge for intervening appropriately so that students are prepared to answer the question of how to intervene in any given social system. By learning level of analysis and feedback loop, students will be equipped to identify structural or interactional leverage point where one can easily intervene and change the behavior of the system. Last, since sometimes system is resilient to change (e.g. policy resistance), students will learn the mechanism through which complex systems become resilient to changes and try to devise an intervention plan that circumvents adaptation and resilience.