In this module, you will develop an appreciation of what difference the applications of complexity principles can make to specific areas of public policy such as health, education, and sustainability. In the health area, you will learn about the applications of complex principles in delivering health care services in the US, UK, Kenya, and Canada cases. You will also learn to apply complexity principles such as self-organization and emergence. In the education sector, you will learn about the inherent nature of complexity in education systems. You will decipher the aspects of education system that can be addressed through education policy levers and are external to the system. The module also introduces you to situative and cognitive learnings and their implications. Finally, you will learn about the applications of complexity theory to sustainable development policy through references to climate change (SDG 13) and economic growth, consumption, and employment (SGD 8).

In this module, you will learn to develop an interdisciplinary approach for data-inspired policy recommendations. The module introduces you to complex systems, followed by tragedy of commons. Furthermore, you will learn how to incorporate various computational modeling techniques to capture the undergoing dynamics using complexity theory and thus enable policy recommendation using a data science approach.

In this module, you will learn to design programs using complex adaptive systems principles. Such design is illustrated by approaches such as that termed “Gentle Action” in which one seeks to work with the energy of the system rather than forcing the system to change through massive external input. You will gain insights into the approach illustrated by concrete examples like the sustainable livelihoods approach to poverty reduction, where you will start with what poor people have rather than what they need. Other concrete examples used include legal empowerment of the poor and resilience building. Next, you will learn about policy design in the face of complexity using various tools such as narrative policy, local justice systems triangulated with cost-benefit analysis, or more recent techniques such as design thinking. Finally, you will learn how to conduct evaluations in complex situations including using practical tools such as developmental evaluation, most significant change, outcomes mapping, outcomes harvesting, and so on.

In this module, you will learn about the limitations and disadvantages of the dominant public service paradigm known as the New Public Management (NPM) and an alternative known as the Human Learning Systems (HLS) approach. The human dimension of HLS recognizes that each person is different, and so are their public service needs. One size will not fit all! Furthermore, you will learn that every person is part of a relationship system that determines how they define and meet their various needs and wants. You will discover that history is not an adequate guide to the future in complex systems that are inherently unpredictable, nonlinear, and constantly adapting. Therefore, learning is the necessary management strategy to be adopted and at the same time constitutes the major outcome of the HLS approach. Finally, based on large number of case studies where people are satisfied with their public services, you will discover that the outcomes result from a complex set of nested relationships among individuals, organizations, and places up to national levels and even beyond, rather than the government departments with outcomes measures based on NPM.

In this module, you will learn to develop an interdisciplinary framework to incorporate various techniques to capture the underlying dynamics through complexity theory, thereby enabling policy recommendations.

In this module, you will learn to distinguish between various types of uncertainty, such as risk and uncertainty, resolvable uncertainty, and radical uncertainty. In much of social science, you will learn the significance and widespread application of probabilities-seeking optimization. You will also identify the situations where this approach is inappropriate, as in puzzles versus mysteries. You will gain insights into many wicked problems that occur in situations of complexity and radical uncertainty that cannot be addressed by probabilities-seeking optimization. You will realize that humans naturally seek patterns, use stories to explain, and make sense of these situations. You will gain insights into the Narrative Policy Analysis that deals with wicked policy problems in situations of complexity, uncertainty, and polarization, where traditional probabilistic approaches often fail. Furthermore, you will learn the basic structure and elements of the NPF and how it uses narrative to support the analysis and formulation of policies. You will learn to apply the NPF in policy research, including setting up research questions, collecting data, and conducting data analysis.