Introduction

Week 1 introduced the basic ideas of systems thinking including the use of systems diagrams for representation, analysis and modelling.

Week 2 begins by defining the Formal Systems Model. This provides a powerful way of eliciting information to build a picture of a system that includes establishing its purpose and structure; its decision-making and performance monitoring subsystems; its interaction with its environment; how resources are distributed; and how it maintains continuity and adapts to change.

This theoretical perspective will be illustrated by applications of systems thinking to real world problems, including the tragic shooting of Jean-Charles de Menezes by police in London in 2005.

An example of unintended consequences leads to the extension of systems thinking into the science of complex systems. In an unpredictable world, this science can give the best insights into how systems are likely to behave, something that is essential for policy and designing the future. We will present this in the context of Global Systems Science, which provides a prescription for solving practical real-world problems by coordinating systems thinking and complexity science, policy informatics and data, citizens and stakeholders, and policy makers [1].

But first, you will see the results of the experiment begun last week on objectivity and consensus when thinking about and analysing systems.

[1] FutureLearn: Global Systems Science and Policy