Robust Decision Making Under Deep Uncertainty

Today’s public sector decision makers face a fast-paced and transformative environment, and many rely on quantitative analysis to navigate future decisions—however, not all quantitative analyses are created equal. For example, computer models might predict whether a water agency’s investments can ensure a reliable, cost-effective supply for its customers. Or a model might predict how future climate change might affect flood risk. But predictions are often wrong and relying solely on them can lead to negative outcomes. Moreover, because decision makers know that predictions are often wrong; they may discount or ignore the crucial information that quantitative analysis can provide.

This module will introduce you to the method of Robust Decision Making (RDM), an analytic framework that helps identify a set of robust strategies. These strategies can characterize the vulnerabilities of such strategies and evaluate trade-offs among them. The aim of RDM is to help decision makers navigate complex problems like resource allocation—problems often plagued with“deep uncertainty.” Or, essentially, scenarios in which stakeholders do not know or can agree on the relationships among actions, consequences, and probabilities such as resource allocation.

In this module, student will gain both a conceptual understanding of RDM as well as provide hands-on experience in conducting RDM analyses. Once complete, students will have an effective tool to help them navigate key decisions within today’s complex policy making environment

Week 1: Introduction to robust decision making

In today’s fast-changing world, even the best predictions of economy, technology and climate are often wrong. Traditional ‘predict then act’ analysis is no longer adequate.This week, we will lay the foundations for the course, describing the basics of RDM and exploring its practical applications.

Week 2: Using RDM to identify vulnerabilities

This week, we will discuss how to carry out each step of the RDM methodology. Last week, we introduced the concepts of deep uncertainty and robustness and introduced the iterative steps of RDM. This week, we’ll dive into each step in more detail.

Week 3: Using RDM to identify robust strategies.

In this final week, you will have the opportunity to organise your own RDM analysis fora policy challenge of your choosing. Concurrently, we will discuss the theory and practice of RDM as decision support.

Upon completion of this module, students will be able to:

• Understand how complexity characterises the policy making process, and some of the available methods and tools for mitigating or minimizing complexity.
• Design a robust decision-making (RDM) analysis.
• Interpret scenario discovery and produce an XLRM framework.
• Critically evaluate applicability of RDM in various scenarios, assessing what would be required to deliver an RDM and whether an RMD is done well.

This short course is for mid-career professionals. Standard entry requirements are a 2:1 degree plus 3 years of relevant work experience. Applicants without a 2:1 or higher degree are welcome to apply and typically require 5+ years of relevant work experience.

One written assignment, plus participation in webinars and discussion forums.

Our modules offer high levels of interaction with regular points of assessment and feedback. Each four week module is worth five Master's level academic credits and includes three webinars with a King's lecturer and peer group of global professionals.

Format: Fully online, plus 3 x 1-hour weekly webinars

This module has been designed specifically for an online audience. It uses a range of interactive activities to support learning including discussion forums, online readings, interactive lectures videos and online tutorials.

Module Creators

Dr Benedict Wilkinson, Senior Research Fellow. Ben is a Senior Research Fellow at the Policy Institute. He joined the institute as a Research Associate in 2013, having studied for a PhD under the supervision of Professor Sir Lawrence Freedman in King’s College London’s Department of War Studies.

Professor Robert Lempert, Director, Frederick S. Pardee Center for Longer Range Global Policy and the Future Human Condition. Robert is a principal researcher at the RAND Corporation. His research focuses on risk management and decision making under conditions of deep uncertainty, with an emphasis on climate change, energy, and the environment.

Professor David Groves Director, RAND Center on Decision Making Under Uncertainty. David is a key developer of new methods for decision making under deep uncertainty,a professor at the Pardee RAND Graduate School, and works directly with natural resources managers worldwide to improve planning for the uncertain future. Please note that this is only the indicative lecturer information. The lecturer may differ from the indicative lecturer listed due to teaching allocations. Please contact us directly for the most recent information.

Please note that this is only indicative information. Lecturers and course content are subject to change. Please contact us directly for the most recent information.