Managing policy risks using big data analytics in the pandemic era: VUCA and wicked policy problems

Abstract

This study aims to introduce the potential of volatility, uncertainty, complexity, and ambiguity (VUCA) as a framework to explain the characteristics of current wicked policy risks. We also analyse how big data informatics help us to overcome volatile, uncertain, complex, and ambiguous wicked policy risks in the context of the COVID-19 pandemic. Specifically, presenting a VUCA framework, this study illustrates how policy risks disturb policy results based on selected cases. Additionally, we argue that big data analytics has become an increasingly significant and feasible instrument for managing policy risks. We discuss potential challenges concerning skepticism about continued politics in policy decisions and implementation processes, and limitations of informatics and the nature of big data, which is often possibly biased and incomplete.