Abstract

This paper draws lessons from the COVID-19 pandemic for the relationship between data-driven decision making and global development. The lessons are that users should keep in mind the shifting value of data during a crisis, and the pitfalls its use can create; predictions carry costs in terms of inertia, overreaction and herding behaviour; data can be devalued by digital and data deluges; lack of interoperability and difficulty reusing data will limit value from data; data deprivation, digital gaps and digital divides are not just a by-product of unequal global development, but will magnify the unequal impacts of a global crisis, and will be magnified in turn by global crises; having more data and even better data analytical techniques, such as artificial intelligence, does not guarantee that development outcomes will improve; decentralised data gathering and use can help to build trust – particularly important for coordination of behaviour.