Restrictions and lockdown measures implemented in response to the COVID-19 pandemic exerted unprecedented pressure on higher education institutions to switch to online-only teaching. This transition was characterised by swift implementation of policy, and the adoption of a wide range of information technologies at extraordinary speed and scale. Our aim was to explore which factors contributed to a successful switch and to what extent. We collected data from university students related to their experience with the deployment of emergency remote teaching. Using a framework of Person, Artefact, and Task factors as indicators, we conducted a hierarchical logistic regression analysis to predict problem-free transition to online-only university education. Transparency of tasks and difficulties with practicals emerged as the most important predictors, among factors related to IT equipment (availability, experience, and attitude), and teachers' availability to communicate with students. We present an impact-prevalence analysis of the predictors to provide guidance for managerial decision-making and prioritisation for future intervention and research. The findings are used to provide an evaluative reflection of the transition, and to promote improvement and planning. Knowledge generated within the pandemic context is especially valuable for future contingencies, such as natural emergencies and disasters, times of conflict, and other unforeseen events.