Pluvial flooding is on the rise as more cities are challenged by a changing climate, increased urbanisation and inadequate sewer systems. Flood forecasting and early warning systems are proposed as a “low regret” measure to reduce flood risk and increase preparedness through forecast-based actions. Nevertheless, many cities do not have the capabilities (data-scarce regions) to produce high-quality rainfall forecast and well-calibrated flood forecast (timing, water levels, extent and impact). As a result, there is a cascading effect on the ability to make and provide good reliable decisions given the uncertainty in the forecast or inaccuracy in the input data. This research aims to highlight the interdependences of the flood forecast and decision-making chain in order to address what decisions can be made given the quality of forecast. The success of such an approach will support robust anticipatory forecast-based decision making in data-scarce cities given limitations in high-resolution data availability while increasing preparedness and strengthening resilience against future extreme events.