Implementing coastal protection strategies presents challenges for coastal managers, particularly in the absence of data driven historical learnings. These challenges are expected to increase with the growing pressures of urbanisation on the coastline and potential impacts of climate change. In an operational setting, where decision making needs to be undertaken in a timely and costly manner, while achieving the best possible outcomes, decision support tools serve an important role. This paper presents a framework for developing a decision support tool to support coastal protection, in particular sand resource management. The framework was developed in a partnership between a local government authority and academia and will be implemented to manage beach nourishments via a sand-backpassing decision support tool. To apply the framework and develop the tool, a calibrated numerical model was used to simulate a series of potential scenarios of dispersion of sand placement that include different wave conditions, initial beach profile condition (e.g. eroded, accreted, average) and volume of sand to be placed at three separate beach locations. The user can weight the relative importance of each location as well as the dispersion rates and beach state to rank the preferred location to place the sand for the best outcome. Here, we demonstrate the importance of the feedback process between beach morphology evolution, incoming waves and the volume of the nourishment on the evolution and dispersion of the sand placement. Moreover, by using the tool the user can identify the best locations to place the sand supporting operational sand management decision making by the local government authority. The framework presented here is flexible and can be used and adapted for other locations and applications where the morphodynamic feedback is important in predicting the lifetime of a sand management strategy. Finally, the importance of the engagement between academia and government for the development of effective coastal protection strategies is demonstrated and highly encouraged.