Abstract: Smart Service Queensland (SSQ) is the 'front door' to the Queensland State Government in Australia, providing services and information for citizens and businesses. Services are delivered through online channels, call centres and face-to-face service centres. Rostering to adequately staff the call centres during business as usual demand is well supported using existing workforce planning tools and content management systems alongside real-time telephonic monitoring. However, during times of large scale emergency events, such as floods and tropical cyclones, effective workforce planning heavily relies upon experienced SSQ personnel constantly monitoring and updating call centre staffing levels leading up to and during the disaster event to ensure customer demands are met. Achieving the right balance of call centre servicing without over provisioning is a challenging task. We present a prototype analytics tool that supports the SSQ Forecast Analyst responsible for workforce planning during disaster events and provides initial results of modelling caller behavior during two recent tropical cyclones. The tool provides a single point of reference to a wide collection of relevant datasets, including population demographics and details of the natural and built environment, data feeds describing the emergency event under investigation, relevant social media posts and call centre operations metrics. The tool is an early proof of concept demonstrator highlighting the utility of data integration, web mapping, real-time event monitoring, and predictive modelling.