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Author (up) Robert Power; Bella Robinson; David Alexander; Mahesh Prakash
Title Predicting Demand for Government Services during Disaster Events Type Conference Article
Year 2018 Publication Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. Abbreviated Journal Iscram Ap 2018
Volume Issue Pages 89-96
Keywords Situation Awareness, Data Integration, Disaster Management, Crisis Coordination
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.
Address Csiro; Csiro; Csiro; Csiro
Corporate Author Thesis
Publisher Massey Univeristy Place of Publication Albany, Auckland, New Zealand Editor Kristin Stock; Deborah Bunker
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-0-473-45447-0 Medium
Track Monitoring and Alerting Systems supporting Business as Usual and Emergency Warnings Expedition Conference ISCRAM Asia Pacific 2018: Innovating for Resilience - 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific
Notes bobapow@gmail.com Approved no
Call Number Serial 1671
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