Defence Mobilisation Planning and Analysis

Approach and Methodology

Synergy Group’s team of analysts and researchers worked to establish a research foundation using open- and classified government data, connecting with APS specialists in the Office of the Defence Chief Economist to leverage available Defence information. Collaborating on a shared research project in the Australian Bureau of Statistics DataLab, our analysts extensively mined, integrated and standardised population-level data to produce modelling and analysis products that informed reporting and insights captured in the Strategic Mobilisation Plan and Mobilisation Analysis Report.

Key Criteria Covered

• Quantitative and qualitative data analysis
• Open-source research and information synthesis
• Identification of opportunities and vulnerabilities
• Comparative and gap analyses
• Data modelling and visualisation
• Stakeholder Engagement

Outcomes and Value Delivered

A Mobilisation Risk Profile was developed using expansive qualitative and quantitative data to develop a risk profile to inform  risk-based decision for Defence and the Commonwealth.

Synergy developed and led the delivery of the mobilisation strategy that involved extensive stakeholder engagement across Industry, Defence and whole-of-government within an ambitious committee schedule.

The Synergy team delivered an extensive Analysis of the Mobilisation Environment research report covering analysis of workforce, infrastructure, critical materiel and industry activity. The analysis employed econometric techniques, including input-output modelling and workforce demand forecasting.

Synergy established a data science research project in conjunction with the Office of the Chief Economist to mine integrated unit record data and to apply deep machine learning techniques to help to evolve assumptions-based planning towards data and evidence-based decision making.

Synergy developed skill-based workforce demand projections both internal to Defence and broadly across key industry segments to model against the global-level shocks induced by the COVID-19 pandemic, as well as the costs of supply chain disruption caused by floodings.