Enhancing Emergency Supply Chain Resilience through Advanced Demand Forecasting, written by Abby Hodgkiss
In the past five years, Australia has confronted a series of natural disasters and health crises, from bushfires to droughts, floods, and COVID-19. Effective responses to such emergencies require rapid and strategic actions to safeguard the community and wildlife, protect homes and businesses, and ensure the continuity of essential services like food, water, power, and communication. Achieving this demands a coordinated effort across federal, state, and local governments, in collaboration with private sector stakeholders.
The National Disaster Risk Reduction Framework, established in 2018, forms the backbone of Australia's strategy to enhance resilience against increasingly frequent and severe natural disasters. Building a resilient response framework is inherently multidisciplinary, necessitating collaboration across logistics, supply chain management, policy, finance, engineering, and more. This article delves into the critical role of forecasting and machine learning in emergency response, emphasising how Advanced Demand Forecasting serves as a foundation for informed decision-making during crises.
Natural Disasters and Emergencies in Australia
Australia has endured several significant natural disasters in recent years. The 2019-2020 Black Summer bushfires scorched over 18 million hectares across multiple states, leading to widespread destruction of homes, wildlife, and agricultural land. Severe flooding in southeastern Queensland and northern New South Wales in early 2022 caused extensive infrastructure damage, while the COVID-19 pandemic created nation-wide challenges, notably shortages of critical medical supplies, and disrupted daily life.
These events have underscored the significant need for increasingly resilient emergency supply chains, capable of responding effectively to unpredictable and rapidly changing demand patterns during crises.
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What is Advanced Demand Forecasting?
Advanced Demand Forecasting goes beyond copying historical data, but learns from it, by utilising sophisticated models that incorporate real-time and predictive data sources, such as weather forecasts, demographic trends, and even social media activity. These models employ advanced analytics and machine learning algorithms to provide more accurate and timely predictions, enabling organisations to anticipate future demand for critical resources and services more effectively.
For example, integrating live meteorological data into machine learning models allows government agencies to predict the trajectory, intensity, and impact of natural disasters like storms or bushfires. This predictive capability enables the estimation of necessary quantities of emergency supplies, optimal pre-positioning of resources, and precise timing for deployment. In addition to predictive analysis of the immediate threat, overlaying estimates of populations, infrastructure costs and more also enables impact estimates, including human injuries or displacement, or the cost to rebuild damaged infrastructure, which are used for forward planning at a government level, and prioritising resources at the time of a crisis (1).
Advanced Demand Forecasting and the National Disaster Risk Reduction Framework
The National Disaster Risk Reduction Framework aims to shift the focus from reactive disaster response to proactive risk reduction, emphasising a unified national approach involving all sectors of society (2). It outlines four key national risk priorities:
• Understand disaster risk: Ensure that meaningful risk information is freely shared and integrated into planning;
• Accountable decisions: Making decisions across sectors that either reduce or prevent disaster risk;
• Enhanced investment: Invest in risk reduction to limit the future costs of disasters;
• Governance, ownership and responsibility: Establish clear roles across all sectors and communities for reducing disaster risk.
The importance of this framework is underscored by the significant economic impact of natural disasters, which have cost the Australian economy around $18 billion per year over the past decade, with projections indicating this figure could rise to $39 billion annually by 2050 without effective risk reduction strategies. Advanced Demand Forecasting directly supports these priorities by providing high accuracy data to inform decision-making, budgeting, and resource allocation. By enhancing the understanding of disaster risks through predictive analytics and incorporating impact estimates, organisations can make decisions that prioritise risk reduction and timely recovery.
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Practical Implications
Implementing advanced demand forecasting can lead to:
• Improved Responsiveness: Faster identification of emerging needs allows for quicker mobilisation of resources, reducing the time lag between when it is needed, and when it arrives.
• Resource Optimisation: Accurate forecasts help in allocating resources efficiently by optimising stock distribution.
• Enhanced Collaboration: Sharing forecasting data among various stakeholders fosters a unified approach to disaster response, ensuring that efforts are complementary rather than duplicative.
The trace. Resilience and Emergency Response Framework
As a member of the Federal Government’s Management Advisory Services Panel, trace. is uniquely positioned to apply our expertise in Supply and Demand Management and Advanced Forecasting techniques to support the financial and economic analysis behind critical disaster resilience decisions. Our structured response framework aligns with the ISO 22301:2019 International Business Continuity Management Systems (BCMS) standard, ensuring that government agencies can maintain essential services during and after a disaster. The purpose of utilising the BCMS framework is “for organisations to plan, establish, implement, operate, monitor, review, maintain, and continually improve a documented management system to protect against, reduce the likelihood of, and ensure recovery from disruptive incidents (3).”
Our approach includes:
• Risk Identification: Support the Australian Government to identify all potential disasters, such as floods, bushfires, or droughts.
• Impact Analysis and Prioritisation: Analysing the potential impact of these disasters from multiple perspectives—economic, social, environmental—and prioritising the most significant risks based on data-driven insights.
• Continuity Strategies and Planning: Recommending tailored continuity strategies, risk mitigation activities, and response timeframes to ensure effective disaster recovery.
How Trace Consultants Can Assist Government Agencies
As part of the Management Advisory Services Panel, trace. can now assist Australian Government Entities with the following services:
• Benchmarking, economic, econometric, mathematical and financial modelling and analysis
• Competition and market analysis
• Economic advice
• Regulatory and policy analysis
• Data analysis
• Business cases and cost benefit analysis
• Supply and demand management and forecasting
Benefits of Our Approach
By engaging trace. to assist with Supply and Demand Management and Forecasting, government agencies can achieve:
• Improved Responsiveness: Faster identification of emerging needs allows for quicker mobilisation of resources, reducing the time lag between when it is needed, and when it arrives.
• Cost Savings: Efficient resource allocation reduces unnecessary expenditures on surplus supplies and minimises losses due to shortages.
• Data-Driven Decision Making: Leveraging robust data analytics supports transparent and accountable decisions, aligning with national priorities for disaster risk reduction.
Next steps
The increasing frequency and severity of natural disasters necessitate a proactive and data-driven approach to emergency management. Advanced Demand Forecasting offers a powerful tool for enhancing the resilience of emergency supply chains. This capability is crucial for safeguarding communities, reducing economic losses, and ensuring the continuity of essential services.
At trace., we are committed to helping government agencies adopt advanced Supply and Demand Management and Forecasting capabilities. With the right tools and strategic planning, we can collectively mitigate the economic and societal impact of future disasters.
If your organisation is seeking to strengthen its preparedness and response capabilities, contact trace. today.
Abby Hodgkiss
Consultant
References
1: Merz, B. et al (2020). Impact Forecasting to Support Emergency Management of Natural Hazards. Reviews of Geophysics, 58(4). Available at: https://doi.org/10.1029/2020rg000704.
2: Department of Home Affairs (2018). National Disaster Risk Reduction Framework Department of Home Affairs. Available at: https://www.homeaffairs.gov.au/emergency/files/national-disaster-risk-reduction-framework.pdf.
3: ISO The International Organization of Standardization (2019). ISO 22301:2019 Security and resilience — Business continuity management systems — Requirements. ISO. Available at: https://www.iso.org/standard/75106.html.
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