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National Shipping Policy Analysis

AI-Powered Cost-Benefit Modeling

Forward Deployed Engineer (FDE)AI-Powered CBAStatistical AIPolicy Simulation

The Challenge: Navigating a Billion-Dollar Policy Decision

Australia's coastal shipping regulations touch every aspect of trade-crew laws, vessel licensing, freight demand, and operating costs. The government needed to choose among several regulatory paths to amend the Coastal Trading Act, each with very different implications for cost, efficiency, national industry, and competitiveness.

"How do we model decades of regulatory change across multiple freight sectors and seafaring regimes?"

The task: forecast and compare long-term economic impacts of different regulatory options to inform a defensible policy.

Our FDE Approach: Engineering a Statistical & AI-Driven Simulation

Working side by side with government officials and industry experts under the Forward Deployed Engineering (FDE) model, our team built a modular simulation engine to test each proposed regulatory scenario.

1. Data IngestionIndustry DataGovt. Policy2. AI Simulation EngineStatistical ModelMarket Share Forecast3. Scenario OutputsNet Benefit / Cost20-Year Projections

Visualized Insights: The Economic Forecast

Net Economic Impact by Policy Option (20-Year NPV)

Projected Annual Benefit (Recommended Option)

The Outcome: A Clear, Defensible Policy Path

~$798M

Net Economic Benefit

Projected for the 'smart regulation' policy.

-$2.5B

Net Economic Cost

Forecasted for the full deregulation option.

20-Year

Forecast Horizon

Providing a long-term strategic view for policy.

Clarity

For Government

Enabled an informed and defensible regulatory decision.

How We Made the Decision-Maker's Life Easier

Clarity from Complexity

The AI model distilled a complex web of laws, economic variables, and market forces into simple, direct comparisons. Decision-makers could see the most likely 20-year outcome of each choice, side-by-side.

Defensibility

Confidence & Defensibility

Instead of relying on opinion, the government could base its decision on a robust, data-driven forecast. This provided a strong, evidence-based foundation to justify their chosen path to the public and industry stakeholders.

De-Risking the Decision

De-Risking the Decision

The simulation highlighted the significant, non-obvious risk of the full deregulation option-a potential -$2.5B cost. This crucial insight helped policymakers avoid a costly mistake and choose the path with the highest positive impact.

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