Richard Paling Consulting / Waka Kotahi NZ Transport Agency
Richard Paling Consulting was commissioned to update the National Freight Demand Study (NFDS), New Zealand's benchmark report on freight flows. The goal was to improve the NFDS with real-world GPS freight data, ensuring that national freight planning reflects actual movement patterns across industries and regions.
Approach
- GPS Data Collection and Processing – Captured and processed comprehensive freight trip data from across New Zealand, standardising all records for integration into the NFDS framework.
- SA2-Level OD Analysis – Broke down freight movements to Statistical Area 2 granularity, enabling regionally precise analysis of flows by origin, destination, and industry sector.
- Industry Type Segmentation – Classified trips by industry, allowing for more nuanced analysis of sector-specific freight patterns.
- Ferry Crossing Quantification – Measured the number of freight trips involving inter-island ferry crossings to better capture national supply chain connectivity.
- Integration with NFDS – Delivered a cleaned, structured dataset that slotted directly into the NFDS modelling process, enhancing its overall precision.
Key Findings
- Enhanced Freight Movement Clarity – Produced the most detailed GPS-derived freight movement dataset used in an NFDS to date, improving route and volume accuracy.
- Inter-Island Freight Insights – Quantified ferry-related freight activity, filling a historical gap in the study's understanding of inter-island logistics.
- Industry-Specific Flow Patterns – Highlighted the distinct routing and intensity patterns for different freight sectors.
Impact
- Infrastructure Planning Support – Enabled evidence-based investment decisions in freight corridors and inter-island transport infrastructure.
- Stakeholder Engagement – Provided industry stakeholders with data to inform advocacy and collaboration with planners.
- Policy Alignment – Supported strategic government and regional planning by grounding the NFDS in real-world operational data.