Probabilities not predictions

New research shows New Zealand can improve the way we forecast demand for infrastructure and take a more flexible approach to planning. This paper, released alongside the National Infrastructure Plan, shows there are better ways to plan for uncertainty.

The covering report is supported by a technical paper prepared for the Commission by independent expert Peter Clark entitled Understanding Risks and Uncertainties in Transport Demand Forecasts with Monte Carlo Techniques. This technical summary demonstrates how using Monte Carlo modelling can be applied to major transport projects, using Auckland Light Rail as an example. Monte Carlo modelling uses repeated random sampling to analyse uncertainty and offers a more robust approach for major transport projects. Rather than assuming one future, it tests thousands of possible scenarios.

Key findings

• Traditional planning approaches that rely on a single demand prediction create significant risks. When forecasts are wrong, we either overbuild (wasting money) or underprovide (constraining growth).
• International and New Zealand examples, including Auckland's rapid transit projects, show how a Monte Carlo modelling approach helps decision-makers understand the range of possible demand outcomes and manage investment risks accordingly.
• Better modelling needs to be paired with flexible design. Infrastructure should be designed to adapt to changing needs, rather than locked into assumptions that may not hold.
• These approaches support the National Infrastructure Plan's goals: making better use of existing assets and ensuring new investments are right-sized and timed to align with demand.