The Prediction of Future Outcomes

The prediction of a future outcome such as the traffic level (e.g. port or airport terminal, transit ridership) logically experiences a decline in predictability and a proportional increase in uncertainty as longer timeframes are being considered. This exercise falls into three main dimensions:

• Forecasting. Commonly using a trend of past observations and trying to infer this trend into the future. It assumes that the parameters related to an outcome remain constant and as such that its extrapolation a relatively simple exercise using time series methods (e.g. moving average). These models also express uncertainty as growing confidence intervals. Once uncertainly reaches a level which is higher than predictability, forecasting ceases to be a relevant exercise, which requires scenario building.
• Scenario building. Tries to predict future outcomes by changing an array of parameters, with each change part of a specific scenario. A common strategy is to present the future within the realm of low, medium and high growth scenarios and apply these scenario to forecasting. Scenario building does not remove uncertainty, but may improve predictability by considering a set of possibilities.
• Speculations. At some point the level of uncertainty is such that any prediction enters the realm of speculation. Quantitative methods lose much of their relevance and under such circumstances the future must be seen mainly as a speculative exercise about what may or may not take palce. A common problem is that forecasting often makes predictions within a speculative timeframe using a quantitative methodology to claim a high level of predictability while this predictability is very low.

Scale has an important impact on predictability as forecasting traffic for a single terminal is much more uncertain than for a region. Some outcomes are obviously easier to forecast than others as they have shown a greater level of stability and predictability in the past. For instance, demographic trends tend to be stable, shifting slowly and not subject to radical changes.

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Copyright © 1998-2012, Dr. Jean-Paul Rodrigue, Dept. of Global Studies & Geography, Hofstra University, New York, USA.
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