The definition may sound a bit confusing, but transport planning as all kinds of planning is the most basic decision making support system. As such, transport planning is mainly a process of human thought and action. In our field, we come across people that are usually technically highly qualified but often miss the same level of training and experience in the fields of philosophy, logic and rhetoric. This sometimes leads both transport planning consultants and public sector officers to unintentionally commit logical fallacies during the process of transport planning. If the public and stakeholder consultation and the risk analysis process of the planning activity are not robust, it may lead to catastrophic errors and waste of valuable resources.
McNamara fallacy
The McNamara fallacy or quantitative fallacy is about transport planning and decision making based solely on quantitative analysis and ignoring qualitative variables and values. This usually occurs when there’s a pressure for “evidence based” practice either in transport policy or in planning. The desire to be able to prove the value of recommendations, leads transport planning practitioners to stick to survey numbers and modelling results and ignore other parameters of the analysis such as conclusions from the public and stakeholder consultation. Most importantly, it leads to ignoring the principles of planning theory and the established higher levels of planning (strategic regional and urban). The American social scientist and author Daniel Yankelovitch, listed the most usual misconceptions:
1. Measure whatever can be easily measured.
2. Disregard that which cannot be measured easily or to give it an arbitrary quantitative value.
3. Presume that which cannot be measured easily is not important or does not exist.
Big transport organisations such as Translink, that gather huge amounts of data daily are starting to understand that you cannot improve something just by consistently measuring it.
1. Measure whatever can be easily measured.
2. Disregard that which cannot be measured easily or to give it an arbitrary quantitative value.
3. Presume that which cannot be measured easily is not important or does not exist.
Big transport organisations such as Translink, that gather huge amounts of data daily are starting to understand that you cannot improve something just by consistently measuring it.
Sunk Cost Fallacy
Sunk cost fallacy, or Escalation of Commitment appears when transport planners recommend and justify increased transport infrastructure or services investment, in a decision based on the cumulative prior investment. This usually happens regardless of new evidence suggesting that the cost outweighs the expected benefit. Such investment may include spending more money on improving a transport system that was recently delivered but is hugely under-performing. Transport infrastructure has by nature high levels of sunk cost. You built a Light Rail system and then you’re almost obliged to support it for a long period or even expand it. Adding more lanes in an already congested motorway is a usual practice although over the years it has been obvious that induced demand keeps level of service (LOS) and delays at the same levels. This fallacy is so common that you will often hear expressions such as “Throwing good money after bad", or "In for a penny, in for a pound" around transport planning offices.
Usually sunk cost fallacious thinking occurs for a number of reasons:
1. Social, political or peer pressure
2. Psychological (usually in gambling but also involving office politics)
3. Project (past commitments especially in terms of higher level planning)
Usually sunk cost fallacious thinking occurs for a number of reasons:
1. Social, political or peer pressure
2. Psychological (usually in gambling but also involving office politics)
3. Project (past commitments especially in terms of higher level planning)
Planning Fallacy
The planning fallacy is the most obvious fallacy that affects transport planning. One would expect that experienced planning professionals would know and avoid this fallacy but a number of transport projects in the past had fallen victim to this. The West Connex freeway and tunnel and the North West Rail Link are just two examples that were just recently identified by the NSW Auditor-General. Planning fallacy is the natural tendency to be overly optimistic when estimating the time and cost that will take for a series of actions to be completed. Transport planning projects are affected by this fallacy when individual team members in the project planning face underestimate their own time for completion of their tasks. Usually this occurs despite the fact that these planners have previous experience of similar tasks taking longer than originally anticipated. Researches have provided a number of reasons for this behaviour that could be simplified as follows:
1. Wishful thinking (informal fallacy) when positive outcomes are thought to be more likely than negative outcomes
2. Self-serving bias (cognitive bias) – when successful outcomes are thought to be caused by the individual but negative outcomes to external factors
3. Future focus – tendency to forget the past, especially if it’s a failure and focus solely in the future, failing to take into account past experience for task cost and time to completion.
1. Wishful thinking (informal fallacy) when positive outcomes are thought to be more likely than negative outcomes
2. Self-serving bias (cognitive bias) – when successful outcomes are thought to be caused by the individual but negative outcomes to external factors
3. Future focus – tendency to forget the past, especially if it’s a failure and focus solely in the future, failing to take into account past experience for task cost and time to completion.
Causal fallacy
Source: Stephen R. Johnson, Journal of Chemical Information and Modeling, 2008,
There’s a series of similar fallacies that fall under the general title of causal fallacy. In trying to analyse an incident or an event and understand what’s causing it, transport planners sometimes incorrectly identify the wrong parameters just because the statistical analysis shows a correlation. Simply because two events are happening together, this doesn't necessarily mean that the one causes the other. Similar to this, merely because one event is always followed by another, again it doesn't necessarily mean that the second event was caused by the first. There’s a famous saying among statisticians that “correlation doesn't mean causation” but this is something that is not always known among transport planning professionals. This fallacy is most common in transport modelling, where practitioners are usually very good at mathematics and statistics and they tend to rely on transport modelling software for their planning work. Analysis on how transport infrastructure affects urban development is another area that this fallacy appears quite often. Transport improvement is not always the cause of increased property development and never the only cause. With this fallacy there’s the risk to take it to the exact opposite extreme and think that correlation never implies causation. There are three conditions that can help understanding correlation and causation:
1. The data analysed and examined needs to be specific and consistent.
2. The causation needs to be plausible and pass the common sense test.
3. Understand the different types of relationship two variables may have other to causation.
1. The data analysed and examined needs to be specific and consistent.
2. The causation needs to be plausible and pass the common sense test.
3. Understand the different types of relationship two variables may have other to causation.
Further reading – Sources
http://chronotopeblog.com/2015/04/04/the-mcnamara-fallacy-and-the-problem-with-numbers-in-education/
Bert van Wee, 2011, “Transport and Ethics: Ethics and the Evaluation of Transport Policies and Projects”, Edward Elgar Publishing
Helen Beebee, Christopher Hitchcock, Peter Menzies, 2012, The Oxford Handbook of Causation, Oxford University Press
This post was first published on LinkedIn Pulse.
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