Humans naturally assume that we play a prominent role in everyone else’s story. When someone is rude, it’s because they’re annoyed at us. When someone’s upset, it must be something we’ve done. However, Hanlon’s Razor states “Never attribute to malice that which can be adequately explained by neglect.”

It’s easy for commuters to assume that poor quality service is part of a conspiracy by train operators to boost profits, whereas in fact, it’s just harder to solve than people might think. Many solutions to the problem are likely to be seen through this lens.

In the absence of past information or experience with historical conditions, members of each new generation accept the situation in which they are being raised as normal. This means that what people perceive as ‘normal’ or ‘acceptable’ changes from generation to generation.

What people consider to be overcrowding in a train station will generally increase from one generation to the next, as the baseline for overcrowding continues to rise.

It seems that our memories are biased, in that our memories of positive and negative experiences are dependent upon (a) what we were feeling at the most extreme (peak) point, and (b) how the experience ended.

To focus upon improving the experiences of commuters, we should be focussing on peaks in their commuting experience e.g. exiting the train upon arrival.

Both Normal and Log-normal distributions are used in statistical mathematics to describe the probability of an event occurring.

However, for commuters, the peaks of arrivals are so extreme and skewed that this isn’t a Normal case. Log-normal distributions are asymmetrical, and allow us to model this sort of skewness. This provides insight into the problem and enables us to make better decisions.

Human centered design is a process that starts with the people you’re designing for and ends with new solutions that are tailor-made to suit their needs.

Understanding the holistic user-journeys of commuters - i.e. outside of the train journey itself - and putting everything into context is crucial in coming up with an effective solution. What do commuters do before their journey? What are their expectations upon arrival? What do they want to change?

Rapid prototyping is a design workflow consisting of ideation, prototyping, and testing. In manufacturing, it often involves technology such as 3D printers. The process helps designers quickly discover and validate their best ideas.

Small scale tests are complex to implement in situations which involves hundreds of thousands of people, like commuting. Rapid prototyping makes this somewhat easier, as we’re able to repeatedly (and quickly) test interventions in such cases.

Occam’s Razor implies that, all things being equal, it is rational to prefer parsimonious theories to bloated ones. It helps us ‘shave off’ concepts, variables, and constructs which are not really needed for our explanations.

Occam’s Razor encourages simple, novel solutions to problems. For example, why think about trying to make a train journey shorter, when you could instead focus on making it more pleasurable or useful?

In engineering, redundancy refers to ‘over-engineering’ a system to reduce the chances of failure. Typically, this involves adding extra instances of critical components to a system so that one can take over from another if something goes wrong.

Increased public pressure on the commuting problem could tempt train providers to remove built-in margins of safety who see them as unnecessary. However, this in turn could increase the frequency and severity of delays.

Opportunity cost is the benefit that is missed or given up when an investor, individual, or business chooses one alternative over another. Knowledge of opportunity costs can help us make educated decisions when we have multiple viable options.

Train providers will consider opportunity costs when weighing up different solutions. Similarly, commuters will weigh up opportunity costs when looking at alternatives to simply coping with peak travel.

A cost benefit analysis gives you a quantitative approach for deciding whether to go ahead with a decision. This is the underlying formal, technical, and rigorous process used to calculate opportunity costs. The method is also helpful for being able to compare tangible costs (such as ticket prices) to intangible costs (such as how busy it is).

There are other, more nuanced methods which tread upon the same idea, such as Net Present Value or Internal Rate of Return.