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  • Pooya Kamvari

“When it comes to traffic, there are as many opinions as people. What we need is data.”

Transport solutions are tricky to implement, expensive and take time to bed in. That’s why they need to be based on facts and data, rather than what people think.

In most sectors, if you want to improve something, you have to measure it first. Without knowing the present situation, you can’t know that you’ve done anything to make it better. It’s the foundation or the baseline that we use to benchmark future progress.

What we found with the school run, is that currently, there is no baseline. The information we have - mainly Hands Up surveys for Transport for London Stars (or ModeShift Stars), where school children are asked once a year (usually during Walk To School Week) how they got to school - isn’t robust enough to properly inform us about what traffic solutions should be implemented

And, when it comes to traffic, there are as many opinions as there are people. Whether we’re doing a school run or not, we all walk, drive, cycle from A to B. And we all have an opinion on it. But as we know, when everything is a matter of opinion - rather than based on a set of information from which it’s possible to draw logical conclusions - the result is often conflict.

As well as connecting communities and enabling journey sharing, HomeRun collects anonymised data relevant to the school run. Once the app is rolled out in a school, the parents update it each term, sharing vital information on how they get their children to school, if they drive, where they park, drop off, etc. This information is then anonymised and displayed on a map. Interestingly, what we discovered, once we had that data, was that everyone, even the head teachers, were surprised by it.

In Hampstead, where I live, we work with a cluster of schools. And the great thing about working with a cluster, is that we start to see patterns repeated.

Key amongst them were:

● Active travel (walking, cycling) is less accessible to younger children

● Journey distance is key. From 1-1.25 miles up, we see active travel dropping as a parental choice, and driving increasing

● In London, areas with high levels of driving suggest a lack of public transport options available

● Unsurprisingly, the availability of more travel options, such as public transport and safe cycling infrastructure, inevitably impacts journey choices.

But while some patterns are shared, the other thing that became clear from the data is how unique every school is. Each school has its own particular commute footprint, dependent on lots of different things. Hilly areas will require different solutions from somewhere that is flat, for example; urban locations need different approaches to places that are more rural. Additionally, there may be transport or cultural problems that aren’t always immediately obvious, even to the people closely involved.

Transport solutions are tricky to implement, and if they are implemented based on opinion rather than data, they are even trickier. However, once you have a clear, data-led view of what the problem really looks like, you can work out which solution in your toolkit is the most relevant.



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