Bike sharing will benefit from learning some data lessons

Bike sharing will benefit from learning some data lessons

This morning’s news that bike sharing firm Mobike was launching in the UK caught my eye.

The story was full of excitement about the convenience and how cycling can help people becoming more active and improve air quality by reducing the number of car journeys. But the story also featured challenges: piles of bicycles on pavements and congested cycling lanes in cities not expecting an increase in traffic. Transport authorities seemed to be caught between the desire to seize the opportunities and head off the complaints.

But one thing that was missing from the story was how familiar the challenges are and how cities are already tackling them in other areas. At theOpen Data Institute, where I work, we like to talk about design patterns for policies that use data to create impact. Some of the patterns needed to make bike sharing better are already in use elsewhere. Bike sharing companies and cities can learn some lessons from cars, buses and other cycling apps to tackle the challenges a bit faster and grab the opportunities a bit sooner.

Mobike is one of a number of firms offering bike sharing services. The service is simple. You download a smartphone app, request a bike, go to the location shown on the app, get the bike, cycle to where you want, leave the bike somewhere convenient and pay your fee.

The bike sharing operator will need to process orders and payments, maintain a fleet of bikes and predict demand so that they can move unused bikes to where they are likely to be needed.

The local Transport authority has a different task. They need to maintain transport infrastructure to suit the different modes of transport (walking, cycling, cars, buses) that meet the needs of different groups of users (able-bodied people, people with disabilities, tourists, residents, business travellers) at different times of the day. It’s great that cities are warmly welcoming trials of another option in this already complex system.

Some of the challenges posed by bike sharing are already being helped by data. Better use of data can tackle them more easily.

Neither cyclists or bike sharing companies want congested cycling lanes. It will make it hard for people to get where they want and risks increasing accidents. That will reduce the number of people who cycle, and reduce the profits that bike sharing companies might make. Giving transport authorities access to data about where people cycle and where accidents occur will help them meet demand and create safer roads. Giving cyclists data about congested cycling routes will help them make better decisions about where to cycle and when.

The bike sharing companies don’t want piles of unused bikes on pavements. They make money when the bikes are used. Bike sharing companies won’t have data on how congested a pavement is because of other traffic: for example bicycles belonging to a competing bike sharing company or because of pedestrians trying to get to lunch. But that congestion can damage their reputation. Giving bike sharing companies access to this data will help them make better decisions about when to move bikes. Giving transport authorities access to this data will help them understand the impact of bike sharing on other types of transport.

Data isn’t a magic bullet. You can give better information to cyclists, bike sharing companies and transport authorities but there is no guarantee that they will use it or that they can even use it quickly. But it can help. We’ve seen it already. The transport sector still has lots to do to improve data but it is a sector which is ahead of most.

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