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Seven things you can learn from our latest eBook

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Seven things you can learn from our latest eBook

The coronavirus pandemic has been - and continues to be - challenging for all parts of society – and public transport operators are not immune from this.

They have had to learn new techniques and skills that would have been unthinkable a year ago. The learning curve from this process has been steep, but despite the adversity and challenges of continuing to operate an essential front-line public service day-in, day-out in the midst of a global pandemic, there have been new technological advances devised and created that will deliver benefit way beyond the trying circumstances we find ourselves in today.

Many of these important and timely new innovations place big data at the heart of this process – large data sets that reveal patterns, trends and associations relating to human behaviour. If exploited competently and fully, the opportunities for operators are immense.

We recently published 'The Data-Driven Bus Operator' – a free guide to how big data, artificial intelligence and machine learning are being used by bus operators around the world, and how transport industry leaders see the potential for big data and technology moving forward.

Here are seven things you can learn from the eBook:

1. Big data can deliver some serious benefits and efficiencies 

Transport operators collect huge amounts of data on a daily basis – and there’s a lot of potential uplift in punctuality, average speeds, and driver/passenger satisfaction that can be gleaned from it. But making sense of all that data is a daunting task. If interrogated at all, it’s often interrogated on a fairly basic level by employees for whom ‘data analyst’ is neither their official job title nor main priority. 

This is where artificial intelligence comes in. By implementing AI, modern bus operators can take full advantage of the value of their data – allowing them to create better, more efficient schedules; quickly adapt to disturbances such as traffic incidents and emergencies, and predict short and long-term demand for their services.

"By implementing AI, modern bus operators can take full advantage of the value of their data."

2. Big data can aid social distancing

One innovation that has emerged from the pandemic is dynamic loading information. Leading UK operators such as the Go-Ahead Group and National Express Bus have used our SwiftConnect APIs to add innovative, AI-driven predictive bus capacity checkers to their passenger-facing apps and websites.

The clear presentation of likely bus loadings offers reassurance to people who are thinking about using the bus, especially those who are nervous about being in enclosed public spaces. Equally important, however, is the additional background information it gives bus operators on bus loads for planning purposes. By maximising the use of capacity, they are also able to maximise revenue.

"The clear presentation of likely bus loadings offers reassurance to people who are thinking about using the bus, especially those who are nervous about being in enclosed public spaces."

3. Big data can improve network planning

Transport for London has used its ticketing data to build a comprehensive picture of travel patterns across London’s bus and rail networks. It uses big data analytics to glean origin, destination and bus interchange (ODX) information. This information helps TfL to improve network and interchange planning and review the impacts of closures and diversions. As Lauren Sager Weinstein, TfL’s Chief Data Officer, noted: ‘By harnessing the potential of all of this data, we will be able to improve the experience of all those travelling in London.

National Express has also been using big data to take the guesswork out of an unprecedented series of network recasts during the Covid-19 crisis. It has deployed our SwiftMetrics network analysis platform and SwiftSchedule timetable optimisation technology across its entire bus network - the UK’s largest outside of London - to optimise services and accurately match vehicle supply with passenger demand.

"National Express has been using big data to take the guesswork out of an unprecedented series of network recasts during the Covid-19 crisis."

4. Big data can be an effective lobbying tool

Many bus operators have had to work closely with stakeholders in implementing new bus priority measures, and big data can be used to drastically improve the speed and accuracy of this process. Bus network design specialist, Adam Hawksworth believes that data is the key to unleashing the power of the bus in urban areas, now more than ever. He says: "We have to provide compelling evidence to local transport authorities about how buses can improve cities. It’s a win-win."

An example of this is how MasterCard used fare payment data to analyse the effect of a car-free day in New York City and help dispel the myth that the car is king. By scrutinising fare payment data, they found that the one-day event had resulted in an increase of more than 30,000 users than the season’s daily average on the city's subway. Retail stores saw no significant adverse effects on commercial activity in the surrounding areas, despite road closures created to facilitate and support the spirit of the event.

"We have to provide compelling evidence to local transport authorities about how buses can improve cities. It’s a win-win."

5. Big data's potential in the public transport sector is enormous

Go North East Managing Director Martijn Gilbert believes that “we have only just scratched the surface” of how data can transform not only the passenger experience but create improvements and efficiencies for operators themselves.

Ralph Roberts, MD of Scottish operator McGill's, says “bus companies have used technology more to their advantage than perhaps any other sector in the public transport industry over the last decade.”

Alex Hornby, Chief Executive of Transdev Blazefield, thinks technology has the capability to reassure passengers in the post-Covid era. It's a view shared by Andy Foster, Deputy Commercial Director of National Express West Midlands. “Shopping and working patterns are changing,” he says. “I think we will rely on data to a greater extent because networks and schedules need to become more efficient.

Shopping and working patterns are changingI think we will rely on data to a greater extent because networks and schedules need to become more efficient.

6. Big data will change the way we schedule buses

Richard Sherratt, a scheduler with Trentbarton, remembers early on in his career having to look through the handwritten paper waybills produced by drivers each day in order to get a feel for passenger loadings. The world has moved on since then! 

He believes technology will play a major part in realising greater efficiencies by helping to maximise vehicle utilisation. This will prove a valuable tool in helping to overcome the effects of ever-increasing traffic congestion. It will also help in matching frequency with demand, both of which are important factors in creating customer confidence.

"Technology will play a major part in realising greater efficiencies by helping to maximise vehicle utilisation."

7. Big data needs to be trusted by passengers

Martijn Gilbert thinks that the challenge for the industry so far has been having tools that allow users to really trust the data. Technology providers such as CitySwift are now providing those tools, and Martijn finds their outputs visually powerful and easy to digest.

If we can get this right, it will be an opportunity for the industry to really embrace the power of big data,” he says. “We’ve got to because I don’t think anybody is expecting customers to return in their normal numbers for some time. There will be changes and for us to find our way to the optimal solutions for both our customers and the business, we’ve got to be influenced by emerging demand.

If we can get this right, it will be an opportunity for the industry to really embrace the power of big data.

To download your free eBook, complete the form below.

The Data-Driven Bus Operator