Informed analysis backed by the use of real-world data and machine learning is going to become ever-increasingly important in accelerating the recovery of bus patronage.
In the fourth and final part of our series on how important passenger demand data is for bus operators, we look at how CitySwift’s Mobility Intelligence as a Service platform can help them to make the right calls and ensure their businesses are fit for the post-Covid future.
We’ve seen some rapid changes in the bus industry over the recent decade, no more so than in the last two years as a result of the Covid-19 pandemic. As the challenges have increased, operators have become ever more resourceful in tackling those problems to stay ahead of the pack.
But as the complexities of those challenges rise, operators will increasingly require data enriched insights to inform them on how to best adapt their networks in years to come. Needless to say, bus companies have always relied on data in order to shape their businesses - but the form and complexity of that data has rapidly evolved over time.
“It’s only relatively recently that people have had sufficient data actually to make thorough use of it,” observes George Cooper, CitySwift product manager.
He points to CitySwift’s ability to easily link with existing systems to process siloed and hidden data sets – eliminating these barriers to transport network data. This means brand new, constantly updated intelligence to make better decisions that dramatically improve performance for the network, teams, and passengers. These insights are completely tailored to each user, so that the right people always have the right information, at the right time.
George explains: “It allows us to go back in time and look at what happened, but it also allows us to analyse that process. We can pull it apart, slice it and get something really meaningful out of the data.”
Part of that process has been powered by the rapid advances we have seen in the ticketing arena. George points back to 40 or 50 years ago when the vast majority of bus operators in the UK were reliant on hand-operated Setright ticket machines with ticket information reported by handwritten paper waybills.
“It was really poor data by today's standards,” he adds. “There was nothing really to speak of. If you wanted what today we’d call ‘insights’, you’d have to go out and physically look at the operation to get a handle on what was going on, or you’d be reliant on a team of revenue inspectors out on the road to do it for you”.
“We’ve transitioned all the way through that to the introduction of the first electronic ticket machines and the very basic reporting you had from them. Now you have the tremendous leap forward we’ve witnessed in the last couple of years.”
George points to developments like ‘tap-on, tap-off’ ticketing, contactless, smartcards and mobile apps - each of those has played a part in helping create a rich mix of very high-quality data, much of which is available to operators for the first time.
“For example, ‘tap-on, tap-off’ ticketing has only really been around a year or two,” he adds. “It’s well embedded with the operators who took that idea and went with it. The data it generates is just incredible; compare it to 10 years ago or even five years ago - we’ve got so much more insight now it’s brilliant. But the real challenge for the bus operators has been to take all that data and distill it into information.”
Part of that challenge has been a result of those technical advances - remember where we were with those Setright ticket machines and paper waybills of the 1970s and 1980s? Today it’s a different ball game. As George said, these new technologies are creating vast amounts of data that is quite granular in its composition - simplistically where someone boards a bus and where they disembark. How do you transform that low-level data into information that key business decisions can be reliably based upon?
“So how can you create that insight without time-consuming manual data processing and analytics?” asks George. “There’s a huge amount of analysis required with this and some of the data files are really quite large and quite challenging for people to process?”
George believes reliable data could help solve some of the patronage issues operators are starting to witness as society returns to normal following the pandemic. As we discussed earlier in this series there are growing concerns that some elements of the patronage mix are not returning to the bus.
“CitySwift will allow you to probe your demand by user types,” he explains. “Be it concessionary users, regular student users or discretionary users - you can slice up that data and view each in turn. What percentage do they make up? Where are they going? Is the trend changing? You can take all that very granular data and then you can slice it up. There’s so much you can get out of it and, most importantly, it has its basis on real-world insight.”
As well as this, CitySwift origin-destination data visualizations enable Schedulers and Network Planners to identify levels of demand across a network, and use that insight to tailor networks for optimal passenger experience and use of resources. This removes the heavy lift from Network Planners and Schedulers and tells them where they need to review service.
How it works:
- Routes or route corridors can be broken down into sections, and capacity/occupancy analysed by time of day
- Users can drill down into capacity/occupancy by trip, direction
- Get info for a specific trip, or view average over time of day or another specific period
Those insights will increase over time, George adds. Thinking back to those paper-based systems of the past and then comparing them to how far we’ve come, it’s clear there will be an upward trajectory in the data that is captured by operators. That will require operators to adapt and ensure they have the very best tools at hand in order to interpret it effectively.
“There’s a lot of traps you’ve got to ensure you don’t fall down and a lot of conclusions you don’t just jump to with that,” he says. “The critical thing is to ensure you have an understanding of the data and that you have the people in place who can interpret it - so the network planners and schedulers as well as the managers.
“We’re giving them the right tools to ensure they have the confidence in what they’re doing.”
Learn more about CitySwift’s Mobility Intelligence platform, request a demo or contact us to discover how CitySwift can help you run a network based on the most comprehensive picture of the latest passenger movements.