Back
Technology is transforming business operations and customer satisfaction across a wide range of industries. And the transport sector is no exception.
In this excerpt from our eBook, The Passenger Satisfaction Playbook, we explain how and why bus operators should embrace cloud-native SaaS technology platforms and Artificial Intelligence.
Look to the clouds
A good technology stack will bring scale and functionality where it’s needed most, along with a high level of insight into the business and the environment in which it operates.
Unfortunately, many bus operators are still using slow, cumbersome systems that were originally built in the 1990s. They don’t take advantage of the massive increases in computing power that have taken place since then – and the huge benefits this brings.
We all use cloud-native SaaS (Software as a Service) technology, whether we realise it or not. From web-based email platforms such as Gmail to streaming music players like Spotify, they have quickly become part of our daily lives.
For businesses, cloud solutions offer significant benefits over software installed on-premise, including lower up-front costs, reduced investment in in-house support and enhanced security.
Cloud solutions offer significant benefits over software installed on-premise, including lower up-front costs, reduced investment in in-house support and enhanced security.
There’s no need to install anything, updates happen automatically, users can access the software from anywhere and data is securely stored and backed up. Integrations with existing technology are the responsibility of the vendor, who will typically have built hooks and APIs to ensure that it’s a simple procedure.
The rise of machine learning
We have already seen the introduction of Artificial Intelligence across a wide range of business applications. Over the next few years, it will become vitally important to almost all industries.
Artificial Intelligence typically refers to a data science technique called ‘machine learning’. It enables programs to learn through training, rather than being programmed with a set of rules. By processing training data, machine learning systems deliver results that improve with experience.
Increasingly, machine learning allows traditional human capabilities – understanding, reasoning, planning, perception and communication – to be undertaken by software efficiently and effectively.
Machine learning allows traditional human capabilities – understanding, reasoning, planning, perception and communication – to be undertaken by software efficiently and effectively.
AI-powered automation has already transformed the way some parts of the transport sector operate. Airlines use it for revenue management and fuel efficiency optimisation. Transport for London uses it to identify and predict causes of disruption. Uber uses it to help customers easily book a ride, knowing there will be an available driver nearby.
Bus operators can use machine learning to drastically improve their business operations and passenger satisfaction.
Unlock the value of your data
Operators collect huge amounts of data – and there’s a lot of potential uplift in punctuality, average speeds and passenger satisfaction that can be gleaned from it. But most of the time, this data is still interrogated by humans, who are probably only unlocking 5% of its value. And by the time they’ve unlocked it, it’s out of date.
By implementing machine learning technology, bus operators will be able to take full advantage of the value of their data for the first time.
By implementing machine learning technology, bus operators will be able to take full advantage of the value of their data for the first time.
Consider the various ways in which machine learning could be used to improve passenger satisfaction in your operation:
- • To create schedules that take into account traffic, weather and other external factors, helping ensure on-time performance.
- • To better understand the effect roadworks or accidents will have on your services, allowing you to temporarily adjust your schedules to compensate.
- • To predict demand for your services and show the impact of major events, the building of a new hospital or closure of a department store, long before they happen.
- • To improve your operational efficiency and prepare your network for the future.
