Using Digital Twins to Improve Customer Experience
It’s easy to think that a digital twin, comprised of sensor readouts, timetable data and schematics, functions only to optimises mechanical systems. However, the end users of the railway are humans not machines! By using digital twins, rail companies are beginning to improve and enhance the end-user experience, especially service reliability. But beyond that, what other avenues could digital twins provide additional value to customers?
The drive for better customer experience
User experience is increasingly becoming an important factor in creating customer satisfaction and loyalty. The most important component in driving a good customer experience is creating a predictable service which operates smoothly. This is something that digital twins in development are geared towards delivering. However, there are other important factors for providing a good service to customer, specifically these are autonomy, and personalisation. Though these have not yet been addressed by twins, these could be.
In 2018, to enhance patients’ experiences Siemens developed a digital twin of the radiology ward in Mater Private Hospital in Dublin. Delivering an appropriate level of patient care was becoming increasingly difficult due to a growing demand on existing capacity, ageing infrastructure, space restrictions and clinical complexity. To overcome these challenges Siemens created a CAD (computer-aided design) model of the facility, used operational data from medical imaging workflows, and held workshops to create a model of the department and its operations. The setup was then used to test different operational scenarios and layouts. The insights gained led to a physical redesign of the facility which increased the efficiency of visits and made the area more accessible to bedridden patients or those that use wheelchair.
This holistic approach to identifying where improvements can and should be made is equally applicable in rail. Although the smaller, closed system of twinning a single ward is unquestionably an easier task than a multi-modal public transport journey.
Turning existing data into the right information, for the right customer, at the right time
In a world where every individual purchase and journey is digitally logged a staggering amount of data is generated. There is even more if data generated on social media, including images and text posts highlighting the positives and negatives of a transport experience is considered. This data presents an opportunity to create digital twins of journeys, of users, or of user groups to better understand and make improvements to customer satisfaction.
A study of passenger values in 2019 highlighted strong desire for improving seat reservation services. Combining the knowledge of individual passenger seat preferences with a digital twin of train seat occupancy, could create an opportunity for a dynamic understanding of actual seat occupancy and use this to provide reliable, detailed and customised seating advice to passengers. Furthermore, this could allow the reservation options for unoccupied seats in last minute bookings.
A real-time representation of how the network operates is perhaps the most powerful tool by which digital twins could enhance customer experiences. Research indicates that 64% of consumers and 80% of business buyers expect to interact with companies in real-time. A passenger values study also identified real-time information as a top priority for customers: sharing train location information and if they will be on time is critical to delivering a good service. Rail already delivers such information through various mobile apps, but digital twins could produce new sources and forms of data in ways that would be of additional value to customers. This could be directly in relation to individual travel experiences or to plan improvements to the overall customer experience at scale.
New rolling stock is being fitted with an increasing number of sensors that generate operational data which can be fed into the digital twin. This information may help to improve customer experience by improving the understanding of, for example, ride comfort (temperature, noise levels). Being open to the possibilities of using data to improve the customer experience may reveal new benefits for its analyses, and the digital twin could provide the integrated platform from which to facilitate this.
Another aspect of the customer experience which digital twins could enhance is accessibility. At present, a significant proportion of people prefer to make car journeys because they are unsure if their needs will be catered for on public transport. They may be anxious that they will not be able to find a step-free route or that not enough understandable or useful information will be available to enable them to complete their journey. While many journey assistance mobile apps have already been developed (several with funding from RSSB), including ones specifically catering to passengers with disabilities, digital twins could contribute information with extra levels of utility.
Digital twins of the network could help to alleviate such concerns through, for example, a journey planning mobile app which integrates live, accurate data about station facilities. This can reassure users that their journey will go as they expect, or help them plan suitable alternatives. Mobile apps which visualise a customer’s entire journey, including turns, changes, and ticket purchasing could help to reduce the anxiety customers may have about public transport.
Digital twins of passenger flow of stations are in development. This will help those who prefer to avoid crowds through either live or predictive information about when the station will be busy. These will incorporating data not only from the network, but also relevant external factors such as the weather or nearby events which could be a hugely helpful addition to the details that existing mobile apps provide.
Using the data we have, well.
The goal for using digital twins in the railway is to improve performance and the primary experience of customers. This can be further expanded by considering what and how the information from such digital twins can be accessed by passengers, or the new ways it can benefit them. Feedback data generated by this process could enable the development of a richer and more refined twin, creating further value for the railways and its passengers.However, with data sharing and harvesting it is important that care is taken in how the data is treated, who owns it, who is liable for it, and how customers can be convinced to share their data. For rail, an additional challenge is to take into account elements of that journey which cannot be measured or influenced by one party alone, since almost all journeys are multi-modal.
How the scale and complexity of the data is handled and governed will feed into a rail digital twin is a crucial question for our industry, and one which will be explored in this series by Peter El Hajj of Mott MacDonald and Programme Manager on the National Digital Twin Programme.
