The mobility industry is collecting more information than ever, says Abhijit Pal, Partner, Mazars: “The potential to capture data has been enhanced immensely in recent years,
web and mobile channels are performing processes while collecting information, and hardware in cars and aircraft are doing the same. The result is a deluge of data.”
Ensuring companies ably collect, analyse and act on this data so they do not drown in the deluge has, therefore, become a key industry success factor.
Data lessons from aerospace
One mobility industry known for turning data to its advantage is aerospace, which uses it to improve maintenance techniques. For the first half of the twentieth century, engineers maintained planes by checking parts at various intervals. However, in the 1940s engineers discovered planes failed more often after their regular maintenance checks than before. Closer investigation revealed this was because repair procedures involved disassembling and reassembling equipment, creating more potential for failure.
This led to ‘condition-based maintenance’ - maintaining parts when necessary, rather than at regular intervals – and it took hold. The next innovation was to fit components with sensors collecting data that could alert engineers when they needed attention, known as ‘predictive maintenance.’
“Since the early 90s,” explains Olivier Guilbert, Senior Manager, Mazars, “predictive maintenance has continuously improved the safety of airlines. In recent years, by collecting data from more parts of the plane, major players in the industry aim to take this approach into a new era.”
Smarter supply chain management
Using data to improve maintenance is not the only lesson other mobility players can learn from the aerospace industry. Predictive maintenance – powered by using data effectively – also builds smarter supply chains.
Guilbert explains: “When you know what is likely to need replacing and when, it becomes much easier to optimise the flow of spare parts and maintenance personnel. By using sensors to collect accurate, up-to-date data on individual components, mobility businesses can incorporate field experience and generate better predictions as a team.” This means getting the right part to the right place at the right time and, as a result, businesses being able to replace parts before they fail.
Improving customer experience
In addition to improving hardware, data can also meet new customer expectations and improve their experience. Take insurance, for instance, “New forms of mobility – particularly those used in urban settings – are creating new needs. Insurers, in turn, are using data to develop offers targeted at electric scooters, Segways, and city cyclists. They have also stepped into the sharing economy, covering shared vehicles and daily, even hourly, car rentals,” says Jean-Claude Pauly, Partner, Mazars.
The aerospace industry offers further best practice for using data to increase customer satisfaction, says Guilbert, “Biometric passports, backed by data, also help reduce waiting time at security checkpoints and significantly boost customer satisfaction.”
Data is not just changing what can be covered but how – with positive outcomes for personalisation. Pauly notes, “Like other sectors, insurers are increasingly automating their processes: using algorithms alongside human intervention to cover a multitude of small risks. Artificial intelligence used correctly allows insurers to offer tailor-made solutions to customers at volume. One other example of this personalisation is ‘pay how you drive’, where a box fitted to a vehicle calculates how many kilometres are driven over a particular period and how the vehicle is being driven in order to create a custom price, based on the data, according to risks taken.”
Recognising new data risks
These developments, however, create their own risk as they impair a basic principle of insurance: the mutualisation of risks between policyholders. “This could lead to very high premiums for some drivers, and others may struggle to find an insurance provider at all,” warns Pauly. “That means data must be handled in ways that can create personalised insurance offers, while guaranteeing the principle of mutualisation specific to the industry.”
New mobility solutions for customers could trigger other changes in the insurance market, illustrated by the development of autonomous vehicles. “As autonomous driving shifts the responsibility from driver to software, insurers will have to respond by clarifying the legal scope of the responsibility and ensuring they can capture and act on new data sources,” warns Pauly. “If autonomous driving takes off then it should result in fewer claims and this could trigger further changes in the wider insurance market.”
Meeting the new challenge of sustainability
As the entire mobility ecosystem searches for ways to become more sustainable, data-assisted solutions are increasingly necessary. Whether it’s ‘mobility as a service’ applications that help passengers choose the greenest modes of urban transport, like ride pooling and car sharing, or airlines using assisted take-off to reduce a plane’s carbon footprint, solutions are increasingly available in the market.
That matches with regulator appetite to see emissions fall: the EU has already set targets for its members, and other countries are following suit. In November 2020 the UK announced its intention to mandate climate disclosure for all large companies (including mobility businesses) by 2025.
In our recent article, Michael Rofman, Partner, Mazars advises mobility manufacturers to explore what decarbonisation opportunities could reside in their smart buildings and car fleets.
Directing the data deluge
As more mobility data is being created, teams should consider smarter storage and the use of innovative datasets to avoid a deluge.
1. Storage and management. “While databases and enterprise resource planning systems are primarily used for this,” Pal advises, “there is also growing demand for Big Data and data lakes - vast pools of raw data - for which a purpose has not yet been defined.” (‘Data lakes’ contrast with ‘data warehouses’ – the latter being a repository of data which has already been filtered, structured and processed with a specific purpose in mind.) Mobility businesses could seek to maximise the advantages of data lakes, which can provide a fertile source for data scientists looking for fresh innovation.
2. Create and use innovative datasets. As cities move towards integrating urban transport networks (see: ‘Bundling in the city: integrating urban transport services’) data is likely to be created about passengers’ full journeys. In cities, this data can be used to build more, and improved, integrated transport options.
There is no doubt that collecting data effectively means smarter, safer mobility options for businesses and passengers alike. To avoid facing an unhelpful data deluge, mobility firms need to channel this information into (and out of) their predictive maintenance and supply chain management operations in a manageable way. Meanwhile, they have to keep an eye on the customer experience, which is increasingly tied up with sustainability concerns and the consequences of wider market innovation. Those that do it all will set themselves up for a flying start to 2021 and beyond.