Chief Scientific Officer Simon Wilson discusses using data to reduce CaaS costs

Using Data to Reduce Car-As-A-Service Costs

Second in a five-part blog series on the part that analytics plays in shared mobility solutions.

By Simon Wilson, Chief Scientific Officer, GTS, and Professor of Statistics at Trinity College Dublin.

Though the Car-as-a-Service (CaaS) market is growing fast, the sector is still far from mature. OEMs, dealerships, and new entrants must explore different go-to-market strategies as they try to match services to evolving consumer demand. They know there’s an appetite for alternatives to car ownership, but ensuring profitability from a CaaS car fleet can be tricky.

The use of data will be integral to helping control costs across the many CaaS business models and use cases. Fundamental to all of them is keeping cars on the road, which means minimizing technical faults and repairs that make them unavailable. There are a number of data-driven strategies to avoid such costly disruption.

Preventative Maintenance

Remotely measuring the performance of technological equipment is nothing new – telemetry has been around for centuries – but advances in sensors, connectivity, and the ability to process collected data is transforming many industries, from utilities to manufacturing. One of the developments that delivers many benefits to CaaS is preventative maintenance.

The use of car telematics has been growing steadily for 25 years, but what’s changed in cars is the proliferation of in-vehicle sensors that surface data about every aspect of the vehicle, enabling preventative maintenance. By analysing engine data over time, it’s possible to detect and fix serious issues before they take the car off the road. It makes the business proactive, rather than reactive.

A/B Testing

With more data-fuelled insights comes more challenges. Just because the data tells you something is going wrong, the car doesn’t have to go into the garage. Depending on the issue and cost of repair, it might make sense to keep the car running until it breaks down. Conversely, investing in new vehicles may be more cost-effective than keeping an aging fleet on the road. It’s a trade-off between over and under-maintaining vehicles, working out where the sweet spot is for acting on preventative maintenance alerts.

We recommend A/B testing, comparing multiple versions of a single variable over time to arrive at the best course of action. If you are running CaaS across multiple locations with a range of vehicles, try different maintenance strategies with different fleets, then analyze which works best for the bottom line.

Accidents and Fraud

CaaS companies will often pick up the bill for minor bumps and damage to their vehicles because car insurance claims increase the premium, but the cumulative effect can impact profitability. Similar to insurance companies utilizing usage-based assessments, CaaS companies can leverage driver behavior data (such as harsh acceleration, abrupt braking, etc.) to pinpoint potential risks related to vehicle collisions or damage. Appropriate actions can then be taken if necessary.

Another approach is to use payment data to identify fraud. By analyzing various data points and indicators, it becomes possible to pinpoint users with the highest potential for fraudulent activities. For instance, individuals with over 10 credit cards linked to their account might warrant further investigation.

Over-Optimisation Risks

Another risk worth noting for CaaS providers is that the efficiency achieved through data insights can also lead to over-optimization of the business. The CaaS system must consistently exhibit flexibility to strike a balance between revenue generation and the longer-term value of customer retention and customer proposition. While having a car booked for 16 hours a day might appear highly profitable, under-supplying cars for a particular area (to increase vehicle utilization) can result in customers being unable to access vehicles when they need them. This inconvenience may prompt customers to stop using the service, ultimately causing financial losses. The key to success lies in leveraging data and insights from a flexible CaaS system to effectively manage profitability while maintaining customer satisfaction.

Next: Using data to increase revenue