5 Min.

Solving Maintenance Data Handling

HIGHLIGHTS

_ Integrating multiple systems and stakeholders across several companies and territories.

_ In addition to data security, the solution had to consider the performance and scalability requirements needed to consume large volumes of data.

_ The development of the MVP was the first step towards a better customer service experience for drivers.

 

After-sales is an important service and retention mechanic for automakers. Every automotive company worth its salt wants to ensure that they deliver the best possible performance and service with the least amount of friction for its customers, even when things go wrong. 

This is easier said than done. It's frustrating for any customer to experience car trouble (e.g. engine failure, a deflated tyre). It's even more frustrating to resolve the issue. The onus is on them to find a service centre, make an appointment, collect information and make a decision about the repairs required. 

One German automaker decided to use the stream of incoming information from their telematic capable cars to provide a better customer experience when maintenance or repair is required. 
 

GOALS

When approaching Acrontum, the automaker in question had a specific vision and end goal in mind: to provide proactive customer support based on available static vehicle data, as well as the continuous stream of incoming data received from the vehicles (e.g. warnings, malfunctioning behaviours). 

They believed that by analysing the respective check control messages (CCM), warnings could be prioritised and channelled to appropriate service centres via call centre agents in the various respective locations. 

However, implementing and mapping the flow of information from the vehicle to the call centre would be complex. It would involve integrating multiple systems and stakeholders across several companies and territories, each with its own privacy laws and considerations that needed to be taken into account and resolved. 

In addition to data security, the solution also had to consider the performance and scalability requirements that would be needed to consume such large volumes of data. 

Vehicles continuously send data which is filtered and aggregated throughout a series of applications, including telematic messages that reveal maintenance issues as they arise (e.g. flat tyres, engine problems, navigation issues). The goal was to prioritise the Check Control Messages according to the urgency and impact of the maintenance issues. 

Once the issue was categorised, it would be routed to the most appropriate call centre in one of four territories (Germany, United Kingdom, United States or Canada). The call centre agents would take action based on the level of urgency required, e.g. calling the customer and suggesting a solution or providing advice to avoid further damage to the vehicle. For data privacy reasons, the driver would have to opt-in and consent to the service inside the car.

APPROACH

While there a basic concept and architecture were already in place by the time Acrontum began the project, creating a one size fits-all-solution that would operate across different systems and data flows with a large user base was difficult to coordinate. Each system required separate integration. 
Acrontum began by identifying the market needs and refining the initial concept before developing and implementing an MVP in four different markets with four different providers. 

While coordination across the different markets was complex, the architecture had to be simple and scalable as more markets would be added over time. 

RESULTS

The MVP version of the ProActive Customer Care application is able to handle more than 500 messages per second without data loss, even though the expected workload was below five messages per second. 

The architecture consists of a message consumer and message producer. By decoupling the two services, the solution enables greater scalability, i.e. the solution can accommodate growth on the message producing side (e.g. more cars entering the market), as well as on the producer side (e.g. expanding call centres).  The modularised business logic will easily enable future maintainability. The customer will be able to adjust message prioritisation, the volume of incoming messages, and market integrations as they scale the solution. 

CONCLUSION

The development of the MVP was not only the first step towards a better customer service experience for drivers but the first step towards preventative maintenance for cars in the field. Preventative maintenance is a common practice in factories where machines are static. 

However, smart automotive technology, coupled with fast and efficient data streams and handling, like the latest MVP built by Acrontum, may mean automakers will be able to identify when and why cars need maintenance - before the driver breaks down. 


Thanks to Acrontum, automakers are able to provide better service when customers experience the frustration of a vehicle failure. Perhaps one day, they'll avoid breakdowns altogether using the same application.