Modernizing the Automotive Industry: Creating a Seamless Customer Experience

The automotive industry generates massive amounts of data; and the amount of this data will continue to increase as autonomous and connected vehicles collect real-time data about customer habits and preferences. Turning this data into relevant insights depends on a company’s approach to innovation.

Compared to a phone application, a software malfunction of the connected vehicle can have dangerous consequences for driving safety. Therefore, automotive manufacturing and innovation cycles have to become interconnected and pass many quality assurance checks before they can be sold. But as customers adjust to rapidly changing digital technologies and the market continues to evolve, automakers and OEMs need to shorten these cycles without compromising safety.

Digital twins, a virtual analogue of a physical car’s software and mechanical and electrical components that can carry real-time inspection data, maintenance history, warranty and defect data, are one of many emerging technologies that can help fill this gap, says Uvarova. .

Driving the continuous improvement of products and services means that working methodologies must also integrate the technology used to innovate modern software-defined vehicles. Uvarova notes that the agile working methodology, which manages projects through iterative stages involving cross-departmental collaboration and a continuous improvement feedback loop, would align with modern innovation practices and serve OEMs well.

“To ensure the support of innovation and the market introduction of state-of-the-art and next-generation software-defined vehicles,” says Uvarova, “many departments have to work together and they have to work together very quickly, indeed, in an agile way. ”

What traditional OEMs often lack is cross-departmental collaboration as many processes continue to work top-down and are confined to silos.

“Many great innovations are born out of cross-pollination, collaboration, synergies between very different departments of the same company, sometimes even partnerships,” says Uvarova.

Data silos, where isolated processes and data streams cannot be easily shared across departments and operations steps, often lead to inefficiencies and duplication of work. Historically, Sayer says, many industries, including the automotive industry, have excelled working in these silos. But working with agility, building connected products, and getting the most out of the data it produces requires collaboration and data sharing.