The automotive sector generates large amounts of data; and the amount of this data will only 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 the company’s approach to innovation.
Compared to a phone app, malfunctioning software in a connected vehicle can have dangerous safety consequences while driving. Therefore, the production and innovation cycles of the car must be interconnected and pass many quality assurance checks before it can be sold. But as customers become accustomed to rapidly evolving digital technologies and the market continues to evolve, automakers and OEMs must shorten these cycles without compromising safety and security.
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 to bridge this gap, says Uvarova. .
Driving continuous improvement in products and services means that work methodologies must also complement the technology used to innovate modern software-defined vehicles. Uvarova notes that agile working methodology, which manages projects through iterative phases that involve cross-departmental collaboration and a continuous improvement feedback loop, would align with modern innovation practices and serve OEMs well.
“In order to ensure that we support innovation and bring to market state-of-the-art software-defined vehicles,” says Uvarova, “a lot of departments have to work together and they have to work together very quickly, in fact, in an agile way”.
What traditional OEMs often lack is cross-departmental collaboration, as many processes continue to operate top-down and are confined to silos.
“Many great innovations are born from cross-pollination, from collaboration, from synergies between very different departments of the same company, also sometimes from partnerships,” says Uvarova.
Data silos, where insular processes and data flows cannot be easily shared between departments and phases of operation, often cause inefficiencies and duplication of work. Historically, Sayer says, many industries, including automotive, have excelled at 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.
