Automotive industries generate huge amounts of data. and the amount of this data will only continue to grow as autonomous and connected cars gather real-time data on customer habits and preferences. Turning this data into relevant insights depends on a company’s approach to innovation.
Compared to a phone app, a malfunction in connected car software can have dangerous safety implications while driving. Therefore, the automotive manufacturing and innovation cycles must be interconnected and pass multiple quality assurance checkpoints before they are sold. But as customers get used to rapidly evolving digital technologies and the market continues to evolve, automakers and OEMs must shorten those cycles without compromising safety and security.
Digital twins, a virtual analog of a physical car’s software and mechanical and electrical components that can transmit inspection data, service history, warranty data and defects in real time, are one of many emerging technologies that can help bridge this gap, Uvarova says. . .
Continuous improvement of products and services means that work methodologies must also complement the technology used to innovate modern software-defined machines. Uvarova notes that an agile working methodology that manages projects through iterative phases that include cross-departmental collaboration and a continuous improvement feedback loop will align with modern innovation practices and serve OEMs well.
“To ensure that we’re supporting innovation and bringing the newest, next-generation software machines to market,” says Uvarova, “a lot of departments have to work together, and they have to work together very quickly, really in an agile way.”
What traditional OEMs often lack is cross-departmental collaboration, as many processes continue to operate top-down and are constrained by silos.
“A lot of great innovations, they’re born out of cross-pollination, collaboration, synergy between many different divisions of the same company, sometimes partnerships,” says Uvarova.
Data silos, where isolated processes and data flows cannot be easily separated 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, creating connected products, and getting the most out of the data it produces requires collaboration and data sharing.