To realize the vision of the factory of the future, auto manufacturers must address topics related to three enablers: strategy and leadership, employee skills, and IT infrastructure. Companies must make the factory-of-the-future strategy an integral part of their corporate strategy and adapt their leadership styles to new ways of working. Manufacturers also must focus on building a workforce with the new set of skills required for performing technology-centered production tasks. Finally, companies must install IT infrastructure that supports connectivity throughout the value chain while ensuring the security of data.
Strategy and Leadership
Manufacturers must include their strategy for implementing the factory of the future as an element of their overall company strategy and put in place organizational structures that promote rigorous governance. Of automotive respondents, 35% see issues relating to the organization as a major challenge. Companies must address three organizational requirements:
- The Strategy and Roadmap. The strategy for implementing the factory of the future must be anchored in the overarching company strategy. Approximately one-third of automotive respondents see the factory-of-the-future strategy as a major challenge. Many companies lack a strategic vision to guide a structured implementation process.
- Governance. To realize their vision, manufacturers must put in place organizational structures (such as clear responsibilities for steering and coordinating all efforts related to the factory of the future) and define the processes required to ensure that their factory-of-the-future strategy is translated into implementation actions. Approximately one-third of automotive respondents see governance as a major challenge, with the main issues being a lack of communication among departments, unclear responsibilities, and insufficient management commitment.
- New Leadership Styles. Automotive respondents say that an advisory leadership style will be more important in the factory of the future, while an authoritarian style will be less relevant. Transformational and group-oriented leadership will also gain in importance.
Although the greater use of robotics and computerization will reduce the number of jobs in assembly and production, the number of manufacturing jobs requiring skills in IT and data science will increase. Approximately 50% of automotive respondents said that they expect to employ more workers with IT skills, and approximately 25% expect the number of IT employees will increase by more than 10%. (See Exhibit 4.) Approximately one-third of respondents expect to need more workers with competencies in maintenance and quality control, while about 25% expect to need people with production planning and logistics skills. These additional staffing resources will be needed to respond to the insights provided by the trove of new data available.
Recognizing that they need to adapt their workforce to the factory of the future, 38% of automotive respondents see employee skills as a major (“big” or “huge”) challenge. (See Exhibit 5.) To ensure that their workforce evolves appropriately, companies must focus on building technical and social competencies. They also must implement new approaches to qualify their employees and ensure that the right skills are in place.
- Technical Competencies. Manufacturers need to strongly focus on technical skills and backgrounds when training or hiring employees. Automotive respondents expect that capabilities in IT, electronics, and “mechatronics” (combined mechanical, electronic, and IT skills) will be more relevant in 2030, while purely mechanical skills will be less relevant.
- Social Competencies. The pace of change in the factory of the future means that workers must be willing and able to continuously learn new skills. Rather than primarily performing repetitive tasks, they will often be called upon to solve problems as members of interdisciplinary teams. More than 90% of automotive respondents see each of the four key social competencies—learning capacity, teamwork, responsibility, and problem solving—as relevant for 2030.
- Training and Qualification. Manufacturers cannot expect workers to build the necessary technical and social competencies on their own. To successfully transition to the factory of the future, manufacturers need to develop an approach to training and qualifying workers. Most automotive respondents in our survey (53%) cited further training of employees as the main route to building the required skills. Significantly fewer cited hiring new employees (29%) or reeducation (18%).
- Technology-Based Learning. The new generation of workers wants training options that enable flexibility in terms of where and when instruction is available. Self-learning programs on mobile devices, not slide presentations in a classroom, are the preferred way to obtain information. Automotive respondents appear to recognize the need to offer innovative, technology-based learning. They see learning by doing, e-learning, and immersive training using virtual environments as more relevant in 2030. They see traditional training courses as less relevant in 2030.
One-third of automotive respondents see IT infrastructure as a major challenge. Two related requirements must be addressed:
- Cloud and Connectivity. Manufacturers need plant-wide connectivity infrastructure (such as a wireless local area network) and technology to capture and store production data. Respondents said that using private cloud services as a central platform for data storage and software as a service will increase in importance, but they are skeptical about using public cloud services. The two main challenges for improving plant-wide connectivity are a lack of network standards and poor network infrastructure.
- Data Security. Enhanced supply chain connectivity is essential, but safeguards are required to ensure the secure exchange of data. Indeed, data security is a major concern of automotive companies. More than 40% of automotive respondents see data security as a major challenge, and about 30% cited concerns over the uncertainty of data ownership.