Unlocking Potential in a Changing Automotive Market: Part Three

Fostering the Essential Data Teams, Roles, and Culture

For automotive players, becoming a truly data-driven company is a transformative journey that requires more than just advanced technology. It demands organizational alignment, structured data management processes, and a strong cultural shift.  

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This process requires the setup of data management processes and tools to generate autonomously data-driven opportunities and extract value from data. The involvement of the entire organization is also needed, starting with an understanding of all the necessary responsibilities and data roles.

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The working assumptions companies should be leveraging before diving into the teams are illustrated below, and are built on a philosophy of starting small, absorbing target data roles within the current organization, and finally, enabling involvement across the whole of the business.
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Building Effective Data Teams

The foundation of a data-driven organization begins with assembling three key data teams:
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Each automotive company must identify specific data roles within these teams based on their backlog of use cases, target architecture, and a strategic approach to insourcing and outsourcing.  
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For every data role, a mix of “outsourcing first, insourcing later” can be adopted: companies can adopt a flexible model, outsourcing certain roles initially and transitioning to in-house capabilities as their data maturity grows.
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Fostering a Data-Driven Culture

To truly leverage data across the organization, automotive companies must go beyond technical expertise and nurture a culture that values and utilizes data effectively. This transformation can be guided by four key axes:

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1. Awareness of Data Potential and Strategy: Employees must understand how data can shape their operations and contribute to the company’s objectives. Standardized processes for working with data should be established to minimize risks and enhance cross-functional collaboration.
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2. Broad and Deep Staff Upskilling: Equip all employees with the confidence to use data tools in their roles. Provide reskilling opportunities for those aiming to take on specialized data roles, from data stewards to scientists.
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3. Ethical and Compliant Data Usage: Ensure all employees are trained in ethical guidelines, particularly regarding personal data use. Teams developing data use cases should adhere to strict compliance standards.
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4. Definitions and Measures of Data-Driven Success: Define quality standards and establish KPIs for each function or team, measuring the impact of data initiatives and reporting progress transparently.
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Initiatives for Embedding a Data-Driven Culture

To bring these cultural shifts to life, automotive companies should implement practical initiatives that promote data literacy and engagement.  

Building a workforce equipped for our data-driven future means companies must first map data skill gaps within their organization. Identifying areas in which employees need further development ensures that training is targeted and effective. This foundational step helps employees gain confidence in using data tools and translating insights into actionable results, fostering a culture of data fluency across teams.

Once skill gaps are identified, organizations can implement a range of initiatives to address them. Continuous learning opportunities, such as self-paced online courses and workshops, can give employees flexible options to develop their foundational or advanced data skills. Collaboration with external institutions can further enhance learning by offering scholarships, hosting project-based exams, or creating internship programs. To inspire and engage employees, immersive experiences like visits to innovation centers or industry fairs can showcase cutting-edge data applications and highlight the transformative potential of data-driven practices.