Leading automotive manufacturers will measure progress based on data insights

2020 was a pivotal year for automotive manufacturers. As the year began, they had to balance the challenges of digitally transforming their IT and operational technology (OT) approaches with the need to respond to many factors. Considerations included the supplier, ecosystem, and environmental pressures created by the connected, autonomous, shared, and electrified (CASE) vehicle revolution. If this weren't challenging enough, automotive manufacturers had to react to the emergence of the COVID-19 pandemic at the end of the first quarter. This confluence of dynamics created an all-hands-on-deck contingency scenario that forced manufacturers to juggle extinguishing the sudden pandemic flames with other in-flight and future investments. Yet, amid this perfect storm, IDC saw a real divergence that separated the effectiveness and response of leading and lagging manufacturers. In particular, IDC saw leading organizations harnessing data, including breaking down data silos and effectively using data across the entire supply chain as a key differentiator.

To track and measure the progress of an organization's recovery, IDC developed a five-stage model aligning COVID-19 economic impacts and the organization’s technology investment priorities. This model includes the following linked stages:

• Stage 1 — COVID crisis. Organizations react to the immediate impact of the crisis, as well as business and operational restoration. Technology investments are minimal as organizations focus on enacting emergency procedures and contingency plans.
• Stage 2 — Economic slowdown. Organizations assess their unknown future by focusing on technology investments that can deliver a tangible, near-term (12 months or less) return on investment.
• Stage 3 — Recession. Organizations encounter their worst-case economic impacts. They use this "bottom" to develop strategies around technology and process investment that will stimulate their business' recovery.
• Stage 4 — Return to growth. Organizations begin to see more economic predictability, freeing them to invest in initiatives with a longer time horizon. This includes investing in new capabilities, partnerships, and business models built around the creation, distribution, and use of data.
• Stage 5 — New normal. Organizations see their economic improvements stabilize, largely due to the technology, process, and organizational changes in the prior stages. These organizations, having emerged more resilient and agile, continue strategic investments, including prioritizing their role in the digital economy where ideas, business models, and partnerships leverage the analysis and exchange of data.

• Understanding the need to unlock data as a tool. Leading organizations understand that data needs to be a foundational asset used across their business. This includes investing in cloud-centric, data-aware technologies that help enable data visibility, mobility, and unification.
• Committing to digitally transform the organization. Leading organizations understand that digital transformation requires real investment and change. Some organizations had bought in before the pandemic and were able to improve their initial response, while others acted decisively to accelerate their transformation.
• Embracing the flexibility of the digital economy. Leading organizations understand that data not only improves the effectiveness of decision making and enables operational efficiencies, it also opens doors to remove constraints that limit business models and customer engagement.
• Realizing that innovation begets innovation. Leading organizations that enable the use of data to innovate and flatten their business understand that once the foundation is built they can move even faster and be even bolder.

• Ensure that your Industry 4.0 strategy encompasses the four pillars of asset transformation, intelligent edge, operational excellence, and cultural convergence. This top-down, inclusive way of thinking enables  organizations to think through the technologies, people, and processes needed to build a strong data foundation and maximize business value.
• Build a broad coalition of organizational representatives to increase the reach and use of data and tooling. Although IT is largely responsible for technology modernization initiatives, the more challenging part of the transformation is people and process driven. Engaging and empowering a broad constituent base early on pays dividends in this area.
• Leverage a comprehensive data fabric to connect all potential endpoints of your data network. This fabric should encompass internal and external endpoints, including the factory floor, multiple edge processing locations, internal stakeholder organizations, connected vehicles, and trusted third-party suppliers and partners.
• Implement a comprehensive strategy to manage and govern data. This strategy needs to include policy-driven data management that satisfies security, cost, access, and scaling requirements.