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The zettabyte revolution may be the driver of the next big innovation for the automotive industry as intelligent cars learn how to communicate with individuals, enterprises, and the devices around them.

First, however, automotive companies must develop a comprehensive Big Data strategy that can capture, analyze, and interpret all those zettabytes,

according to the authors of a recent article on in 360° – the Business Transformation Journal. The article, entitled “Gaining Traction,” says that with such a strategy, organizations can expect opportunities for differentiation, growth, and innovation that revolutionizes the core of existing business models.

To help understand what’s involved in developing a Big Data strategy, the authors interviewed the management of leading companies in the Deutscher Aktien Index (DAX) who have undertaken Big Data projects. Summarizing these conversations, the authors created the Big Data Chain – or as series of proven best practices – that includes the following key process steps aimed at reducing the complexity of a Big Data initiative.

  • Identify use cases. According to the article, this can be one of the most challenging aspects of any Big Data project and it requires creativity, business insights, and a deep understanding of what’s possible technologically. One way to tackle this is with the Design Thinking methodology, which merges what is desirable from a human point of view with what is technologically and economically feasible.
  • Develop a portfolio of initiatives. In successful Big Data implementations, use cases are prioritized; then a Big Data roadmap can be developed, along with a lean cost-benefit analysis for identifying the monetary and process benefits of each use case.
  • Implement by test and learn approach. Big Data projects typically require a specific implementation approach because of their nature and complexity. The article recommends an agile approach that will help companies achieve a few quick successes to support the development of a longer-term strategic approach.
  • Scale to success. Using the agile approach suggested in the above step, companies can then launch a few smaller projects in quick succession before expanding to a broader scope of projects. This helps reduce acceptance barriers and ensures a smoother commitment process by key stakeholders.

Be prepared for challenges along the way

No project of this size and nature would be without challenges. The authors share five critical factors that will help create a blueprint for success in a Big Data strategy, which include:

  1. Build a technological foundation to support the complexity of Big Data
  2. Reduce barriers to adoption of Big Data throughout a company
  3. Find (and retain) people with Big Data skills
  4. Ensure the quality of the data to be used in the initiatives
  5. Develop data privacy policies that align with industry and government regulations

As automotive companies reassess their business models, the insights here will be critical in their efforts to become a competitive leader in the industry. Yes, there will be pitfalls and challenge along the way, but those that can put a successful, well-orchestrated Big Data strategy together will have a leading edge.

To gain more insights on this topic, access the full article on page 42 of Issue 10 of 360° – the Business Transformation Journal. This publication is produced by the Business Transformation Academy, a thought leadership network devoted to providing cutting-edge insights on innovation and business transformation. For more business transformation articles on the SAP Community Network, please visit the 360° – the Business Transformation Journal library.