As industries are facing shifting marketing conditions, globalization, increased competition and new technology they are entering a business environment that is changing at an astonishing pace. One industry that have felt these changes is the automotive industry. With everything from self-driving cars to heightened customer expectation the automotive industry is on the verge of a huge transformation, if not a revolution. The main focus of this transformation is the power of artificial intelligence and big data analytics.
The ability to harness data and to further process and analyze it has not truly been embraced by the automotive industry. But due to this rapid transformation of ecosystem and the influx of new players it has become an inevitability for staying competitive. The huge amount of data that is now available can be daunting, especially for an inexperienced industry such as the automotive. But utilizing it effectively can mean improvements and value creation in a myriad of different fields such as customer-, marketing- and supply chain analytics. And even tough analytics is a powerful tool, applying it correctly and effectively requires knowledge beyond statistics, information technology or operations. Organizations requires capabilities that integrate with multiple functions and teams to fully benefit for analytics.
To know your business is to know your customers. The digital world has changed the way customers research, purchase and manage the upkeep of their products, such as vehicles. Customers have come to expect a consistent personalized experience across all their access channels. There is vast amount of data available for automakers to collect, but the magnitude and complexity also makes it difficult to collect, analyze and act on. Automakers need to holistically understand their customers’ needs and behaviors to develop a clear view of the customer and finally create differentiated and compelling offers throughout the sale and marketing. Knowing the value of different customer segments and using that knowledge to use strategical marketing and customer retention are examples of the potential of data analytics in customer segments. Companies can further use customer data to analyze and improve their marketing management. Combining different data from both internal and external sources related to marketing allows automotive companies to better understand what marketing strategies work and what doesn’t. This will allow for better decision making and cost-effective spending.
Finally, data analytics is a powerful tool for supply chain management. The industry is moving away from the old reactionary management models, and nowhere is this more prominent than at the supply chain level. Data analytics empowers manufacturers and suppliers with proactive management, sensing industry changes around them and localizing and responding to supply chain issues. A typical example of data analytics in action is using product configuration or web interaction allowing companies to anticipate trend changes, such as demand, much earlier. Allowing them to respond to the specific changes accordingly.
Supply chain management is under pressure from a myriad of different forces. Globalizing the company’s operations to take advantage of growing markets, optimization of the manufacturing process and managing regulatory environments are just a few that can be mentioned. But on the positive side there are vast quantities of data that is being stockpiled and awaiting to be processed and utilized. When it comes to using data analytics to manage their supply chain most companies are severely lacking. Even though technology moves fast, most industries and companies are still immature. Quick action now, means you can stay ahead of the curve.