Data Analytics in the Automotive Industry

automotive data analytics

Feedback from automated vehicles and internet connected cars is a highly visible and intriguing application of analytics from the automotive industry. However, this industry has been collecting information of all kinds for many years. Everything from production numbers, sales, customer service feedback, and inventory. The automotive industry tracks a wide variety of data that informs their day to day decision making and their long term planning. Legacy analytics have typically made this process time consuming and difficult, but advances in data analysis have created opportunities for efficiency and accuracy throughout multiple data sets.

Every facet of the automotive industry thrives on data, vehicle performance information, product development information, and marketing statistics are just more pieces that drive the automotive industry forward. What if there was a way to merge all the relevant information and create a complete overview of every common area, revealing how the different operational aspects affect one another?  Advanced AI powered analytics can provide that crucial element to data feedback from the automotive industry. By merging structured data, production time, inventory count, parts prices, labor times, and more with unstructured data such as customer surveys, online feedback, and social media, the automotive industry can create data driven decisions based on real data. Artificial intelligence and machine learning can process millions of disparate pieces of information in minutes to provide actionable insight into company performance.

Advanced data analytics with artificial intelligence augments human intuition and creativity. It frees up the analyst’s time by automatically cleaning, organizing, and processing information to provide completely unbiased results. This reveals unknown topics and trends that a company may not have been looking for, allowing them to make adjustments quickly and address issues before they become major problems. Visualizations allow for deep dives into the data layers and create a common language that lets everyone from analysts to valued decision makers understand the data. Advanced analytics with artificial intelligence make data analysis faster and more efficient, allowing industries such as automotive to make better data driven decisions and move their companies forward.

Tim Roberson