Data refers to figures and facts gathered from various sources. Companies use data mining to pool sets of data from multiple sources, then apply data analysis techniques to process the data and transform it into meaningful information.
The automotive industry produces cars, trucks, and other vehicles. The global automotive industry generates trillions per year, with Statista reporting projections showing 88 million light vehicles will be manufactured in 2023. Producing vehicles involves gathering and analyzing a lot of data. Let’s look at how the automotive industry accesses data and the types of data used to inform operations.
How do automotive companies access and process data?
Data analysts in the automotive industry use data mining and data analytics software to gather data sets. In some cases, analysts use data integration to combine data from various sources physically. Analysts may also use data virtualization software.
When using a data virtualization solution, the data remains at its source. The software can manipulate and analyze data from multiple sources without relocating it, saving time and storage space since the analysts aren’t replicating large data sets. This is a convenient option for large industries that have multiple locations producing site-based data in addition to data about their entire industry.
Data virtualization allows analysts to employ predictive analytics to identify patterns and project outcomes. This software also generates reports about production levels, sales, and other variables affecting operations.
What type of data does the automotive industry analyze?
The automotive industry encompasses multiple businesses. While car manufacturers produce vehicles, other manufacturers produce automotive parts. Marketing experts also develop promotional strategies to sell vehicles, and staff at car dealerships sell vehicles to consumers.
Automobile manufacturers review data to ensure they’re making cost-effective business decisions. Like computer manufacturers, car manufacturers need computer chips. Since the COVID-19 pandemic, a computer chip shortage has impacted these industries, making it challenging to maintain pre-COVID production levels. Consequently, vehicle manufacturers may find themselves evaluating which vehicles use the lowest number of computer chips to maximize their production rate.
Automobile manufacturers use predictive analytics to establish demand levels and consumer trends. Suppose consumer data indicates more buyers are investing in electronic vehicles or fuel-efficient cars with low emission rates. This may prompt manufacturers to prioritize electronic vehicle production while decreasing the production of gas guzzlers, such as sport utility vehicles (SUVs). Manufacturers can also use siloed information to evaluate demand levels in specific regions, which may prompt them to maintain current production levels at some plants while adjusting the focus at other plants.
Automotive part producers use data analysis to determine which vehicle parts are in demand. Part retailers use sales statistics and other data to determine which parts to carry in stores and how many to order. For example, if an analysis shows that most people purchasing the popular trunks want to protect their pinch welds, parts retailers may increase pinch weld guard orders. Pinch weld protectors stabilize a vehicle’s components. A pinch weld refers to welded components near the front of a vehicle connecting the exterior and interior parts. The pinch weld can bend if floor jacks are used without protectors, but adding protectors protects the integrity of the vehicle.
Car manufacturers, parts retailers, and car dealerships can use data analysis to identify the best computer software to secure information and perform tasks. Car show organizers can also use data analysis to determine what software they need to organize events and process registrations.
Automotive businesses can use data analysis to identify the most cost-effective shipping routes and sources for parts or products. Manufacturers and retailers can also use analytics to establish customer satisfaction rates and identify the main complaints with various products, enabling manufacturers to incorporate improvements into subsequent vehicle designs.
The automotive industry is a large industry encompassing many types of businesses and uses data analysis to improve operations, increase revenue, and improve customer satisfaction levels.