How Predictive Analytics Helps Auto OEMs, Dealerships and Consumers

The automotive industry is rapidly transforming with new technology, and predictive analytics is being utilized to find trends and make predictions about future events using techniques like data mining, data modeling, machine learning and artificial intelligence (AI).

As our vehicles become more and more connected and advanced, the way we build, sell and use cars is changing—and predictive analytics have become a big part of that shift. Below are some of the benefits predictive analytics will bring to the automotive industry.

Benefits for OEMs

For OEMs, predictive analytics are a powerful tool for optimizing forecasting, efficiency and performance.

Smart manufacturing systems that integrate machine learning can increase production capacity by 20%, lower material consumption by 4%, and improve yield rates at the machine, production cell and plant levels. Data monitoring can provide manufacturers with the scale to manage and increase Overall Equipment Effectiveness and preventative maintenance of equipment.

Data mining software that tracks and traces data will also help guard against expensive recalls. This could significantly reduce the $45-50 billion the industry spends on recalls and warranty claims annually. Teradata Corp, a data analytics company, is claiming that their software can cut warranty costs by 10-13%, administrative costs by 20-25%, and compliance costs by 30%.

Looking towards the future, autonomous cars in development will benefit from predictive analytics—sending and receiving data about locations, local driving conditions and other factors. Manufacturers are also using machine learning to make the auto pilot program on autonomous models learn to become a better driver.

Benefits for Dealerships

For dealerships, predictive analytics will help sales teams close the deal and promote preventative maintenance.

Data mining can help optimize pricing against the competition and even provide insights into strategies that will help accelerate the sales process. Software like AutoAlert’s AlertMiner finds the most profitable opportunities based on critical customer info, then provides the deal that customers will be most receptive to. Sales teams can even edit and customize deals based on their customers’ unique needs.

For maintenance and repairs, predictive data algorithms can cross check information from thousands of vehicles to identify trends, which can help prevent expensive recalls. Predictive data can also drive preventative maintenance by looking at warranty repairs or reoccurring problems to identify what needs to be repaired or replaced before it ever becomes a problem.

Benefits for Consumers

For consumers, predictive analytics can help with saving money and staying safe on the road.

Preventative maintenance data from predictive analytics has obvious benefits to consumers, as it helps reduce the need for expensive emergency repairs and reduces the likelihood that they’ll have to deal with a recall situation.

Additionally, as the autonomous car becomes a reality, AI technology will create a better driving experience and enhance safety. Further, usage-based car insurance could help consumers save money by tracking data on how, when and where they drive, then offering competitive quotes to ‘safe drivers’.

Until all this technology is fully ready to hit the market, car buyers can invest in a vehicle service contract in order to help them afford unexpected repairs after the manufacturing warranty expires. To help them add this F&I product, dealerships can offer buyers a no-interest or low-interest installment payment plan through providers like Budco Financial.

For more updates on the automotive market and insights for OEMs, dealerships and consumers, follow Budco Financial on LinkedIn and Twitter.

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