Big data analytics is used around the world for a variety of different procedures in all kinds of different enterprises. There are still a lot of individuals out there however, who are not conscious of just how pervasive big data really is. That's why we have been using research studies that relate to industries that everyone knows. Examples of Big Data from real life significantly streamline the processes involved and put the advantages on the table for everyone to see.
And where to look better than in the automotive sector. Car manufacturers have been paragons of innovation for more than a century, continuously pressing themselves and their products forth with fresh technology and new approaches. Today, with battery powered and self-driving vehicles perfectly positioned to completely change our world, we stand at the cusp of another automotive advancement. Big data has of course, played a role in this transition, and will only become more essential as automotive companies use analytics for everything from production optimisation to customer satisfaction improvement.
Manufacturers of cars that use big data analytics
In all manner of different facets of the car production and selling process, big data analytics have been used. While some brands began using analytics sooner than others, the way data is accessed and used is really the growth of technological advances that is turbo-charged. Owing to a number of devices, processing units and other on-board tools that track an enormous volume of information, the modern car gathers an incredible amount of data - traditionally to make it easier to perform repairs or to quickly identify a fault.
However, long-term 'connected vehicles' with internet connectivity will immediately make all this information available to automakers, unlocking a new range of skills such as advanced analytics.
Since big data is collected from the network of sources, it is possible to draw inferences about consumer behaviour, for example to determine if there is a connection between people listening to music and driving through eateries they frequent. These kinds of links can affect the allocation and budgets of advertising resources, and thus the information collected from linked cars is commercially invaluable.
Improving on-road performance and driver experience may be the new era of analytics in the automotive industry, but big data is already used by the world's largest car brands to promote loyalty and retain existing customers for more.
As you generally know, cars do not communicate any human language at all. If they could, they would also be able to provide a ton of information that would be crucial to the network of OEMs, drivers and dealers. Exposure to vehicle information may not be relevant and it is already possible to use diagnostic tools in the garage in such a way, but it can be world-shattering to integrate it with data about the operating environment of a vehicle at a given moment in time. Ever more vehicles have already been equipped with sensors and natively integrated connectivity solutions to gain access to this information. A steady stream of vehicle, motor, driving behaviour and environmental conditions data will be provided by connected cars.
It is no simple task to extract definition from this mass of mixed data produced at incredible speed and volumes. The challenge now is how to better capture, analyse and redistribute these data-in-motion to the relevant receivers, eventually in real-near real-time. But the rewards will be enormous: an interconnected view of the vehicle supplying real-time insight into how the different vehicle systems perform under different driving patterns and weather factors for car manufacturers. Major advantages include the ability to provide timely maintenance services and parts promotions to improve the distributor's network of profitable aftermarket service and product sales, to provide driver assistance by issuing alerts or coaching to achieve maximum fuel economy by determining the correct speeds and RPM range for shifting gears.
But connected cars can also open up new business opportunities for OEMs who as insurance companies or roadside assistance operators, provide integrated vehicle evidence collected to third parties. It can ensure that Terabytes of data and elaborate streaming of data are stored in actual environments and in an economical manner. High-speed analytics can run on the channel in seconds to perform complex algorithms and provide real-time insights directly to the car dashboard and the smartphone app of the driver, tailored to the situation in which the driver is at that precise point or to the various players in the linked value chain.
Fresh opportunities for effective preventive maintenance
In order to minimise this risk, manufacturers generally apply preventive maintenance programmes, which are largely a calendar-based approach that requires equipment to be serviced or replaced at prescribed times or periods of time. Any production disruption is a potential huge loss of revenue to businesses due to loss of production output, repair costs and waste generated in the process. This could include substituting a part for a specified interval of time or number of operations. Conversely, a condition-based management system focuses on the status of the equipment and how it works rather than on a predetermined schedule or length of time.
What companies are able to learn from automobile manufacturers
Not every company now has access to that money or technical development of the largest automotive brands in the world, but that certainly does not mean that there are no good lessons from the achievements of companies. First and above all else, what we can see from the world of auto manufacturing is that, depending on the type of information that can be analysed, it is possible to use data analysis for all sorts of different uses, especially in related industries such as car towing companies and ride-sharing services. The growing ubiquity of the Internet of Things makes it easier than ever to capture information, no matter what your product is and adopting this feature can be crucial to collecting relevant information about customers and improving their experiences.
Secondly, for more than just enhancing your service or product, analytics can be used. During the marketing process, it can also revolutionise the way you treat your clients, moving from a blanket policy to a more customised, individual style that has the possibility to pay enormous dividends - both in acquiring new business and retaining existing customers.