How is big data and analytics helping the automotive industry?

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A look at some brand-new degrees of opportunities in the automotive industry, arising from the adoption of big data and analytics By integrating big data and advanced analytics, automotive firms can derive better efficiency and deliver elevated customer experiences to realize better business gains and profitability in the long run. Turning over a new leaf in its ever-growing possibilities of applications, big data and advanced analytics is fast finding favour with businesses in the manufacturing industry. From enhancing manufacturing efficiency to streamlining supply chain partners and managing inventory to delivering superior customer experiences, companies today are using big data and analytics to uncover future trends and extract insightful information in ways previously impossible. Let’s look at some brand-new degrees of opportunities in the automotive industry, arising from the adoption of big data and analytics: 1) Telematics and OBDs Systems: Combining the prowess of telecom and informatics, the use of Telematics systems is revolutionizing the management of warranty claims in the automobile industry. Telematics data can help companies effectively analyse warranty claims and optimize the cost associated with the entire cycle of warranty management. These systems can be combined with onboard diagnostics (OBDs) to further make the tracking of vehicles and identification of potential faults more efficient and cost-effective. The data supplied by both telematics and OBDs can be utilised in several different manners and can also benefit allied functional departments by uncovering futuristic trends in their own respective fields. In fact, the advanced levels of Telematics and OBDs Systems go one step further and offer nearly real-time information related to almost important parameters associated with vehicles and their mobility. Whether it is the health of the engine, tyre pressure, or fuel-efficiency, everything can be tracked, monitored, and plotted on the computerized map and insightful observations can be deduced with the help of big data analytics. The information can be then utilised to plan, implement, and control important strategic decisions by delivering superior customer experiences. 2) Driving Dynamics: By constantly monitoring, tracking, and analysing behavioural patterns, big data analytics can prove instrumental in fostering better and safe driving habits among drivers. The regular exchange of feedback to drivers on how to inculcate best driving practices in their routines can also prove a game changer in changing the dubious status of our country as the world’s leading nation grossing the highest number of road fatalities. The promotion of safe and secure driving practices can also help in extracting more efficiency, thereby bringing a lot of cost savings for drivers and fleet owners. The insights from the analysis can also be used by legislators to make a review and assessment of the present policies and come up with a more comprehensive framework to cover all participants in the transportation and mobility ecosystem. These steps in terms of policy reviews and updating will also help the government to achieve its ambitious objective of reducing road fatalities and inculcating a sense of responsible driving among stakeholders. 3) Predictive Maintenance: The use of big data analytics can help firms to predict system/ machine failures so that maintenance operations can be carried out in advance to avoid potential failures in future. Not only predictive maintenance helps in saving organisations from critically damaging failures but also extends the values of assets by reducing the chances of incurring high costs associated with reactive maintenance. 4) Personalized Insurance Contracts: The use of big data analytics helps in the collection, assimilation, and analysis of vehicle data on a range of different variables. Insurance companies can easily use the insights to personalize insurance contracts and offer users policies based upon their driving patterns, use frequency, safety records etc. This personalization can help companies effectively reach potential customers with the best offers, prices, and terms and conditions so that both seller and buyer get benefitted from transactions. 5) Roadside Assistance leveraging Vehicle Telematics data: The collection, analysis, and maintenance of vehicles’ data can prove instrumental in offering near real-time assistance to distress signals and calls from broken-down vehicles. Using big data analytics can help process, analyze, and interpret signals emanating from sensors and help in optimising the dispatch of rescue vehicles to minimize further damage and cost associated with mechanical, electrical, or any other type of failures associated with vehicles. In fact, offering accurate analysis in case of a vehicle breakdown can also prove helpful in saving lives by offering first-aid help to distressed people on time. 6) Better Fleet Management: Big data analytics can help to make operations of fleet management better in a range of different ways. From efficient tracking of the vehicles to accurately predicting their average life and delivering enriched customer experiences to monitoring the behaviours of drivers, the application prospects of big data analytics in ensuring efficient and effective fleet management are too many to count. There is hardly any doubt about the transformative potential of big data and advanced analytics for the automobile industry. Big data and analytics have the potential to help the automotive industry become more sustainable by making available equitable benefits to all industry stakeholders. The adoption of big data analytics into the business model will have some financial implications; but the top management and shareholders of the companies need to view this as an investment that has the potential to yield significant returns in the foreseeable future. The article was originally published in Manufacturing Today
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