Analytics On the Road – How Data Is Changing Driving as We Know It
Technologies such as Big Data, Cloud, Artificial Intelligence, IoT have made the shift from being interesting concepts to ubiquitous business features. This rate of technological change is transforming how businesses operate and are opening up new business opportunities. The automotive industry is no different. Technology has brought us to a new frontier where concepts like the smart car/driverless car have become a tangible reality. As we reach that point where lines dividing reality from fiction continue to blur, the automotive industry is gearing up for an exciting future ahead.
It is expected that there will be over 10 million self-driving cars that will be hitting the road by 2020. It is also estimated that we will have around 250 million smart cars on the road by the same timeframe. Automotive companies like Tesla, Mercedes, and BMW have jumped on the technology wave and have already introduced several connected car features in their existing vehicle range. Daimler Trucks launched the 18-wheel, fully autonomous truck that has the capability to go on the auto-pilot mode under certain conditions. Along with companies like Google, who has been the front-runner in the driverless car project, you have Uber testing out self-driving vehicles.
But what drives these driverless/ connected/smart cars? The answer lies in analytics.
Big Data to improve Customer Experience
Customer experience takes top priority today. We are now used to a connected ecosystem with our devices becoming increasingly interconnected. Our phones, tablets, laptops, and virtual assistants are now capable of sharing real-time information for better customer experience. The Connected Car also aims to improve the customer experience where big data and analytics play a crucial role. Even the driverless car experience, though operating on sensors, is being driven by data generated by these sensors. As the volume of data in this connected ecosystem keeps increasing, auto manufacturers have to leverage analytics to not only improve vehicle health but the customer experience as well. It is with the help of analytics that auto manufacturers such as Mercedes, Toyota, Ford, BMW, Hyundai are capably releasing features such as virtual assistants for personalized infotainment experiences, enabling vehicle safety check features, organizing better maintenance schedules, customized dashboards, automated maintenance setups, hard breaking and speeding alerts, automatic collision notifications…the list goes on.
Clearer insights for design and production
As the personalization tsunami hits us, big data and analytics are giving auto companies the additional bandwidth to design automobiles that are safe and personalized. Using data, automotive companies are relating real-world driving experiences to understand usage preferences, factors governing performance, safety parameters such as battery life, fuel efficiency, and the gaps impeding vehicle performance, etc. – all this data is helping them gain better insights to improve the automotive design and meet the customer demands.
Data analytics is moving beyond the capacity of an able diagnostician and is helping automobile industries develop the quality and reliability of the cars, accelerate innovation, and understand how the customers are using these cars to drive this wave of innovation using complementary technologies such as IoT and AI. Analytics is providing quantified insights into these organizations and is helping them with inputs that contribute to making the assembly line more efficient, increase operational efficiency and factor in continuous improvement cycles to deliver better automobiles.
Better predictive maintenance
Predictive maintenance is one of the most intelligent uses of data analytics in this new age automotive ecosystem. Leveraging predictive analytics, automotive companies can identify potential maintenance issues before they occur. Predictive analytics brings the capability to identify potential performance anomalies using aggregated data from numerous vehicles that could have reported a seemingly insignificant problem when viewed in isolation. Predictive analytics can access and analyze large and complex data sets, and ensure that the connected car spends more time on the roads and less in the repair shops.
Improved supply chain
With greater visibility into the supply chain, big data helps auto manufacturers improve the manner in which they respond to customer demands and evaluate supply chain risk. With analytics, these organizations can compare costs, reliability and the quality of the several components that make the connected car work. Armed with this information, they can procure the best fits for the automobile. Not only does this data help these organizations discover and manage supplier relationships more effectively, it also gives them insights into how the customers interact with the company using different channels, and be in a position to better predict customer needs.
Greater automobile safety and security
Analytics using data generated from sensors, car-to-car connectivity, and predictive analytics models can take automobile safety and security to the next level where collisions will be a thing of the past. Nissan, for example, has a predictive collision avoidance system that utilizes the data generated from sensors on the front of the vehicle, analyzes the speed and distance to the vehicle traveling ahead and preceding it and sends out a visual alert and audible signal to the driver. A signal also simultaneously locks the seat belts in case of an impact. These predictive collision avoidance systems will become even more effective as we add more data points based on the driving behavior of the user.
Much like any other software system, connected cars and smart cars are also susceptible to cyber threats. In order to protect these systems, automotive companies have to stay a step ahead of these cyber criminals and detect a cyber attack before it occurs. As predictive analytics can identify anomalies and patterns with dexterity, it helps in identifying behaviors or a combination of behaviors that are inconsistent with the behavior of an authentic user to outwit these attackers.
Yes, our driving experience is changing and is at the cusp of a complete overhaul where reality will mimic science fiction movies. With a change in customer preferences, rapid technology adoption, and increasing competition in shifting market dynamics, automotive companies have to leverage the power of data and analytics to remain ahead of the curve.