The mobility industry is rapidly evolving and transforming due to technological advancements. The industry is experiencing a significant shift towards a data-driven approach. Several Original Equipment Manufacturers (OEMs) use data analytics to make informed decisions, optimise operations, and improve the overall customer experience.
Data analytics helps provide better control over raw material procurement processes, near real-time visibility into work-in-progress inventory, and a better understanding of overall spending. By modernising legacy processes and increasing access to business intelligence, it is helping OEMs to enable real-time decision-making.
Ride-sharing services have significantly reduced congestion in major cities by offering more efficient transportation options. According to a report by MIT, ride-sharing services could reduce congestion by a factor of three while still serving the same number of people. Data analytics has played a critical role in achieving this feat.
The development of autonomous vehicles is another exciting and transformative area for the mobility industry. According to a report, 94% of all traffic accidents are caused by human error. Autonomous vehicles could reduce these accidents by the same. Data analytics is crucial in developing autonomous vehicles by providing insights into traffic patterns, road conditions, and driver behaviour.
Data analytics for the mobility industry
Data analytics has revolutionised the mobility industry by providing valuable insights to businesses, enabling them to make data-driven decisions. Here are some of the uses of data analytics in the mobility industry:
Predictive maintenance
Predictive maintenance utilises real-time data from sensors and other sources to predict potential vehicle faults before they occur. The use of data analytics in predictive maintenance has led to a significant reduction in vehicle downtime and maintenance costs. According to a report by MarketsandMarkets, the predictive maintenance market is expected to grow from $4.2 billion (Rs 34,637 crore) in 2021 to $15.9 billion (Rs 131,127 crore) by 2026, at a CAGR of 30.6%.
Operational efficiency
Data analytics can help OEMs to identify and reduce bottlenecks at various stages of the business. By following an efficient data ingestion process and building a single source of truth for the entire organisation, data analytics can help to automate several processes and achieve better efficiency. All these actions can reduce operating costs and provide better control over the business.
Fleet management and optimisation
The usage of analytics is transforming the way companies manage their fleets. By analysing vehicle data, companies can optimise their fleet operations, reduce fuel consumption, and increase efficiency. A study by Frost & Sullivan revealed that fleet management systems could save businesses up to 20-25% on fuel consumption and increase productivity by up to 15%.
Route planning
Businesses are using data analytics to optimise their routes and improve delivery times. Companies can identify the most efficient ways and delivery times by analysing traffic patterns, weather conditions, and customer demand. A report by McKinsey estimates that demand-based routing and dispatching could reduce urban delivery costs by 25% to 45%.
Demand forecasting
Companies use data analytics to predict demand for various products and services in the mobility sector. By analysing historical data, companies can identify patterns and trends in customer behaviour and use this information to optimise their services and allocate resources more efficiently.
Personalised marketing and customer service
According to a study by Epsilon, 80% of consumers are more likely to purchase when brands offer personalised marketing experiences. By analysing customer behaviour, preferences, and buying patterns, companies can tailor their marketing and customer service strategies to meet the needs of their customers.
As technology advances and more data become available, the potential applications of data analytics in mobility are boundless. With the advent of smart cities and connected infrastructure, we can expect to see even greater utilisation of data analytics in areas such as traffic management, public transportation, and urban planning. As the industry evolves and adopts more data-driven approaches, a seamless and efficient mobile experience for all can be expected.
By Anurag Shrivastava
The author is the Founder & CEO of Lumenore, a unified business intelligence and analytics platform.
Disclaimer: Views expressed are personal and do not reflect the official position or policy of Financial Express Online. Reproducing this content without permission is prohibited.
