The impact of the global emphasis on electric mobility is gradually extending towards commercial mobility. For fleet operators, the rising cost of energy sources like Diesel is leading them to transform from ICE vehicles to EVs. However, this comprehensive transformation from traditional energy sources to electric mobility is opening up new areas of concern regarding operational costs, vehicle downtimes and onboarding drivers — aspects that are leading the sector to introduce data-driven infrastructure for optimizing operational efficiency and costs.
For EV fleet operators irrespective of the sector — from ride-hailing to last-mile delivery or commercial logistics — charging time of vehicles is considered idle time that calls for an optimization for business growth. This idle time reduces business scalability through increased logistics time, something that has an adverse impact on revenue growth. Additionally, accessibility to charging infrastructure around driver catchment areas plays a pivotal role in maximising operational efficiency. By optimizing operations through a data-driven infrastructure, fleet operators effectively become more efficient in managing the charging patterns of EVs, helping them to plan trips, schedule and coordinate charging sessions, and ensuring smooth and seamless mobility solutions for transportation requirements.
Furthermore, by incorporating data-driven EV charging infrastructure, fleet operators receive crucial data about real-time energy cost and source, directly translating to reducing the expenditure whilst also decreasing environmental impact. As the fleet operators understand energy consumption patterns, aspects like optimization of charging schedules, driver check-in/checkouts and vehicle charging costs fall in line automatically.
Data-driven EV charging infrastructure: A necessity
Gone are the days when energy consumption costs were unregulated by fleet operators. As energy prices soar, reducing operational costs has become a priority for business scalability. With the analytic capabilities of data-driven infrastructure, fleet operators are enabled with real-time insights and remote monitoring of different aspects, leading to timely actions and unprecedented agility for fleet management.
These infrastructures not only monitor the vehicles but also the charging and discharging patterns, electricity costs & demand, usage, source of energy generation, and many more metrics — providing a more accurate picture of the entire operation. These metrics can be helpful in making informed decisions that have an impact on reducing operational costs while enhancing productivity and ensuring business scalability, growth and efficiency.
This monitoring also helps to make proactive decisions. For instance, if an electric vehicle is consuming more energy than expected, data-driven analysis would help identify the problem, which could be due to driving behaviour, battery degradation or any other issue with the vehicle.. With metrics designed to discover any underlying problem, this helps to unearth whatever issue the particular vehicle is facing and maintenance efforts can be taken to ensure it does not lead to any downtime. As a result, this helps to ensure seamless business connectivity, and uninterrupted operations in reduced expenses — something that is being considered the catalyst for growth in the coming years for commercial fleet operators.
Furthermore, the reduction of operational expenditure will also attract more fleet operators, including government transport authorities in countries with significant public transport usage. This will not only help to sustain public transportation but also play out as one of the critical catalysts for EV adoption across the world. In countries like India, data-driven infrastructure to reduce operational expenditure will not only reduce expenses, but also inefficiencies, and downtime while enhancing the scope of business, and therefore, industry growth.
More aspects
The impact of data-driven EV charging infrastructure is not limited to the aforementioned details. For example, number plate detection, park and charge, and automated authentication at chargers can also be used as metrics or indicators that can help in driver and vehicle monitoring, with minimal human intervention, thus reducing operational costs and increasing accuracy. This could be used to understand the performance of the vehicle or the driver, and coupled with other appropriate data — drivers, fleet managers and leadership of operator organizations can be enabled for significantly better decision-making. With more methodically aligned decisions, efficient reduction of operational expenditure, and thus increasing productivity across stakeholders can be expected.
Additionally, critical EV charging data generated at hubs/charging stations that are used by multiple operators can be critical for both the fleet operations and OEMs, leading to understanding user behaviour, and requirements and thus aligning to streamline the product innovation at large. Also, seamless integrations such as billing, reporting and others into existing systems will assist in reducing overhead wire dependency — create an extra barrier of safety and reduce expenditure across levels.
Future outlook
With a more methodical outlook of electric mobility being preferred by commercial fleet owners, it will be only a matter of time before data-driven infrastructure is established worldwide to measure the efficiency of EVs. This offers a unique scope of opportunity for businesses operating in the space to make inroads in terms of innovation, premium product manufacturing and business scalability. Furthermore, as large fleet operators adopt electric mobility at large, it will not only lead to increased adoption rates but also unprecedented innovation in creating data-driven infrastructure that reduces operational expenditure in mobility, creating a chain reaction that will have a favourable impact on end-users worldwide.
