Features
22 Feb 24

Driving Efficiency: The Tech Revolution Transforming Van Fleets

Light commercial vehicle (LCV) fleets rely heavily on vans to deliver goods and services but are often constrained by small margins. Many are turning to technology to optimise operations and deliver efficiencies. A tech-driven approach can translate into increased profits and better financial performance if executed well. 

The benefits of technology for LCV fleets are widely understood and include reduced operating costs, improved customer service, enhanced driver and vehicle safety and sustainability. 

The Fleet Europe LCV Expert Day is a 1-day international industry event, 100% dedicated to Light Commercial Vehicle management and focusing on the largest commercial fleets in Europe. The purpose is to learn, experience and network. 

What technologies are van fleets turning to?

AI (artificial intelligence), machine learning, and IoT (Internet of Things) are reshaping many operations, and fleets are no exception. 

Using AI algorithms, real-time traffic data is helping fleet managers analyse traffic patterns, accidents, road closures and weather conditions in real-time and dynamically adjust routes accordingly. Amazon utilises complex AI and real-time data to optimise delivery routes for millions of packages daily. 

Optimising routes and satisfying customers

Such applications are often used alongside geofencing and route planning tools to define service areas, optimise multi-stop deliveries and schedule pick-ups. This can minimise travel time and save on fuel. 

This also ties in with delivery management platforms that integrate with customer order processes and inventory data to plan routes, improve order fulfilment and - importantly - increase customer satisfaction in a competitive world. 

Extending vans’ operational life with predictive maintenance

In real-time, IoT sensors in vehicles and telematics monitor critical parameters, such as engine performance, tyre pressure, fuel economy, and driving style. This enables fleet operators to analyse historical data to make informed future predictions about vehicle performance and customer demand. This also helps the business by informing inventory allocation and replenishment cycles. AI-powered warehouse management systems also enlighten picking, packing and routing, thus increasing efficiency and accuracy. 

DHL lowered unplanned downtime by 20% and extended vehicles’ operational lifetime by implementing IoT sensors and predictive maintenance. 

Optimising field service fleets

Matching technicians with the right skills and tools to undertake certain jobs will maximise resource utilisation. AI is key in analysing technician expertise in field service fleets and their availability. It’s also being used to ensure vans are equipped and resourced optimally. 

Real-time traffic and availability are important here so routes can be dynamically adjusted based on live traffic information, technician locations and job completion times. This helps to ensure on-time arrivals and reduce idling. This is particularly important where multi-skilled engineering teams are concerned to optimise team schedules by considering overlapping skill sets and locations. This can allow technicians to handle multiple jobs in a single trip and ensure they have the right parts on the van. 

In this sector, augmented reality (AR) assists technicians remotely. They can receive real-time visual and troubleshooting guidance from remote experts, thus improving repair accuracy and their knowledge simultaneously. 

But what are the challenges to implementing technology?

While promising, implementing new technology in van fleets comes with challenges that should be considered before leaping. 

Cost is an issue. Advanced technologies like AI and IoT are expensive. The designers and suppliers of these systems want to claw back as much as possible from their investment in research and development, so they are always more expensive in the early days until they become mainstream. Smaller fleets might struggle with affordability. 

For data to be useful, it must be clean, accurate and reliable. Data integration and management is no easy job, especially when dealing with legacy data. It often requires technical expertise, which can be costly, alongside robust data management protocols to ensure it stays clean. 

Drivers and technicians can sometimes be resistant to adopting new technologies or practices. Anything unfamiliar may be perceived as complex, or drivers may fear being replaced by technology. This is often the case until they start using the new system and discover how much it helps them do their job. So, in the initial stages, positive training and communication are key. 

Cybersecurity is also a concern. Sharing vehicle and driver data comes with risks that must be addressed with robust cybersecurity measures and transparent data usage policies. 

And, of course, let’s not forget that technology needs to be maintained to take care of bug fixes and updates, which may also require technical help. Few van fleets have these resources in-house, so they must be in-sourced. 

How best to overcome these challenges

The advice is to start small and scale. Begin with a pilot project that’s quick and easy to implement while delivering benefits. Evaluate ROI (return on investment) before scaling up and look for solutions with flexible pricing models, such as pay-per-use or pay-per-transaction. Focus on data integration, which will be a cornerstone of the project’s success. Consider partnering with IT consulting firms or integration specialists. Prioritise training and support, plus data security and privacy, as this will help elicit system utilisation and thus deliver benefits more quickly. 

Above all, remember that technology adoption is a journey, not a destination. By being aware of the challenges, planning strategically, and addressing them proactively, van fleets can harness the power of AI, machine learning, and IoT to achieve significant operational improvements and long-term success.

Image: shutterstock-1394544941 Production Perig

Authored by: Alison Pittaway