Most fleets already have enough operational data to uncover meaningful savings, but the challenge is knowing where to look. In the second part of our interview with Alex Crane-Robinson, Regional Director UK & Ireland at Webfleet, we explore the areas most likely to hide unnecessary cost, why downtime can be more expensive than it first appears, and how better use of fleet data can help operators improve utilisation, maintenance and productivity.
If you looked at a typical fleet that already has plenty of operational data but isn't using it to its full potential, what are the first three areas you would analyse for unnecessary cost?
I’d start with fuel or energy consumption, which can tell you a lot about what’s happening across the fleet. Things like idling, driving style and differences between vehicles or drivers can point to inefficiencies. Even relatively small inefficiencies can add up quickly across a large fleet.
I’d then look at vehicle utilisation. Are vehicles being used as effectively as the business thinks?
Are some assets covering very high mileages while others are underused? Are routes, schedules or time spent on site resulting in unnecessary mileage? This kind of data can help fleets see whether vehicles are being deployed in the best way and whether they really need the number of vehicles they have.
Third would be maintenance and downtime. Recurring faults, servicing patterns, tyre issues and the reasons vehicles are off the road can all have a significant impact on cost. And it’s not just the repair bill – downtime can also mean replacement hire, missed jobs and lost productivity.
Fuel use, utilisation and maintenance often overlap, so looking at them together can help reveal where cost savings can be made.
For a large fleet, is reducing downtime potentially a bigger financial opportunity from connected technology than reducing fuel or energy consumption?
It can be, depending on the type of fleet and how important each vehicle is to keeping it moving.
Fuel and energy costs are highly visible, so they naturally receive a lot of attention. Downtime can be harder to quantify because it can show up in lots of different places. There’s the repair itself, but also things like replacement vehicle costs, lost productivity, delayed jobs and potentially unhappy customers.
For a fleet that relies on having vehicles out on the road every day, just one avoidable breakdown can prove very expensive.
Connected vehicle technology gives fleets an opportunity to manage this more proactively. Vehicle diagnostics can flag potential faults earlier, while maintenance scheduling and tyre-pressure monitoring can help operators deal with problems before they result in a vehicle unexpectedly being taken off the road.
Across a large fleet, even a small improvement in vehicle availability can add up to a significant saving.
If we revisit fleet management technology in five years, which tasks currently occupying fleet managers' time do you expect AI to have largely automated?
I think AI will take over much more of the routine work involved in monitoring and interpreting fleet data.
It will increasingly work in the background, flagging things like maintenance requirements, compliance deadlines or changes in driver behaviour before fleet managers have to go looking for them.
AI should also do more of the initial analysis. Rather than simply showing that a KPI has changed, it could explain what’s likely to be behind it and suggest what to look at next.
This should help free up fleet managers’ time so they can devote it to making the decisions that call for their experience and an understanding of the business.
What should fleet managers be doing today to make sure their fleet and their data are ready to take advantage of the next generation of AI-led fleet technology?
Start with the basics – make sure your fleet data is accurate and accessible in one place.
AI can only work with the information it has, so if it’s scattered across different systems, it’s worth considering how it can be brought together.
It’s also important to be selective about what you measure. There’s no point collecting data just for the sake of it. Focus on what you want to improve and the information that can help you achieve this.
Finally, make use of the data you already have. Those fleets that use data to underpin decisions will be better placed to get the most from the next generation of AI tools.
What should more people know about fleet management that not enough people ask?
I think people sometimes underestimate how much fleet data can tell you about the wider business.
If a vehicle is sitting idle, for example, or spending more time than expected at certain locations, it could highlight problems with scheduling, workload or how jobs are planned.
The same is true of things like safety and maintenance. Fleet data can highlight patterns that tell you a lot about what’s happening across the business.
• For fleet managers, more data is not necessarily the answer. The real value comes from using the information already available to identify inefficiency, prevent avoidable downtime and understand what is happening across the wider operation.
As technology takes on more of the routine monitoring and analysis, the fleets best placed to benefit will be those with accurate, joined-up data and a clear idea of the decisions they want it to support.
If you missed it, check out part one of our interview series: Alex Crane-Robinson of Webfleet on data, downtime, and using AI to its potential.
Similar Stories
Alex Crane-Robinson of Webfleet on data, downtime, and using AI to its potential
Meet Alex Crane-Robinson, Regional Director UK & Ireland at Webfleet. Wit...
Public Charging Price Watch: subscriptions start to challenge PAYG
Public charging is moving beyond simple pence-per-kWh pricing, with subscript...