A five point list aimed at helping fleets gain maximum insight from their data has been issued by FleetCheck as businesses seek to identify new levels of efficiency as they head into 2021.

The fleet software specialist says that the continuing economic uncertainty caused by the coronavirus crisis has prompted many to look again at their fleet fundamentals – and how they measure key aims has become an important topic.

Peter Golding, managing director, explained: “It’s been a trend for many years that fleets are finding themselves with access to more and more data, and most of them will admit that they haven’t kept on top of everything it can be used to achieve.

“However, we’re now at a moment when the pandemic means that a huge number of businesses are re-examining their fleet activities from the ground up – and data is an area where it is generally agreed that real gains can be made.

“The aim of these fleets is to use the information available to measure key objectives but also to investigate areas where they are able to gain new levels of insight over their operations. They are very much open to new ideas and new thinking.

“The top five has been created by our team to help fleets travel down this road, to get them thinking about new approaches to the information to which they now have access – and how to avoid common issues such as a feeling of being overloaded with data.”

It would be very much a positive development, Peter added, if the list served as a means to prompt further discussion across the industry in this area.

“We have believed for some time that the majority of fleets could be using their data more effectively and we are very keen for this top five to serve as the starting point for new conversations, both with individual fleets and more widely across the sector.

“This is one of the areas where fleets that are under pressure to show gains in terms of budgets and efficiency could make real gains in the wake of the pandemic, and also where the whole industry could gain from sharing best practice.”

The top five is:

1. Ensure your data has context. Knowing a driver has three points on their licence is different to knowing the driver has three points and only passed their test six months ago. Similarly, knowing a vehicle has low tread on a tyre is different to knowing this vehicle had the same tyre replaced only three months ago.

2. Define different levels to how you examine data. To work efficiently you need both a high-level overview of key data sets but also the ability to drill down into detail when needed. Not being able to switch between the two is often what creates an impression of data overload.

3. Integrate your data. This is an obvious step but linking datasets together can serve two key purposes – contextualising information and saving a huge amount of time through automating processes. Both of these are essential to good data use.

4. Set the right metrics. Identify your key targets and ensure that you have data in place that measures your progress accurately. It is virtually impossible to do everything that data might potentially deliver, so decide on your priorities.

5. Undertake frequent reviews of the data you analyse. Data sources are constantly changing with some improving and some degrading. Reviewing your data quality at specific intervals helps to avoid scenarios where companies are stuck with poor data from suppliers that have not developed their offering.