Fleet management: why will big data become a strategic issue?


Today, fleet management software is essentially used to manage individual vehicles and the events associated with them. This micro management of each vehicle with its associated driver(s) allows the manager to monitor his fleet on a daily basis.

On the other hand, the macro analysis of the data generated by all the fleets remains rather limited. And yet, millions of extremely useful data are now produced by fleets:

Basic data recorded in the management system: events related to the vehicle or drivers, fixed and variable charges, etc.

Data recorded by on-board systems such as OBD (On Board Diagnostic): mileage, consumption, maintenance, alerts ...

Embedded IOT (Internet Of Things): more and more connected objects are present in vehicles and also send data

And finally, the APIs (Application Programming Interface) that allow the retrieval of data from the company's partners: Total GR, leasing companies, Sage for accounting, for example.

Why is this data so strategic for the fleet manager?

In fact, these data will bring out major trends that will enable him to do his job differently: instead of being subjected to events, the fleet manager will increasingly be able to follow a predictive logic in order to better rationalize the management of his fleet:

Pro-active maintenance: faced with recurring breakdowns, the manager will be able to define new processes and take the appropriate decisions by involving the actors concerned, in particular the drivers and the dealer for example.

Controlled consumption: over the long term, he will be able to compare his real consumption with that displayed by the manufacturer and thus analyze the reasons for the differences

The comparison between fleets or between driver types: immediately the differences in measurements will allow him to identify the behaviors on which to act in priority in order to improve the fundamentals of his fleet: driving style, expense management, fines, etc.

A new vision of fleet management:

By benchmarking the fundamentals of his fleet more systematically, the manager can find relationships and corrections between different factors. These new indicators also give him a new vision of his business which will be more and more focused on predictive management.

The key issues of big data integrated into its business being:

Reduce vehicle downtime

Improve ROI and TCO

To make structural savings on important items such as fuel or tires

Digiparc, a big data oriented fleet management solution:

But the greatest danger with Big Data is the data itself and its rampant inflation which, if not controlled, can render any attempt at interpretation ineffective.

Basically, Digiparc is structured to respond perfectly to these challenges. Indeed, the logic of strong separation between the repository and the operational, allows to generate data easy to exploit and analyze.

Thanks to an approach based on reporting (more than 50 types of reports available), Digiparc also offers the possibility to cross-reference data in all directions on your main areas of interest.

Moreover, the systematization of alerts allows the manager to rely on a robust system of predictive interpretation of the data.

Enfin, avec la nouvelle version 5.0 de Digiparc, les tableaux de bord sont désormais présents à tous les nouveaux niveaux de l'interface et vous permettent d'avoir à tout moment une vision globale de la situation de votre parc.

To conclude, the big data revolution in the world of fleet management has just begun!

Business Development Manager France