Discover why big data is important for your fleet operations and how to apply it to the different aspects of logistics management.
What is big data?
Learning to identify and process big data can bring enormous benefits to many different types of industries, including the automotive industry and the transportation and logistics management sector. There are currently around 37.9 million connected trucks in the world, compared to the 17.1 million that existed until 2015 and, according to specialists, the trend of the connected car and the use of intelligent management of vehicles and their data (car data) will be getting stronger.
Big data is a term that defines the type of data ranging from 30-50 Terabytes to several Petabytes and that’s generated at a high speed and with a high degree of variety, thus fulfilling the three Vs of big data: velocity, variety and volume.
How to improve fleet management using big data?
Although understanding and using big data may sound like an extremely complicated task, it is easier than it seems. It is simply about having the right guide, that is, hiring the right telematics intelligence solution that’s based on state-of-the-art tools and user friendly systems that allow you to easily and reliably identify and decipher your fleet’s data.
Location World has been working with big data for over a decade and has successfully applied it to all of its solutions: CarSync Drive, CarSync Business and CarSync Fleet. The latter is directly focused on intelligent fleet management and has had an interesting evolution in the last three years.
How do we apply big data to fleet management? Specific and important data is collected from each vehicle in the fleet, thanks to the use of GPS devices, combined with CAN BUS devices and other types of specialized accessories. This data is entered into the CarSync Fleet software platform, and is transformed into easily accessible dashboards intended to keep track of all this data in a systematic, clear and accessible way.
When a reliable telematics solution, as CarSync Fleet, is in place, the big data generated by a fleet is intelligently organized so that it can be used to improve the performance of the entire fleet. It is thus possible to optimize fuel efficiency, vehicle performance, drivers’ performance, logistics performance of the entire operation and even improve its future or long-term performance.
Thanks to the intelligent use of big data, parameters such as distance traveled, exact fuel consumption, idling time, among others, can be compared for each vehicle separately. Big data allows us to:
-Identify vehicles that are having excessive fuel consumption
-Identify the cause of excess fuel consumption (idling, inefficient gas stations, damaged vehicles, etc.)
-Know where and when are your drivers supplying and the exact cost of each supply, among other things.
With this data it is possible to prepare daily, weekly or monthly reports and analyses and use them as a basis to change fuel strategies and make them more efficient.
This is where preventive and corrective maintenance come into play.
Thanks to the use of big data, it is possible to obtain information on the status of each of the parts of each vehicle and establish the right moment to carry out changes and maintenance, so that you can always be one step ahead of potential problems and breakdowns.
Using big data, problems with brakes, tires, fluid leaks, etc. can be identified long before they become a safety risk or a hindrance to a vehicle's performance and therefore to the productivity of the entire fleet.
By identifying and studying your fleet’s big data, it is possible to configure preventive maintenance in a simple way, avoiding corrective maintenance as much as possible, since it’s usually more expensive and messy.
Many times, fleet managers neglect a very important aspect: their drivers’ behavior. However, this trend is changing and there is increasing awareness of the need for real-time monitoring of the driving style of each of the employees in a fleet.
Using specialized tools, solutions like Location World's CarSync Fleet allows access to big data information such as:
-Specific identity of each driver behind the wheel
-Number of fleet drivers who are speeding
-Number of drivers who commit other dangerous maneuvers, such as sudden stops or uncontrolled acceleration
-Number of hours a driver was behind the wheel in the last week or month
-Inputs, outputs and fulfillment of deliveries of all drivers in a fleet
-Global driving score of all drivers in the fleet and each one separately, among other types of indicators.
This allows having both an individual and collective vision of the performance behind the wheel of a driver; anticipate possible failures and risks and avoid them in time, through assertive decision-making.
Big data can also optimize the performance of staff members from other areas of a fleet, such as the administrations department, through the optimization of inventory processes, schedules, billing, etc.
Likewise, the use of big data through telematic intelligence systems allows keeping a record of maintenance expenses, fines, expenses for legal procedures, additional payments to drivers, accidents, insurance, etc. and identify detrimental and beneficial patterns for the overall budget of a fleet.
5.-Future performance: the power of advanced analytics
The optimization of this type of performance comes as a logical consequence of all the previous performances and a step further in the use of big data and its application to fleet management. This is what we call “advanced analytics”, which uses digital tools and systems to carry out complex analysis of large volumes of data in a quick, clear and very precise way.
If simple tools for reading and using big data can help us identify simple patterns, imagine all we can do through the use of advanced analytics. We can use big data to actually forecast the future performance of a fleet with a high degree of accuracy, as well as its productivity potential and profitability.
This is achieved thanks to four specific functions of advanced analytics:
-Descriptive analysis: describes a specific problem or risk, using clear and precise figures.
-Corrective analysis: shows possible solutions to a fleet’s problem
-Predictive analytics: gives you a look at all the different possible scenarios that could take place as a result of that problem
-Prescriptive analytics: it offers you a prescription, that is, a clear recommendation of the best path you can take to solve a problem. It helps you make the best choice for your fleet.
Now that you know how to apply big data to fleet management, what aspect of your fleet would you like to start optimizing? Follow our content to see all the ways in which a company can grow and evolve thanks to the use of new systems and technologies.