Big Data and telematics data: everything you need to know

Big Data and telematics data are closely related in order to carry out the management of vehicle fleets. It is also useful for insurance companies in order to reduce insurance premiums.

Big Data and telematics data are a big part of the picture, especially in the automotive industry. Indeed, the sharing economy prevails in this sector where vehicle fleets are increasingly supplanting private vehicles. Therefore, it is important to choose a good strategy to monitor and manage vehicle fleets for a variety of reasons. One can mention cost reduction, as well as increasing the efficiency rate. Big Data seems to be the most appropriate solution for this. In this article, we will discover the relationship between Big Data and telematics data.

Table of contents

What do we mean by telematics solutions?

The easiest way to explain what telematics is is to compare it to the black box. The black box is an indispensable part of the aircraft. It is the tool that collection and accumulates all relevant information that is essential for the proper functioning of the device. The stored data will be transferred to the technical department foranalysis and decoding.

Telematics solutions encompass services that use technology to receive or send data, whether public or private. In addition, these solutions also provide access to files and to monitor certain operations. Today, telematics solutions are used to manage a fleet of vehicles. They provide a means of constant monitoring, accessing the details of all activities of each vehicle in the fleet.

How telematics works

Telematics works by capturing information useful for monitoring each element of the fleet. For a fleet of vehicles, the system records locations, speed, fuel consumption and much more. Note that the captured data is displayed in real time. Currently, the vast majority of vehicles on the market have a telematics control unit.

The majority of insurance companies have access to the information collected. They need it in order to obtain accurate information in the event of an incident or failure of the vehicle. But companies in the transport and logistics sector also need this data. This helps to reduce the costs of transportation, in particular, the fuel.

What is the relationship between Big Data and telematics data?

As we already know, Big Data encompasses a whole myriad of tangled data. In fleet management, Big Data is used to collect telematics data.

In principle, there are two types of data, the basic data and the advanced data. For a car-sharing company, vehicle usage can be counted per member. In contrast, for a company that works in freight forwarding, one trip is one delivery across the country.

In all cases, the common criteria for each trip such as departure and arrival time, distance traveled, etc. allow the predictive maintenancebut not only. Such information does not require advanced technology to collect it. It is called basic data. On the other hand, some information collected from the more extensive telematics systems is called advanced data.

Basic data

Baseline data is the set of data collected during a single trip. This data is often recorded by vehicle tracking solutions such as the GPSfrom the odometeretc. Indeed, the parameters can be different from one trip to another, from one fleet to another.

The technology will then take care of completing this information by collecting certain information such as GPS time stamp, vehicle status, power supply voltage, fuel consumption and others. Trip-specific information such as power outage can also be collected using advanced technology.

Fleet monitoring is based on data captured by theaccelerometera device that is used to record sudden movements. Examples include acceleration, hard braking, and hard cornering.

Advanced data

Big Data also encompasses the more detailed information when investing in broader telematics solutions. Fleet management is not just about minimizing costs and reducing fuel consumption. Contractors in the sector also need to ensure that every trip is optimalTo ensure that the customer is satisfied. In this way, each vehicle must work perfectly.

To do this, it is necessary to ensure that more detailed, or advanced, information such as engine load, fuel level, fuel used, etc. is obtained. This also applies to the technical information on each vehicle such as the cruise control switch or the malfunction indicator.

The data recorded in this way will make it possible to monitor and control the fleet. This allows not only companies to optimize their costs, but also insurance companies to minimize the insurance premium.

Uses of Big Data in telematics

There are many ways in which Big Data materializes its use in telematics systems. First, the megadata collected are used for monitoring purposes. Secondly, they allow for make decisions crucial fleet management decisions.

Big Data to build telematics data dashboards

Big Data management for a fleet can be done on a daily, weekly or monthly basis. Customers can view the most important data on a dashboard. The resulting dashboard shows the Big Data information about the telematics data. It accesses the instantaneous tracking of peaks and incidents, allowing toact accordingly.

For example, when a vehicle is idling, it is the dashboard that allows the customer to identify it. The customer can then report it immediately to stop it. In general, idling results in increased fuel consumption.

Conduct a fleet review

There are a number of parameters that need to be closely examined during a fleet review, fuel consumption, the driving hazards and vehicle maintenance, among others. Having this data in hand allows for the detection of key areas for improvement after reviewing the fleet.

In this way, it can be said that Big Data, specifically, telematics data is a crucial aid in decision making. The decisions can be about the next purchases of vehicles or the type of vehicles to be purchased by referring to the result of the examination.

For example, at some point, the company needs to consider replacing some vehicles in the fleet. Before making the purchase, it is important to know what type of vehicle to purchase, given the problems encountered during the last review. In addition to this, the company may also choose to go electric for some of the vehicles in the fleet.

Provide time savings for the management team.

Big Data offers a ready-made solution for collecting telematics data to save management overtime WORK. Gathering reports based on various requirements can lead to the company spending extra hours.

With a Big Data report, which is well structured, decision makers can get the relevant information, as well as key areas of focus and upcoming trends. This is an opportunity for the management as it offers more time for criticism and improvement of the company’s life.

Reduce fleet management costs

Big Data fleet statistics from telematics data also includes MPG and fuel consumption for each vehicle. However, it is known that such information is essential for fleet management, including cost management.

With good statistics, one can extend the results to a larger scale with the goal of improving the entire fleet. In this way, the company can reduce certain costs related to fleet management, such as fuel consumption and maintenance and repair costs.

Motivating staff

Big Data, especially telematics data, offers a individual score for each driver. However, it is not possible to make a comparison with the other drivers or the other fleets of the company. To do this, it is necessary to create classification tables to allow compare these voluminous data.

The resulting ranking will then motivate the drivers and allow for some sort of internal competition, i.e., between drivers or between fleets. This is a good motivation. The result is both the development of the company and the satisfaction customer satisfaction.

Reducing insurance premiums with Big Data from telematics data

As stated before, Big Data through telematics data helps to reduce insurance premiums. Indeed, insurance companies need to have the loss ratio for comparison to the averages. This ratio is obtained from a national database.

In this particular case, Big Data on key KPIs will thus be measured from telematics data. This includes, for example, difficult driving events and speeding. The comparison shows the value of the loss ratio compared to the averages. The lower the loss ratio, the lower the premiums.

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