The advancement in digital technology has compelled every business in utilizing it. Gone are the days when every operation was performed manually. With everything becoming digital, companies do not have to worry about the inconvenience of paperwork anymore. They have everything available on their screen through a single click. Like other businesses, transportation companies have also gone fully digital, relying heavily on fleet management systems.
During fleet operations, there is a lot of data generation. Vehicles have to complete several trips daily, and many tasks need to be allocated to the drivers. All of this calls for an effective mechanism that can organize and preserve the data. The monitoring solutions utilize this data to facilitate business in achieving their goals. In this blog, we will discuss data analytics’ role in fleet management thoroughly.
Types of Data Analytics Used in Fleet Management Systems:
Before getting into any detail, firstly you should know about different kinds of data analytics used in vehicle tracking systems. They are as follows:
- Predictive Analytics:
Predictive analytics provides accurate prediction to help a manager proactively organize their operations accordingly. It facilitates a business in getting a foresight that helps in better strategy making.
- Descriptive Analytics:
Descriptive analytics summarizes raw data making it understandable for humans. It describes past occurrences helping businesses in learning from them.
- Diagnostics Analytics:
Diagnostic analytics is a source of problem-solving providing detailed diagnosis of a problem, including its reasons. It helps analysts to get a deep understanding of the issues assisting a business not to repeat the same mistakes.
- Prescriptive Analytics:
Prescriptive analytics provides the best practices for a given scenario. After analyzing all the possible pros and cons, it suggests various options to the managers. Managers can take timely and correct decisions by relying on predictive analytics.
How Data Analytics Help in Fleet Management?
Maintenance is an essential requirement for running successful fleet operations. Due to excessive mileage and non-stop working, the vehicles are likely to malfunction. It can not only halt the routine operations but is also pretty costly. Therefore, preserving the fully functional condition is the least mangers can do. It is only possible by adopting a proactive approach during maintenance.
There is a massive role of data insights in preventive maintenance. The tracking device attached to the vehicles shares the real-time updates about their status and location. This data is shown on the software facilitating the managers to strategize their maintenance tasks. For example, if a manager has set a fixed mileage limit for inspecting the vehicle, they will get notified whenever it is achieved.
As there are many automobiles in a commercial fleet, maintaining all of them becomes a problem. By using the telematics solution, the managers can keep track of every vehicle’s maintenance needs. The data produced from every individual vehicle helps the manager in prioritizing the maintenance tasks. It helps in ensuring that all the vehicles get their due service and repair.
Proper Task Scheduling:
Managers have to look after a lot of things during routine operations. They have to monitor the activities of several vehicles and allocate tasks to the drivers. At times, there is a lot of confusion while distributing daily tasks amongst drivers. There is always a threat of task overlapping between various drivers. However, all such situations can be avoided by strictly relying on data analytics.
If managers follow the data insights about the vehicle and driver status, they can efficiently schedule tasks. The modern fleet management systems provide information about the availability of every driver. It also updates the driver’s current location, making it easier for the managers to assign trips. After completion of a task, it is shown as completed on the software preventing overlapping of tasks.
Due to the hectic routine, the managers tend to ignore certain things that can lower productivity. However, data analytics are not prone to any such mistakes. They provide a comprehensive analysis of every situation with discreet details. For example, the managers can view the drivers’ working duration, the total number of completed trips, idling time, routes taken etc. This information gives them a clear picture of the performance of all the drivers.
In addition to the employees’ performance, the managers can also gauge the operational efficiency. For example, information like vehicles’ downtime, working time, fueling expense etc. is available on a monitoring software. The various types of reports can be compiled based on the available data to provide managers with a broader view of the overall performance. All such information plays a pivotal role in conducting goal-driven fleet management.