How Data Mining of Data Helps Fleet Management Today, data mining techniques are widely used in fleet management systems such as vehicle route planning and driving behavior analysis. Fleet managers are extracting useful information from their own databases to manage their operations more effectively and also improve service and driver retention.
Data Analysis and Mining to Curb Driver Attrition and Manage Routes
Predictive modeling techniques are often employed to mine and analyze data from the company’s database. Averitt Express, a transportation and logistics company based in Cookeville is using predictive modeling to improve safety and driver performance. A few years ago, they employed data mining to address one of the major issues - driver attrition
While doing the analysis of driver retention data, they noticed that drivers who had an accident have a greater tendency to leave the company than others. When analyzing the reason for this, they noticed that drivers who had an accident was sent with a canned message to their mobile, informing that they had lost a number of points and had three days to appeal. So Averitt changed its policy by mining the data, finding out the issues, talking them over with the concerned drivers and reassuring them that they had chances to improve.
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Southeastern Freight Lines, Lexingon employs data mining to improve their routes. They analyzed customer specific data and used the results to understand their pickup and delivery costs at each account. This allowed them to reduce the loading and unloading times for the customers who took more time. Other companies are using data mining software to improve operational efficiency, maintenance activities and customer care.
How Business Can Make the Best Use of Their Data
Getting big chunks of data from diverse data sources is not enough for intelligent decision making. What fleet mangers required is information that gives them the ability to get more insight into their business. There are many ways by which a company can make best use of the information they gather:
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Conventional business intelligence in the form of charts, graphs, tables and reports are useful indicators of performance over a period of time
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Data mining which employs analytical/statistical techniques to extract useful information from customer data
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Looking at ‘Big data’ to analyze patterns across several industries
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The important thing is not just to collect data but to analyze and mine it so that the results can be used to take important decisions. Government entities and large companies with extensive consumer bases may need to use advanced statistical tools to look through large chunks of data for information that may not be apparent.
Sourcing the Data
Getting the data to extract the necessary information is crucial. Fleet companies have a lot of data relating to trucking management and maintenance systems, information from their mobile communication systems such as GPS, speed and engine data and data from cargo temperature monitors, tire pressure monitors, safety devices, and much more. To get useful nuggets of information for decision making they need to collect and look at everything from planning and fleet telematics to work order management. Advanced technology has made it possible to collect all this information.
However, it may not be practical for all businesses to manage data collection and data mining in-house as it could deviate from their core responsibilities. The reliable option is to partner with a data mining company that can help to extract information from their large databases, sort out of the information, and analyze it to find the relevant information to build the right kind of business model.
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(800) 670 2809