Importance of Data Mining in Fleet Management

by | Published on Feb 3, 2014 | Outsourcing Services

Data mining is becoming increasingly important in managing truck fleets. Predictive modeling techniques and data analysis often helps fleet managers manage their data better.

For instance, proper data analysis and predictive modeling techniques can be used to determine residual values and help fleet managers make better decisions on purchase, leasing, or selling their inventory. Residual value determination is one of the hardest jobs in fleet management, and is not easier get right when organizations have highly mixed fleets. If an incorrect residual value is put into a vehicle’s “whole of life” (WOL) cost calculation, it can have serious financial implications.

Data mining (in fleet management) can also find applications in analyzing vehicle route, driving behavior, poor vehicle behavior, in proposing maintenance plans, and much more. Averitt Express, a transportation and logistics company based in Cookeville has been using mining techniques to improve safety and driver performance and resolve driver attrition.

When analyzing the data, they noticed that drivers who had an accident have a greater tendency to leave the company than others. Using this information, Averitt was able to change to a more driver-friendly policy and reduce their driver attrition rates.

However, techniques such as predictive modeling which can provide fleet managers with a clear picture of the factors that will impact their fleets’ future needs, is impossible if managers do not have adequate data analysis training. Risks can be minimized by using relying on professional data mining services.

A data mining company can help businesses make the best use of their data by

  • Collecting relevant information with data capture systems
  • Organizing data as charts, graphs, tables and reports
  • Using advanced data mining or analytical/statistical techniques to extract useful information
  • Help in analyzing big data or large sets of data

Data collection is usually easily accomplished. But data is meaningless unless it is properly mined for useful information and analyzed to boost business benefits. Professional support is available for everything from for capture data entry and data cleansing to data mining work.

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