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Is Predictive Analytics All Set to Drive Success in the Transportation Industry?

Jan 23, 2018

There is an unprecedented amount of information available in the transportation industry today, which contains immense potential for deriving insights that aid in planning and managing transportation networks. This data is captured from various sources such as onboard sensors and data collection points introduced by passenger counting systems, systems scheduling, asset management systems, ticketing and fare collection systems, and vehicle location systems. Players in the transportation industry can leverage advanced analytical techniques such as predictive analytics to use the available data to improve operations, reduce costs and better serve travelers.

Get in touch with a predictive analytics expert to know how you can benefit by leveraging predictive insights.

How Can Predictive Analytics Help?

Any technology that can improve efficiency on a “more is less” paradigm has the capability of making things much easier for both transit agencies and the passengers they serve. Predictive analytics can fill that role to some degree. With the help of predictive analytics, transportation companies can answer the question of “What’s the best possible outcome?” instead of explaining the prior history. In this manner, it can help them with many different capacities, from vehicle fleet maintenance to planning new lines of services.

To know more about how predictive analytics can help the transportation industry, request more info.

Let us explore some of the critical areas in which predictive analytics will help the transportation industry players:

  • Predictive analytics can help companies to determine the impact of unplanned events such as a transit labor strike on transportation utilization and the local economy.
  • Transit agencies can also understand how subway line closures, planned road-works, or transit maintenance projects can affect public transport. They can then use this insight to plan the optimum change in transit schedules and communication strategies to deal with the impact.
  • Identify and predict the likely occurrence of routine unplanned service incidents like a traffic accident or vehicle breakdown, and suggest optimum responses.
  • Predictive analytics can model the impact of various proposed urban development projects on transportation and help in the identification or alteration of the projects to achieve sustainability objectives while supporting the need for mobility.
  • Companies in the transportation industry can pinpoint events such as bus breakdowns, late-arriving buses, or signal outages that have the highest economic impact to a transit agency and recommend ways to eliminate the events or reduce the effect.
  • Predictive analytics can help transportation players to predict the impact of the planned expansion of transportation networks by having a clear understanding of the patterns of usage.
  • Transportation agencies can understand when the vehicles require maintenance well in advance with the help of predictive analytics. Such advanced analytics capabilities help to identify irregularities and forecast a range of asset performance risks before trouble arises in the case of vehicles owned by the transportation agency.
  • With the help of predictive analytics, public transportation companies can predict significant events or days during which they would experience a high demand for services. They can adjust or supplement their facilities accordingly to accommodate visitors better and avoid putting additional cars on the road that cause congestion.

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