Transportation has always been a critical determining factor for economies and quality of life worldwide. Inefficiencies in transportation cost money as well as increase emissions. Traditionally, the increase in demand for good transportation infrastructure is much faster than the supply of this infrastructure by the authorities. Even if there were a limitless supply of money and personnel for road construction, many areas are already built out. This is the key imperative for the transportation industry to turn towards business analytics to better utilize available resources. The key driver for succeeding in this initiative is the availability of data and the ability to use this data for making smarter decision with the use of analytics insights.


Customer Challenges

Key customer challenges are:

  • Data sources that bring in the data from transportation are not connected with each other.
  • As authorities provide multi-modal transportation for moving people and goods, it requires comprehensive data collection capabilities.
  • The transportation industry, being one of the oldest industries, is slower in adapting to new technologies, thereby making it difficult to analyze data across different components of the transportation chain.
  • A lack of a synchronized control platform for monitoring transportation leads to reactive decision making as compared to the proactive decision making required.
  • Large parts of data collected in the transportation industry are unstructured.

Solution Offerings

CloudMoyo’s transportation analytics platform provides for a cloud-native platform that enables the organization to synchronize data from disparate transportation systems and feed that data to the data analytics engine. This enables the organization to optimize the CapEx and OpEx requirements. CloudMoyo’s Transportation Analytics Platform enables the following:

  • Perform predictive maintenance for fleet thereby reducing the risk of unscheduled maintenance, prevent expensive failures and extend part-life.
  • Reduce revenue loss due to service disruptions.
  • Accuracy in demand forecasting resulting in optimized operations, real-time supply chain visibility, higher availability of assets.
  • Provides the ability for the organization to perform dynamic pricing and revenue optimization.