Data-driven transformation in Transport and Logistics

Data-driven transformation by land, sea and air

Where will data take you?

Data science is revolutionising the movement of people and cargo around the world, with transport and logistics companies using advanced analytics and AI/ML to transform supply chains, optimise use of resources and exceed customer expectations.


How do we forecast demand? What’s the most efficient way to reach each destination? How can we reduce running costs?

The transport and logistics industries generate vast amounts of data from all around the world via IoT devices, GSP, real-time traffic monitoring and e-commerce. This information holds incredible value, but it’s often unstructured and highly complex.

Mango Solutions helps companies use their data to predict supply and demand, allocate resources and reduce costs whilst maximising profits. Data science has been used to: discover hidden patterns in the supply chain; automate time-consuming processes; improve strategic thinking and enhance driver control and route-mapping. We give suppliers an edge in a market of razor thin margins – creating new efficiencies and enhancing customer service to drive sales and boost retention.

How Mango Solutions helps transport and logistics businesses:

Drawing on our data science skills and expertise in the transport and logistics sectors, Mango Solutions delivers value from your data-driven transformation with use cases such as:

  • Operational efficiency – analysing multiple variables (delivery trends, daily volumes, climate, economic data etc.) to optimise delivery routes, allocate resources, reduce fuel costs and enhance customer service.
  • Dynamic price modelling – using advanced analytics to align pricing to real-time cost data and external factors (e.g. weather) to increase transparency, minimise churn and maximise cross and upsell opportunities.
  • Accident prevention – collecting, interpreting and applying data (e.g. traffic, road conditions, weather etc) to develop predictive modelling and prevent accidents.
  • Demand assessment – aligning local supply and distribution to identify patterns of high demand, reduce unnecessary transport costs and develop strategies for emerging sales trends.
  • Predictive maintenance – analysing data from vehicle/equipment sensors to preempt and prevent failure by scheduling repair work proactively, ordering parts ahead of time.

Ready to embrace data-driven transformation in transport and logistics? Contact our Account Manager Leon Walker for more information:

Leon Walker

Get in touch


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