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Fleet of Trucks
Leveraging AI and machine learning to improve Supply Chain

The last decade has seen huge investments, continuous investments and continuous improvements by both technology providers and logistics consumers like the airlines, airports, cargo systems, shipping, ports, container handling systems, road transport etc., all in an effort, to improve Supply Chain and drive Supply Chain optimization and predictability.  Every industry, from retail to manufacturing, transportation to warehousing are today working with large amounts of data and implementing Machine learning and AI to track and improve predictability in Supply Chain to can radically improve operations, upto the last mile and hyper-local level.  These effort were more accentuated and visible during the effects of the pandemic across the world. 

The adoption of data science and machine learning techniques allows companies to optimize logistics and determine factors that affect performance, thus increasing productivity. 
Cargo Ship
Operational efficiency 

The logistics and transportation industries are largely driven by economics: fuel cost, security measures, time to delivery, supply chain reliability, domestic distribution networks, offshoring, and so on. By linking historical activity data with consumer profiles, economic indicators, and geolocalized market data, logistics, transportation providers are able to predict demand with increasing accuracy. This allows for anticipation of daily volumes, optimization of delivery routes, and the allocation of resources accordingly.

  • IoT-enabled fleet management with telematics shares data between vehicles and fleet managers to improve productivity, visibility, and maintenance.

  • Fleet owners and drivers can act accordingly with predictive fleet maintenance, asset management, pallet tracking, driver management, and more.

Automation, optimization and demand-supply prediction

When it comes to machine learning and AI in the supply chain, a key step to optimization is automation of processes and reducing steps that involve manual processes done by humans. This frees up human energy to perform more strategic tasks and develop further system improvements.
The past few years one of the major industries to improve and evolve continuously is the airline industry. From ticketing, web check-ins, luggage check-in, crew management, in-flight dining and food choices, loyalty programs etc. These involve large amounts of data, covering data privacy, security, governance and unbiased passenger profiling. 
Staying competitive today means offering the best at the least cost to customer and shareholder.  Read more about how Dataiku works with customers in the airline industry looking to implement ML and AI algorithms, to better understand every aspect of operation in their journey of optimization.
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