CHICAGO - 3PL & Supply Chain Summit, Stand 203 – StormGeo, a global provider of advanced analytics for weather sensitive operations, introduces new advanced analytic weather tools to improve the operational efficiency of supply chain logistics: on land, at sea, and in the air. The resulting efficiencies help freight and logistics companies across the entire supply chain to reduce weather-related risk, delays, and cost.

“Weather can be an unpredictable and costly factor in logistics,” said Daniel Mathew, StormGeo’s vice president of onshore business. “To help customers manage the weather’s impact on the supply chain, we have developed the first integrated logistics solution for road, sea and air, allowing customers to track and analyze their trucks, ships and planes in real-time and rapidly understand weather impacts.”

Driven by deep innovation, StormGeo’s fleet management solution introduces new analytic tools that can be utilized standalone, or consumed through Application Programming Interfaces (APIs) into customers’ existing platforms. These operational solutions include:

  • Weather impedance calculators
  • Weather route delays
  • Refined ETA prediction

Additionally, the solutions are fully supported by StormGeo’s meteorologists and data scientists through its global network of 24/7 weather centers.

“The cost of weather-related delays in the supply chain accounts for billions of dollars. Companies are looking to advanced analytics to predict and improve weather impact, and that’s where StormGeo can help. Our holistic supply chain solution spans road, sea and air,” Mathew added.

Since its inception, StormGeo has analyzed petabytes of data. DeepStorm™, StormGeo’s machine learning platform, uncovers complex weather patterns in supply chain logistics that:

  • Predict weather-driven price fluctuations in freight contracts
  • Identify potential weather disruption
  • Highlight untapped weather efficiencies

These predictive analytics can identify latent weather efficiencies, and forecast customers’ future freight price exposure, allowing them to buy contracts when the price is favorable. Driven by customers’ own Data Lakes, the result delivers new predictive models that challenge how logistics operates today.