Predicting Demand to Optimize Supply Chain and Logistics for a Shipping Company

Addressing the challenge of accurately predicting demand in ocean trade logistics, Factspan's prediction model brought significant improvements to a prominent shipping company. The solution optimized inventory management, leading to enhanced customer satisfaction, improved profitability, and substantial cost savings for the organization.
Predicting Demand to Optimize Supply Chain and Logistics for a Shipping Company

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    Executive Summary

    One of the largest shipping companies in the world, that offers land, air, and ocean logistic services, wanted to improve their  ocean trade logistics. The company experienced a significant spike in demand post pandemic and wanted to streamline  operations. It was a challenging task as they operated at multiple trade levels (specific geographic region or trade route) and  across multiple trade corridors.

    The client desired to enhance the current inventory management dashboard, which had a prediction accuracy of 40-60% for  demand. Their objective was to assist customers in better optimizing their inventory management for seamless operations. The  team at Factspan used historical data available to build a new machine learning model to boost prediction accuracy and provide  valuable insights for proactive inventory optimization strategies.

    Project Highlights
    • Enhanced ocean trade logistics through improved demand prediction capabilities
    • Optimized logistics for diverse trade operations across multi-trade levels and corridors
    • Enhanced forecasting demand accuracy to 80%+ and reduced inventory costs by 25%
    • Integrated the new model into the existing system without downtime
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