Advanced machine learning algorithms are streamlining the freight procurement process by accurately predicting lane pricing.
Freight procurement is a critical function in logistics. Shippers and 3PLs often follow laborious conventional contracting processes to secure reliable capacity and move their loads cost-effectively. The advent of machine learning (ML) technology has altered the game in freight logistics by accurately predicting lane pricing.
Modern ML models based on advanced algorithms integrate dynamic market data and historical freight data to correctly forecast lane pricing. This streamlines the process of freight procurement, ensuring shipper demands are met with adequate carrier capacity.
In this whitepaper, we demystify the freight contracting process and the impact of technology in guaranteeing accurate freight rate forecasting. Dive deep into insights on topics including:
- Factors impacting lane pricing
- Why it’s important to consider dynamic market disruptions while determining freight rates
- Limitations of the traditional freight contracting process
- How machine learning technology has streamlined freight forecasting, driving increased efficiencies and business value
If you are wondering how to integrate advanced machine learning models in your transportation management system to benefit from real-time freight forecasting, download this whitepaper and contact us today.