Freight and trucking data: how historical and contract load tender data create a trucking rate predictor

Adam RobinsonFreight Market Blog

freight and trucking data predictive

Freight and trucking data makes for an excellent resource for shippers and logistic service providers (LSPs) alike. The data obtained from historical and contract load tender information creates a valuable tool – a trucking rate predictor. Trucking rate predictors utilize freight and trucking data to provide shippers and LSPs with a wealth of knowledge and actionable insights to streamline strategic positioning. Shippers and LSPs should use freight and trucking data for the very value associated with an accurate trucking rate predictor. And it’s important to know why tendered, non-paid data can add so much weight.

Why lagging data contributes to limited insight into trucking rates

One of the most significant issues plaguing the trucking industry comes from lagging freight and trucking data. Carriers focus on moving as much freight as possible, which amounts to faster invoicing. Sadly, more data, in this case, amounts to a higher risk for error and mistakes in the assumption of where freight rates are headed. While higher tender volumes help boost the industry and the economy, they also create the potential for lagging data that causes the industry harm. 

Think about it. Most predictive analytics functions capture and focus on paid invoices – all the parts that go into completing freight settlement. Unfortunately, carriers and shippers can cause some delays by only paying invoices in the first place, especially for those that leverage outdated systems and technology. This lagging data leads to limited insight into trucking rates. And little insight into trucking rates creates several avoidable problems for carriers. Such problems appear as significant rate deviations, can be inaccurate or lack value within short-term contract commitments and more. These problems begin a trickle effect, leading to even more problems. These include but are not limited to poor asset utilization, higher driver turnover and lost return on investment (ROI). All these issues can dissipate through better tracking of freight and trucking data.

Historical and contract load tender data offer near-real-time data access and analysis

A benefit of utilizing historical and contract load tender data is capturing and analyzing near-real-time freight data. Near-real-time freight and trucking data provides shippers and LSPs with accurate and useful information. Historical and contract load tender data tracking and analysis have proven valuable to understand what to expect. Unlike paid data, tender data can be captured at the execution time. 

Such freight and trucking data grants shippers and LSPs the ability to capture tender data and end delays caused by lengthy freight settlement processes. Additionally, trucking carriers can gauge rate fluctuations better and maximize their profitability. And the significant benefits of predictive analytics have gained a tremendous amount of attention. According to Supply Chain Dive, “The number of supply chain professionals who say they’re currently using predictive analytics at their company has grown 76% from 2017 to 2019, according to a Supply Chain Dive analysis of the annual MHI Industry Report. In 2019, 30% of respondents said they were currently using this technology, up from 17% in 2017.” This underlines that historical and contract load tender data offers enormous value for carriers.

More data streamlines asset allocation to maximize profitability per load

The increase in the utilization of freight and trucking data streamlines asset allocation to maximize profitability per freight loads, create the right mix of long-haul and short-haul trips and more. Shippers and LSPs that can access this freight and trucking data can better manage and track their assets. Armed with the wealth of knowledge from freight and trucking data, shippers and carriers can better coordinate. And both parties maximize profitability, reduce unnecessary expenditures and improve loading and delivery times.

Increased insight from freight and trucking data helps carriers predict rate changes and avoid losses

Increased insight from freight and trucking data also helps carriers predict freight rate changes and avoid losses. Remember that freight rates on various lanes can fluctuate daily (and sometimes multiple times daily). And analytics provides carriers with the tools to improve carrier operations significantly. Carriers use freight and trucking data to track current rates and any changes, both present and past, so they can better predict pending freight rate fluctuations. More accurate freight rate predictions also limit unnecessary monetary losses, if not eliminating them. This means that carriers can improve their preparedness and provide more accurate rates to shippers, meaning more business and more revenue, without abandoning contract freight altogether or attempting to put out the fires within the spot freight market

Capture better freight data and strategic advantage with the right freight forecasting platform

Historical and contract load tender data is a necessary part of shipping technology in the modern age. The value that comes from this freight and trucking data offers a multitude of benefits. However, shippers and LSPs can capture even better freight data and gain a strategic advantage with the right freight forecasting platform. Of course, it also means ensuring that the platform used has a large-enough dataset and is designed to analyze it effectively. FreightWaves SONAR carries those features and even includes a predictive rates app. Request a FreightWaves SONAR demo by clicking the button below.