Big data and predictive freight rates in the digital supply chain are nothing new. Nearly all shippers, brokers and carriers collect and use data to derive insights, including predictive rates. Unfortunately, the most robust applications of that data will quickly diminish in value as data ages. Old data can point to changing market conditions that do not reflect observed conditions. Regardless of segment, the need for technology and insight via real-time predictive freight rates that can explore the specifics are critical to success. And as reported by Supply Chain 24/7, “Leveraging technology, shippers are able to see regional trends and specific lane cost information, as well as driver preferences, while carriers have access to details like loading/unloading times and lane history data.” Let’s take a deeper look at the costs of lagging data versus the opportunities of real-time data-based rates and how they can be measured for their accuracy too.

The challenges and setbacks caused by lagging data

On average, bad or outdated data costs an average of $15 million annually in lost earnings, says the Global Marketing Alliance. Failures to understand the severity of the problem can quickly amount to massive waste across different sectors, particularly in transportation procurement and execution. 

For instance, paying an extra $100 per freight load may not seem like a major overpayment, but applied over a year, coinciding with extreme growth in e-commerce, the costs grow more severe. In other words, a lack of accurate and insightful data means it’s even more challenging to find the best transportation rate. Even worse, predictive freight rates using outdated data may do more harm than good. 

To further drill into this example, consider an individual lane with high market volatility. While shippers may be only overpaying a few cents per mile in a low-volatility market, the stability of that market is still strong. So, they’re essentially paying extra when a lower rate may be available among other carriers. The secret, here – mapping the trucking market – is to know when that happens and preempt it, which is why more shippers have turned to mini-bids to escape the confines of locked-in rates and applying real-time data to stay both strategic and tactical.

Real-time data and predictive freight rates promote end-to-end supply chain benefits

Real-time data allows organizations to identify their most at-risk moves. Risk can also be a misnomer today. Traditionally, risk is associated with negative outcomes and conditions. However, objective risk management implies seeing both the threats and opportunities to improve the supply chain. That amounts to using analytics to save on truckload procurement with better freight rates, to avoid problems securing capacity and to stay tactical with up-to-date insights. Why?

The value of real-time intervention is paramount to the supply chain, noted another Supply Chain 24/7 article. “Analytics point out the opportunities that are ripe for improvement and applied across a real-time collaborative logistics platform. Analytics can help companies review order-to-cash process cycles, expectations for demand, review available inventory, and better manage interactions with partners and customers. As a result, the likelihood of financial losses and out-of-stock issues decline.”

The consideration of freight analytics can only go as far as the size and validity of the data analyzed, so all predictive freight rates need to have as much useful data as possible – and data that’s reflective of observed market conditions.

Using real-time data to measure analytic validity and boost routing guide compliance with tactical mini-bids

Enterprise shippers can apply accurate predictive freight rates to preempt issues that might cause delays or setbacks. That occurs by knowing when to increase the per-mile rate to reduce risk of tender rejections, identifying which lanes are likely to experience routing guide failures due to volatility and more. At the same time, any attempt to initiate a new onboarding process, even through a mini-freight bid, is futile without a way to view how accurately those very metrics aligned with market conditions. But by capturing freight data and using it to create meaningful predictive freight rates, it’s much easier to recognize the best versus the worst lanes and moves. As such, real-time data and mini-bids go hand-in-hand to empower shippers with the insights needed to make tactical negotiations a reality.

Summary: Tactical transportation advantage rests with accuracy and accountability of actionable data

The best transportation management strategy uses data, and that data must be accurate, valid and timely. With disruption the new normal in logistics management, more organizations and enterprise shippers are turning to intuitive and easy-to-use platforms like SONAR and SONAR SCI. These resources unlock predictive freight rate insight and value with real-time data and proactive intervention across a full suite of indices, analyses and easy-to-use resources. Request a FreightWaves SONAR demo to get started, and unlock the most value by further requesting a FreightWaves SONAR SCI demo today.

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