Although data continues to help proliferate the supply chain, making companies more agile and boosting revenue, there’s one critical area that has lagged behind: logistics. Shippers use data to measure when products are picked up and dropped off and where a shipment is along a given route. But this data only tells half the story, which means logistics managers are missing key insights in order to drive efficiency across freight procurement operations.
From on-time delivery (OTD) to freight cost measurement, there are massive gaps within freight procurement. However, with the right technology, shippers can gain the insights needed to optimize this critical process within the ever-so-important supply chain.
Here are a few areas where data gaps currently exist, and what shippers and carriers can do to help fill the gaps.
Supply & Demand
The freight procurement process has remained unchanged for decades. When contracted carriers reject a shipment, shippers turn to the broker market. Unfortunately, brokers were never in the business to share data. Brokers don’t want shippers to know the current supply and demand landscape, and what the carrier is asking for to haul a load (we define this as true market cost). To overcome this, shippers and carriers are using Data Science tools, such as AI, to track supply and demand to gain a better sense of freight market conditions.
Market Rate Cost
Understanding the true market cost to haul a specific load/ lane is another major data gap. For example, a broker’s hidden margin is added into a shipper’s total cost per load, so the shipper never knows how much the broker versus the carrier is making. In essence, the broker’s hidden margin actually inflates the “true cost” to haul the load. Data Science tools are helping shippers and carriers connect directly to eliminate the need for the non-transparent broker middlemen and provide 100% pricing transparency so the shipper understands exactly what the carrier wants to get paid each time.
Data Interchange
Because supply chain management is a massive ecosystem, technology adaption is slow. As more shippers begin to prioritize data-driven insights, they will look for ways to close the gap between their existing data set and actionable decision-making agility. If the gap remains open, the shipper loses the ability to make important decisions quickly to gain a competitive advantage. AI allows companies to break down these barriers to react in a fraction of the time.
To help overcome new challenges, shippers will continue to dive deep into their current data sets to understand where insight gaps exist. They will also continue to turn to sophisticated data technology and strategies.
For more information on this topic, read “Closing the Logistics Data Gap” published on Dataversity (6/1/21).