Today’s Data Dose: Transit and Wait Times

Today’s Data Dose is an original Transfix series that helps shippers identify the key metrics they should track to get the most out of their supply chain. Which data measurements should an organization prioritize, considering their unique pain points, network, and goals?

We’ve got answers. We’ve got experts.

Metric 4: Transit & Wait Times

The adage “haste makes waste” may generally be true, but when it comes to metrics analysis, time is definitely of the essence. Forming an accurate understanding of the time it takes to move freight can be a big cost saver. Having an accurate picture of wait times for carrier pick-up or delivery should also not be neglected.

“Understanding transit time allows shippers to plan ahead and set the right expectations around when they should expect product to arrive,” says Paulo Moreira, Director of Account Management at Transfix. “From a receiver perspective, this provides time to properly staff facilities with manpower and ensure that there is space to receive product. On the shipper side, knowing transit time gives perspective into how often they need to ship product out and provide forecasts to carriers.

“Having insight into wait times can be a cost saver, not just because it allows businesses to pinpoint where inefficiencies like detention are occurring. Reducing wait times to under two hours is also critical to being considered a shipper of choice.”

Even those companies that don’t hold sustainability as one of their core values may soon find that wasting detention or dwell time hurts their bottom lines—it isn’t just about the high price of diesel. Today’s consumers are mindful of the environmental impact from the companies they do business with, and tons of “detention delay” carbon emissions are not ideal for the customer or the planet. Look to cut down wait times to enhance your ESG reporting.

When a shipper is able to identify markets with notably high costs, this could be because of inefficient scheduling or routes. To give an exaggerated example: a shipper might offhandedly estimate a route through some Appalachian mountains as having roughly the same transit time as a route of similar length through Kansas. That would be a mistake, though, if high, twisting roads take longer than flat land; failing to estimate big time differences like that could lead to spoiled reefer loads or worse.

It may be difficult to create solid time estimates for a route without a database of existing metrics. Perhaps the shipper needs to take into account things like seasonal weather, regional trends, and competition for resources. (This is why Transfix’s software keeps track of key data, analyzing it with AI.) Even without accurate predictions up front, an organization can analyze data from their recent loads to help determine which aspects might be changed to improve future times.

Stay tuned for our next Data Dose, #5: “Payload Utilization.” Click here to learn more about Transfix’s Intelligent Freight Platform.

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