Freight Optimization through Freight Matching & Route Planning

Updated: Apr 20

When talking about our product at FreightWeb, we talk a lot about combining our proprietary freight matching and trip optimization algorithms with our SmartRack system to enable 20-30% more capacity per truck. This efficient cubic utilization allows carriers and brokers to pass on some of those margins as savings to shippers; on average, creating 25% in cost savings over a full truckload. The advantage for the shipper is in being able to better forecast their spend with this “pay per use” pricing model. It works especially well when trying to combine and match volume LTL (less-than-truckloads) and partials truckloads (somewhere in that six to twenty pallet range).

So what exactly are these algorithms and how do they solve a part of this puzzle?

Freight Matching

Our freight matching algorithm searches available loads to find optimal matches while considering important factors like deadhead miles, freight size, weight, packing order, revenue and more with the overall goal of maximizing profits. Since these factors will not be relevant across all users, the algorithm filters and weights them accordingly. Using this algorithm, you can take one otherwise unprofitable partial truckload or volume LTL shipment and pair it with another going the same direction to fill the truck up. The algorithm can also identify if the full truckload you have can in fact be a partial load if it were to use our SmartRack System and in addition, can identify other freight to match with it. In contrast to traditional LTL methods where one shipment may be moved on multiple trucks throughout its journey, in this newer “hubless” model, freight never leaves the truck once loaded. This decreases the risk of damage to the shipment without needing to pay for a dedicated truck. You can also use this to build up profitable routes in backhaul lanes that would otherwise be unprofitable.

Rate Estimation

When matching a carrier's own loads together it’s usually pretty clear what the revenue of a load is. However, when considering external loads from brokers, load boards, and the broader market, it can be difficult to quickly estimate the market rate. When considering loads from load boards, many are snapped up within minutes so the ability to generate real-time rate predictions can enable you to act quickly on the best matches. This could be the difference between grabbing the best match at a great rate and wasting minutes on the phone negotiating for mediocre loads. To solve this problem, we’ve built proprietary machine learning algorithms to provide real-time market rate forecasts.

Adding in SmartRacks

Things get really interesting when you add matching palletized freight and real-time rate estimations to using our SmartRack system. On the carrier side, if the racks are being used, you can optimize truck capacity, adding more dollars to your bottom line in addition to saving time and fuel.

Now, if you take the macro view and imagine every truck on the road utilizing this methodology, you can begin to see the positive environmental impact from the overall reduction in CO2 emissions. That’s the future we envision by putting these freight optimization tools in the hands of everyone in the transportation industry; helping save the budget, and the planet, one truck at a time.

8 views0 comments

Recent Posts

See All