Understanding ORCHESTRATED Collaboration™

Frequently asked questions.

Can you explain how SemiCab works? How does the platform make the most optimal decisions while considering in all the variables at play?

The core of SemiCab’s approach is our predictive capacity optimization engine. On the demand side, the platform predicts demand from shippers in the network across lanes/locations and combines that predicted demand with actual demand to create an aggregate view. On the supply side, SemiCab brings together the actual and predicted locations of carriers’ equipment along with drivers’ hours and duty cycles. The aggregate demand and supply is optimized to create new opportunities for shippers to help them better utilize their own private and/or dedicated fleets, reducing volatility and increasing efficiencies. Demand and supply are continuously evaluated by the engine to be sure the collaboration being orchestrated reflects the most optimal matches that consider pickup, delivery, and  DOT constraints.

The key to our platform's success lies in the AI/ML and optimization models that are:
#1 continuously evaluating the changing demand and supply.
#2 orchestrating collaboration opportunities among shippers and carriers without them having to do anything different.

Does SemiCab use a partner tool for machine learning like AWS SageMaker, or is it internal technology?

The problem SemiCab solves for is unique and has not been adequately addressed at this scale until now. We, therefore, decided to build our own models for prediction and optimization.

How is the SemiCab solution different from other digital freight models?

This isn't your average tactical system that matches trucks with loads and leaves it to the shippers and carriers to do the heavy lifting. We know that technology can boost the benefits of collaboration, but it doesn’t enable it on its own. Our key differentiator is what we call Orchestrated Collaboration™. We achieve this by optimizing aggregate demand and supply across a multi-enterprise network and continuously creating collaboration opportunities for shippers and carriers to work together to increase efficiencies and eliminate empty miles, waste, and volatility. Our shippers don’t have to change a thing to benefit from collaborative opportunities.

Our approach differs greatly from other approaches out there that are focused on matching a single load at a time, don’t leverage the network as a whole, and leave the hard work of collaborating to the network participants themselves.

How long does it take to start seeing the benefits of joining the platform?

We start with an assessment to determine overall value over the course of one to two weeks. We take a look at shipment history: loads, routes, and volumes in the past so that we can better understand a shipper’s needs. By analyzing historical data, we identify domiciles and lanes where we can eliminate empty miles in the fleet or deliver more efficient one-way capacity. This leads to an engagement that may run six to eight weeks, which demonstrates the potential value and identifies the best place to start. From there, we can expand coverage to the rest of a shipper’s network.

How do you deal with inaccurate data from shippers, be it size, weight, special requirements, issues where loads are not ready for pick up when they were supposed to be, or risks of missing delivery appointments?

Operational challenges like this are never going to go away. With SemiCab, our optimization works in real-time, so it is always learning. The predictive piece doesn’t just tell us when the demand is going to come up, it also tells us where, providing insight into where all trucks are going to be at any particular point in time. The advantage of machine learning is that it can predict that something is going to go wrong with a particular trip/load assignment. From there, you can feed that scenario into the optimization algorithm and let it deal with avoiding the issue by reassigning and rerouting.

Another benefit of machine learning is that as issues arise over time, a pattern emerges and from there, we’re able to adjust and learn from it. The combination of prediction through machine learning and continuous optimization is at the core of what we do to ensure we adhere to pickup and delivery windows, carrier duty cycles, and HOS regulations.

Dynamic pricing has become popular recently, is it actually adding value?

Dynamic pricing has a place in some digital freight models, helping address unforeseen fluctuations in demand as long as there is transparency around process and market factors. It is hard for an enterprise to operate exclusively on a dynamic pricing model for all its truckload needs as budgeting for freight becomes almost impossible with this approach. In essence, dynamic pricing really only helps on a case-by-case basis, rather than adding reliable and continued value to the freight network the way Orchestrated Collaboration™ does.

Digital freight models have brought smaller carriers and owner-operators in the ecosystem. Why has that not stabilized the market?

Digital freight models have leveraged technology for creating better matches of loads with carriers by tracking asset location. While this has alleviated the burden of finding a suitable load and partially automated the processes of bidding and accepting loads, it has not fundamentally changed anything from how things have worked conventionally. This strategy still depends on matching one load at a time, retains the transactional flavor, and is not designed to make the overall network more efficient. This transactional approach, in fact, increases volatility as participants try to pursue rates that favor them individually. The antidote to this volatility is to increase the efficiency of the entire network by reducing empty miles, which in effect adds capacity without adding trucks.

How can Orchestrated Collaboration™ help increase private and dedicated fleet utilization?

SemiCab's Orchestrated Collaboration™ enables shippers to manage their transportation without the need to change their process. It helps shippers increase the utilization of their private and dedicated fleets by enabling them to offer their underutilized capacity to a multi-enterprise network.

Since private and dedicated fleets represent a significant part of the overall trucking capacity in the U.S., many shippers decide they need private/dedicated fleets to fulfill their customer service needs, but it is often more expensive than one-way transportation. With the inherent imbalance in each supply chain, these fleets are also frequently underutilized. The only way to increase their utilization is to augment their use with other shippers’ freight, what SemiCab's Orchestrated Collaboration™ enables.

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