Understanding our Collaborative Transportation Network: SemiCab
Frequently Asked Questions
Read below for answers to all your questions about virtual dedicated capacity, collaborative transportation networks, long-haul freight, and more. And be sure to keep checking back, as we’ll be updating these as we continue to evolve, learn, and grow.
Q: Can you explain how SemiCab works? How does the software, the engine, make the most optimal decisions while factoring in all the variables in the equation?
A: The core of SemiCab’s approach is our predictive capacity optimization engine. It predicts loads from shippers in the ecosystem across lanes/locations and combines that predicted demand with actual loads to have an aggregate view of the demand. Similarly, on the supply side, SemiCab brings together the actual and predicted locations of carriers’ equipment along with driver’s hours and duty cycles. The aggregate demand and supply is optimized to create highly efficient capacity for shippers both for one-way loads as well as private and dedicated fleets with lower empty miles. This is continuously evaluated by the engine for assigning loads, improving empty/loaded miles, and compliance with pickup and delivery windows, all while keeping them within the DOT duty cycles. The key to our platform's success lies in the AI/ML and optimization models that continuously optimize the platform’s performance across the entire network of shippers and carriers.
Q: Does SemiCab use a partner tool for machine learning like AWS SageMaker, or is it internal technology?
A: The problem we are solving at SemiCab is unique and has not really been addressed at this scale until now. Therefore, we decided to build our own models for prediction and optimization to retain the IP and create a better solution.
Q: How is the SemiCab solution different from other digital freight brokers or digital freight marketplaces, like Uber Freight, Convoy, all of them?
A: The key solution differentiator for us is that we optimize aggregate demand and supply on the platform to create efficient capacity with lower empty miles, in comparison with the other approaches out there that are focused on matching a single load at a time. Our approach is enterprise-centric where our objective is to make overall freight capacity more efficient for shippers both for one-way loads as well as private and dedicated fleets. As we work with shippers’ preferred carriers to make them more efficient, shipper-carrier relationships are strengthened for the long-term, rather than being transactional, as is the case with single load-matching solutions.
Q: How long does it take to start seeing the benefits of joining the platform?
A: We start with an assessment to determine overall value over the course of three or four weeks. We take a look at your past history, loads, routes, and what you've done in the past, so that we can better understand your needs. From there, we identify domiciles and lanes where we can eliminate empty miles in your fleet or provide efficient one-way capacity and go through an initial engagement to demonstrate value, a six-to-eight week process; we expand from there to the rest of your network.
Q: How do you deal with inaccurate data from shippers, be it size, weight, special requirements, issues where loads are not ready when they were supposed to be for pickup, or when you have a risk of missing delivery appointments?
A: 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 is not just for when the demand is going to come up, it also includes where it is going to come up, or where the truck is going to be at any particular point of time. The advantage of machine learning is, you can predict that something is going to go wrong with a particular trip/load assignment, you can feed that scenario into the optimization algorithm and let optimization deal with that in terms of assigning and rerouting.
The second benefit of machine learning is that as issues arise over time, a pattern emerges and we’re able to adjust to that 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.
Q: If dynamic pricing is one of the causes for freight marketplace volatility, why don’t shippers and carriers switch to binding contracts, would that not be a way to eliminate volatility?
A: Binding contracts only shift the cost and do not address the underlying issue. The changes in shipping demand simply reflect the natural variability of demand for any product. Binding contracts require commitments that do not model the reality of this natural variability. In addition, trucking supply is not static, since trucks move from one area to another shifting the available supply picture continuously. The solution to this volatility lies in the ability to predict and react to this emerging picture of demand and supply in real time and across the network. This is what we are doing with the technology that is now available. We believe that binding contracts between individual shippers and carriers actually lead to lower network efficiency and higher costs for everyone.
Q: The dynamic pricing approach works in a lot of market segments. Why not in freight?
A: Dynamic pricing has a place in the freight segment as well. It can address the 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 – budgeting for freight becomes almost impossible in this model and transportation is a large part of total product cost for any enterprise.
Q: Digital freight brokers have brought smaller carriers and owner-operators into the ecosystem. Why has that not stabilized the market?
A: Digital brokers 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 the loads, this approach did not fundamentally change anything from how things have worked conventionally. This approach still depends on matching one load at a time, retains the transactional flavor, and is not designed to make the network more efficient. The transparency created by way of making loads and rates visible to all potential carriers and shippers, may in fact, increase volatility as participants try to pursue higher rates and available capacity. 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 the trucks.
Q: Can shippers sign dedicated fleet contracts to address both short and long-haul needs?
A: Private and dedicated fleets represent a significant part of the overall trucking capacity in the U.S.. A shipper takes the decision to go for this solution primarily based on their customer service needs – reliable capacity – and as we know, it can be more expensive than one-way transportation most of the time. With the inherent imbalance in each supply chain, the only way to increase utilization of these fleets is to augment it with other shippers’ freight. In our experience, a many-to-many approach represented by an ecosystem is the only efficient way to address this, not a shipper trying to find complementary freight on a daily basis.
SemiCab is the Collaborative Transportation Network poised to eliminate volatility from the freight marketplace by providing virtual dedicated capacity. Join our ecosystem and start reaping the benefits today.
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