Perhaps surprising no one, Schneider recently announced a pay increase for its drivers – on the homepage of its website no less. Many smaller companies have increased driver per mile rates for a while now, but with many carriers forecasting demand that edges ever closer to pre-pandemic levels, driver costs are on the rise.
A quick scan of the truck manufacturing numbers bears this out. In a recent article, American Trucker looks at Class 8 truck production as a strong economic indicator for the industry, and saw that net orders surged in September, hitting 32,000 units — the most since October 2018. September order activity is up 55% compared to August and 160% compared to September 2019.
With all that, the competition between carriers for drivers was bound to heat up. Freight Waves is openly speculating, with probable cause, that this opening salvo by a major operator is sure to spur its competition to match or even exceed the $0.61 a mile Schneider is saying its drivers can make.
Once the large carriers all join the pay fray, they will once again be forced to find other ways to retain drivers as well as rationalize and optimize schedules to increase driver utility. This means filling more orders and generating more revenue to cover additional per mile expenses, all while continuing to maintain other cost structures, as well as service and safety parameters.
Here at BoldIQ, we have seen that customers describe one of Solver’s chief benefits is its ability to maximize utilization of existing assets and personnel, and to do that in real-time. Solver’s preference-based scheduling harnesses the power of operational AI to optimize resources, loads and routes while considering regulations and business rules in real time. In the end, they push more orders through the same or even fewer fleet resources.
For example, in a recent case study we completed with an industry leading supply chain solutions provider, Solver improved order fulfillment by 11%. For carriers this means less spot market activity, clearly a cost saving measure, and for those with large dedicated and for-hire fleets, it also contributes to increased revenue.
Another carrier we worked with wanted to optimize an existing schedule by employing rules that prioritize giving drivers more nights at home as part of a driver retention strategy. This scenario will come likely into play in the new year as it becomes a “drivers” market.
Solver’s operational AI optimized resources, loads and routes while considering regulations and business rules in real time, increasing the total number of miles driven in the same duty shifts by 18.5% and the actual drive time by 18.7%. Preferred drivers were granted their preferred duty shifts and were able to pack more miles into each of those shifts. The result was more pay for valued drivers, and of course more nights at home if so desired.
The bottom line is that with AI optimization, carriers can balance duty hours for drivers evenly if that is the business priority or provide more duty hours to preferred drivers to increase driver satisfaction and retention. Additionally, Solver can prioritize company drivers and owner operators based on the fleet operator preference.
Importantly, Solver’s AI optimized scheduling generates an immediate increase revenue by deploying existing assets to fulfill a greater number of orders. Over a longer period, this results in a corresponding increase in revenue and profitability, and most critically, an edge in this increasingly competitive market beyond just a few cents more a mile.