Q&A: How AI powers an AI-Native Transportation Management System for Fleets — Workforce & Payroll

1. How does AI simplify payroll in trucking?

AI can simplify payroll in trucking if it feeds off data that is collected by a transportation management system in the delivery process. State-of-the-art transportation management systems feature native driver workflow capabilities where the TMS allows collecting data from the driver either through the telematics in the truck or through digital workflows or work forms that require the driver to collect certain data. All of this constitutes activity data that can be used in the generation of automated driver payroll calculations. While data is the precondition for automation, automation can also introduce errors if data is not validated. Artificial intelligence algorithms can be useful to flag potentially incorrect data. For instance, if a driver requests a $120 lumper payment but the lumper payment ticket only shows $80 in lumper fees, the fee request can be flagged and adjusted or even excluded from the pay statement. AI techniques will be used to extract the actual payment amount from the lumper ticket.

2. How can I optimize dispatcher workload with automation?

Dispatchers are one of the most valuable human resources in the fleet, effectively functioning as the brain of the entire operation. The productivity of a dispatcher can be measured by the number of loads dispatched and the quality of their decisions in terms of fiscal impact. Historically, fleet owners and managers had to hire additional dispatchers to be able to scale a fleet. For fleets where dispatchers are highly specialized or otherwise hard to come by, this may not be an option. So, improving productivity and quality may be the only way to think about improving the scalability of a fleet.

Optimizing the workload of a dispatcher requires thinking of the "cognitive load" a dispatcher can take; this means thinking of the mental bandwidth a dispatcher has as limited and allocating tasks to dispatchers where their human capabilities are most valuable and hard to be replaced by a machine. This also means protecting their bandwidth from menial tasks that accept mental processing power and result in depleting finite cognitive capabilities, like attention span or even willpower.

Transportation management systems often do a disservice to dispatchers in this regard. The set of tools they offer dispatchers are rarely of help. Think about making planning decisions about scheduling in a list view or decisions about routing on a list view. These tasks would be mentally less strenuous if completed on a calendar or a map. But even load entry or driver management activities can result in depleting mental capabilities. Old TMS are manual in that regard and offer limited predictive capabilities that can free up dispatcher productivity and quality decision-making.

Modern TMS, on the other hand, differentiate in how they offer dispatchers a workspace that effectively reduces their cognitive load and directs attention to what really matters. They automate order entry, suggest assignments, schedules, and routes, and offer visual interfaces that can allow adjusting smartly and swiftly. Finally, predictive alert functionality makes sure that dispatchers only spend time on handling exceptions rather than checking on 90% of the drivers where everything is all right.

3. What is the best way to manage driver schedules in real time?

Driver schedules are best managed in real time by integrating ELD data with load planning, driver activity data from driver workflows, and payroll calculations. ELD data provides the necessary HOS constraints that drivers are required to comply with by law. Load data and driver activity data constitute the ever-changing assignments of tasks a driver must complete to earn a paycheck. Payroll calculations can be automated off ELD data, load data, and driver activity data. Many fleets start using ELD data to automate certain payroll calculations, as it incentivizes drivers to be compliant in using their ELDs.

4. How can I integrate my TMS with payroll and compliance tools?

Modern transportation management systems (TMS) seamlessly integrate with payroll and compliance tools through native APIs. Whilst with older systems the connection between a TMS and a payroll or compliance system would live outside of the TMS and require a third party to connect, modern systems that are architected as multi-tenant systems have a native integration layer that connects directly to the payroll and compliance tools. In a multi-tenant system, all users share the same infrastructure (although data is of course segregated), and therefore once an integration into a payroll or compliance platform is built, such integration can usually be cost-efficiently extended to other fleets, reducing the total cost of owning such an integration for an individual fleet.

Hans Galland is the founder and CEO of BeyondTrucks, a vertical SaaS provider of Transportation Management System (TMS) solutions. A serial entrepreneur in real estate, investment banking, and logistics, he received the Gold Stevie Award for Best Entrepreneur in Transportation for advancing AI-native innovation in trucking.