The traditional TMS performs an important function: centralizing your historical data. It provides visibility into events that happen in your supply chain, and the reports and alerts it offers are valuable…but all after the fact.
With recent advances in AI, the industry is shifting toward a new model where technology doesn’t just report what happens – it analyzes, understands, and offers your team advice on what should happen next. It can even help execute that next action.
The result is a more agile operation with faster decision-making and better performance. And while the transition from a system of record to a system of action may seem daunting, the benefits make the effort more than worth it.
Why Shift from a System of Record into a System of Action?
Your TMS is a system of record. It tells you what has happened in your supply chain and provides reports and alerts on those events, but those reports always lag behind real-time occurrences.
In an environment that keeps moving faster and keeps getting more competitive, that visibility on its own is no longer enough. “This model forces transportation teams to spend a lot of time chasing updates, making calls, reconciling information from spreadsheets and emails, and then manually executing corrective actions,” says Greg Price, CEO & Co-Founder of Shipwell.
Allowing teams to focus on more strategic parts of their jobs requires a shift from the system of record model to a system of action. This modern approach builds on the traditional TMS with guiding insights for how your supply chain data should inform future decisions.
Monitor > Recommend > Execute: AI Advances Enable a System of Action
While automation and AI aren’t new to the transportation industry, AI has advanced to the point that it can reason across real-time operational context. Instead of just presenting reports, it can now bring together information from multiple systems, evaluate changing conditions and determine what actions should come next. That level of AI action wasn’t possible even a short time ago.
So how does an AI-empowered system of action work?
“A system of action does things in stages,” notes Price. “First, it monitors all incoming information from across your transportation network. Then it recommends the next best action based on real-time context and defined guardrails. Finally, it helps execute that action with appropriate human oversight.”
A real-world illustration of this in action is missed delivery appointments. In a traditional TMS environment, the system alerts your transportation manager that a truck will miss its appointment, leaving the manager to figure out what to do next.
A system of action, on the other hand, can recognize the risk before the truck misses its appointment, thanks to its continuous monitoring. It can then evaluate the available options, recommend or initiate rescheduling, communicate with the driver, customer and manager, and keep your operation moving smoothly.
Price explains: “The ultimate goal is getting the right goods to the right place at the right time.” AI allows you to do that by responding earlier and reducing disruption. With a system of action, you gain more than just speed – you gain the ability to operate more consistently and scale quickly without increasing your manual overhead. For a supply chain organization that wants to become more agile and remain competitive, that’s crucial.
Choosing the Right Partner Is the Key to System of Action Success
Not every AI solution is built for transportation. Because of the unique needs of supply chain organizations, choosing the right partner is critical to the success of your AI deployment.
“Look for strong governance, transparency and control,” says Price. “Understand how your information is being used and how your partner and AI tool will make decisions.”
Price lists several criteria for evaluating AI providers to ensure you partner with someone who can meet your needs and goals:
- Deep transportation expertise
- A proven ability to execute across transportation workflows
- Governance, transparency and control
- Defined guardrails and human oversight
- An AI solution with high-fidelity, connected operational context
- The ability to tie AI initiatives to measurable outcomes
The effort of finding the right AI partner to support your transportation tech stack pays off in better use of your team’s time. While a generic model can collect data and generate an answer, an AI purpose-built for transportation understands the network, systems, partners, constraints and business rules unique to this industry, so that it can act safely in your operation.
As AI continues to advance, the potential benefits for the transportation industry will become even more exciting. Instead of just telling teams what’s happening (or what’s already happened), it will understand those events in the context of the network, reason through the options to decide what should happen next, and help teams keep freight moving.
That will make getting the right goods to the right place at the right time a much easier goal to hit.
To learn more about Shipwell’s AI solution purpose-built for transportation, visit https://www.shipwell.com/.
