From transportation control toward predictive orchestration with Mars

Supply chain leaders face constant pressure. Costs are rising, disruptions are more frequent and service expectations remain high. Yet many organizations still rely on fragmented systems and siloed decisions that slow response and limit coordination.

The impact is significant. Disconnected supply chains are estimated to cause revenue losses of 6-10%. Meanwhile, only 5% of companies have successfully scaled AI initiatives and supply chain costs are rising 2-4% above baseline inflation. 

This is not only a systems problem. It is a daily challenge for planners, buyers, customer service teams, and operations leaders who must reconcile conflicting signals and respond to issues after they surface. Those delays are felt across plants, warehouses, retailers, store shelves, hospitals, households and the people and pets that depend on reliable supply.

The issue is not due to lack of effort. It is that today’s environment moves faster than disconnected tools can support. Supply chain technology needs to go beyond visibility and control to help organizations anticipate risk, connect planning with execution and act before disruptions escalate.

Why supply chains need more than transportation control

Transportation control towers have delivered real value through better visibility, execution and cost management. But they have clear limits.

Transportation is often where a problem becomes visible, not where it starts. By the time a shipment is at risk, the cause may already be upstream in demand planning, capacity allocation, inventory positioning or production constraints. In those cases, even a strong transportation response is still reactive.

When teams can only respond after issues appear, they spend too much time on manual coordination and late intervention. Costs increase, service becomes less stable and resources shift toward troubleshooting instead of higher-value decisions.

What supply chains need is not simply more data. They need the ability to turn data into decisions early enough to prevent disruption.

Mars and 4flow: a practical shift toward predictive orchestration

Mars offers a practical example of this. As a global manufacturer of pet food, confectionery and other food products, Mars operates in a highly complex network. In 2020, Mars and 4flow began a 4PL control tower partnership focused on transportation management. The model improved visibility and generated savings.

But it also revealed a deeper issue: many logistics disruptions did not originate in transportation. They were driven by upstream planning challenges. As a result, transportation teams were reacting to constraints that had already formed elsewhere in the network.

That led to too much late-stage intervention and manual coordination. The impact extended beyond transportation costs to suppliers, Mars factories, market warehouses, retailers and ultimately to pet owners. The estimated effect of reactive operations across that ecosystem amounted to millions in avoidable spend.

This insight made one thing clear: the opportunity extended beyond transportation control.

Focusing on a high-impact use case

To move from insight to action, Mars and 4flow identified a high-impact use case: logistics capacity constraints management. The question was straightforward: could future bottlenecks be identified early enough to prevent downstream disruption?

Instead of waiting for execution issues to appear, the goal was to make planning more aware of capacity risk before problems occurred. 

Using optaire, the teams simulated future network conditions to test that approach.

Simulating the future network with optaire by 4flow

optaire by 4flow is a modular, AI-native platform for end-to-end supply chain and logistics optimization. It connects network, logistics, risk and disruption so organizations can improve decisions across planning and execution instead of managing them in silos.

With optaire, Mars could look beyond day-to-day execution and identify potential capacity bottlenecks earlier in the planning horizon. As risks emerged, affected areas were highlighted so teams could focus quickly on the issues that mattered most.

Thanks to optaire’s forecasting engines, mismatches between demand and available capacity could be flagged, while its risk logic evaluated live operational signals to determine which constraints were most critical. At the same time, cost, utilization, and logistics impacts were calculated instantly, giving teams a clearer view of likely business consequences.

This moved things beyond isolated alerts. Not only could teams see that a problem might emerge, but also what was driving it, where it would hit and what it could mean across the network.

From reactive response to preventive action

Using optaire, Mars moved from reactive to preventive network management, achieving an 18% reduction in forecasted unplanned costs while improving service stability and reducing operational troubleshooting.

More importantly, the use case showed what becomes possible when planning and capacity are connected and forecasts are treated as forward-looking risk signals rather than static inputs. 

This is the essence of predictive orchestration: identifying likely constraints earlier, evaluating their network impact and intervening before cost and service issues escalate.

Taking the next step

For supply chain leaders, the Mars example highlights a broader point. The next phase of supply chain transformation is about creating an environment where planning, logistics and risk work together.

While traditional tools often work well in one area, they fail to align the broader network. optaire helps companies detect emerging risks earlier, understand likely business impact faster and evaluate better response options before disruption spreads.

The role of AI here is not to replace human judgment, but to strengthen it. By surfacing the right signals and modeling likely outcomes, it enables faster, more confident decisions across the supply chain.

optaire helped Mars take that step by connecting planning signals, capacity risk and logistics impacts in one environment. That is the promise of end-to-end supply chain optimization: not just seeing what is happening, but shaping what happens next.

This blog is based on a presentation delivered at the Gartner Supply Chain Symposium/Xpo 2026 in Orlando, Florida.