For decades, supply chain leaders have optimized around landed cost. Product cost plus freight, duties, handling and other logistics expenses is a familiar formula and a useful way to measure sourcing efficiency and protect margins. But recent years have exposed a major weakness in that model. Landed cost measures what a supplier costs, but it leaves out how likely that partner is to become a risk or disruption.
Today, risk matters more than ever. Economic pressure, geopolitical instability, extreme weather, regulatory changes and operational disruptions force global supply chains to operate in a state of persistent volatility, just as organizations are expanding supplier and contractor ecosystems to improve sourcing flexibility and long-term competitiveness. In this environment, a broader operational lens is needed.
One way to get there is by understanding landed risk alongside landed cost.
Landed risk expands supplier and contractor evaluation beyond price and logistics to include the operational conditions that influence their stability and resilience. It considers the likelihood that hidden vulnerabilities inside your supplier network could eventually affect production, fulfillment, compliance and/or profitability.
Because in many cases, those vulnerabilities are already present long before disruption occurs.
Safety as a leading operational indicator
One of the clearest examples to include in a landed risk calculation is contractor and supplier safety. Too many organizations still treat safety performance as a compliance matter rather than a supply chain continuity issue. In reality, unsafe contractor environments can directly impact operational reliability through site incidents, shutdowns, workforce disruption, delayed output, lengthy investigations and reputational exposure.
Third-party safety data can be an early indicator of broader operational instability. A supplier struggling with incomplete training records, recurring near misses, inconsistent audits or weak safety controls may also be struggling with workforce turnover, operational discipline and process reliability. Those signals, over time, will affect uptime, production consistency and delivery performance.
Emissions exposure now affects margin
You can see a similar dynamic around Scope 3 emissions. As regulatory expectations continue to evolve across global markets, customers, investors and business partners are placing greater scrutiny on supply chain emissions. High-emissions suppliers can create cost volatility, reporting burdens and sourcing limitations. Procurement decisions are beginning to reflect not only cost and availability, but also suppliers’ ability to support broader compliance requirements and operational objectives. If problems arise, margins can suffer.
Expanding supplier networks
Risk is particularly relevant as organizations diversify supplier networks across regions, contractors and third-party partners. The challenge isn’t supplier diversity itself, but how to evaluate operational maturity consistently across larger and more distributed networks. Traditional supplier scorecards weren’t designed for this level of complexity.
Risk data today is frequently fragmented across many different systems, departments and suppliers. Procurement teams may evaluate cost and delivery metrics. Safety teams monitor incidents and inspections. Sustainability teams track emissions reporting. Operations teams focus on production output. Each function may be working from accurate information, but not from a unified understanding of supplier health.
This fragmentation limits visibility into emerging risk. And as supplier ecosystems expand, this becomes only more difficult to manage manually. Organizations need a way to connect operational risk signals before disruptions materialize downstream, impacting opportunities and margin.
The growing role of AI in supply chain intelligence
Much has been said about the productivity improvements AI can deliver. In supply chain operations, however, AI’s greatest value may lie beyond automation in its ability to synthesize fragmented information and surface risk earlier than humans can at scale.
With volumes of operational data, supply chain leaders are less challenged by data collection and more so by its integration and interpretation. Risk indicators commonly sit across disconnected records and workflows, including incidents, inspections, audit findings, corrective actions, emissions reporting, contractor management systems and operational performance metrics. When this information is viewed collectively, risk patterns begin to emerge. AI is very effective at identifying those patterns.
We’re making progress. In safety today, most teams use AI for automated dashboards and reporting, according to a 2026 study. More advanced use cases, however, can help organizations detect recurring contractor safety concerns across facilities, identify deteriorating operational conditions, surface gaps in supplier controls and flag trends that identify the potential for disruption. Rather than waiting for a shutdown, compliance failure or missed delivery to expose a problem, organizations gain earlier visibility into risky conditions.
When used in this way, with strong governance, AI can help organizations shorten the time between risk emergence and operational response.
Connected intelligence as a competitive advantage
A supplier’s operational reliability, safety performance, emissions exposure and compliance maturity are no longer separate conversations. They influence one another in ways traditional procurement models often fail to capture. Landed cost has helped supply chains optimize efficiency during a more stable era of global operations. But today, resilience has become just as important as efficiency.
Landed risk isn’t a replacement for landed cost. It’s the layer of operational intelligence that organizations increasingly need to navigate volatility before it becomes disruption.
