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Supply-chain scenario planning is most useful when it treats disruption as a set of risks that can interact—not as a list of isolated events. Past disruptions can help teams identify familiar risk categories and test their assumptions, but precedent cannot guarantee that a specific event will be predicted or prevented.
Why familiar risks can still feel like surprises
Pandemics, trade disruption, infrastructure and logistics failures, and policy shifts are recognizable categories of supply-chain risk. That does not mean the timing, scale, or precise effects of any particular event are predictable. Caldwell Hart’s article in The AI Journal argues that disruptions can seem unprecedented when organizations have not translated lessons from familiar categories into planning assumptions and action.
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The useful distinction is between predicting an event and preparing to respond to uncertainty. Hart writes: “The role of supply chain leadership isn’t to predict disruption—it’s to build systems and processes that are ready for disruption when it happens.” This is a recommendation about organizational readiness, not evidence that every disruption can be anticipated.
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A scenario built around a single risk can miss how operating pressures compound. A tariff change, for example, could coincide with transportation constraints, a supplier’s capacity problem, or a labor shortage. Planning around each risk independently may leave teams unprepared for the combination.
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Use scenarios to examine how these pressures might overlap and what decisions the organization would need to make. The point is not to enumerate every possible chain of events. It is to identify consequential dependencies and test whether current plans remain workable when several assumptions change at once.
Keep scenarios connected to operating conditions
Static scenarios can become detached from the business they are meant to prepare. A plan based on outdated assumptions about supplier performance, lead times, capacity, or flexibility may offer little guidance when conditions shift.
Hart recommends grounding scenarios in current information about supplier performance, capacity, and risk exposure. Teams can use that information to test whether assumptions still hold and whether the organization has practical options if they do not. This turns scenario planning into a reviewable operating practice rather than a one-time exercise.
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Use technology for analysis and people for judgment
Technology and analytics can help teams assess more variables and explore more combinations of risks. They do not decide which assumptions matter in a particular context or which trade-offs an organization should accept. People remain responsible for choosing relevant scenarios, interpreting what the analysis means, and making decisions.
This division matters because a larger number of modeled variables is not automatically better planning. Analysis is useful when it informs a decision; human judgment is needed to connect model outputs to supplier relationships, operational priorities, and the choices available to the organization.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Make readiness a repeatable process
Preparedness is not a claim that every event can be forecast or every consequence avoided. It is the ability to incorporate new information, revisit assumptions, and revise scenarios as operating conditions change. Hart’s article frames readiness as a continuing capability, not a one-off planning document.
The article is thought leadership rather than an empirical study: it offers no quantified evidence that scenario planning prevents disruptions or that most disruptions can be predicted. Its practical case is narrower and more useful: organizations can apply lessons from recognizable risk categories, examine combinations of risks, and keep plans connected to current conditions.
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