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Supply-chain disruptions can feel unprecedented without being wholly unforeseeable. The useful distinction is between predicting the exact event—which leaders cannot reliably do—and preparing for familiar categories of risk by applying lessons from past disruptions. That is the central argument of Caldwell Hart’s 28 August 2026 article in The AI Journal, “There’s No Such Thing as Supply Chain Surprises—Only Unused Precedent.”
What “unused precedent” means for supply chains
The headline is deliberately provocative: it does not mean every disruption can be predicted or that every event has an exact historical match. Hart’s point is that many shocks belong to recognizable categories, including pandemics, trade disruption, infrastructure and logistics failures, and policy shifts. A new event may differ in scale, timing, or circumstances while still testing capabilities that earlier events exposed.
The failure, in this framing, is not necessarily a lack of information about the past. It is failing to turn prior experience into planning assumptions, operating processes, and decisions that can be used when conditions change. Hart summarizes the leadership task this way: “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.”
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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Plan for interacting risks, not isolated shocks
A scenario built around one risk at a time can miss the way disruptions compound. A tariff change, for example, could coincide with transportation constraints, supplier capacity problems, or labor shortages. The planning question is therefore not only what happens if one assumption fails, but how the organization responds when several pressures arrive together.
Map the dependencies
Identify which suppliers, routes, facilities, and operating decisions are exposed to each risk. Then look for shared dependencies: a supplier and a transport route may appear to be separate exposures but could both be affected by the same regional or policy change.
Test combinations that change decisions
Use combinations of risks to examine whether teams would make different sourcing, inventory, logistics, or operational choices. The purpose is not to enumerate every imaginable event. It is to expose where a plausible combination would overwhelm an assumption or leave decision-makers without a workable response.
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Keep scenarios connected to operating conditions
Scenario planning loses value when its assumptions drift away from the business. Hart advises testing assumptions about supplier performance, lead times, and operational flexibility, and grounding scenarios in current information about supplier performance, capacity, and risk exposure.
That shifts the exercise from a static document to a continuing management practice. Teams can use changes in supplier conditions or capacity to revisit the assumptions that matter to their scenarios. The key is to connect information to decisions: a data point is useful when it changes an exposure assessment, a response option, or the timing of a choice.
Use technology for analysis; keep judgment with people
Technology and analytics can help teams evaluate more variables and explore more combinations than a manual exercise can easily handle. They do not decide which assumptions are relevant to the organization, interpret every contextual factor, or make trade-offs on leadership’s behalf.
People remain responsible for choosing the scenarios worth examining, understanding what the information means in context, and deciding how to respond. Treating an analytical output as a prediction would go beyond Hart’s argument: the aim is to support readiness under uncertainty, not to promise a precise forecast.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Make readiness repeatable
A one-time workshop can identify gaps, but it cannot keep scenarios aligned with changing supplier performance, capacity, and risk exposure. Hart presents readiness as a repeatable capability: incorporate new information, review the assumptions behind plans, and revise scenarios over time.
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That approach does not remove uncertainty or ensure that disruption can be prevented. It gives the organization a structured way to apply past lessons and update its preparation as operating conditions change. Hart’s article is thought leadership rather than an empirical study; it offers recommendations, not measured proof that scenario planning prevents disruptions or quantifies its effect.
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