By Jon W. Hansen, FCIPS | Procurement Insights · October 2026
One war, three swans
The war in Iran began on 28 February 2026.
Within about eight weeks, the world’s largest brewers had named it. In April, Heineken warned of the war’s impact on energy, transport and supply in particular markets. Carlsberg said it was hedged against cost increases for the year and was planning for a continued crisis. By August, Heineken had put the war’s added cost inflation at about €100 million for the first half, absorbed by savings. In late October, the costs began reaching margins: AB InBev named diesel it could not hedge in certain markets as a third-quarter cost, and Carlsberg said it plans price increases for 2027.
For those companies, the war was a grey swan. They saw it, named it and hedged against it. What they could not know was exactly when each cost would arrive.
Now picture an independent brewer with no hedging program. Energy, cans, glass, carbon dioxide, malt and freight all rose from the same source, through different suppliers, on different invoices, at different times. Each looked manageable alone. For a brewer who never saw those strands as one, the same war could arrive as a black swan.
And for anyone who had traced the strands, from Hormuz to diesel, from diesel to energy and aluminum, and from there to the dates each hedge would expire and be renewed at a higher price, the same war was a white swan: a crossing seen coming, with time to act.
One event. Three colors. The difference was never in the event. It was in what each observer had traced.
The swan is in the observer
In May 2025, I wrote: “I don’t believe in black swan events, but I believe in grey and white swan events, especially in procurement and supply chain.”
I am not the first to see that a black swan depends on who is watching. Nassim Nicholas Taleb, who gave us the term, makes the same point with his turkey: the day before Thanksgiving is a black swan for the turkey, not for the butcher. He also called COVID-19 a white swan, because pandemics were expected even if their timing was not.
What I add is the mechanism that moves an event along the scale. Here is the scale as I use it:
A black swan is a crossing of strands the observer never saw.
A grey swan is a crossing whose strands the observer saw, without knowing when they would cross.
A white swan is a crossing the observer traced, with time to act before it arrived.
What moves an event from black toward white is strand recognition: seeing the strands, understanding how they cross, and noticing the one, or ones, that nobody declared.
Why distance and timing decide the color
A tsunami is barely visible in deep water. It can pass under a ship as a gentle swell. It becomes destructive in shallow water near the shore, where its energy has nowhere to go but up. The people onshore did not cause the earthquake. But how early they recognize the wave, and how much buffer stands between them and it, decides whether it arrives as a warning or a catastrophe.
Business works the same way. Hedges, inventories and balance sheets are deep water. They spread a shock out and make the first months look calm. The wave stands up where the protection ends: at the unhedged cost, at the contract renewal, at the business with the thinnest margins.
Distance from the original cause does not mean less impact. The further a shock travels, the more strands it crosses and the less anyone traces it back to its source. A brewer’s cost increase is reported as “the Middle East conflict,” not as Hormuz plus diesel plus refinery strikes plus hedge timing. The causal tie thins. The impact does not.
Strands also fade in and fade out. When Hurricane Isaias made landfall on 9 October 2026, the storm dominated the coverage. Within days, a policy strand, a diesel supply deal and a sanctions waiver, had changed how fuel prices had to be read, and the storm faded to what it was: the meeting point where several strands crossed.
Some strands are primary: they run continuously, like fuel prices, policy and supplier capacity. Others are intermittent: they fade in, cross the primary strands, and fade out again. A storm is one. Recognizing a strand means knowing which kind it is, and noticing when an intermittent one is crossing something that matters. Recognition is not a map drawn once. It is a disciplined methodology and a continuous practice. Maps are static snapshots of what is believed to be true. The real world does not work that way.
What the supply map shows vs. what the storm crosses. On the left, the fuel supply drawn as one route. On the right, the strands it depends on, with the storm as an intermittent strand crossing them at landfall. Shared on 8 October 2026, before Hurricane Isaias made landfall. Illustrative, not measured data.
Recognition is not prediction
Strand Commonality™ holds that seemingly unrelated strands have unique operating attributes that collectively contribute to a single outcome.
It does not predict events. It discovers the strands already in motion. A black swan is rarely a true surprise. More often, it is the crossing of strands nobody had traced.
Discovery has limits, and they should be stated plainly. It does not always reveal when a crossing will occur. And where strands are deliberately hidden or manipulated, recognition is harder. When our multimodel panel assessed three so-called black swans in May 2025, three of four models found the strands of the 2022 war in Ukraine visible from 2014 onward. The fourth found it the most difficult of the three events to read in advance, because the strands that mattered most, intent and military planning, were restricted and distorted.
Others have reached the same ground independently. Andrea Lombardo applied Strand Commonality™ in the Italian logistics magazine Logistica in June 2025, arguing that some events called black swans are better understood as grey swans. In May 2026, Vitalii Opanasiuk and Iurii Mohylevskyi made the same argument in the Kyiv Economic Scientific Journal, applied to COVID-19, the war in Ukraine and the 2026 Iran conflict.
Why strand recognition is the true skill the AI era rewards
AI extends how many strands a person can hold at once. In 1998, I began by following three or four strands at the same time, and within about a year and a half, four to six. With ARA™ RAM 2025™ running on SLAP OS™, it is 10 to 12, and steadily increasing.
But AI works inside the frame it is given. An agent can be grounded perfectly in an organization’s data, definitions and permissions and still be grounded in the wrong operation. In 1998, every record showed procurement as the choke point. The question that found the real problem was “What time of day do the orders come in?” No record contained the answer, and no system would have thought to ask it. In May 2025, I put the challenge directly: how would agentic AI have known to ask that question?
The same thing happened this October. I am not an energy specialist. But because policy had been named as a strand before Hurricane Isaias made landfall, I recognized the diesel deal as a policy matter when it surfaced, not as an energy story. That recognition came from strand logic, not domain expertise.
That is why I believe strand recognition is the skill the AI era rewards most. The tools will keep getting better at processing the strands they are given. The advantage belongs to the people who can see which strands matter, notice the one, or ones, that are missing, and understand how they cross before the outcome arrives.
What the skill looks like in practice
Start from the outcome, not the plan. Ask what result matters, then trace back from it, rather than mapping forward from the process as described.
Look outside your own walls. Suppliers, carriers, customs, regulators and customers are strands too, each with its own incentives and timing.
Ask where the strands cross, and on what clock. A cost that cannot be hedged reaches you immediately. A hedged cost reaches you later, when the hedge contract expires and is renewed at the new, higher price.
Watch for strands fading in. For the brewers, carbon dioxide, next season’s malt and a dormant tariff strand are not yet in anyone’s results. They will decide 2027.
Keep tracing. What the outcome reveals maintains or changes the next decision.
The same event, a different swan
The war in Iran did not choose its color. Each observer did, through what they had traced before it arrived.
Black swans will keep being reported. Most of them will be crossings of strands that were there all along, waiting to be seen. AI will help us hold more of those strands than ever before. It will not tell us which ones we forgot to look for.
That is the work: identifying the hidden strands and aligning them with a business’ operating reality.
Truth Is Believing. Accuracy Is Knowing. Outcome Is Proof.™
Black Swans, Grey Swans and White Swans: Why Strand Recognition Is the True Skill the AI Era Rewards
Posted on October 31, 2026
0
By Jon W. Hansen, FCIPS | Procurement Insights · October 2026
One war, three swans
The war in Iran began on 28 February 2026.
Within about eight weeks, the world’s largest brewers had named it. In April, Heineken warned of the war’s impact on energy, transport and supply in particular markets. Carlsberg said it was hedged against cost increases for the year and was planning for a continued crisis. By August, Heineken had put the war’s added cost inflation at about €100 million for the first half, absorbed by savings. In late October, the costs began reaching margins: AB InBev named diesel it could not hedge in certain markets as a third-quarter cost, and Carlsberg said it plans price increases for 2027.
For those companies, the war was a grey swan. They saw it, named it and hedged against it. What they could not know was exactly when each cost would arrive.
Now picture an independent brewer with no hedging program. Energy, cans, glass, carbon dioxide, malt and freight all rose from the same source, through different suppliers, on different invoices, at different times. Each looked manageable alone. For a brewer who never saw those strands as one, the same war could arrive as a black swan.
And for anyone who had traced the strands, from Hormuz to diesel, from diesel to energy and aluminum, and from there to the dates each hedge would expire and be renewed at a higher price, the same war was a white swan: a crossing seen coming, with time to act.
One event. Three colors. The difference was never in the event. It was in what each observer had traced.
The swan is in the observer
In May 2025, I wrote: “I don’t believe in black swan events, but I believe in grey and white swan events, especially in procurement and supply chain.”
I am not the first to see that a black swan depends on who is watching. Nassim Nicholas Taleb, who gave us the term, makes the same point with his turkey: the day before Thanksgiving is a black swan for the turkey, not for the butcher. He also called COVID-19 a white swan, because pandemics were expected even if their timing was not.
What I add is the mechanism that moves an event along the scale. Here is the scale as I use it:
What moves an event from black toward white is strand recognition: seeing the strands, understanding how they cross, and noticing the one, or ones, that nobody declared.
Why distance and timing decide the color
A tsunami is barely visible in deep water. It can pass under a ship as a gentle swell. It becomes destructive in shallow water near the shore, where its energy has nowhere to go but up. The people onshore did not cause the earthquake. But how early they recognize the wave, and how much buffer stands between them and it, decides whether it arrives as a warning or a catastrophe.
Business works the same way. Hedges, inventories and balance sheets are deep water. They spread a shock out and make the first months look calm. The wave stands up where the protection ends: at the unhedged cost, at the contract renewal, at the business with the thinnest margins.
Distance from the original cause does not mean less impact. The further a shock travels, the more strands it crosses and the less anyone traces it back to its source. A brewer’s cost increase is reported as “the Middle East conflict,” not as Hormuz plus diesel plus refinery strikes plus hedge timing. The causal tie thins. The impact does not.
Strands also fade in and fade out. When Hurricane Isaias made landfall on 9 October 2026, the storm dominated the coverage. Within days, a policy strand, a diesel supply deal and a sanctions waiver, had changed how fuel prices had to be read, and the storm faded to what it was: the meeting point where several strands crossed.
Some strands are primary: they run continuously, like fuel prices, policy and supplier capacity. Others are intermittent: they fade in, cross the primary strands, and fade out again. A storm is one. Recognizing a strand means knowing which kind it is, and noticing when an intermittent one is crossing something that matters. Recognition is not a map drawn once. It is a disciplined methodology and a continuous practice. Maps are static snapshots of what is believed to be true. The real world does not work that way.
What the supply map shows vs. what the storm crosses. On the left, the fuel supply drawn as one route. On the right, the strands it depends on, with the storm as an intermittent strand crossing them at landfall. Shared on 8 October 2026, before Hurricane Isaias made landfall. Illustrative, not measured data.
Recognition is not prediction
Strand Commonality™ holds that seemingly unrelated strands have unique operating attributes that collectively contribute to a single outcome.
It does not predict events. It discovers the strands already in motion. A black swan is rarely a true surprise. More often, it is the crossing of strands nobody had traced.
Discovery has limits, and they should be stated plainly. It does not always reveal when a crossing will occur. And where strands are deliberately hidden or manipulated, recognition is harder. When our multimodel panel assessed three so-called black swans in May 2025, three of four models found the strands of the 2022 war in Ukraine visible from 2014 onward. The fourth found it the most difficult of the three events to read in advance, because the strands that mattered most, intent and military planning, were restricted and distorted.
Others have reached the same ground independently. Andrea Lombardo applied Strand Commonality™ in the Italian logistics magazine Logistica in June 2025, arguing that some events called black swans are better understood as grey swans. In May 2026, Vitalii Opanasiuk and Iurii Mohylevskyi made the same argument in the Kyiv Economic Scientific Journal, applied to COVID-19, the war in Ukraine and the 2026 Iran conflict.
Why strand recognition is the true skill the AI era rewards
AI extends how many strands a person can hold at once. In 1998, I began by following three or four strands at the same time, and within about a year and a half, four to six. With ARA™ RAM 2025™ running on SLAP OS™, it is 10 to 12, and steadily increasing.
But AI works inside the frame it is given. An agent can be grounded perfectly in an organization’s data, definitions and permissions and still be grounded in the wrong operation. In 1998, every record showed procurement as the choke point. The question that found the real problem was “What time of day do the orders come in?” No record contained the answer, and no system would have thought to ask it. In May 2025, I put the challenge directly: how would agentic AI have known to ask that question?
The same thing happened this October. I am not an energy specialist. But because policy had been named as a strand before Hurricane Isaias made landfall, I recognized the diesel deal as a policy matter when it surfaced, not as an energy story. That recognition came from strand logic, not domain expertise.
That is why I believe strand recognition is the skill the AI era rewards most. The tools will keep getting better at processing the strands they are given. The advantage belongs to the people who can see which strands matter, notice the one, or ones, that are missing, and understand how they cross before the outcome arrives.
What the skill looks like in practice
The same event, a different swan
The war in Iran did not choose its color. Each observer did, through what they had traced before it arrived.
Black swans will keep being reported. Most of them will be crossings of strands that were there all along, waiting to be seen. AI will help us hold more of those strands than ever before. It will not tell us which ones we forgot to look for.
That is the work: identifying the hidden strands and aligning them with a business’ operating reality.
Truth Is Believing. Accuracy Is Knowing. Outcome Is Proof.™
-30-
References
Share this:
Like this:
Related