Supply Chain Resilience

On October 1 ADP reported continued softening in the US labor market. CNBC explained, “Private payrolls saw their biggest decline in 2½ years during September, a further sign of labor market weakening that compounds the data blackout accompanying the U.S. government shutdown.”

On October 3 the Institute for Supply Management reported, “In September, the Services PMI^® registered an unchanged reading of 50 percent, 2 percentage points lower than the August figure of 52 percent. The Business Activity Index moved into contraction territory in September, registering 49.9 percent, 5.1 percentage points lower than the reading of 55 percent recorded in August. This is the first time the index has entered contraction territory since May 2020.” (Here is the complete report.)

Both reports use credible data sources to reach plausible judgments regarding the current direction of travel for demand and supply. The similar direction found by two independent reports reinforces claims of validity. These retrospective indicators are suggestive–but far short of conclusive–for future speed and direction of travel.

The current hiatus in US government data outputs is a meaningful moment to reflect on the role and limitations of data — and related issues of fundamental epistemology and decision-making.

I conceive a ladder of learning consisting of:

Step 1: Occurrence, duration, and variation are simultaneously distributed across space.

Step 2: Observations of Step 1 from different spatial and temporal angles of more or less scope.

Step 3: Qualitative and quantitative measurements of Step 2 that generate usable data.

Step 4: Organizing data by various characteristics to generate targeted, often purposeful information.

Step 5: Contextualizing information by reference to dependent, interdependent, and independent variables to generate knowledge.

Step 6: Carefully and creatively applying knowledge to solve a problem or engage an opportunity.

Whether this ladder ascends to wisdom or descends into foolishness depends on the accuracy and validity of each Step 2-6 and, in my experience, especially on the quality of Steps 5 and 6.

Step 1 is infinite in scope. Subsequent steps attempt to narrow scope to fit human capacity for understanding. Steps 2, 3, and 4 are usually radically reductionist. Observations can be equally valid yet contradictory. Measures can be accurate but exclude crucial aspects of occurrence. Data can be thoughtfully and carefully curated while unable to elucidate known-unknowns, much less unknown-unknowns, or even (especially?) unknown-knowns. Contextualization can be highly contentious as echoes of infinity are reintroduced for purposes of reliable knowledge-making.

When widely accepted that the ladder of learning stands on flooded soggy soil and leans against a rather wobbly wall, the step-wise process can be helpful. Each step offers probabilistic insights for decision-makers to consider, but the ladder does not lead anyone into the delusion of risk free certainty. Problems will escalate and accelerate if certainty is perceived or claimed.

So, more data is better than less. Continued access to well-validated longitudinal data, with known limitations, is particularly helpful (such as BLS, BEA, and Census data). Honest, self-critical, and courageous decision-makers ready to boldly test, but not over-commit, to data-informed hypotheses can accelerate toward wisdom and divert from foolishness. Resilience is most likely to emerge from a humble relationship with reality.

The current absence of government data is unhelpful. There are other sources of data. Quality and quantity of data matter. But the quality and care of decision-making matters more.

According to the Bureau of Economic Analysis, during August US consumers earned and spent a bit more. “Disposable personal income (DPI)—personal income less personal current taxes—increased $86.1 billion (0.4 percent) and personal consumption expenditures (PCE) increased $129.2 billion (0.6 percent).” These are nominal, not-inflation-adjusted measures. The first chart below shows the real, inflation-adjusted, expenditure pattern.

This volume and velocity of demand-pull can sustain strong supply-push, even in the context of significant flow volatility (e.g., here and here and here and here).

In its reporting on August Personal Consumption Expenditures, Bloomberg included, “Services were the driver behind the advance in PCE inflation while goods prices were tame. In particular, prices for recreational goods and vehicles, major appliances and household supplies all declined. Such discounts helped propel spending in those categories.”

The Washington Post explains, “The wealthiest Americans have been doing even better than previously thought — and are driving a consumer spending surge that has been fueling the U.S. economy as they splurge on travel, hotels and dining out, newly-revised economic data shows.” (More and more.)

US consumer spending has been described as “exceptional“, “stubborn“, “surprising“, and “crazy“. But President of the Richmond Federal Reserve Bank, Tom Barkin, says, “… recent data show consumers resumed spending over the summer, especially those with higher incomes. And why wouldn’t they? Unemployment is still low, nominal wages are still increasing, and asset valuations are near all-time highs.”

There are — and have been — indicators of lower spending ahead (here and here). But, so far, actual consumer behavior has earned the adverbs used above. The soon-to-be-upon-us holiday season should be informative. Tariff related price increases seem to be trickling into retail prices. Credit card spending is down from last December (if still historically high). Since the pandemic, consumption by the upper one-fifth of US income earners has seldom shown much sustained restraint. If restraint surfaces the economic reaction — perhaps over-reaction — could be considerable.

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At about the same time I posted what’s above, Bloomberg published a very helpful overview of the global context for August PCE. As I wonder and worry about how long US consumers can continue their recent spending habits, the authors of the Bloomberg report see continued positive potential. “The US economy grew in the second quarter at the fastest pace in nearly two years as the government revised up its previous estimate of consumer spending. The third quarter is also looking solid, with recent reports illustrating resilient consumer spending and business outlays for equipment…” especially in comparison with other major economies.

US retail sales increased in August, even more than expected. See chart below. Bloomberg initially characterized the outcomes with, “consumers are still spending even as tariffs boost the cost of some goods, sentiment remains subdued and the labor market shows signs of faltering. Though wage growth has cooled, many workers’ pay gains continue to outpace inflation, and others, particularly the wealthy, are benefiting from a stock market rally.” This sort of demand velocity should be sufficient to continue recent high volume flows.

Several recent tariff-related conversations have ended-up mostly focused on presumptive motivations for radical shifts in US tariff policy. Supply chain executives want to discern the why behind the what to better frame their own tariff-related decisions. If they can better understand where these tariffs are trying to take us, these executives hope they can develop more resilient supply chain strategies.

I have offered previous explanations of the still emergent tariff policies (here and here and here). But in recent weeks I found supply chain executives much more receptive to a microeconomic framing of these policies.

While President Trump’s approach to tariffs is informed and executed by many others, it is his personal understanding, vision, and enthusiasms that deliver the most reliable “motivational framework” for this administration’s tariff policy. The President’s particular experience in real estate development, branding, and measuring success have significant influence on how much higher baseline tariffs are being conceived and deployed. Three sources of microeconomic leverage are key: 1) product differentiation, 2) premium pricing, and 3) cash flow. Here’s the gist of each:

Product Differentiation: President Trump’s father, Fred, was a successful housing developer in Brooklyn, Queens, Staten Island, Norfolk (Virginia), and elsewhere. Fred’s company constructed, sold, and rented thousands of homes and apartments subsidized by the Federal Housing Administration. Late in the Depression a Brooklyn newspaper called Fred Trump, “the Henry Ford of the home building industry,” developing mass market products at mass market pricing. Over time Fred Trump owned and operated sufficient low and middle income housing and related commercial properties to generate many millions in cash flow. Donald Trump perceived that even better profit margins and more cash flow could be generated serving the aspirations of higher income consumers with real estate that reflected those aspirations. While the father continued to operate in the outer boroughs, his son focused on developing upscale hotels, residences, and offices in Manhattan and diverse formats worldwide. In Midas Touch (2011), Mr. Trump wrote, “building a brand may be more important than building a business.”

Premium Pricing: A luxury brand effectively tethered to the aspirations of a sufficient number of affluent consumers can command profound pricing power. The average purchase price per square foot in Manhattan is roughly $1600, while in Staten Island the average is under $500. A prestige residence in the right Manhattan neighborhood can be priced at $4000 SF and much more. Why build Ford Model A’s when you can sell Pierce-Arrows? The investment costs may be double or triple, but the return on investment can be ten-times or better. In 2024 a $1 million initiation fee was charged for membership in the Mar-a-Lago Club. The Trump Organization has developed nineteen golf properties with similar business models.

Cash Flow: Positive cash flow is a fundamental measure of financial health for any person or enterprise. The more cash flow, the more opportunity for debt-financed growth , self-financed growth, and/or profit taking. In mid-August 2025 President Trump emphasized, “They found last month, as you saw, $25 billion of excess cash flow. They say, where did it come from? I said, I’ll tell you where it came from. It came from a place called tariffs…” (more and more).

In many ways President Trump views baseline tariffs as initiation fees for outsiders to “join” the US economy. (The reciprocal and sectoral tariffs involve additional motivations.) The United States is the ultimate high-end retail destination. US consumers have more and consistently spend more of their disposable income compared to any other large economy (here and here and here). For those with something to sell, the United States is a good place to operate. Charging this “non-resident membership fee” improves US government cash-flows — at a time when the US government’s debt load needs the extra cash. Mr. Trump also tends to view trade deficits as the macroeconomic equivalent of microeconomic negative cash flow. Adam Smith and David Ricardo would disagree. This worldview has nothing in common with what motivated the Bretton Woods system of international trade emerging from the second world war.

President Trump’s motivations for baseline tariffs are much more consistent with mercantilist worldviews of 16th Century Venetians or Queen Elizabeth I of the not-yet-United Kingdom or even of her successor King George III. This original mercantilism could never have nurtured the sort of economic growth experienced over the last two centuries. It is, however, possible — risky but not unreasonable — to deploy the comparative advantage of US consumption patterns in an effort to improve US government revenues and even reclaim some domestic manufacturing capacity and jobs. Pay the non-resident membership fee or buy a residence (i.e., build a US factory) to set up your sales table in this very rich bazaar. (President Trump is also inclined to use reciprocal tariffs as a means of sanctioning “members” that he perceives are behaving unclubbably; see India.)

Will this comparative advantage survive this sort of deployment? So far, higher-income US consumers are continuing to spend (here and here and here). Middle and lower income consumer spending has become more constrained, but not yet enough to tarnish the transactional glitter. Current comparative advantage in large part depends on continued spending by, at least, the top one-fifth of US households. The top quintile’s capacity and confidence to spend is not unrelated to the economic health of the remaining 80 percent. Staples inflation, the dollar’s exchange rate, wage increases, and job stability will all have an influence on that “excess cash flow” celebrated by the President . The 2025 end of the year holiday season will be a significant test of how well US consumer spending persists. Will the US economy’s “product differentiation” remain sufficiently exceptional to justify premium pricing and maximize positive cashflow? If so, supply chain executives should treat this as their strategic context for most of 2026 and well-beyond. If not, I have no predictions (yet) for what is most likely to come next.

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On August 29 the US Court of Appeals for the Federal Circuit found that current baseline tariffs and some reciprocal tariffs are illegal (here and here and here and here). If this decision is not overturned by the Supreme Court, current policy and processes are likely to become even more complicated. But I perceive the President’s existing motivations will persist as long as he views tariff revenue as positive cashflow. As a result, other methods will be found to charge similar and related “membership fees”.

In September 2015 I published an online primer for Supply Chain Resilience. In August 2025 I reviewed and — very slightly — updated this decade-old content. No corrections were needed. No oversights required gap-filling. For my purposes, the principles and patterns set out then still apply today. My revisions consisted entirely of more recent data that confirmed trajectories projected ten years before.

I am pleased. I am also surprised.

For dynamic complex adaptive systems — such as supply chains — ten years is a very long time. Given the shocks and stresses of these particular ten years, I would not have been surprised by some systemic shifts prompted by, let’s say, a murderous pandemic that suddenly and significantly altered the volume and velocity of global product and financial flows.

Instead, networks of demand and supply mostly responded to shock and stress by doubling-down on core characteristics (such as modularity, scalability, clustering, concentration, and betweenness). When and where system operators made decisions coherent with these characteristics, the network almost always responded constructively — even creatively (one example).

Where and when flows failed to effectively adapt there was almost always a pattern of human decision-making (or fear and non-decisions) inconsistent with principles of network fitness (here’s an example and here’s one more). As usual, we have met the enemy and it is us. In Gaza fear and non-action by many suppliers has been an understandable if still consequential choice. Until recently too many executives were waiting for so-called “tariff clarity” to make a choice for them. “The best way to predict the future is to create it.“

This is encouraging. The supply chain results of the last decade demonstrate the potential for realistic, evidence-based principles informing perceptions, choices, and actions.

This is discouraging. The last ten years also demonstrate a recurring human tendency to respond to shock and stress with delusions of control rather than creative collaboration (with reality and each other). There are too often patterns of human choice making bad situations even worse.

There are many different ways to articulate principles of network behavior ranging from poetry (De rerum natura) to management narratives (The Power of Resilience) to calculus and statistical probability (Network Science).

Specific to Supply Chain Resilience, here I will offer:

• Large-scale, high-volume, high velocity networks emerge over-time with recognizable recurring tendencies.
• One such tendency is increasingly concentrated capacity.
• Bad things happen. Catastrophic potential increases as network capacities become more concentrated.
• Human choice can mitigate over-concentration.
• Human choice can constructively respond to consequences of over-concentration.
• Human choice can exacerbate the consequences of over-concentration.
• Effective mitigation and response depend on collaborative, strategic, and operational relationships among high proportion supply chain stakeholders (please see Rules,Games, and Common-Pool Resources or almost anything inspired by Elinor Ostrom).
• Research, mapping, and planning related to Supply Chain Resilience can contribute to mitigation and response when these activities are understood primarily as outreach functions to facilitate collaborative, strategic, and operational relationships. Research, mapping, and planning not deeply connected to relationship-building will be Dead-On-Arrival.
• Transactional networks of stakeholders (such as business-to-business suppliers) can inform and effectuate Supply Chain Resilience choices. Self-interest, mutual and otherwise, is often a meaningful factor in relationship building.
• Sustained and successful collaboration around coherent Supply Chain Resilience strategies and operations depends on shared confidence in the intention, competence, and likely behavior of a critical mass of stakeholders involved.

These are classic principles regarding reality — far beyond supply chains. Centuries of evidence demonstrates that adoption and application of these principles can be quite uneven. Happy collaborations are all alike, every unhappy collaboration is unhappy in its own way (with apologies to Tolstoy).

Happy collaborations are the outcome of consistent, mission-achieving, mindful, risk-informed, other-aware mutual investments made day after day. Approaching the close of her Nobel Prize Lecture, Elinor Ostrom argued, “… a core goal of public policy should be to facilitate the development of institutions that bring out the best in humans. We need to ask how diverse polycentric institutions help or hinder the innovativeness, learning, adapting, trustworthiness, levels of cooperation of participants, and the achievement of more effective, equitable, and sustainable outcomes at multiple scales.”