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Comparing Apples and Oranges?

Posted on by Philip J Palin

In late September the Asheville, North Carolina metro area and nearby was hit hard by the remnants of Hurricane Helene  (more). In late October Valencia, Spain and nearby experienced catastrophic rains caused by the high altitude collision of warm and cold air (more) sometimes called a gota fria (cold drop).

Some comparisons:

Asheville Three Day Precipitation Total (September 25-27): 13.99 inches.  But not far away, totals were double and more.  At Busick, North Carolina near Mt. Mitchell over 30 inches were recorded over the same three days (here).

Valencia One Day Precipitation Total) (October 29): 11.8 inches.  A few miles inland — and upstream — the total precipitation was measured at over 19 inches.

Population of metro Asheville:  417,000

Population of metro Valencia: 1,580,000

Asheville Storm-related Fatalities: 42

Valencia Storm-related Fatalities: approaching 200 (still being recovered)

Elevation of Asheville: 2130 feet

Elevation of Valencia: 50 feet

Mean stream level of French Broad River (discharging into the Tennessee River): 1.78 feet.  It flooded to over 20 feet.

The stream level of the Turia River (more and more and more) (discharging into the Mediterranean Sea) is usually less than one foot.  Like the Los Angeles River, during most of the year the Turia runs close-to-dry.  There is, however, a well-known pattern of catastrophic flooding especially in September-October such as in 1957, 1895, and 1776.  On October 29 river levels exceeded 15 feet in some places.

Two very different places experience similar extreme weather.  Disruption, destruction, and death shake both areas. The physical impact on Valencia is more concentrated in time and involves a more densely concentrated population than at Asheville. Consequences are, as a result, amplified.

Comparing Valencia oranges to tart Carolina apples is treacherous.  But once again we seem to confirm that Risk = (Threat x or / Vulnerability) x Consequences. In the case of Asheville and Valencia, Vulnerability was, perhaps, roughly equal (some further vulnerability assessments are needed in both places).  Valencia’s peak Threat was concentrated in one-third the elapsed time. Valencia’s Consequences included at least 3-times more spatial concentration of people.

Demand pulling strong

Posted on by Philip J Palin

The Bureau of Economic Analysis report on September Personal Income and Outlays signaled healthy and growing demand. According to the BEA:

The $105.8 billion increase in current-dollar PCE in September reflected an increase of $72.1 billion in spending for services and an increase of $33.7 billion in spending for goods (table 2). Within services, the largest contributors to the increase were health care and housing and utilities (led by housing). Within goods, the largest contributors to the increase were other nondurable goods (led by prescription drugs), food and beverages, and motor vehicles and parts (led by new light trucks). These increases were partly offset by a decrease in gasoline and other energy goods.

This increased demand was paid for with higher wages (up 0.5 percent from August) and another slight decline in the personal saving rate. Even with strong demand, the inflation rate continued to moderate. The BEA finds, “From the same month one year ago, the PCE price index for September increased 2.1 percent. Prices for goods decreased 1.2 percent and prices for services increased 3.7 percent. Food prices increased 1.2 percent and energy prices decreased 8.1 percent. Excluding food and energy, the PCE price index increased 2.7 percent from one year ago.”

The chart below reflects inflation adjusted “real” personal consumption expenditures. The blue line is total real PCE. The red line is real PCE on Food-At-Home. To be very clear: spending due to inflation has been smoothed out of these outcomes. Overall PCE has recovered its long-term pre-pandemic incremental increase. Slightly more affluent folks expend slightly more on consuming goods and services. This is good news.

The red line is also good news, but more mysterious (at least to me). During the pandemic FAH purchases suddenly surged when Food-Away-From-Home was much less available and other forms of consumption were likewise constrained. But FAH consumption has stayed higher even as FAFH reopened and many splurged on other forms of “revenge spending.” Even while spending much more on eating out and often complaining about grocery price inflation, consumers continue to expend much more on inflation-adjusted grocery purchases than they did pre-pandemic.

Downstream to Upstream

Posted on by Philip J Palin

There is, of course, great variation as scope is adjusted local to global. But in terms of US pull and push, the fourth quarter began in good shape — even very good shape.

Downstream demand as measured by real Personal Consumption Expenditures continues to edge upward (see chart below). Inflation-adjusted wages are above their pre-pandemic peaks and have risen for ten of the last eleven quarters. The personal savings rate has been slowly falling, but is double its 2022 low point. I perceive the US economy is increasingly bifurcated between the top two quintiles (annual mean household income: $123,000 and $282,000) and the bottom three quintiles (annual MHI: $16,000, $46.000, $78,000). But those top two have plenty of power to pull. (Here and here and here and here.)

Upstream production and services have been responsive to this pull. Real Gross Domestic Product per capita has consistently increased since mid-2022 and is more the eight percent higher than its pre-pandemic peak (see second chart below). Non-durable goods manufacturing (e.g., food, fuel, beverages, clothing), banking/finance, and medical goods) have been the fastest growing GDP components. It is still interesting how the Great Recession (2008) prompted a great reset in US production of non-durable goods. Our consumption of refined fuel is slowly declining. US imports of non-durable goods have increased.

Midstream flows are robust — and a bit better balanced than in many years (here and here). Speaking of imports, according to Maritime Executive, “the twin ports of Los Angeles and Long Beach have both posted their busiest quarters ever, as well as all-time highs for the month of September.” This surge includes avoiding the long-anticipated strike at east coast and Gulf Coast ports. Quickly ending — or at least postponing — the dockworkers strike has helped smooth midstream velocities. Rail is tight — tis the season (here and here and here). Trucking markets are tightening. On October 20 FreightWaves reported, “Tender rejection rates on a national level have eclipsed 5% once again, reaching one of the highest levels of the year so far… (but) there is still an excess of capacity in the market.” (see third chart below). Carriers are less pleased than shippers. But consumers appreciate the outcomes of the competitive context (here and here).

Plenty of demand, plenty of production, plenty of flow… from and for the top forty percent or so.

Reductionist Resilience

Posted on by Philip J Palin

On September 23 I posted on a prospective dock strike. Four weeks later I resume blogging following a brief dock strike, two major hurricanes (Helene and Milton), another grim permutation of the Gaza crisis, and plenty of evidence of persistently strong flows — almost everywhere except where most needed.

It is a month-long story of bottlenecks becoming chokepoints.

Post-Helene In the Western Carolinas and Eastern Tennessee chokepoints emerged for water, food, fuel, and more. Food and fuel were unchoked within a couple of days. Water has been much more difficult. In Central Florida the fuel network was seriously threatened by both Helene and Milton. It was hit but did not shatter. Some day we will not be so lucky.

For purposes of Supply Chain Resilience, flow is the motion of specific volumes of selected material intended to fulfill expressed demand (usually effectual demand ) at specific places and times. A flow network emerges from myriad independent agents working to move different materials at different volumes and different velocities while sharing adjacent space, some principal modalities, and many closely connected sources of demand.

So, for example, trucks are used to move various different materials. Regardless of material being moved or the final delivery destination, a high proportion of trucks will often use the same high-capacity roadways, bridges, and truck-stops. Both human-built and natural networks tend toward these capacity concentrations, clusters, nodes with channels, or modules. In many cases the most influential modules co-locate to produce a network with hourglass characteristics.

Here’s how Constantine Dovrolis, a network scientist at Georgia Tech, and his co-authors explain the modularization of hourglass structures:

…many complex systems, both in technology and nature, exhibit modularity: independent modules, each of them providing a certain function, are combined together to perform more complex functions. Additionally, modular systems are also organized in a hierarchical way: smaller modules are used within larger modules recursively. Examples of such systems exist in a wide range of environments: in natural systems, it is believed that hierarchical modularity enhances evolvability (the ability of the system to adapt to new environments with minimal changes) and robustness (the ability to maintain the current status in the presence of internal or external variations). In the technological world, hierarchically modular designs are preferred in terms of design and development cost, easier maintenance and agility (e.g. less effort in producing future versions of a software), and better abstraction of the system design.  

Big flows almost always depend on manifold discreet interactions. A driver needs to get to the fuel tanker truck. The fuel tanker itself needs fuel to go. The truck needs most of its tires to stay inflated. The truck needs roads to be accessible between where it was parked and the fuel rack.  Grid or emergency power is needed to pump the fuel to the rack and into the tanker truck.  The financial transaction system needs to still work or be quickly replaced. Roads to the retail location need to be open. Et cetera, etc.  Each of these independent functions are often modularized to perform more complex functions.

To reduce costs and speed fulfillment, demand bottlenecks are fused to supply bottlenecks becoming an hourglass. Smooth, continual, sustainable, timely flows are the result. But the neck of the hourglass can be especially vulnerable. If the neck is clogged or broken, flow is stopped.

Over the last month, in Asheville, North Carolina, Greeneville Tennessee, Gaza, and several maritime ports, necks were broken. Some healed fast. Some are still being mended.

One example: The Central Florida Pipeline. More than 40 percent of all refined fuels consumed in Florida usually flow through Tampa Bay ports. This Tampa-sourced pipeline supplies an even larger proportion of fuel consumption in the Orlando metro-area. On September 29 Hurricane Helene’s storm surge disrupted pipeline operations for at least three days (here and here). Then on October 8 the pipeline was preemptively shutdown for the approach of Hurricane Milton (more). The gasoline pipe was reopened on Friday night, October 10. The diesel and jet-fuel pipe did not reopen for another two or three days, more precisely when or how is not yet clear to me. I have not yet confirmed the cause for this delay.

Port Tampa Bay, its terminal racks, and loading bays are the fuel hub for Gulf Coast Florida. The Central Florida Pipeline from Port Tampa Bay to Taft Terminal near Orlando International Airport is crucial to fuel accessibility across Central Florida. Continuity of flows from these channels and racks is especially important to support emergency power generation when the grid is gone including for ongoing water pumping and food distribution.

A time-extended – weeks long – loss of the concentrated fuel capacity at Tampa is a complex network adaptation challenge.  If Port Canaveral is (as with Milton) simultaneously targeted/constrained, it becomes almost impossible to meaningfully mitigate lost network capacity. A wide area event impacting the heart of the Interstate-4 corridor (that Milton paralleled slightly to the south) and featuring an extended grid outage, would result in most retail grocery stores being unable to continue operations on emergency power within 48 to 72 hours.  Given other high priority demands on limited fuels, it is even possible that grocery distribution centers would be unable to continue operations.

On October 9 at 0500 eastern the National Hurricane Center reported, “Milton has been maintaining its strength as a catastrophic category 5 hurricane… Damaging winds, life-threatening storm surge, and heavy rainfall will extend well outside the forecast cone… Milton has the potential to be one of the most destructive hurricanes on record for west-central Florida.”  Less than 15 hours before landfall many models included strong probabilities for a route that would have seriously disrupted and perhaps caused a hard stop of fuel and food supply chains serving much of Central Gulf Coast Florida and extending east to Metro-Orlando (more).

On October 10 Mansfield Energy, a national energy distributor, based in the Southeast United States, reported on Milton to its clients, “A last-minute turn southward by the storm helped avert a worst-case scenario for fuel infrastructure of a direct strike on Tampa, with the storm making landfall roughly 40 miles south of the city. Given the storm’s counterclockwise rotation, the worst storm surge came to the south, away from Tampa Bay.”

These sorts of high-capacity, high proportion bottlenecks are core characteristics of contemporary high volume, high velocity supply chains. Other examples are water treatment plants, grocery distribution centers, and major freight routes. When and where these bottlenecks survive, supply chains have lots of options. When and where these hourglass necks are broken, options shrivel.

My reductionist formula for Supply Chain Resilience: Vital bottlenecks are vulnerable to becoming deadly chokepoints. So, find the high proportion capacity concentrations and their essential functions.  Identify the related interdependencies.  Identify Sentinels to help understand and intervene where and when needed.  Watch, listen, think, act. Repeat as necessary.

NOAA Worst Case Projections for Storm Surge at Tampa Bay

Hurricane Helene forecast on afternoon of 9/25

Path of Hurricane Milton

Developed by Bloomberg

Possible Dock Strike Disruption

Posted on by Philip J Palin

In another seven days US Atlantic and Gulf coast ports may be hit by a dock strike. (Here and here and here and here and here and here.)

This possibility has been recognized all year. It is likely that higher-than-usual summertime flows into these same ports reflect supply chain front-loading (more). Recent record volumes arriving into the ports of LA and Long Beach probably represent some proactive redirection of flows (here and here). There is considerable variation — and varied constraints — among alternative freight channels (more and more).

Despite mitigation efforts, any extended strike will seriously disrupt many supply chains. Whenever this scope and scale of flow is disrupted otherwise hidden pinch-points will be exposed. We can watch carefully as the network shudders, shakes, and attempts to adapt. These behaviors and outcomes will help us understand dynamics that are too often obscured. This understanding can help us help the network to effectively adapt.

Even a short strike will prompt network congestion (more). As seen so clearly during the pandemic, this will take considerable time to clear. How much congestion, how far upstream from idle ports is something we can model and anticipate. I will be surprised if anyone can predict anything close to complete outcomes. It has been too long — and the supply chain has changed too much — since the last large scale US dock strike.

How other unions (here and here) and non-union workers react to a dock strike can make a bad situation even worse. But anytime this much capacity is suddenly extracted from midstream flows the outcome will be tough. This labor dispute could slash over half of US maritime flows. Especially when preexisting capacity is concentrated in so few high capacity nodes, resilient options are scarce.

The Biden administration was active and successful in a 2023 effort to avoid a strike of west coast dock workers (here and here and here). It is not yet clear such efforts will be attempted in the next few days (here). But the Biden administration has said it will not invoke a “cooling off period” to delay the Atlantic and Gulf coast labor action. The International Longshoremen’s Association has promised slow-downs if a cooling off period is imposed. The scuttlebutt that comes my way expects a strike (for both good and bad reasons) and once the strike begins expects a painfully long strike (the result of very human reasons — such as pride, anger, and fear — that will intensify the longer the strike continues).

Next week there will still be abundant supplies. There will still be enormous demand. The infrastructure and functionality to match this demand with that supply will persist. In case of a strike, however, network capacity will suddenly be cut basically in half. Demand will often not be fulfilled. Prices for still available flows will increase. Those on strike will not be the only ones losing a paycheck as flows into and out of major ports slow and eventually stop.

+++

September 24 Update: Bloomberg reports, “Just as US policymakers shift focus from curbing inflation to shoring up the job market, the economy faces a jolt that threatens the kind of supply-chain disruption and consumer discontent rife during the pandemic. This time, the shock looms just weeks before a knife-edged election. Some 45,000 dockworkers at every major eastern and Gulf coast  port are threatening to strike Oct. 1. With talks at a stalemate since June, industry officials now believe a strike is inevitable, and ocean carriers and port operators have started sending out customer advisories and making contingency plans.”

US food flows flatten

Posted on by Philip J Palin

Bloomberg reports, “US retail sales unexpectedly rose in August, supported by online purchases that masked more mixed results at other merchants. The value of retail purchases, unadjusted for inflation, increased 0.1% after a revised 1.1% gain in July, Commerce Department data showed Tuesday. Excluding autos and gasoline stations, sales advanced for fourth month.” Good demand is good news for Supply Chain Resilience. A slight decline in retail Inventories (here and here) should also be good news for manufacturers and carriers selling to replenish inventories.

I have particular personal and professional interests in food flows. Below are the retail sales trends for Food Away From Home (blue Line) and Food At Home (red Line). These are nominal dollars. Some obvious observations that are nonetheless worth highlighting:

  1. Both FAFH and FAH are generating sales well above pre-pandemic trends.
  2. Spending on FAFH now seems to have displaced FAH as where most US food dollars are spent. Pre-pandemic this was already true in many (especially urban) places. But post-pandemic consumer preferences (and passed along costs-of-inputs) have accelerated a significant structural shift.
  3. High rates of growth have cooled — since January 2023 for FAH and since January this year for FAFH.

As always, the question is, “Whither goest demand?” Right now it is going fine but flat for food. Behavior in other retail segments do not suggest sustained rapid deterioration is likely anytime soon. But the “mixed results” referenced by the Commerce Department will probably continue as a post-pandemic “new normal” increasingly takes hold.

Supply Chain Summit

Posted on by Philip J Palin

Tomorrow — Tuesday, September 10 — the US Department of Commerce and the Council on Foreign Relations will host a Supply Chain Summit. It is organized to explore proactive strategies to strengthen global supply chain resilience. At the link you can still register to participate virtually.

Rana Foroohar, one of my favorite thinkers and writers, will moderate a morning panel. In today’s FT she writes:

US commerce secretary Gina Raimondo… told me last week that the biggest surprise of her tenure was learning “just how unprepared the federal government was to identify and react to supply chain disruptions, and how unsophisticated the approach to this has been for so long”. Part of this is down to the fact that the entities holding the best and most granular information about supply chains are private companies. They tend to be looking for individual risks in specific areas, rather than systemic issues across the economy. Governments, on the other hand, may be able to identify the need for more resilience in areas that are crucial for economic or national security — such as semiconductors or pharmaceuticals — but have little understanding of the particulars of each supply chain, or how they might interact with areas like logistics, transport, energy or power in the midst of a crisis.

This summit is being hosted to enhance understanding. A Department of Commerce Supply Chain Center has been created. Other federal agencies have created similar functions. Various data gathering efforts and analytical approaches are underway. Over the years I have contributed some thoughts about how to be more data-informed regarding big flows under serious stress.

It is important work. We are early in the work. We need to work smart — both near-term and long-term.

Contemporary high volume, high velocity demand and supply networks are Complex Adaptive Systems — not neat Newtonian machines. The more granular our flow data, the more dynamic — and paradoxically — unpredictable our outcomes. Probabilities can be estimated and assessed. More and better data will improve our sense of probabilities. But strict predictability will remain elusive.

Several weeks ago a client asked me to help them look at an emerging risk to some crucial flows. Other outsiders were also asked to offer insights. I tend to focus on midstream flows, especially the confluence of several flows (aka capacity concentrations). One of the others generated a sizing and siting of downstream — fairly granular — demand. I deduce midstream probabilities from diverse indicators. They induce demand dynamics from specific, carefully curated data sources. I hope to be data-informed. These others are definitely data-driven.

In this particular case, for a host of idiosyncratic reasons, the data sources available were seriously wrong. Unfortunately, the data curators and analysts involved did not have a sufficient contextual understanding to recognize several signals of data deficiency. Instead of running the results, recognizing problems, and trying a different way to slice and dice their data, they generated an authoritative report of initial results.

The client did not need me to point out problems. The client understood their own demand well-enough to immediately suss-out fundamental problems in the data-driven analysis. It was embarrassing for everyone. But quickly recognizing the problems was much better than making decisions off wildly skewed angles on reality.

The client was wise in involving several different angles on their potential problem. The client was wise in not expecting a silver bullet. This client’s senior decision-makers are well-informed regarding context. More than many others, these decision-makers are very curious and consistently humble (somehow those two characteristics seem seldom-enough compatible).

I have seen this client be decisive. But they are, if anything, unusually patient. Their corporate culture values shaping and recognizing the “right time” for making and executing a decision. They watch their flows — upstream, midstream, and downstream. They listen to their suppliers, stakeholders, and customers.

This client brings well-informed, well-conceived deniable hypotheses to potential problems. They actively probe context. They adapt their hypotheses to emerging signals. They act courageously, continue to watch/listen for outcomes, and adjust accordingly. They are not afraid of being wrong. They assume that even when they are right, their actions will create outcomes requiring adaptation. The goal is less a matter of being right or avoiding wrong and much more about being effective in context.

Of course data is needed to make constructive decisions. More quantitative and qualitative data is usually better than less. But no matter how much granular data is eventually gathered by all the fabulous sensors distributed across our 2054 Internet-Of-Things, the decisions to be made — by human wet-ware or the most advanced AI — will still require a sense of context, purpose, and emergence.

Data gathering, creation, and analysis is tough. Synthesizing outcomes in meaningful context to advance constructive purposes is crucial.

Vulnerability can multiply or divide

Posted on by Philip J Palin

The 2024 Atlantic Hurricane Season opened with a big bang named Beryl, the earliest-forming Category 5 storm on record. Outcomes in the Caribbean, Gulf, and east Texas punctuated the forecast for more high-energy storms. But Chris and Debby were mostly rain events. Ernesto saved his worst for the open ocean. Since mid-August, not much.

Axios summarizes, “The Atlantic Ocean is near record warm, and a favorable La Niña climate cycle is developing in the tropical Pacific Ocean. Yet at what is normally the peak of hurricane season, the ocean basin has stubbornly stayed in a deep slumber.” (More and more.) Even as there remains plenty of time, heat, and opportunity for the Atlantic season to re-awaken.

Still, for those of us who begin mornings with NHC maps or ECENS loops, our respect for threat variability and uncertainty has been reinforced. The data models and forecast methods are insightful and helpful. But Complex Adaptive Systems resist precise prediction even as they reward strategic anticipation.

Threat vectors are especially difficult to predict. Potential reproduction rates for gray rhinos and black swans can overwhelm — and in this context our tendency for risk discounting is not entirely self-subverting (if we are self-aware and self-correcting regarding this cognitive vulnerability).

Tropical Storm Ernesto produced plenty of mayhem in the Lesser Antilles, Puerto Rico, and US Virgin Islands. But Ernesto did not reach hurricane strength until north of Puerto Rico and east of the Bahamas. Shipping and swimmers could avoid Ernesto’s threat by not exposing their vulnerability and thereby not suffering consequences.

Threats are multiplied or divided by vulnerability and this outcome is then multiplied by consequence. Electrical grids are innately vulnerable to strong storms, the stronger the storm the greater the threat. The more innately fragile a specific network’s structure, the greater the impact of any threat’s impact. The larger the population dependent on this network, the greater the consequence of this interplay of threat with vulnerability.

The interdependencies of threat, vulnerability, and consequence are highlighted in a recent analysis of global insured risk. Verisk reports, “the average annual loss (AAL) from global natural catastrophes has reached a new high of $151 billion (with non-crop losses making up $119 billion). Additionally, the average exposure growth is expected to be 7.2 percent… ” (See chart below.)

Verisk gives close attention to 1) Rapid Urban Expansion, 2) Surge in Event Frequency, and 3) Climate Variability/Climate Change as principal sources of this exposure growth (amplified by inflation). Climate change is implicated in increased event frequency. Urban expansion has been especially pronounced in places exposed to climate related hazards (e.g. hurricanes, wildfire).

Verisk models for US/Caribbean hurricanes and wildfires project AAL will increase “at least 1% year-on-year for each of these perils due to climate change.” As this threat-level increases incrementally, in some places vulnerability and consequence multipliers can increase much faster. As more people gather in more densely populated places, critical infrastructure, supply chain capacity, and exposed loss potential follow. Even if a hazard’s hitting power remains the same, vulnerability multiplied by consequence makes for a much fatter target. A softball is easier to hit that a baseball. Even I can hit a volleyball. When an unusually powerful hitter encounters one of these fat targets — say an M8-plus earthquake at Memphis or Seattle — take cover quick.

In most of the United States, Japan, and Europe most supply chains are resilient — unless concentrated flow capacity is seriously disrupted or destroyed. I give most of my attention to how supply chains can continue to fulfill demand even when the grid is gone, telecoms are sparse, and transportation networks are fractured. When concentrated capacity survives for crucial products (e.g., water, food, and fuel) restoring flow can be very tough but doable. The vulnerability that is most challenging to mitigate is the loss of a high proportion capacity concentration (or two or three). But even this vulnerability can be reduced if strategically anticipated and meaningfully engaged before the hit is received.

+++

September 7 Update: AccuWeather outlines five reasons for the paucity of tropical storms this season.

July PCE for Food

Posted on by Philip J Palin

In July 2019 residents of the United States, according to the Bureau of Economic Analysis, expended 1, 081 billion “real” inflation-adjusted dollars on Food-At-Home. This July we spent 1, 173 billion real dollars on groceries and related, about eight percent more. With inflation included, in July 2024 we spent almost 26 percent more on groceries than in July 2019. This compares to a roughly 19 percent inflation rate for all personal consumption expenditures. See chart below where blue is nominal dollars expended on groceries and red is real dollars (chained 2017 dollars).

There is disagreement regarding the cause of late-pandemic and post-pandemic inflation. There is even more controversy regarding food price increases (at link see August 28 Update below video). The classic cause of inflation is a mismatch of demand and supply where “too much” demand is chasing “too little” supply. The more time-extended this mismatch the more inflation. The more intense — even price-insensitive — the demand, the higher prices will track.

Before the pandemic many Americans spent over half their food dollars eating away from home. From March 2020 through the end of 2021 spending on Food-Away-From-Home was disrupted. Consumers shifted their food dollars from eating out to eating in. This created a classic mismatch of demand and supply. Food prices increased accordingly (again, see chart below).

What has surprised me is how demand for Food-At-Home has remained well above pre-pandemic patterns even as consumers returned to eating out. By mid-summer 2021 US consumers were spending about the same nominal dollars at “food and beverages places” as we were pre-pandemic (today we are spending one-fifth more eating out than in July 2021). Late summer 2021 we finally stopped spending consistently more real dollars on groceries. Between January 2022 and March 2023 we reduced our real grocery spending by almost five percent. This makes sense. This reflects our return to restaurants, fast food, and other Food-Away-From-Home. I expected this gradual rebalancing to continue.

But by mid-Spring 2023 this spending adjustment stopped. Since this Spring — even as food inflation has flattened — US consumers have started spending more real dollars at the grocery store, even as we spend more more than ever before on eating out.

In late July and early August McKinsey and Company interviewed a statistically valid sample of US consumers. Among the questions asked was, “With regard to products and services you will spend money on, do you plan to splurge/treat yourself over the next 3 months? For example, are there categories of products or services where you expect to make more expensive purchases than normal or purchase something to treat yourself?” Food is the most popular answer, see second chart below. Among Millennials and GenX consumers food is even more a “treat” than for others. According to this and similar findings, food is now less a staple and much more a discretionary expense — even a small luxury.

A supply chain for staples is different than a supply chain for luxury goods. Demand for staples is — or usually has been — less volatile than that for luxury. A paternal great-grandfather was a tailor. My grandfather explained that he became a grocer, “because I was the best dressed kid in school but was always hungry.” But for the last generation “Center Store” — where most of the staples are shelved — has consistently declined as a proportion of total sales. Fresh and prepared foods are the profit leaders. Is Food-At-Home an emerging luxury category? Produce, cheese, olive, and sushi cases suggest yes. The proliferation of and throughput at food banks suggest no.

High volume, high velocity supplies originating from many different places and flowing to many different places with sustained, demonstrable, effectual demand implies an innately resilient system. So far, many luxury-oriented “treats” have been well-integrated into nodes and channels that deliver staples. Center-Store flows have not become appreciably less resilient and supply chains for fresh, prepared, and other periphery-products have become more resilient. Everything is more complicated, costly, and complex (which has resilience implications) and the system-as-system is robust.

The food production and logistics capabilities that supplied my grandfather’s grocery stores could never have fulfilled contemporary density, diversity, and intensity of demand — at any reasonable price-point. Today’s supply networks have demonstrated amazing resilience when 1) effectual demand persists and 2) capacity concentrations continue operations. If effectual demand is lost, but capacity concentrations persist , flows can continue and often will continue unless the network determines demand is not coming back anytime soon.

Loss of upstream or midstream capacity is more quickly and certainly a fatal blow. It depends on context — especially distance from other sources of capacity — but once food networks experience long-term loss of between one-quarter and one-third of capacity, the preexisting flow network is unlikely to survive. A new network may form around surviving push capacity and continued demand pull, but at least in my mind this is less a matter of resilience and much more a matter of triage. It is also true that in the thirty-plus years since the emergence of the contemporary food supply chain we have not experienced anything close to the loss of such a huge capacity proportion for a full network over a wide area. I would prefer to avoid any significant opportunity to prove or disprove this hypothesis.

Demand as Strength and Vulnerability

Posted on by Philip J Palin

Supply is generated, delivered, and sold to fulfill demand. Supply Chain fitness reflects the capacity of upstream and midstream supply to fulfill downstream demand in a timely and affordable way. Contemporary high volume, high velocity supply chains depend on persistent (preferably increasing) demand.

During the month of July real — inflation-adjusted — personal consumption expenditures in the United States continued to slowly expand in a manner that should support Supply Chain Resilience. See the first chart below, where blue is real PCE for services and red is real PCE for goods. Explaining July results, the Bureau of Economic Analysis offers, “The 0.4 percent increase in real PCE in July reflected an increase of 0.7 percent in spending on goods and an increase of 0.2 percent in spending on services. Within goods, the largest contributor to the increase was motor vehicles and parts. Within services, the largest contributor to the increase was health care.”

Reuters reports, “Consumer spending, which accounts for more than two-thirds of U.S. economic activity, rose 0.5% last month after advancing by an unrevised 0.3%… After adjusting for inflation, consumer spending gained 0.4% after rising 0.3% in June, and implied that spending retained the momentum from the second quarter, when it helped to boost gross domestic product growth to a 3.0% annualized rate.” That solid increase in GDP suggests the current level of demand is more than ephemeral. See the second chart below, where blue is real GDP and red is GDP per capita. At least for me this steady increase in both GDP and demand is especially impressive as evidence accumulates that the lower earning two-fifths of consumers are cutting back (even as the highest earning one-fifth spends more, here and here and here).

For those making and moving and selling goods that are purchased directly by consumers, this demand pattern supports continuity, operating efficiencies, and confidence. During 2023 and early 2024 soft freight demand and more excess capacity resulted in a tough freight market. Some excess capacity has since been shed. Improved second quarter demand has resulted in much more sustainable rates in many markets for many carriers. See the third chart below.

Is something close to current demand and supply sustainable? There are known risks. If an October 1 dock-workers strike happens, US freight flows, especially east of the Mississippi will be disrupted. Labor issues and other constraints in Mexico and Canada have downstream implications for the US. Prospects for a China-US Trade War seem entirely plausible (here and here and here). We are in the early stages of a significant re-wiring of global supply chains (here and here). Accelerating US federal debt and interest payments threaten to suppress economic growth (here and here and here and here). Any high-end seismic event along the San Andreas, Cascadia, or New Madrid faults could have devastating long-term impacts on US supply chains. Losing more than one major refinery in the same hurricane season would be a serious challenge (here and here). There are, of course, plenty more Gray Rhinos, Black Swans, and other exogenous exotics.

Supply Chain Resilience is, however, less about any specific threat and much more about systemic vulnerabilities. Such vulnerabilities are almost always the dark side of a significant strength. US supply chains are well-organized around high-volume, high-velocity patterns of demand. Where there is effectual demand, supply chains will scurry to adapt. Any sudden and sustained shift in demand patterns will cause cascading complications, disruptions, and delays — as seen during the pandemic. As also demonstrated in 2020-2022, those supply chains with the best understanding of and engagement with demand dynamics are the most effective and agile at adapting.