The headlines tend to bounce between semiconductor chips and vaccines. But mismatched supply and demand extends into many more channels, nodes, and products.
Each mismatch has its own tale to tell. Yet similar protagonists and antagonists are shared: disrupted production, congested transport, and shifting demand are each and all implicated, even when differentiated as cause or effect.
A recurring storyline: During the first half of 2020, Non-Pharmaceutical Interventions (or less often, disease penetration) interrupts flows of raw materials needed to produce X. Demand for X either plummets or sky-rockets, sometimes each in a matter of weeks. There is a sudden reduction in the number of container ships, air cargo “bellies”, and truckloads available to carry X.
When prior demand resurfaces and unexpected demand surges, re-jiggered production is complicated — especially if product adaptation is required. New inputs are ordered. Some prior orders are canceled. Carriers from macro-maritime to micro-trucking practice prudent self-protection. What once was slick is now sticky. Friction accumulates. Each delayed or rejected load creates more congestion at some critical node and many edges in-between.
Variable (not-predicted) demand plus volatile supply (not Just-In-Time) equals lower velocity flows. Lower velocity reduces overall volumes. More stock-outs emerge. Upstream stock-outs generate wider — sometimes deeper — experiences of volatility. Velocity further declines. Volumes are reduced. Downstream stock-outs proliferate.
Some — enough? — are willing to pay higher freight rates. But many veteran operators have retired (more), their problem-solving skills departing with them. The pandemic has reduced the number of new operators being trained and licensed. Trucks are parked. Many bellies are still grounded. Maritime flows have been snarled for lack of dock space and/or drayage, not to speak of Ever Given’s sudden slant.
Disequilibrium delivers uncertainty, injecting further variability where many already are feeling vertigo. Network theory suggests that in non-linear systems equilibrium ultimately resurfaces through spontaneous and widely shared self-organization around a “strange attractor“. This is often a factor reflecting the system’s abiding preferential attachments. In this case: Profit? Market Share? Survival? Further functional concentration?