Natural Demand Analysis Providing Critical Insights to Optimize Future Automotive Market Production in a Post-Pandemic Era
The current imbalance between low supply and high demand in the automotive industry has created unprecedented profit margins on historically low volumes.
ALG, a part of J.D. Power, has a concept of natural demand that quantifies key economic and industry factors to predict critical aspects of automotive supply and demand, creating a more transparent comprehension of registered vehicles required to meet the needs of U.S. car buyers.
Several market factors have emerged through ALG research to generate accurate market forecasts during periods of disruption.
Eric Lyman, ALG, Part of J.D. Power
New vehicle production issues combined with steady demand fueled by continued population growth has created unprecedented profit margins on historically low volumes. The past 18 months have raised many pressing issues about the sector’s ability to sustain this high-octane dynamic. Among them is how industry executives can make the best decisions when conventional key performance indicators (KPIs) are out of whack.
For instance, intuitively, most leaders understand that the current trends are not indefinitely sustainable. The question is: When will market conditions shift in a new direction?
According to the ALG natural demand metric—first developed (and proven) in the wake of the Great Recession—a potential inflection point for the relationship between supply and demand to flip could come as soon as 2024, barring any other major disruptions in the market. While manufacturers and dealers can leverage ongoing supply and natural demand imbalances to support higher transaction prices, it will be necessary for the industry to be prepared for swift adjustments when natural demand is eventually met.
Natural demand addresses pent-up demand from deferred sales during economic disruptions by measuring the need for vehicles by eligible drivers in the United States and comparing that number against annual scrappage rates. A slowdown in new vehicle production and sales will result in higher transaction prices, lower incentives, and potentially fewer vehicles sent to the scrap yard—which increases the average age of vehicles in the U.S. An oversupply yields the inverse: lower prices and higher incentives as automakers force vehicles into the marketplace. The transition from one condition to another can often occur suddenly, catching key players by surprise. In these circumstances, the key is to avoid getting seduced by prevailing market conditions.
This is easier said than done because the industry, collectively, trends toward bad habits regarding sales and production discipline. Ebbs in demand are not always met with appropriate prompt production adjustments, resulting in overcrowded dealerships that ignite a downward spiral in profitability across the industry.
This is where data-driven decision-making comes into play. Automotive executives who properly manage data and predictive metrics can significantly reduce the risk of missing a critical turn in production requirements and inventory.
Hindsight is 2016
In creating the natural demand metric, several market factors emerged through market trends dating back to the 1960s. The analysis revealed high levels of stability in the data patterns preceding inflection points, enabling ALG analysts to accurately generate market forecasts during times of disruption. In so doing, a more transparent comprehension of the needs of U.S. consumers emerged.
The aftermath of the Great Recession put natural demand’s automotive forecast metrics to its first test. In 2012, for instance, natural demand analysis projected that the country would reach an inflection point around Q3 2016.
The prediction bore fruit. In 2016 the industry observed an increase in incentivized spending that validated the formula. However, production continued at a rate that exceeded demand during this period, requiring dealers to create more incentives for consumers to sell the overflow of vehicles.
Situational Awareness Through Predictive Data
Similar dynamics are in play today at an even more dramatic level. ALG’s natural demand equation predicts that supply will exceed demand by the middle of the decade, at which point incentive spending will rise in response.
ALG’s natural demand formula has created three potential scenarios for how automakers will approach the current supply imbalance and consumer behavior:
The first scenario assumes lower scrappage rates and fewer cars per driver. Lower scrappage rates minimize the vehicles flowing out of the market, requiring fewer vehicles to backfill demand. It suggests that record-high prices of vehicles today will result in consumers being more willing to maintain or fix aging cars for extended periods before purchasing new ones.
A second scenario assumes fewer drivers and owners. Fewer consumers would be getting their driver's license or owning a vehicle because of a heavier reliance on rideshare and car-share services. In this scenario, reliance on public transportation, rideshare, and car-share services result in a surge in the number of miles traveled per vehicle, causing a subsequent increase in the scrappage rate. However, the second scenario seems unlikely due to continuing hesitation in the safety of public transportation and sharing services.
The third scenario assumes a continued overall increase in automotive production. If automakers could, they would already be producing more. As shortage issues remain unresolved, automotive manufacturers will have a strong desire to satisfy demand. This scenario is the most logical outcome, but it will take time to ramp up the required production to reach parity with demand. The earliest expectations of achieving that goal are 2024, assuming sales figures rebound in 2022 and 2023.
At this point in the industry’s history, timing will be essential. Natural demand analysis enables the automotive industry to monitor the market’s inventory to benchmark supply, incentives, and vehicle pricing. As pent-up demand nears satisfaction, the automotive industry should heed the overproduction warnings of the past.