Normalization vs Deterioration – What's the Difference?

In our post-pandemic world, the terms normalization and deterioration have developed new fame. The definitions of each term are often subjective and nuanced, and understanding both is crucial to gaining insights from the data they are used to describe. When I am looking at data, whether it be customer, client, consumer or simply sports data, here is how I think about normalization vs. deterioration.

Normalization 

Normalization is the act of returning to a regular pattern or distribution. It is returning to the mean, the average, or regular data trends and patterns. To me, normalization is cyclical, where trends are driven by repeated, well-understood forces. For instance, credit card spending tends to spike around the holiday season and then return to more normal levels in the first quarter of each year. Spring and fall tend to be hot times to buy/lease automobiles given holiday sales (Memorial Day, 4^th of July, Labor Day, and tax credit spending). Both examples show predictable impacts on data for the sector. Normalization indicates the data is presenting a pattern that has been “lived” before, and the trend’s impact on the industry is widely understood. Based on these parameters, it is logical that data deviates slightly above and below what observers consider to be historical norms, but generally fall within an expected range +/- (like standard deviation) over time. Covid caused huge deviations in all sorts of data. Returning to normal patterns is generally a good thing in my opinion, especially after the 2-3 year period we endured where data was all over the graph!

Deterioration

Using deterioration to define data indicates the sector in question is no longer operating in the typical/normal range and the data is now in uncharted territory – a serious cause for alarm. Seeing data patterns that deviate significantly from the norm indicate stressors on the sector are stronger than moderating forces. Signals of deterioration indicate there are structural issues within the sector. Typically, these issues take time work out and will have a negative impact on the sector’s results for some time. Looking at the used auto lending market as an example; consumers are faced with high vehicle prices (thanks to Covid, supply-chain issues, and a crippling lack of inventory) and continually rising interest rates. According to TransUnion, the rise in used vehicle prices over the past two years (+30-40% higher) has led to a significant spike in average loan-to-value data. Higher LTV typically translates into higher delinquency rates. Recent vintage curves for used vehicles reflects significant deterioration in comparison to previous years – meaning more consumers are delinquent on their used car loan than ever before. With the average payment for a used vehicle sitting around $530+, it is no surprise more and more consumers are walking away from their bloated used vehicle loans and causing serious deterioration to show in loan payment data. This is an ominous sign for the health of the consumer and one to keep watch on.

When reading the press, remember that normalization is not always bad or an indicator of market stress. Data is showing a sector is returning to historical norms that may have been thrown off by the pandemic. Deterioration, on the other, is something to be very worried about and taken seriously. Look for signs the data shows stress that has not been seen before, especially before the pandemic timeframe.