Recently I posted an article to the Aftermarket Analytics blog about replacement rate modeling in the automotive aftermarket. It’s a sizable post, worthwhile for anyone interested in demand modeling in any industry. I’ll post an excerpt here, but head over to the post to get the full article and images.
“An important piece of the automotive aftermarket category management puzzle involves an understanding of your category’s replacement rates. Replacement rates, which are also referred to as repair rates or failure rates, are essentially an estimate of the likelihood that a vehicle will need to a replacement part due to failure or normal wear and tear.
So, how should replacement rates be calculated?
Well, it starts with determining an appropriate numerator and denominator. The denominator should represent an estimate of the total population of vehicles. The numerator should represent an estimate of the total number of vehicles that required a particular part replacement.
As I understand it currently the two most common ways of calculating replacement rates go something like this: (1) replacement rates are simply calculated using a consumer survey where the total number of a particular vehicle in the survey is used as the denominator and the number of repairs/replacements reported is used as the numerator; or (2) some data/technology providers generate replacement rates based on repair shop part “look-ups” – meaning how frequently a part is queried in an online database of parts. So the number of look-ups is used as the denominator and the number of reported repairs/replacements is used as the numerator.
I don’t like either approach.”