Replacement Rate Models for Category Management in the Automotive Aftermarket

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.

Miles Driven Forecasting: Not So Fast My Friend

When it comes to forecasting the future I like to think of two quotes from one of the smartest people I’ve ever worked with (the quote may not be precise but hopefully you’ll get the idea).

1. Forecasts are always wrong.
2. Forecasts with longer time horizons are always worse.

David Simchi-Levi brilliant MIT Professor and my former boss at LogicTools (now part of IBM), told me this in person and I’m pretty sure he’s expressed the same idea in one or more of his many now-famous supply chain related publications.

I thought of these quotes immediately when I read a special report published in November by the Automotive Aftermarket Supply Association titled, “Don’t Discount Miles Driven in Long Term Forecasts”.

The Automotive Aftermarket

WHAT IS THE AUTOMOTIVE AFTERMARKET?

If you own a car, there’s a high chance you’ve had direct experience with the automotive aftermarket, whether you realize it or not. Anyone who has had to repair a windshield, replace brakes, purchase new tires, or even buy windshield wipers has participated in the automotive aftermarket, as has anyone who has re-outfitted their car with heated leather seats or a bike rack.

What is It?

Finding Your Way to a Healthy Bottom Line: Applying Geospatial Visualization to your Aftermarket Business

A severe outbreak of cholera was ravaging the Soho neighborhood of London during the summer of 1854. While city leaders and health officials struggled to determine the source of the outbreak, a physician named John Snow had a groundbreaking idea: he used a map of the neighborhood to plot cases of cholera. Ultimately, his method not only revealed the source of the outbreak, but also provided new information about the nature of the disease itself.

Data mapping photograph
Dr. Snow’s work is often considered to be the founding event in modern epidemiology. For me, it’s also a great illustration of the power of a simple map and its ability to illuminate patterns in data. Much like the citizens of London, business analysts throughout the world struggle to understand and diagnose pain points in their businesses. Why are we having trouble keeping SKU# 123 in stock in Morgantown, West Virginia? How can we minimize the cost of getting parts to installers in Wyoming? How can we avoid costly product returns? Sound familiar?

Amazon.com and the Drive to Sell Aftermarket Auto Parts

By now you’ve likely heard the news that Amazon wants a big slice of the aftermarket auto parts pie, and that Amazon has already made deals with some large parts manufacturers — Federal-Mogul and Bosch being a couple of these companies. We have had over a week to digest this news; admittedly it was received with some alarm at first. After all, the thought that this online e-commerce behemoth could chew up and spit out our neighborhood parts stores was a bit shocking.

Many of us, if not nearly all of us, have purchased items from Amazon and may order from Amazon on a regular basis.

Estimating Category Market Demand in the Automotive Aftermarket

Until recently the Automotive Aftermarket was provided data from key channel distributors indicating monthly sales activity and market share for various vehicle part categories. At the beginning of 2012 the consortium of companies that provided these data collapsed.  Since then, parts suppliers and others in the Aftermarket have been searching for a new source of data to fill the void and this very issue is being discussed by industry representatives at the AAIA Fall Leadership Days conference in San Francisco.

Market Demand Forecasting Example

In this post I propose a methodology for estimating market size and discuss how this estimate of total demand can form the basis for replacing, and perhaps improving upon, the market data previously provided by NPD.