For aftermarket automotive parts suppliers and manufacturers, the likelihood that a particular part will be replaced determines production and inventory. Your company may have invested in Bill Thompson’s IMR survey data in an effort to quantify this crucial part of the puzzle. This mountain of raw data can be difficult to understand. Aftermarket Analytics can leverage your investment in data and turn it into meaningful replacement rate models for your business’s products.
We examine several years of survey data to calculate actual repair rates; we then fit the data to a statistical model that predicts repair rates based on vehicle age and type. This baseline model allows you to assign a replacement rate to any vehicle, no matter how obscure it might be.
Although baseline models provide an excellent starting point for assigning replacement rates, factors create differences in replacement rates, even among vehicles of the same type. Climate, for example, can impact rates. A unique, targeted replacement rate for nearly any vehicle on the road can be created by analyzing the differences between actual and predicted repairs.
The final step in the modeling process is data validation. In order to ensure we are providing the best possible model, we review the predictive accuracy of our findings. After applying the appropriate adjustment factors, we look at how closely our predicted replacement rates fit the survey results. We continue to analyze and make adjustments as needed.