US New Vehicle Mix Change

By: Pete Kornafel 

General Motors announced a significant headcount reduction and closing of several plants on 11/26/18.  There are three major factors that led to this. 

One is a flat market for new vehicle sales in 2018.  Rising interest rates have largely killed the zero-rate financing deals, and have increased payment sizes and lease rates for most vehicle purchases.  Absence of major new models also contributes to the flat market. As a result, 2018 US new vehicle sales are up a tiny 0.2%vs. 2017 YTD through October.

Second, there continues to be a significant change in the mix of new vehicle sales.  Figure 1 is a chart from the Wall Street Journal article about General Motors announcement in late November 2018.

Aftermarket Echoes of the Recession

Written By: Pete Kornafel

Most people in the automotive industry are painfully aware that the US recession created huge swings in new vehicle sales a decade ago.  New vehicle sales in the US exceeded 16 million units per year from 1999 through 2007. New vehicle sales fell to about 13 million in 2008 and 10 million in 2009.  They slowly came back but did not reach 16 million again until 2014.  This Created a huge “gap” in the population of vehicles during the recession years.

It did not impact all makes and models equally.  For example Chevrolet Silverado 1500 sales fell from about 500,000 in 2007 to about 300,000 in 2009.  That was just one factor that led to GM’s bankruptcy in 2009.  Silverado 1500 sales continued to fall to below 200,000 in 2010.  As a comparison, Lexus sales dipped a lot in 2009, but fully recovered in 2010 to their 2007-2008 level of almost 300,000/year.

Technology Newsmaker Q&A

Check Out the Q&A with our CEO Justin Holman in Aftermarket Business Word.

Earlier this year, Aftermarket Analytics in Pueblo, Colo., launched its Inventory Analyst tool – a web-based software to help aftermarket companies improve inventory planning. Company CEO Justin Holman recently discussed the new product with us and talked about the challenges of inventory planning…

Read the full article here.

Discover in 90 seconds how you can increase accuracy and improve your margins.

 

10 features of Inventory Analyst, our demand forecasting software solution

 

10. Now you can generate accurate SKU level demand forecasts

9. Cloud based software. Available on the web. Anywhere at anytime

8.Simply upload your part catalog and P2V files for SKU level demand forecasts

7. Easily download your demand forecast reports (CSV)

6. VIO data comes with your IA license – no need to buy third party data

5. Includes one Replacement Rate (RR) category. Additional RR categories available

Justin Holman, CEO of Aftermarket Analytics – Lets Tech Session at AAPEX 2018

Justin Holman (CEO) was delighted to present on the Lets Tech stage at AAPEX 2018.  The topic of his presentation was  “Data Science & Technology for demand forecasting in the Aftermarket”.

Watch the 1 min 44 second summary below featured on AAPEX TV.

https://aapextv.com/list/lg1IwOCf/video/ctKqpal1/lets-tech-sessions-at-aapex-18

For more information or to arrange a demo please contact Shawn Wills, (303) 956 2848, shawn.wills@aftermarketanalytics.com

IA and CEO Justin Holman featured in Aftermarket Business World!

Take a look at the great article and interview by Brian Albright for searchautoparts.com and Aftermarket Business World.

Automotive sector expands investment in inventory analytics

With the number of SKUs expanding and more and more companies moving to an omnichannel model for parts sales, inventory planning and demand forecasting in the aftermarket has become increasingly complex. Companies are turning to advanced analytics tools to help make more accurate and faster inventory decisions. IndustryARC predicts that automotive data analytics market will reach $3.81 billion by 2023, with a compound annual growth rate of 15.4 percent. That growth will be fueled, in part, by the increasing amount of data available from autonomous and connected vehicles or telematics systems.

Read More »

Inventory Recommendations from Spreadsheet to Easy Street

One of our first clients in the Automotive Aftermarket was a manufacturer of replacement parts. They had developed their own in-house methodology for generating inventory stocking recommendations for their customers. They didn’t need us to reinvent the wheel. But, they had problems applying their methodology efficiently.

They had built their system in Microsoft Excel and it was a fairly complicated process to generate SKU-level recommendations. It required a lot of copy-paste to get the right data in the right spreadsheet cells. And the manual data input process led to frequent mistakes and frustrations. Because of this, they had 2 full-time analysts who spent almost all their time waist-deep in the spreadsheet trying to keep up with requests for data-driven recommendations.

We suggested that we take their approach and spreadsheet and convert it into a web application. This had several benefits and a rapid ROI:

Understanding Vehicle Prevalence

In my last post we looked at the population of Honda Accords in New York. We calculated a few descriptive statistics and examined a few data distributions. This helped us get to know the Honda Accord population in New York but there’s a lot more we can do to understand this potential population of aftermarket part customers.

We now know the size of the Accord population but what about the rate of Accord ownership? Where are Accords popular or unpopular? Of course there are more Accords in the New York City metropolitan area where there are millions of people. But where do people own Accords at higher or lower rates? And how do these ownership rates compare with similar vehicles? This may help us avoid having too many or too few parts on the shelf in certain locations.

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?