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.
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.
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) 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.
For more information or to arrange a demo please contact Shawn Wills, (303) 956 2848, email@example.com
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.
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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:
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.
This simple question is at the core of what VIO data are all about.
Imagine the entrepreneur who has invented an innovative aftermarket replacement part. The part might fit dozens of different models but, for the sake of a simple illustration, let’s say it only fits the Honda Accord. So, finding out the vehicle population is the same as finding out the size of the market for this new part. And this is the denominator in the equation to calculate market share. Pretty important number, explaining why companies are willing to spend money on VIO.
According to data we downloaded and processed from data.ny.gov, the answer to the question is there are approximately 300,000 Honda Accords in New York state.
Hey, why not give the exact number? Because all VIO data are estimates.
Even if we retrieve the data today, this minute, it would be just a static snapshot of registration records. New vehicle sales in the past month won’t show up. Recently purchased vehicles registered in a neighboring state won’t show up. Recently scrapped vehicles will still be counted. Occasionally people drive to another state and need a repair. Heck, some people register their vehicle in another state…for tax reasons or whatever. Sometimes vehicle registrations are clustered in a corporate or government office location even though the vehicles themselves are spread around the state or the country. It doesn’t matter how hard you try, the best count you can get is an estimate. If you’re thinking you’ll gain significant advantage from obtaining higher levels of precision you may be missing the mathematical forest for the trees.
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Aftermarket Analytics Launches Inventory Analyst
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The Greensheet Issue #18-18 (Full) _ The GreenSheet (1)