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Lithia & Driveway

Is this your company?

Stay away!!!! - Anonymous employee Lithia & Driveway Employee Review

1.0
Jul 1, 2023
Anonymous employee
Recommend
CEO approval
Business Outlook

Pros

You get to have a job.

Cons

40% pay cut since Lithia took over our dealer… so much turnover I can’t keep up with names. Someone in Corporate made up a story of how they believe in the fundamental core values… LOL!!! Don’t be fooled as you’ll just get the promise of success in the future if you stick it through .. all the while you’re getting plastered to a wall. I’ve lost so many customers of 10 years plus because of the Lithia core value. Don’t buy into the smoke show as all you’ll be doing is constantly looking for another job that can pay you for what you’re worth. if you work in service be ready for the non stop lothia lifetime oil changes for 40.00 that make you squat since they change your pay plan to work only on gross.. and at a percentage lower than any other dealer on that note. Just imagine a bunch of rich gay tardes running the show from a far away island infatuated with the cardashians signing your check… they come from Oregon so just think about that.

Explore other reviews about Lithia & Driveway

5.0
Jun 6, 2026
Recommend
CEO approval
Business Outlook

Pros

Love what I do. Great team members.

Cons

Very Hot on summer days.

5.0
May 15, 2026
Recommend
CEO approval
Business Outlook

Pros

Strong exposure to real business data from automotive sales, finance, inventory, and customer operations. Opportunity to work on high-impact analytics that directly affect dealership performance and revenue. Large-scale company with many datasets and business units, which is good for learning business intelligence and predictive analytics. Growing digital transformation initiatives can provide opportunities to work with modern analytics tools and automation.

Cons

Legacy systems and fragmented data sources may make data cleaning and integration challenging. Traditional corporate structure can sometimes slow down decision-making or the implementation of data-driven ideas. Work may lean more toward reporting/dashboarding than advanced machine learning, depending on the team. Stakeholders may prioritize quick operational insights over long-term data science experimentation. A high-pressure retail environment can lead to tight deadlines and rapidly changing priorities.

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