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Lithia & Driveway

Is this your company?

GM Level Leadership: Beyond Questionable. - Manager Lithia & Driveway Employee Review

2.0
Aug 1, 2023
Recommend
CEO approval
Business Outlook

Pros

Health Benefits. Honestly, that’s about it.

Cons

Where to start. GMs are given free rein, stuck with a horrible GM, you are screwed. Start - Lithia buys store. Promises blue sky’s and minimal changes. 6 months - Most good folks gone, pay cut, all new processes/software implemented. 1 year - Lithia corporate cracks down on each GM/store for more profit, introduce lot rent, etc. From there, the downfall and exodus of the last few good folks left standing. GM’s cut everyone’s pay to make corporate happy and pad their own pockets, thin out key roles, overwork you, you get the picture. Lithia is too big for their own good. Decisions are made by board rooms of folks who have probably had their cars delivered to them by a car concierge for the past 20 years and the only time they have every stepped foot inside a real dealership is to show face for a PR event. Just look on any/all job board in any city, every Lithia store is always hiring - reason each store is a revolving door and top talent has gone elsewhere.

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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