“When dealers band together, no crisis can win.”
We used to say it a lot more often when COVID, chip shortages, and inventory chaos were every other headline. Lately, the conversation has shifted to affordability, and once again the entire industry is showing what happens when alignment replaces finger-pointing.
At the J.D. Power Auto Summit, the focus turned to inventory, specifically how dealers can use data to move units faster in 2026. The panel broke down the data behind configuration, turn rate, and margin, then tied it back to dealer decisions.
On stage were:
Doug Betts, President, Automotive & Dealer Solutions, J.D. Power (Moderator)
Jason Skerse, AI Solutions Product Management, J.D. Power
Mike Stanton, President & CEO, NADA
Here are the big takeaways.
Vehicle configuration complexity is slowing down dealership sales velocity
J.D. Power pointed out what every dealer already feels: the industry is drowning in versions. Excluding color, there are roughly a million configurations across vehicles in the market. Some single models can have 1,500 variations in a segment.
That kind of spread creates inventory risk. It also puts dealers in a familiar spot: expected to stock “what the market wants,” while dealing with a menu so long it turns ordering into guesswork and reconditioning into punishment.
How can dealers reduce configuration complexity and stock the right builds in 2026?
Reduce your active build list. Pick the trims and option packages that reliably sell in your market.
Create a “core builds only” standard by model line, then enforce it. Exceptions should be rare and intentional.
Review slow movers by configuration, not just by model. “This package mix sits” is useful.
Dealer inventory that matches shopper demand increases close rates
J.D. Power pulled from its Sales Satisfaction Index (SSI) data and landed on a simple point: customers notice when you have the exact vehicle they want.
One of the top reasons buyers purchase is that the dealer had the exact configuration. One of the top reasons they do not is that they could not find the configuration they wanted, even if they liked the vehicle.
Translation: a full lot does not help if the mix is wrong.
How can dealers track shopper demand and improve inventory match rate?
Track lost deals by feature. Not just the model they walked on, but what they wanted that you did not have.
Standardize your “what are you looking for” intake: must-haves, nice-to-haves, and payment target, then feed it into ordering.
Stop calling it preference if it repeats. If customers keep asking for the same packages, that is demand.
Dealer and OEM survey data shows configuration overload hurts inventory planning
The panel shared results from a dealer survey and an OEM survey focused on configuration complexity and its impact. Both sides landed in the same place: the growing list of configurations makes it harder to match shoppers and harder to manage inventory.
That matters because it opens the door to better conversations with your OEM and your rep group. Less posturing. More proof.
How can dealers use data to get better OEM allocation and ordering support?
Bring two lists into every OEM call: more of this (fast turns + strong gross) and stop sending this (slow turns + incentive dependency).
Ask for market-level guidance, not national averages.
Share configuration performance inside 20 Groups and regional circles so stores stop repeating the same mistakes.
Configuration-level profit and turn rate data explains aged inventory
One slide did a lot of heavy lifting: a profit matrix where each dot represented a specific configuration. The chart separated builds that sell faster and hold margin from builds that sit and erode gross.
And yes, the ugly dots were still being ordered. That is the part dealers live with every month: vehicles that burn floorplan, become discount magnets, and create pressure to move metal in ways that train customers to wait.
How can dealers identify and stop reordering slow-selling vehicle configurations?
Build a do-not-reorder list tied to aged inventory by configuration.
Tag every aged unit to its build decisions. Which options turned it into a slow mover in your market?
Set a time-based trigger: at X days, that build goes under review before it shows up again.
Regional vehicle demand data proves the same build sells differently by market
The panel showed a regional example where one configuration averaged 63 days to sell in one market and sold faster in another. Nothing about the vehicle changed. The buyer mix did.
This is where dealers get burned by broad guidance. The build that flies two states over can hang around your store long enough to start collecting dust and interest.
How can dealers use market-level data to build inventory that sells faster locally?
Break turn rate down by configuration inside your PMA.
Compare against local competition. Sometimes your configuration sits because a competitor offers a cleaner package at the same payment.
Commit to local winners. If a package mix performs in your market, lean into it and repeat it.
AI and predictive analytics can improve dealership ordering decisions
The panel addressed AI in the only way that helps dealers: analysis at a level humans cannot do quickly at scale. The point was spotting patterns across configurations and markets to reduce guesswork.
They also referenced the advantage of simplified lineups and integrated systems, calling out why some newer models are built for speed: fewer combinations, tighter control, cleaner feedback.
How can dealers use AI-driven inventory insights without adding more dashboards?
Ask your vendors or OEM tools for configuration-level days supply, gross trends, and market recommendations.
If your tools cannot do that, start smaller: top 10 fastest configs and bottom 10 slowest configs by model line.
Review monthly and adjust ordering quarterly.
Dealer-OEM communication improves when inventory decisions are backed by data
Mike Stanton framed the OEM-dealer relationship as long-term and sometimes tense, and that is normal. The useful part is where the tension gets pointed at the right thing: data-backed decisions instead of assumptions.
If a build keeps landing on the lot and keeps needing help to move, that is a repeatable outcome.
How can dealers use inventory performance data to push back on bad build recommendations?
Ask for the data behind build pushes and allocation.
Document outcomes: days to sale, incentives required, customer objections.
Bring those outcomes into the OEM conversation early, not after the damage is done.
The bottom line: sales velocity starts with smarter inventory strategy
Sales velocity starts before the customer shows up. It starts with ordering decisions that match how your market buys.
The stores that move units faster in 2026 will not be guessing louder. They will be stocking smarter.
