Walmart's AI Markdown Strategy Raises the Stakes for Suppliers
- The HRG Team
- 1 day ago
- 8 min read
Walmart suppliers are beginning to face a new kind of markdown conversation: AI-driven markdowns may be more precise, but the central issue is whether suppliers can verify the charges that follow.
Instead of applying the same price cut to every store, Walmart's AI markdown tool can analyze inventory and sales at each location. One store might need a small price drop, another a bigger one, and some stores may not need a markdown at all if sales are strong.
This level of detail can help Walmart move inventory faster and protect suppliers from unnecessary markdowns in stores where their products are already selling well. At the same time, it creates a new challenge: the more precise the markdowns become, the harder it can be to verify supplier charges.
But when suppliers are expected to cover a large share of these markdowns, the financial side becomes more complicated. More precise markdowns do not always mean the charges to suppliers are clearer or more accurate.
Walmart has talked about using artificial intelligence, machine learning, and inventory technology to make better decisions across its business. Its Element platform supports several AI tools, and other systems help improve inventory accuracy, product availability, and supply chain performance. Walmart says AI is becoming a key part of its retail operations.
For suppliers, the main issue is not whether Walmart uses AI for markdowns. The real question is whether suppliers will have enough information to understand, verify, and challenge the charges that follow.
Store-Specific Markdowns Could Be Good for the Business
It's easy to see why more targeted markdowns make sense for the business.
If a product sells slowly in 200 stores but does well in 800 others, marking down the price everywhere could hurt revenue where it's not needed. Store-specific markdowns let Walmart lower prices only where it makes sense based on inventory and demand.
That approach may create several benefits:
Slow-selling inventory can move faster.
Stores with healthy sell-through may avoid unnecessary price reductions.
Pricing can better reflect local demand and inventory conditions.
Suppliers and retailers may carry fewer end-of-season liabilities.
Targeted markdowns may reduce the cost of broad clearance activity.
Better inventory movement may create room for new items or seasonal transitions.
Walmart has noted that having the right inventory in the right categories and locations helps minimize markdowns while supporting stronger in-stock performance. The company has also connected strong seasonal sell-through with markdown savings.
The idea makes sense. Suppliers start to worry when thousands of local decisions are combined into one large charge or deduction, because the central issue is whether that charge can be verified.
Greater Precision Creates Greater Complexity
A typical markdown program already includes different items, locations, dates, prices, and funding rates. When markdowns are decided for each store, the number of details to track goes up a lot.
One program could include differences across:
Stores and markets
Individual items
Original retail prices
Markdown amounts
Effective and ending dates
Reported inventory quantities
Sell-through rates
Supplier-funding percentages
Subsequent price changes
Claim and deduction timing
For example, a program with 500 stores, 4 items, and 3 possible markdown prices could generate thousands of combinations before even considering quantities, dates, reversals, or funding terms.
Suppliers might not see all this complexity at first. Instead, they may just receive a single markdown charge with a summary or spreadsheet attached, making it harder to verify whether the charge is accurate.
This makes it harder to manage deductions. Suppliers have to figure out what happened at each store, check whether the activity matched the agreement, and ensure the amount is correct.
An AI Decision Is Only as Reliable as Its Inputs
AI tools can handle large amounts of data quickly, but they still rely on obtaining reliable information in the first place.
If a markdown is based on reported inventory, suppliers need to know if that inventory is really there and available to sell.
Consider a fictional example involving a seasonal home product.
Walmart's system shows that one store has 36 units on hand, but the item has recorded only 2 sales over the past 3 weeks. Based on those numbers, a markdown appears reasonable.
What if 20 units are sitting unprocessed in the backroom? What if eight were damaged but haven't been removed from inventory? What if the shelf location is empty even though the system says the product is available? What if the store received the wrong item under a similar product number?
In each of these cases, the data might show low demand, but the real issue could be how the store handles inventory or keeps records.
That distinction matters because the supplier is expected to fund the solution.
Problems such as phantom inventory, receiving errors, shrink, unprocessed returns, damage, incorrect item setup, and shelf availability issues can all affect the numbers used to judge performance. A markdown might seem reasonable but still end up costing the supplier more than necessary.
The AI may be accurately interpreting the data it received. The underlying data may still be wrong, which is why supplier verification remains essential.
Supplier Funding Should Come with Supplier Visibility
If suppliers have to pay a significant portion of the markdown costs, they need sufficient detail to verify what they're actually paying for and whether the charge matches the agreement.
At a minimum, suppliers should seek visibility into:
The specific stores and items included
The original and reduced retail prices
Markdown effective dates
On-hand quantities when the decision was made
Units sold at each reduced price
Inventory remaining after the markdown.
The approved supplier-funding percentage
Whether funding applies to inventory marked down or units actually sold
Subsequent markdowns, reversals, returns, or price changes
The calculation behind the final claim or deduction
There’s a big difference between paying for marked-down inventory and paying for items that actually sold, and that difference goes to the heart of whether a supplier charge is valid. Suppliers should know which basis applies before accepting the charge.
Once that distinction is clear, the next step is checking whether the claim matches the agreement.
Suppose 100 units are marked down by $2, and the supplier agrees to fund 50% of the reduction. If only 40 units sell at the markdown price, should supplier participation be based on all 100 units or the 40 units that actually sold?
The agreement should make this clear, and the claim should match the agreed terms so suppliers can verify the charge.
Without details at the store and item level, suppliers may not know if they paid for a real sale, a projected markdown, or inventory that was later sold under a different program.
A Markdown Recommendation Isn't the Same as a Valid Charge
A valid supplier charge requires several events to connect correctly:
The AI tool recommends a markdown.
The markdown is reviewed and approved.
The correct price is activated for the intended stores and items.
Inventory sells at the reduced price.
Supplier participation is calculated in accordance with the agreement.
The claim or deduction matches the documented activity.
If anything goes wrong in this process, it can lead to a charge that isn’t supported or is inaccurate, which is why suppliers should be able to trace every step and challenge anything that doesn't match the agreement.
Potential areas of exposure include:
Funding applied to the wrong stores or items
Incorrect inventory quantities
Charges for inventory that didn't sell at the reduced price
Duplicate or overlapping markdown periods
Funding rates that don't match negotiated terms
Incorrect effective dates
Markdown claims overlapping with rollbacks or promotions
Price-protection funding applied twice.
Charges lacking sufficient store-level support
Not every markdown claim is incorrect. Many are valid and make good business sense.
The first step is knowing which charges are real business expenses and which ones can be challenged.
Suppliers should not challenge valid charges. But they also should not assume that every charge based on an AI recommendation is automatically correct; each should be checked against the support before it is accepted.
Markdowns Don't Exist in Isolation
Markdown activity should be reviewed alongside the broader retail picture, including:
Point-of-sale performance
Inventory records
Replenishment activity
In-stock and shelf-availability conditions
Promotional calendars
Rollback agreements
Price-protection programs
Returns and defectives
Shortage activity
Previous claims and deductions
Looking at all these factors together helps suppliers see whether a markdown reflects real customer demand or another issue in the retail process, so they can focus on what matters before accepting the charge. That broader view is important because a markdown rarely tells the full story on its own.
Low sales combined with high reported inventory may suggest weak demand. However, if inventory isn't reaching the shelf, the real issue may be execution. If the on-hand count is inflated, phantom inventory may be affecting both replenishment and the markdown recommendation. If the item was already included in a rollback or promotional program, the supplier may need to determine whether the new funding overlaps with an existing agreement.
Just looking at the markdown doesn't give suppliers the full picture.
How HRG Helps Suppliers Understand Markdown Activity
HRG helps suppliers move from an aggregate charge to store- and item-level understanding, so they can see what they are actually paying for.
As the company that pioneered retail deduction recovery, HRG combines experienced retail auditors with data capabilities that help suppliers connect pricing activity, inventory signals, agreements, claims, and deductions.
That allows suppliers to:
Validate claims against negotiated funding terms.
Identify duplicate, overlapping, or unsupported charges.
Compare markdowns with point-of-sale, inventory, promotional, and shortage data.
Separate legitimate markdown expense from recoverable revenue
Build an auditable record for retailer discussions.
Identify recurring patterns that can improve future planning.
Better understand the effect of markdowns on collected revenue and margin.
This analysis has value beyond dispute management. Repeated markdowns at the store level can indicate problems with product selection, restocking, forecasting, distribution, shelf setup, or item setup. The goal is to understand why the charge occurred, confirm its accuracy, and use the findings to make better decisions.
Questions Suppliers Should Be Asking Now
Suppliers should not wait for a big markdown deduction before asking questions. It's better to clarify the program, data, and funding terms before things get busy.
Key questions include:
What data does the AI markdown tool use?
How frequently are recommendations updated?
What approval occurs before a markdown is activated?
Will suppliers receive store- and item-level support?
Is supplier participation based on units marked down or units sold?
How will inaccurate on-hand inventory be addressed?
What happens when a markdown is modified or reversed?
How are funding percentages established and documented?
How will markdown funding be separated from rollbacks, promotions, and price protection?
What support will be available if the supplier questions a charge?
Can suppliers measure whether the markdown improved sell-through?
How will unsold inventory be treated after the markdown period ends?
Getting clear answers now can help avoid confusion, lost profits, and tough disputes with retailers later on.
Smarter Retail Requires Smarter Validation
AI-powered markdowns may help Walmart make faster, more localized inventory decisions. For suppliers, the approach could reduce unnecessary broad markdowns and help move slow-selling products more efficiently.
But it also brings new financial challenges, especially when suppliers are asked to cover much of the cost. Advanced technology doesn't automatically create an accurate charge. Suppliers still need visibility into the inputs, approvals, execution, agreements, and calculations behind it.
As retailers rely more on AI, suppliers will need to integrate data, review financial results, and protect their revenue.
Practical Takeaways for Suppliers
Document markdown funding terms before the program begins.
Confirm whether funding applies to inventory marked down or units sold.
Request support at the store-, item-, date-, price-, and quantity-levels.
Compare reported inventory with point-of-sale and replenishment activity.
Investigate phantom inventory and shelf-availability issues.
Check for overlap with rollbacks, promotions, and price-protection programs.
Reconcile aggregate charges to the underlying store-level transactions.
Monitor repeated markdown patterns for operational root causes.
Preserve agreements, claim support, and retailer communications.
Review questionable charges before they become routine write-offs.
Take Action
Is your company prepared to validate store-specific markdowns, pricing, inventory, agreements, claims, and deductions so they can distinguish legitimate expense from recoverable revenue and make better-informed decisions? Retail complexity doesn’t come with directions.
A smarter way to navigate it is coming. Turn Insight into Action. Coming Nov. 1.
