Every ceramic distributor has a SKU graveyard—outdated styles, forgotten formats, or over-ordered mosaics that linger in warehouse racks long after demand has dried up. AI is now giving commercial teams the power to predict SKU obsolescence before it’s too late—saving cash, reducing write-offs, and making room for high-velocity lines.
The SKU Obsolescence Problem
With constant product churn driven by design trends, builder demands, and channel shifts, keeping a bloated catalog leads to:
Dead inventory
Misallocated warehouse space
Picking inefficiencies
Higher carrying costs
But most systems don’t flag at-risk SKUs until they’ve already become stranded.
What AI Looks For
Declining quote frequency
Reduced sample request activity
Drop-off in adjacent SKU performance
End-of-life design indicators (e.g., discontinued formats)
SKU “cannibalization” from newer styles
The model gives each SKU an “obsolescence risk score,” which updates weekly.
Use Case
A 4×16 glossy ceramic wall tile sees an 18% drop in builder orders, a 30% decline in quoting, and reduced sample pulls across multiple branches. AI flags it as 83% likely to become obsolete in the next 90 days—prompting merchandising to plan a final-push campaign before write-down.
Results
Proactive exit strategies for aging SKUs
Better catalog management across channels
Leaner inventory with higher velocity
Improved financial control over inventory value erosion
AI helps you stop burying capital in tile that no one wants anymore—and shift that space toward what customers are actually buying.
