Forecasting float, laminated, or coated glass becomes a guessing game when your catalog is out of control.
Inventory forecasting is one of the toughest jobs in distribution—especially in the glass industry, where seasonality, regional demand, and project-driven orders wreak havoc on traditional planning models. But even the best forecasting tools struggle under the weight of one silent killer: SKU proliferation.
Distributors of architectural, safety, or decorative glass often carry thousands of SKU variations based on:
Size (width × height)
Thickness (3mm to 19mm)
Edge type (seamed, polished)
Coating (low-E, UV, mirror-backed)
Color (bronze, gray, blue, clear)
The result? A forecasting nightmare. The more SKUs you carry, the harder it is to predict demand accurately—and the greater the likelihood of overstock, stockouts, and missed sales.
The Cost of Complexity
Let’s say you carry five variations of 6mm tempered glass in standard sizes. If only two of those consistently sell across multiple accounts, the others distort your forecasting data. Demand averages flatten. Trends get buried. You end up purchasing based on false signals—or worse, gut feel.
The cost of getting it wrong is high. Glass is heavy, fragile, and expensive to store. Overstocked SKUs eat up racking space and invite handling damage. Understocked items mean expedited freight from fabricators—plus frustrated clients and lost credibility.
Forecasting Algorithms vs. Real-World Use
Many ERP systems use past sales to project future demand. But when your catalog is cluttered with rarely ordered SKUs, even sophisticated forecasting tools lose accuracy. Rare events—like one-off bulk orders—get treated as repeatable patterns. You stock for ghosts.
One Canadian distributor audited their glass catalog and found that over 40% of SKUs had only been ordered once in 18 months. These items skewed demand forecasting for entire product families, leading to frequent last-minute adjustments and costly supplier rush fees.
By streamlining the catalog and focusing on the top 200 SKUs (which accounted for 78% of revenue), forecast accuracy improved by 24% in just two quarters. That translated into better fill rates, fewer emergency shipments, and a leaner inventory profile.
Strategic SKU Rationalization
To improve forecasting, you don’t need to eliminate every low-volume SKU—just treat them differently. Move slower movers to a made-to-order model with clear client expectations. This removes their noise from the forecast pool while still allowing access when needed.
You can also create forecast zones—grouping similar SKUs together (e.g., all ¼” clear tempered) and forecasting at the family level, then allocating inward supply based on real-time sales splits.
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Glass distributors can’t afford poor forecasting—and bloated SKU lists are often to blame. By trimming the catalog, isolating custom demand, and grouping products strategically, you bring clarity back to your planning. When you forecast smarter, you stock smarter. And that’s where margin lives in this business.
