Glossary

SKU-Level Forecasting

In one line: SKU-level forecasting predicts demand for each individual product variant — not just category totals. It’s the difference between useful and useless inventory data.

Why the granularity matters

“We’ll sell 200 units of t-shirts next week” is interesting but unhelpful. Which colors? Which sizes? Without that, you can’t order intelligently. SKU-level forecasting answers: 47 black mediums, 32 white larges, 18 navy smalls, and so on for every variant.

Where it’s critical

• Clothing — size curves vary dramatically; getting them wrong means lost sales and excess markdown
• Electronics — model variants, storage capacities, colors all sell differently
• F&B — specific ingredients and dishes, not just “total covers”
• Education — specific titles by syllabus level, not generic “math books”

The technical challenge

SKU-level forecasting is computationally harder because there’s much less history per item (a new product variant might only have a few weeks of sales). Good models handle this by sharing patterns across similar SKUs — learning that a new “navy medium” will probably behave like the average of similar items, even without its own history.

What it enables

• Precise reorder quantities and timing
• Smarter allocation between stores
• Earlier markdown decisions on underperforming variants
• Better buying decisions for next season

Related terms

Demand Forecasting, Inventory Optimization, Cold-Start Problem