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AI USE CASE
Demand forecasting for inventory & staffing
Forecast SKU-level demand and staffing needs 4-12 weeks out.
What it is
A time-series ML model combines historical sales, seasonality, promotions, weather and macro signals to predict demand and required staffing. Buyers and ops planners replace gut-feel with data-backed decisions.
Data you need
24+ months of clean transactional sales data, ideally daily granularity.
Required systems
- erp
- ecommerce platform
- data warehouse
Why it works
- Start with the top 100 SKUs by revenue, expand later
- Track forecast accuracy weekly and trigger retraining on drift
How this goes wrong
- Model trained on COVID-era data without regime detection
- No closed-loop on actuals, model never improves
When NOT to do this
Skip if your data is fragmented or you don't have a planner who'll actually use the output.
Example vendors
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