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Is it better to forecast in Excel or use a machine-learning model?
Excel is often enough for a few products, stable demand and monthly planning. Machine learning becomes worthwhile when you have many items or locations, rich drivers, frequent forecasting cycles and a decision where small accuracy gains are valuable. Choose by the size of the problem, not by what sounds modern.
Spreadsheet strengths are transparency and familiarity. Weaknesses are fragility, version confusion, errors in formulas and difficulty refreshing at scale.
Signs you have outgrown Excel:
- Forecasts take days to update.
- Several people maintain different copies.
- You need per-store, per-product forecasts that refresh automatically.
- Promotions and prices must be modelled together.
An intermediate step is a scripted statistical forecast on a database, which stays simple but is repeatable and auditable.
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