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Fundamentals

Demand, time series, how far ahead to look, and how much history you need.

9 min

What is demand forecasting?

Demand forecasting estimates how much of a product or service people will want in a coming period, so you can buy, staff, and price before the rush — not after it has already walked in.

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8 min

Time series forecasting, explained

Time series forecasting predicts the next values of something that was recorded in order — sales by day, load by hour, tickets by week — by learning from its own past, and from anything that regularly moves with it.

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7 min

Predictive analytics vs forecasting

Forecasting asks what a number will be next. Predictive analytics often asks who or what will do something. They share models and data; they do not share the clock, the score, or the decision they feed.

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8 min

Choosing a forecast horizon

The horizon is how far ahead the forecast looks; the grain is how finely it ticks. Pick both from the decision they serve — lead time, planning cycle, and how fast the world can change — not from what the model can print.

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7 min

How much history do you need to forecast?

Enough to see the pattern you are betting on. A weekly seasonal business wants more than one year; an hourly series can learn a week of shape faster. Quality of the target beats another dusty decade of the wrong grain.

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8 min

Hierarchical forecasting

You rarely forecast one series. You forecast stores that must sum to a region, and SKUs that must sum to a brand. Hierarchical forecasting predicts at more than one grain and reconciles so finance and ops are not holding two official numbers.

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7 min

Nowcasting

Nowcasting is a forecast with a horizon of this afternoon. The official close has not posted; you still have to staff the evening or dispatch the next hour. You use faster series — traffic, partial files, a weather nowcast — to estimate the present.

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7 min

Holidays and calendar effects

A calendar is the cheapest accurate feature in the building. Christmas, payday, school terms, a 4-day week, Ramadan, Chinese New Year — if the model has to rediscover those from residuals, you are wasting folds on a date table.

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Glossary in this topic

Time series Seasonality Trend Stationarity Forecast horizon Granularity Nowcasting

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