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Which forecasting method to use, and why that choice matters considerably less than the quality of the data behind it.
What they differ on
How much weight recent weeks carry, how strongly seasonality is applied, and how quickly the forecast reacts to a change in trend.
All of them are reading the same history; they disagree about what to emphasise.
The rough guide
- Stable volume, clear weekly pattern. A method leaning on seasonality works well.
- Growing or shrinking steadily. One that weights recent data, or the trend is always behind.
- Volatile, campaign-driven. No algorithm handles this alone; you will be adjusting manually.
The six, by name
These are the names you choose between when you test.
| Eight-weeks average | A running average of the past eight weeks. Straightforward and the usual choice. |
| Eight-weeks average with momentum | The same, but it follows an upward or downward trend in those weeks instead of flattening it. |
| Prophet | For strong seasonal patterns with several seasons behind them. Copes with gaps in the data and with a trend that shifts. |
| XGBoost and LightGBM | Machine learning on decision trees. They differ in how the trees grow, which matters to them and rarely to you. |
| LSTM | A neural network that learns long sequences. The heaviest of the six. |
Test rather than reason about it
Run two against a period you already know and compare with what happened. Twenty minutes, and it answers the question definitively for your data.
Choosing on the description of the method is guessing.
Data quality beats algorithm choice
A clean history with the abnormal weeks taken out, run through an ordinary method, beats messy history through a sophisticated one every time. And you do not pick the method anyway: Zendesk WFM tests them against your history per workstream and uses whichever fits best.
If the forecast is poor, look at the data before changing the method.
Do not change it often
Switching methods every time a week is off means you never learn whether any of them works. Choose one, run it for a quarter, and judge it on the quarter.
Per channel, possibly
Phone and email behave differently enough that different methods can suit them. Worth testing once rather than assuming one setting fits both.
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