Demand PlanningSeasonality
Seasonality
The repeating shape of demand, separated from trend and one-off events.
Peak month
Dec
Index 1.24
Lowest month
Jan
Index 0.88
Seasonal amplitude
36%
Pattern confidence
High
3 full years of history
Seasonal index by month
1.00 = average month
Recurring events
| Event | Window | Effect on demand | Notes |
|---|---|---|---|
| Ramadan slowdown | Feb – Mar | -14% | Reduced site access in industrial customers. |
| Summer shutdowns | Jun – Jul | +22% | Planned turnarounds drive spare-part and service demand. |
| Budget release | Oct – Nov | +12% | Government and enterprise capex approvals. |
| Year-end close | Dec | +24% | Buyers spend remaining budget before reset. |
How seasonality is applied
The baseline forecast is deseasonalised, projected on trend, then re-seasonalised with these indices. Because December runs at 1.24, a flat month-on-month plan would understate December demand by roughly a fifth — the model corrects for that automatically and flags the resulting inventory build in September.
Upload events calendar
Holidays, shutdowns and campaigns as model features.
Drop a CSV here or
Expected columns: date, event, impact_pct
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Answers are grounded in the platform's seeded workspace data plus any CSV you uploaded.