Seasonality and Trend Decomposition
seasonality
trend
forecasting
Industry
Retail
For Whom
Inventory Planners, Demand Forecasters, Merchandising Teams
Why You Need This
Guessing at busy and slow months leads to stockouts or overstock. See actual trends and seasonality in your data.
How It Works
Time series decomposition separates seasonality, trend, and anomalies for planning clarity.
Data Type
Time Series
What You Need
Historical sales or demand data by week/month.
What You Get
- Trend and seasonality graphs
- Segment definitions: High season, Off-season, Baseline trend periods
- Actionable calendar for stocking, staffing, and promo timing
How To Use It
Use outputs for buying, hiring, and promotional calendar planning.
Technique
Time Series
Business Impact
Reduce lost sales, lower excess stock, improve forecast accuracy (track forecast error, stockout/overstock events).
How We Deliver This
Interactive dashboards, PowerPoint readouts, and training on seasonality interpretation.
Can Be Extended To
Weather-driven modeling, event impact analysis, multi-site or multi-category planning.