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Supply Chain & Retail Solutions user guide
- Overview
- Platform setup and administration
- Platform setup and administration
- Platform architecture
- Data Bridge onboarding overview
- Connecting a Peak-managed data lake
- Connecting a customer-managed data lake
- Creating an AWS IAM role for Data Bridge
- Connecting a Snowflake data warehouse
- Connecting a Redshift data warehouse (public connectivity)
- Connecting a Redshift data warehouse (private connectivity)
- Reauthorizing a Snowflake OAuth connection
- Using Snowflake with Peak
- SQL Explorer overview
- Roles and permissions
- User management
- Inventory management solution
- Commercial pricing solution
- Merchandising solution
Forecast dataset containing demand forecast values per product and location, an optional forward-looking demand signal for Inventory Management.
The forecast dataset contains demand forecast values for each product at each location. It provides an optional forward-looking demand signal that customers can supply if they already produce their own forecasts.
Purpose
The inventory management solution uses forecast data as an additional demand signal to complement historical demand analysis. When customers already generate their own forecasts, this dataset allows those forward-looking values to inform replenishment and stock optimization recommendations.
Required fields
| Field | Description | Type | Use | Notes |
|---|---|---|---|---|
product_id | Unique identifier for the product. | string | Application | N/A |
location_id | Unique identifier for the store or distribution centre. | string | Application | N/A |
cutoff_date | The date on which the forecast was generated. | date | Application | N/A |
start_date | First date of the forecast period. | date | Application | N/A |
end_date | Last date of the forecast period. | date | Application | N/A |
horizon | Number of periods ahead of the cutoff date that the forecast covers. | integer | Application | N/A |
yhat | Forecasted demand value for the period. | float | Application | N/A |
frequency | Length of the forecast period, in days. | integer | Application | N/A |
Usage notes
- This dataset is optional and only required when customers already produce their own demand forecasts.
- Product and location identifiers must align with the corresponding Products and Locations datasets.
- Forecast periods should be consistent, with
frequencydefining the length of each period in days. - Forecast values should reflect expected demand, not historical actuals.