Pricing dataset

Pricing dataset containing historical and future cost and retail price information per product over time, used by Inventory Management to evaluate financial impact.

The pricing dataset contains historical and future cost and retail price information for products over time. It represents how product prices change and is used by the inventory management solution to evaluate the financial impact of inventory decisions.

This dataset can include both historical price changes and planned future prices.

Purpose

The solution uses the pricing dataset to:

• Evaluate inventory value and exposure in financial terms
• Assess the revenue impact of stock availability or shortages
• Support inventory KPIs that depend on product price, such as lost sales value or capital tied up in overstock

During presales, pricing data is also used to estimate the potential financial impact of inventory optimization.

Required fields

About the Constraint column: every field listed must be provided in your data. Non-null means its value cannot be null; Nullable means the value may be sent as null (or left blank in your source). Primary key, Unique, and Foreign key describe the field's role in the data model; a Primary key is always non-null.

Field	Description	Type	Constraint
product_id	Unique identifier for the product SKU.	string	Primary key
location_id	Identifier for the store or distribution centre.	string	Primary key
unit_cost_price	Cost of a single unit of stock to the business during the validity period. Units must match those used in related datasets (for example, Customer orders and Stock).	float	Non-null
unit_list_price	Retail price of a single unit during the validity period.	float	Non-null
valid_from	Date and time when the price becomes valid. Can be NULL to indicate validity from any date before valid_to.	datetime	Nullable
valid_to	Date and time when the price is no longer valid. Can be NULL to indicate validity after valid_from.	datetime	Nullable
created_at	Date and time (UTC) when the record was created.	datetime	Primary key

Usage notes

• If both valid_from and valid_to are NULL, the price is assumed to be valid for all dates.
• Historical pricing data improves the accuracy of financial impact analysis.
• Pricing units must be consistent with units used in demand and stock datasets.
• When pricing varies by location, location_id should be populated accordingly.