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Supply Chain & Retail Solutions user guide

Product cost dataset

The Product Cost dataset contains cost information for products used in commercial pricing scenarios. It defines the unit cost of products over time and provides the financial context necessary to evaluate margin and profitability.

This dataset is required for application deployment and pricing insights analysis.

→ For the canonical technical schema (data types, validation rules, request/response examples), see Product Cost in the API Guide.

Purpose

The commercial pricing solution uses the Product Cost dataset to:

  • Calculate product-level margins
  • Evaluate profitability of quoted or recommended prices
  • Support trade-off analysis between revenue and margin objectives
  • Ensure pricing guardrails reflect cost constraints

Cost data is essential for generating pricing recommendations that balance competitiveness and profitability.

Required fields

About the Nullable column: every field below must appear in your data. Nullable: Yes means the field can be sent as null (or left blank in your source) when no value is available; Nullable: No means a non-null value is required for every row.

FieldDescriptionTypeNullable
product_idUnique identifier for each product. Used to join product metadata to quotations and sales for model training and guardrails.stringNo
region_idRegion identifier (Primary Key, Foreign Key)stringNo
updated_atTimestamp when the record was updated. Used to identify the most up-to-date data in the UI and when optimising prices. For model training, used to match the cost price to the date of each quote.timestamp_tzYes
product_costCost price of the product. Used to calculate the margin/profit applied to all quotations and sales orders for model training and optimising prices.floatYes

Usage notes

  • Cost data should reflect the actual cost basis used for margin calculations.
  • All referenced identifiers (product_id, region_id) must exist in their corresponding datasets.
  • Successive versions of a product cost are appended with new updated_at values, preserving the cost history needed for accurate profitability analysis over time.
  • Historical cost changes improve the accuracy of profitability analysis and recommendation stability.
  • Units of measure must be consistent with related datasets (for example, Quote Line and Sales).

Why this dataset matters

The Product Cost dataset enables the solution to evaluate pricing decisions against profitability objectives. Without cost data, pricing recommendations cannot reliably assess margin impact or enforce pricing guardrails.

  • Purpose
  • Required fields
  • Usage notes
  • Why this dataset matters

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