Enterprise Inventory Management Best Practices

Overview

Inventory entries can contain two fundamentally different types of data: authoritative data drawn directly from the systems or processes that are designated as the source of truth for specific attributes, and derived data calculated or inferred from authoritative data through transformation, aggregation, or analysis. Mixing authoritative and derived data in the same inventory entry without distinction makes it impossible to know which attributes can be trusted absolutely and which reflect calculated estimates that may carry uncertainty.

Best Practice

Define, for every attribute in every inventory schema, whether the attribute is authoritative or derived. Authoritative attributes are sourced directly from a designated authoritative source and reflect known facts. Derived attributes are calculated or inferred and reflect analysis or estimation. Make this distinction visible in the schema documentation and where feasible in the inventory data itself, so that consumers of the inventory can distinguish between what is known and what is inferred. When authoritative data conflicts with derived data, the authoritative source takes precedence.

Benefit(s)

Distinguishing authoritative from derived data prevents the loss of data provenance that occurs when different types of data are mixed without distinction. Decision-makers can assess the reliability of the data they are using. Automated processes can treat authoritative and derived data differently — using authoritative data for compliance and reporting, and derived data for analysis and planning. When derived data is found to be incorrect, the derivation logic can be corrected without affecting the authoritative data it was derived from.