KPI store

A KPI store is a centralized data layer, database, or service that is dedicated to calculating, storing, and serving key performance indicators (KPIs) in a consistent way across an organization. In industrial and manufacturing environments, it is commonly implemented as part of an operations intelligence, MES, or data platform architecture.

Core characteristics

A KPI store typically includes:

• Standardized KPI definitions with agreed formulas, time bases, and filters (for example, a single definition of OEE, NPT, or yield).
• Pre-calculated metrics at common grains such as shift, line, work center, asset, product, or work order.
• Historical retention of KPI values for trend analysis, benchmarking, and audit support.
• Programmatic access through APIs, queries, or analytic tools so that dashboards, reports, and MES or ERP screens all pull from the same values.
• Data lineage and traceability that connect KPIs back to underlying event, production, quality, or transactional data.

The KPI store may be implemented in a data warehouse, data lakehouse, time-series database, or as KPI-focused tables within an MES or historian, as long as it acts as the designated source of truth for KPI values.

Operational usage in manufacturing

In regulated or complex manufacturing, a KPI store commonly supports:

• Shop-floor visibility by feeding consistent KPIs to operator boards, andon systems, and daily management reviews.
• Management reporting on OEE, throughput, scrap, rework, schedule adherence, and other operational metrics across plants or value streams.
• Quality and compliance monitoring through standardized defect, NCR, CAPA, and COPQ-related indicators.
• Cross-system alignment so that MES, ERP, QMS, and BI tools all use the same KPI values and definitions, reducing reconciliation effort.

What it is not

A KPI store is not:

• Raw data storage only. It is more than a simple data lake or historian; it focuses on curated, computed indicators.
• Just a dashboard tool. Visualization tools may consume data from the KPI store but do not replace the store itself.
• A full MES or ERP. Those systems generate events and transactional data; the KPI store organizes and standardizes metrics derived from that data.

Common confusion

• KPI store vs data warehouse: A data warehouse holds broad subject-area data, whereas a KPI store is scoped to standardized metrics (sometimes implemented as a layer inside the warehouse).
• KPI store vs historian: A historian captures high-frequency time-series data from equipment; a KPI store typically uses aggregated or processed data, often including non-OT sources such as ERP and QMS.