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MIDAOPS03-BP01 Define meaningful KPIs and metrics - Modern Industrial Data Technology Lens
Implementation guidance

MIDAOPS03-BP01 Define meaningful KPIs and metrics

Manufacturing and industrial organizations require comprehensive visibility into the health and performance of their data-driven operations. Proper definition and monitoring of KPIs verify that manufacturing processes remain efficient, reliable, and aligned with business objective.

Desired outcome: Establish a comprehensive set of metrics and KPIs that provide insights into the performance, reliability, and efficiency of your operations, production, and industrial data workloads. These metrics and KPIs should enable proactive identification of issues and optimization opportunities.

Benefits of establishing this best practice: By adopting the best practice and prescriptive guidance, your organization gains improved visibility into manufacturing operations, enabling timely detection of potential production issues, enhanced operational efficiency, better resource utilization and reduced downtime and maintenance costs.

Level of risk exposed if this best practice is not established: High

Implementation guidance

Implement industrial workload-specific KPIs monitoring and alerting that aligns with industry standards like ISA-95 and focuses on critical production metrics.

Implementation steps

Define industry-specific KPIs applicable for your workload. Examples of common metrics industrial data workloads:

  1. System availability and uptime

  2. Data ingestion rates and latency

  3. Processing system performance

  4. Security events and access patterns

  5. Network connectivity status

  6. Edge device health status

  7. Gateway operational status

  8. Resource utilization (for example, CPU, memory, or storage) for edge gateways and cloud services