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sourceDocument: Australia Governance, Risk, and Compliance
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/governance-risk-compliance

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    - australia

ft:locale :

    - en-US

ft:publication_title :

    - Australia Governance, Risk, and Compliance

ft:clusterId :

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---

# Components of GRC: Metrics

# Components of GRC: Metrics {#ariaid-title1}

* Release version: Australia
* 
* Updated March 12, 2026
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read

Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Components of GRC: Metrics

The GRC: Metrics application allows users to effectively manage and automate the collection of metrics through defined components, enhancing data accuracy and operational efficiency across various business units.
Show full answer Show less  

## Key Features

* **Metric Definitions:** Serve as templates for core metric properties, including unit, direction, nature, precision, frequency, and category. They streamline metric creation, allowing for easy attachment of entities and data collection.
* **Types of Metric Definitions:**
  * Automated Metric Definition: Collects data automatically.
  * Manual Metric Definition: Requires manual data input.
  * Calculated Metric Definition: Aggregates data from other child metric definitions.
* **Metric Data:** Generated when metrics are executed. For manual definitions, values are drawn from metric data tasks. Ad hoc tasks can be created for real-time updates but do not contribute to aggregated data.
* **Metric Definition Data:** Created automatically upon metric execution and aggregation.
* **Metric Data Tasks:** Specific to manual metrics, allowing data owners to input responses. These tasks can require approval based on the metrics manager's discretion.

## Key Outcomes

Utilizing the GRC: Metrics application simplifies the metric collection process, reduces redundancy, and provides accurate insights into performance through systematic data management. Users can expect improved data integrity, efficient metric tracking, and the ability to respond swiftly to ad hoc requests for information.  
A metric consists of several components such as metric definition, metric data, metric definition data, metric data tasks. All of these elements or parts contribute to the metric collection process in various ways.

## Metric definitions {#elements-of-metrics-irm__section_awz_cv2_1yb}

A metric definition is a template-level record that helps set the core properties of a metric. These properties include the unit, direction, nature, precision, frequency of
data collection, and category of the metric. The metric itself collects scores, which are then aggregated into the defined metric. The advantage of creating and using a metric definition lies in its ability to streamline the process
of creating metrics using these metric definitions. For instance, imagine you have several business units, and you must collect revenue data for each of them. Without a metric definition, you would have to create separate templates
for every business unit and repeatedly specify the metric properties. However, by using a metric definition, you simplify this task. Once you have created the metric definition, you can easily attach your entities (business units in
this case) and collect the metrics without duplicating efforts.
The GRC: Metrics application provides the following types of metric definitions:

* Automated metric definition: Data is collected automatically.
* Manual metric definition: Data is collected manually.
* Calculated metric definition: Data is collected by aggregating data from other child metric definitions.
{#elements-of-metrics-irm__types-of-metric-definitions_ul_zdj_lcr_nrb}

## Metric data {#elements-of-metrics-irm__section_jqp_dnm_rsb}

When you execute a metric, the metric data gets created. For manual metric definitions, the values of metric data are copied from the metric data tasks when the metric data tasks are closed. To address off-cycle requests for the most
up-to-date information on existing metric definitions and metrics, you can create ad hoc metric data tasks on manual metrics. On the metric data form, the option Ad hoc denotes if the metric data task was
created as an ad hoc task. It's important to note that these ad hoc tasks do not contribute to the aggregated metric definition data, aren't considered for entity hierarchy rollup, and aren't evaluated for threshold rating,
Variance(%). However, in a calculated metric definition, if the Calculation level is set to Entity, and there are ad hoc tasks from the manual metric definitions, then these tasks are
aggregated to derive the calculated metric definition data.

For a scripted automated metric definition, the values are updated when you execute the script. For a basic automated metric definition, the values are updated from the selected table. The field Variance (%)
shows the variation in between current period and the previous period metric data and is displayed in percentage. The field Last period data refers to the previous period's metric data.

## Metric definition data {#elements-of-metrics-irm__section_wj1_zv2_1yb}

Metric definition data gets automatically created when the metric definition gets executed and aggregated.

## Metric data tasks {#elements-of-metrics-irm__section_gmx_zv2_1yb}

Metric data tasks only apply to manual metric definitions. These tasks are generated whenever manual metrics are executed and the data owners provide responses for these tasks manually. You can provide responses to multiple metric
data tasks using the metric data table. For more information, see [Metric data table](https://servicenow-prod.fluidtopics.net/T4vqKEVqoC_BFvEQeI~0~Q "The metric data table enables data collection for metrics across the organization using an easy-to-use interface like a spreadsheet with multiple filters and a task management workflow.").

A metrics manager has the authority to determine whether a metric data task needs approval. If approval is necessary, you can choose between two methods: Simple Approval or Advanced Approval by using the Metric approval property. For more information about this property, see [Components installed with the GRC: Metrics application](https://servicenow-prod.fluidtopics.net/54xPRN4cN0pTBJoiSNP2jg "The GRC: Metrics application adds roles that are listed here.").