Automated metric definition form

The fields of the automated metric definition form are explained in this topic.

Table 1. Automated metric definition form

Field	Description
Basic details
Name	Name of the automated metric definition. For example, Number of incidents.
Active	Option to mark the automated metric definition as active. When enabled, the metric definition becomes active and ready for use.
Description	Brief description of the automated metric definition.
Unit	Unit for the automated metric definition. You can define the units in which the data is shown.
Aggregation method	The Aggregation method refers to the method used to calculate the metric data for all the entities. For example, when a metric applies to multiple entities, such as people, departments, or regions, you calculate each entity’s data and combine it into one score that shows overall performance. Your choice of aggregation method depends on your goal of metric collection. For example, if you’re interested in overall performance and want to account for differences in scale or size between entities, the sum or average may be more appropriate. If you’re interested in identifying the best-performing entity, the maximum may be more appropriate, while if you’re interested in identifying the worst-performing entity, the minimum may be more appropriate. The aggregation happens across time periods based on the frequency defined in the metric definition. If the frequency is monthly, the calculation takes place every month. The four choices for aggregation methods are as follows: Sum: The metric data for all entities are added to create a single score. Average: The metric data for all entities are averaged to create a single score. Maximum: The highest metric data among all entities is used as the single score. Minimum: The lowest metric data among all entities is used as the single score.
Precision	Number of decimal places after the decimal point on a score. When an indicator has a Precision of 0, the indicator rounds the result to the nearest whole number. For example, if an indicator with Precision 0 calculates the values 7 + (5 / 2), the indicator rounds the result up to 10. When an indicator has a Precision greater than 0, the indicator rounds to the nearest decimal point for the given precision. For example, an indicator with Precision 1 rounds a result of 4.45 as 4.5.
Class	Class to which the metric definition belongs. The choices are as follows: KPI: Indicates how well the risk exposure is managed against objectives. Use this option to add entities and additional entities to the metric definition. KRI: Indicates the amount of exposure to a given risk or set of risks. Use this option to add risks and risk statements to the metric definition. This option is available if the Advanced Risk plugin is activated. KCI: Indicates the effectiveness of any controls that have been implemented to reduce or mitigate a given risk exposure. Use this option to add controls and control objectives to the metric definition. This option is available if the Policy and Compliance Management plugin is activated. Important: This field appears only when the metric definition is created from the IRM suite of applications. It doesn’t appear for Operational Sustainability Management.
Calendar	Calendar to use for metric aggregation. Only the configured calendar options are available for selection. This field is automatically set to Standard Calendar. Note: Standard calendar refers to the Gregorian calendar.
First run date	Start date for the collection frequency schedule for the automated metric definition.
Frequency	Collection frequency with which the metric is executed. Indicates how often the metric definition should collect the data. The choices are as follows: Daily Weekly Monthly Quarterly Semi-annually Annually
Data collection
Method Type	Type of automated metric. The choices are as follows: Basic: Indicates using aggregation methods such as sum, average, maximum, minimum, and count distinct. Scripted: Indicates using a script to collect the data. This option can be used when, for example, you want to collect data from multiple tables. External Source: Indicates that the data will be collected from external sources. For example, if you want to source data about the number of employees in your organization and their gender ratio, you can obtain the information from an external source such as Workday which is an application that stores human resources data. Note: If you select Scripted, you must save the form and select Add script to add your script. Only users with the sn_grc_metric.developer role can add scripts.
Table	Table from which data is obtained for the metrics. This field only appears if the Method Type field is set to Basic.
Criteria	Condition for the record from which data is collected. Build a filter by adding conditions that contain a field, operator, and values and then select Set. For example, you can build a condition that you want to collect data for only those incidents the due date for which is in the current month. This field only appears if the Method Type field is set to Basic. Note: You must select a value for the Table field before modifying this field.
Aggregate	Method or the calculation used to aggregate the data from the chosen table. When an option is selected in the Aggregate field, a new Aggregation Field is displayed next to the Aggregate field. The Aggregation Field displays the selected record. The choices for the Aggregate field are as follows: Count: Count of the number of records that are obtained from the chosen table. For example, if you want a count of the incidents, you can select this option. Note: The Aggregation Field isn’t displayed when Count is selected. Sum: Sum of the column that is selected in the Aggregation Field. Average: Average of the values of the column that is selected in the Aggregation Field. Maximum: Maximum of the values of column that is selected in the Aggregation Field. Minimum: Minimum of the values of the column that is selected in the Aggregation Field. Count Distinct: Number of groups in the result set that is grouped by the Aggregation Field.
Table field	Column or field of the table that is selected in the Table field. For example, you can select the Caller column in the Incident table. This selection enables you to understand that which callers are associated with the Incident table and compare them with the callers of your entities. Note: You must select a value for the Table field before modifying this field.
Aggregation field	Column or field from the table that is selected in the Table field on which the aggregation must be performed. Note: This field doesn’t appear if Count is selected in the Aggregate field.
Entity field	Column or field from the entity table. The entities are matched based on the field selected in the Table field and the field selected in the Entity field. This field is automatically set to Applies to record. In the context of the Incident table in this procedure, this field enables you to compare, for example, which particular incident has been logged by which caller.
Create metric data task	Option to mark the creation of metric data task.
Data owner assignment type	Type of the data owner assignment for the metrics within the metric definition. The choices are as follows: Simple: The system assigns the specified Data owner or Data owner group to the Metric. Advanced: The system assigns a Data owner based on the assignment configuration. Risk admins [sn_risk.admin] can set assignment configurations to dynamically assign data owners. For more information on creating assignment configurations, see Create an assignment configuration and Assignment Configuration New Record. Note: This is available if you have the GRC: Approver Configurator application installed. For more information see, Using Approver Configurator for setting up approvals.
Data owner type	Type of the data owner responsible for the metric definition. The choices are as follows: User User group
Data owner	Data owner responsible for the metric definition. Select a data owner from the list. Note: If you selected the advanced option for Data owner assignment type, this is the assigned data owner if the assignment configuration doesn’t return any results.
Instructions	Instructions for the data owner.
Collect supporting data	Option to enable collection for supporting data. Note: Collected supporting data is automatically deleted after a certain period, with the retention time varying according to the data frequency. Daily: After 30 days Weekly: After 30 days Monthly: After 3 months Quarterly: After 3 quarters Semiannually: After 3 semi-annual periods Yearly: After 3 years
Supporting data fields	Specifies the data fields to be shown in the supporting data. Note: For optimal performance, limit your selection to 4-5 fields if your data is extensive. Selecting more fields may result in performance issues.
Approval required	Option to indicate if an approval is required for the metric definition. Note: When the Approval required option is enabled, the Approver type and Approver fields are displayed.
Approver type	Specifies the type of approver for the metric definition. The choices are as follows: User User group Note: This field appears only when the Approval required option is selected.
Approver	Approver user or approver group that is responsible approving the metric definition. The choices are as follows: Approver: Displayed when the User option is selected. Approver group: Displayed when the User option is selected. Note: This field appears only when the Approval required option is selected.
Metric Properties
Type	Method used to determine if the data is collected manually or in an automated manner. The choices are as follows: Automated Manual Select Automated because the procedure is to create an automated metric definition.
Enterprise Owner Type	Type of enterprise owner who is responsible for the automated metric definition. The choices are as follows: User User group
Direction	Direction that you want to see the metric in. The choices are as follows: None: If you don’t want any change in the metric direction, select this option. Minimize: If the desired metric direction is downward or descending, select this option. For example, minimize the number of risks assessments that remain open beyond their due date. Maximize: If the desired metric direction is upward or ascending, select this option. For example, you want to maximize the number of critical controls. Milestone: Option to select when the metric direction is not applicable, but the metric is tracked against a milestone. For example, if your organization has a goal to complete all the risk assessments for an entity by the end of the month, the upcoming date for the goal is considered as a milestone. Note: Thresholds can be set for all directions excluding Milestone. For more information on creating thresholds, see Create a threshold for a metric definition.
Group	Area that the metric relates to. For example, the metric may be related to the stress indicators, failure indicators, and so on.
Reporting classification	Tag used to categorize the metric.
Enterprise owner	User who is the owner of the metric and is responsible for the metric. For example, for a metric such as revenue collection, the vice president or the general manager of the business unit could be the enterprise owner.
Nature	Nature of the manual metric definition. The choices are as follows: Leading: A leading metric is predictive and helps anticipate future risk outcomes. For example, an organization may use a leading metric such as the percentage increase in control failures within critical processes. By monitoring early signs of control degradation, the organization can predict a potential rise in operational or compliance risk. Tracking this metric enables risk teams to identify emerging risk exposure and take preventive actions before the risk materializes or exceeds defined risk tolerance. Lagging: A lagging metric measures the impact of past risk events or actions. For example, a lagging metric could be the number of risk events that resulted in financial loss or regulatory penalties during a reporting period. This metric provides visibility into the organization’s historical risk impact. By tracking this metric over time, risk teams can assess how effective past risk mitigation and control efforts have been and identify patterns that require corrective action. Lagging metrics help evaluate outcomes after risks have materialized and support improvements to future risk strategies. Current: A current metric monitors active risk exposure across operations. For example, the number of active operational risks rated as high or very high helps organizations understand their present risk posture. Monitoring this metric enables risk owners to focus on high-exposure areas and initiate mitigation actions in real time.
Subgroup	Subgroup that the metric relates to.
Key metric	Option to indicate if the metric is a key metric for your business.
Confidentiality
Note: This section only appears when: The sn_grc.enable_record_confidentiality property is enabled under GRC properties. The record is in Draft state.
Confidential	Option to mark the record as confidential.
Allowed users	Users who can view the record. Note: By default, the logged-in user is added to the list of confidential users.
Allowed groups	Groups that can view the record.