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Performance Analytics concepts

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Performance Analytics concepts

Performance Analytics uses terms and concepts that can differ from industry norms due to the unique nature of the ServiceNow platform.

Note: Performance Analytics is used by other applications, such as Benchmarks. The information below describes the core Performance Analytics functionality. For information about other applications that use Performance Analytics, refer to the documentation for those applications.
Performance Analytics includes the following concepts and components:

Key components

define a performance measurement taken at regular intervals of a business service, an activity, or organizational behavior. These performance measurements result in a series of indicator scores over time. Businesses track these scores to measure current conditions and to forecast trends.
Key characteristics of indicators include:
  • Indicator scores can be generated automatically from a set of records defined in an indicator source, entered manually, or calculated from other indicators.
  • Indicator scores can be viewed or analyzed in the Analytics Hub or presented, via widgets, on dashboards.

For convenience, you can organize indicators thematically into an indicator group.

Synonyms: Metrics, business metrics, KPIs

Indicator sources
define filtered sets of records to evaluate when collecting indicator scores. An indicator source configuration specifies a table, such as Incident [incident], and it specifies the frequency with which to collect data from that table. An indicator source cannot specify a rotated table. Multiple indicators can use the same indicator source.

Typically, an indicator tracks the situation on a certain date. The indicator source conditions usually include a date-related filter, such as [Opened][on][Today]. Indicators collected less frequently might specify a larger date range, such as [Closed][on][This month].

Breakdowns and elements
enable you to group or filter indicator scores for more detailed analysis, such as to show separate scores for each assignment group. You can apply a breakdown on the Analytics Hub and on dashboards.

For example, you can look at the Number of Open Changes by Assignment Group. Or you can see the Number of New Changes by Priority.

The values for each breakdown are called breakdown elements. For example, the Priority breakdown may have the elements Critical, High, and Low. Breakdowns are categorized as automated, manual, or external, depending on where these elements come from. Automated breakdown elements are specified in breakdown sources. Manual breakdowns have their elements entered manually to define an organization. Lastly, an external breakdown specifies the JDBC data source and SQL statement for retrieving breakdown elements.

Synonyms: dimensions, drill-downs
Breakdown sources
specify which unique values, called breakdown elements, a breakdown contains. A breakdown source is defined as a set of records from a table or database view or as a bucket group. Multiple breakdowns can use the same breakdown source. For example, instead of seeing ALL assignment groups for the Number of Open Changes indicator, you can limit the element list to just those groups that are part of the change process by configuring the Breakdown Source.
Breakdown mappings
specify the relationships, or 'map,' breakdowns to indicator sources. A breakdown mapping either specifies a field on the indicator source or specifies a script that queries the indicator source. The latter is sometimes called a scripted breakdown mapping, and a breakdown with such a mapping is called a scripted breakdown.
Data collector
is the engine that collects the process and service performance data that are presented through indicators and breakdowns. You can set up data collector jobs to run automatically according to a schedule. Usually set a job schedule to match the frequency in the indicator source. You can also set up jobs that run manually, such as historical jobs, which you run only when collecting data for a new indicator.


Analytics Hub
is the central interface where you assess, compare, and predict the performance of an indicator over time. Set on the indicator record whether that indicator is to be included in the Analytics Hub.

The Analytics Hub was previously named the Scorecard.

are single-screen displays of multiple Performance Analytics, reporting, and other widgets. Dashboards can be responsive or non-responsive. To create or share a responsive dashboard, you need at least one role, but this can be any role. You can drag to move and resize widgets on responsive dashboards. Non-responsive dashboards use less flexible drop zone layouts, and require Performance Analytics roles to view, create, and edit.
Time series
can refer to either of the following items:
  • A type of widget that aggregates and shows multiple scores of an indicator collected over a period.
  • A statistical function applied to collected indicator scores over a time period in the Analytics Hub or in a widget, also called an aggregator.
are goals your organization wants to achieve, operationalized as indicator scores. Targets enable you to visualize the difference between the desired score at a certain date and the actual score of an indicator.

A target can be personal or global. A personal target is visible only to the user that created it and appears as a light line. A global target is visible to all users and appears as a dark line. Personal targets appear only on Analytics Hubs, whereas global targets appear on Analytics Hubs and time series widgets.

define a normal range of scores for an indicator and alert you when certain events occurs, such as when a score reaches an all-time high or low.

When a threshold is triggered, the instance generates an email notification. This message is associated with the indicator and the message is directly available via the Analytics Hub.

A threshold can be personal or global. A personal threshold is visible only to the user that created it and appears as a light gray dotted line. A global threshold is visible to all users and appears as a dark gray dotted line. Personal thresholds appear only on Analytics Hubs, while global thresholds appear on both Analytics Hubs and time series widgets.

are reusable graphic visualizations for use on dashboards. In Performance Analytics, widgets show the scores of one or more indicators. For example, a widget can display the evolution of an indicator over time, how an indicator can be broken down, or how several indicators look side by side. Many variations are possible. Widgets are visible only when added to a dashboard.

Other concepts

can refer to either of the following functions:
  • The Performance Analytics function of aggregating, or collecting, indicator scores over time. The indicator configuration includes the frequency with which indicator scores are collected.
  • Statistical functions applied to collected indicator scores over a time period. For example, you can apply a 3-month SUM to indicator scores. Aggregation functions can be added either in the indicator form or later in the Analytics Hub or widget. Aggregation functions in the Analytics Hub or widget are named time series.
Bucket groups
are used to recategorize data so it can be used as a breakdown, for example by grouping a range of values into discrete buckets.

To work with a bucket group, create a breakdown source that uses Bucket [pa_buckets] as the facts table and specifies the bucket group in a condition. If a breakdown built on this source uses a breakdown mapping with a script, the breakdown groups the values that the script returns into buckets. If the breakdown mapping specifies a field instead of using a script, the breakdown groups the values of the mapped field into buckets.

In the data architecture, bucket groups are defined in Bucket Group [pa_bucket_groups] records and buckets in Bucket [pa_buckets] records. Each Bucket [pa_buckets] record contains a Bucket Group field that is a reference to a Bucket Group [pa_bucket_groups] record.

A day in Performance Analytics is always defined as 24 hours. Performance Analytics does not use the concept of 'business days.'
Scripted breakdown
is a breakdown that uses a script to query the indicator source as its breakdown mapping.
are the lists of records (sys_ids) that are collected at the time that the scores for those records are collected. A snapshot is made only for indicators with Collect records selected.

The snapshot/list of records can be retrieved in the Analytics Hub.

Snapshots are kept for the main indicator and for first level breakdowns. Second level breakdown snapshots are derived as an intersection of the two first level breakdown snapshot lists.