Performance Analytics concepts

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  • Updated July 31, 2025
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    Summary of Performance Analytics concepts

    Performance Analytics in ServiceNow provides a framework for measuring and analyzing business performance through regularly collected data points called indicators (KPIs). These indicators track the status of business services, activities, or organizational behaviors over time, enabling organizations to monitor current conditions and predict future trends. The concepts described focus on the core capabilities within the Performance Analytics module, which is also leveraged by other applications like Benchmarks.

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    Key Features

    • Indicators (KPIs): These are performance measurements derived from data sets and aggregates (such as counts) with optional conditions. Indicators can be automatically generated, manually entered, or calculated from other indicators. They are viewable and analyzable in the Analytics Hub, dashboards, and KPI Details.
    • Breakdowns and Elements: Enable grouping or filtering of indicator scores by qualitative attributes (e.g., Priority, Category, Assignment Group). Breakdowns have elements representing the possible values and can be automated, manual, or external (via JDBC/SQL). Up to two breakdown levels can be applied to an indicator.
    • Data Collector: This engine collects periodic snapshots of process tables and stores scores. Jobs can be scheduled to run automatically or manually, often matching the frequency of the indicator source, and can generate scores for multiple indicators sharing the same source.
    • Aggregation Functions: Performance Analytics applies aggregate functions over time, such as summing indicator scores across months. Aggregations can be configured in indicator definitions or applied dynamically in analytics views (time series).
    • Breakdown Mappings and Sources: Breakdown mappings link breakdowns to indicator sources via fields or scripts (scripted breakdowns), defining how data is grouped. Breakdown sources specify the unique elements for a breakdown and can be based on tables, views, or bucket groups for recategorizing data.
    • Bucket Groups: Allow grouping ranges of values into discrete categories (buckets) for more meaningful breakdowns, managed through specific bucket group records in the data architecture.
    • Indicator Sources: Define the data set by specifying a table, filtering conditions, and collection frequency. Multiple indicators can share an indicator source, ensuring consistent data collection points.
    • Snapshots: Lists of record IDs captured when scores are collected, available for automated indicators with record collection enabled. Snapshots support detailed analysis and are retrievable within analytics views.
    • Spotlight Feature: Highlights specific records within the data to bring attention to items that might otherwise be overlooked.
    • Complimentary Performance Analytics for Incident Management: A limited version included in the base system for users to familiarize themselves with core functionality before subscribing to the full Performance Analytics suite.

    Key Outcomes

    By leveraging these concepts, ServiceNow customers can systematically track and analyze performance metrics over time, segment data for deeper insights, and automate data collection processes. This enables informed decision-making, trend forecasting, and targeted operational improvements. The structured approach to data aggregation, breakdowns, and snapshots supports comprehensive performance management tailored to organizational needs.

    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

    Indicators
    (KPIs) 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.

    Technically, an indicator combines a data set and a data aggregate, such as Count, along with optional conditions.

    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 Platform Analytics data visualizations and KPI Details. In the Core UI, view them in the Analytics Hub or in widgets on dashboards.

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

    Synonyms: Metrics, business metrics, KPIs

    Breakdowns and elements
    enable you to group or filter indicator scores by a qualitative attribute such as Priority, Category, or Assignment Group. You can apply a breakdown on the Analytics Hub, in KPI Details, 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.

    You cannot apply more than two levels of breakdown to an indicator.

    Synonyms: dimensions, drill-downs
    Data collector
    is the engine that takes periodic snapshots of your process tables and stores them in the Scores and Snapshots tables. 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. One job usually generates scores for multiple indicators that use the same 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.

    Other concepts

    Aggregate/Aggregation
    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 the Analytics Hub or widget. Aggregation functions in the Analytics Hub or widget are named time series.
    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.
    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.
    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.

    Day
    A day in Performance Analytics is always defined as 24 hours. Performance Analytics does not use the concept of 'business days.'
    Indicator sources
    are data sets consisting of filtered records from one table or database view. An indicator source configuration specifies a table, such as Incident [incident], conditions for filtering records from that table, and a frequency that you base on the conditions. An indicator source cannot specify a rotated table. Multiple indicators can use the same indicator source. Data collection jobs query the database once for each indicator source. Thus, all indicators that use the same indicator source get data from the same point in time.

    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].

    Scripted breakdown
    is a breakdown that uses a script to query the indicator source as its breakdown mapping.
    Snapshots
    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 automated indicators with Collect records selected.

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

    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.