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Share the Wealth: Performance Analytics in ServiceNow

Updated: Feb 1, 2021

In this week’s Share the Wealth video, David Tapia of GlideFast gives an overview of Performance Analytics in ServiceNow.

What is Performance Analytics?

Performance Analytics visualizes business process, performance trends, and summaries for continual service improvement. Key characteristics of Performance Analytics include that it exists as a native in-platform solution built for ServiceNow data, visualizes ServiceNow process and service data in real-time dashboards, proactively tracks the health of processes and services, and anticipates trends and notifies stakeholders upon performance change.

How does Performance Analytics work?

Performance Analytics trends business process performance data for continual service improvement in three steps:

  1. Create indicators to represent KPIs

  2. Collect service and process data

  3. Build process trend visualizations

Reporting vs. Analytics

A report is a snapshot of the process measured at a specific time while an indicator is a series of measurements collected over time.

Indicator Scorecards/Analytics Hub

Scorecards display data for a single indicator. Scorecards enable you to gain insights on how indicator scores broken down by different dimensions change over time.

Scoresheets display scores and breakdowns as a spreadsheet.

Data Collection

The data collection process is the core process that feeds raw measurement data into Performance Analytics score tables. The Performance Analytics score tables are used to provide data for Scorecards and Dashboards widgets.

Historic collection collects snapshots from several days of historic data. It typically only runs once for an indicator and the run interval is set to On Demand.

Scheduled data collection is the most widely used method because it collects snapshots of data at regular intervals, usually daily. Other available Run intervals are Weekly, Monthly, and Periodically.

Automated Indicator and Breakdowns

Indicator sources are a set of records from a process (Facts) table. They are used as the base source for multiple indicators. This includes the date field in condition.

Automated indicators is a process metric based on a source and trended over time. This describes the count/total/average/max/mix value of a process. Optional additional conditions (Filters) allowed to refine the metric.

Breakdown sources are a source of categorization data that specifies the allowed categories to classify by.

Automated breakdowns categorize indicator data into dimensions such as category, priority, state, etc. This specifies Facts table and Field to category by/map. This is based on a source.

Bucket Groups and Breakdown Relations

Bucket groups are elements in the buckets [pa_bucket] table used as breakdown sources for non-categorical data such as age, date, percent, etc.

Breakdown relations are navigational links between two breakdowns.

Formula and Manual Indicators

Manual indicators are scores manually entered into Scoresheets or imported from a spreadsheet.

Manual breakdowns are similar to automated breakdown. The difference is that the elements of a manual breakdown are not retrieved from an automated breakdown source but entered manually.

Formula indicators are scores calculated based on the scores of other indicators.

Actionable Data and Predictive Analytics

Time series aggregate scores using an operator such as SUM or AVERAGE for a specific period of time such as Week, Month, etc.

Targets sets quantifiable goals for indicators and provide context to scores and direction for performance improvements. Users can see when in the future they will reach their target.

Thresholds allow for indicator exception reporting and alerting.

Element filters are dynamic query applied to a breakdown in scorecard different from navigation by breakdown element.

Widgets and Dashboards

Widgets are reusable visualization of the indicator scorecard. Multiple types and graphing formats are available:

Dashboards refer to multi-tab arrangement of Performance Analytics widgets and reports that can be shared and used as a homepage.

Data filtering refers to interactive filters which are widgets that filter the contents of widgets and reports to display a subset of data. Interactive filters ONLY apply to report type widgets, not Performance Analytics widgets.

Context Sensitive Analytics, also referred to as “In-Form Analytics” are designed to provide incident technicians with relevant incident insight.

Spotlight refers to ranking records based on multiple weighted criteria.


Interested in working with experts like David? Reach out to our team. We would love to learn more about your ServiceNow challenges and how we can help your organization build better solutions.

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