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
working with Performance Analytics
, you can
- 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.
The following are some key characteristics of the Business
- Indicator scores can be generated automatically from a set of records defined in
an indicator source, entered manually, or calculated from other
- Indicator scores can be viewed or analyzed in generated scorecards or presented,
via widgets, on dashboards.
Synonyms: Metrics, business metrics,
- Indicator sources
- define filtered
sets of records from a facts table to evaluate when collecting indicator scores.
An indicator source configuration specifies a
table, such as incident, and it specifies the frequency with which to collect data
from that table. Indicator sources can also include filter conditions to limit the
included records. Multiple indicators can use the same indicator source.
Typically, an indicator tracks the situation on a
certain date. The indicator source conditions usually includes a date-related filter,
such as [Opened][on][Today]. Indicators collected less frequently
might specify a larger date range, such as [Closed][on][This
- 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 scorecards and dashboards.
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. Breakdowns are automated,
manual, or external, depending on where these elements come from. Automated breakdown
elements are based on existing data in breakdown sources. A field in the
facts table is mapped to a set of records on the breakdown source, or a script is used
for more complex mapping. 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 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 in your instance for Number of
Open Changes, you can limit the element list to just those groups that are part of the
change process by configuring the Breakdown Source.
- 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 scorecard or widget.
Aggregation functions in the scorecard or
widget are named time series.
- Bucket groups
- are custom groups that can be used when you define a
breakdown source that uses Bucket [
pa_buckets] as the facts table.
Bucket groups can also be used with a script.
When configuring the indicator, you can attach a script that runs through the collected
data and places the records into a bucket group. For example, you can arrange open
incidents according to age, such as <1 day, 2-5 days, 6-30 days, >30 days old. In
this case, the indicator Open Incidents is broken down by
- 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.
- A day in Performance Analytics is
always defined as 24 hours. Performance Analytics does not use the
concept of 'business days.'
- 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.
- 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 detailed
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.
- are a graphical visualization of the scores of an indicator.
Indicators generate scorecards automatically. The basic feel and look of a scorecard can
not be changed. Scorecards can be enhanced by adding targets, thresholds, trendlines,
and useful comments for significant changes. In a scorecard, the scores of an indicator
can be analyzed further by viewing the scores by breakdowns (scores per group),
aggregates (counts, sums, and maximums), time series (totals and averages applied to
different time periods) and drilling down to the records on which the scores are
- 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
a scorecard or 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
scorecards, whereas global targets appear on scorecards and time series
- 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
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 detailed scorecard.
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 scorecards, while global thresholds appear on both
scorecards and time series widgets.
- are reusable graphic visualizations on a dashboard. 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.