Applying time series to result or to contributing indicators
Summarize
Summary of Applying time series to result or to contributing indicators
In ServiceNow Performance Analytics, when using formula indicators, you can apply time series aggregations either to each contributing indicator individually or to the final formula result. This behavior is controlled by theApply time series to resultoption, found in the Other properties tab of a formula indicator record. This setting influences how time series aggregations operate across Core UI Performance Analytics widgets, Analytics Hub, and Data visualizations within Platform Analytics.
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Key Details on Applying Time Series
- The Apply time series to result option determines if time series aggregation is applied after the formula calculation (to the result) or before (to each contributing indicator).
- This option affects any selected time series aggregation and the default time series set on the indicator; however, the default time series only applies in Analytics Hub and KPI Details views.
- If no time series aggregation is selected on a widget or visualization, the default time series does not apply.
- The setting only takes effect if a real aggregate is chosen when no default time series exists.
- If the time series corresponds simply to the indicator frequency (e.g., daily, weekly), this setting does not affect the outcome.
How the Setting Changes Calculations
- When checked: The formula is calculated first on raw indicator values, and then the selected time series aggregation is applied to the final formula result over the time window.
- When unchecked: Time series aggregation is applied individually to each contributing indicator first, and then the formula is evaluated on these aggregated values.
- The two approaches can produce significantly different results; neither is incorrect but reflect different analytical perspectives.
Practical Example
Consider the formula indicator "% of new P1 incidents", which calculates the daily percentage of Priority 1 incidents:
(Number of new Priority 1 incidents) / (Number of all new incidents) 100
If you want to display a 7-day running average by default, you can set a 7-day running average as the default time series and apply it to the formula result. This calculates the percentage each day, then averages the percentages over seven days.
Alternatively, if the option is unchecked, the 7-day running average is applied separately to the numerator and denominator before calculating the percentage, potentially leading to a different result.
Comparing both formulas in a time series widget helps determine which method best fits your measurement goals.
Why This Matters for ServiceNow Customers
Understanding and correctly setting how time series aggregations apply in formula indicators is essential for accurate and meaningful analytics. It allows customers to tailor calculations to their specific reporting needs, ensuring that the data reflects the intended measurement period and aggregation approach.
Choosing the appropriate method helps avoid misinterpretation of trends and supports better decision-making based on Performance Analytics data.
Related Concepts and Tasks
- Preventing a contributing indicator in a formula from following breakdowns
- Using breakdown matrices in formula indicators
- Indexing multiple indicators in a formula
- Managing changes to scorestart/end times due to different user time zones
- Applying time series aggregations effectively
- Creating formula indicators and using analytics methods within formulas
- Detecting indicators with no scores in a formula
For a formula indicator, a time series aggregation can apply either to each indicator in the formula individually or to the formula result.
- The default time series applies only on the Analytics Hub and KPI Details. If you do not select a time series aggregation on a widget or data visualization, the default time series does not apply.
- For the setting to take effect on the Analytics Hub or KPI Details, you must choose a real aggregate, if the indicator does not have a default time series set. If the time series is just the indicator frequency (daily, weekly, and so on), theApply time series to result setting does not apply.
When Apply time series to result is checked, first the formula is evaluated and then the selected time series is applied to the final result. When Apply time series to result is not checked, each contributing indicator is evaluated and the default time series is applied to it. Then the formula is evaluated. The results between the two settings can differ significantly. Neither setting is wrong, but you have to think carefully about what you are measuring before making your choice.
Applying a time series to result compared to applying it to contributing indicators
Consider the formula indicator "% of new P1 incidents". Every day this indicator calculates the percentage of new incidents that are Priority 1 - Critical:
You decide that you want the result to display a 7-day running average by default on the Analytics Hub. In the
Other tab of the indicator record, you select the 7d running AVG default
time series. You apply the time series to the result.
In the resulting calculation, the formula is resolved for each day. Then the average of the result is taken for that day and the previous six days:
You aren't sure if you want the 7-day average of the final result or the average 7-day average of each indicator. So, you copy the previous formula indicator, with the same time series, but with Apply time series to
result unchecked. Now, the time series is applied to the Number of new incidents > Priority = 1 - Critical and Number of new incidents contributing indicators separately before
the formula is resolved:
You plot both formula indicators in a time series widget to see the difference in outcome
between the two settings. Because the default time series only applies on the Analytics Hub, you also add the 7d
running AVG time series to the widget: