Normalization of application scores
Summarize
Summary of Normalization of Application Scores
Normalization of application scores in ServiceNow enables you to calculate standardized scores for applications based on various indicators and their weights. These scores help assess, compare, and make strategic decisions about applications regarding retention, replacement, maintenance, or investment.
Show less
How Scores Are Calculated
- Application indicator data is collected according to the frequency defined in each indicator.
- The raw data, called Application Weight, is stored in the Application Indicator Score table.
- Normalization converts raw application weights into a score on a 1 to 10 scale using the formula:
(Application Weight - Target minimum) / (Target maximum - Target minimum) 9 + 1 - If Target maximum and minimum values are not set, they are dynamically derived from the range of application weights.
- The system applies intelligent logic to determine target values unless the "Consider Absolute Values" option is selected, which enforces user-defined targets.
- Directionality (Maximize or Minimize) of indicators affects scoring: for Minimize, lower raw values yield higher scores, and vice versa.
- Normalized values are adjusted by the application profile’s weightage to calculate individual indicator scores.
- The final application score is the sum of all indicator scores within the profile.
Important Considerations
- Target maximum and minimum values influence normalization only when the indicator frequency matches the fiscal scoring period.
- If frequencies differ, dynamic normalization uses current application weights to avoid inaccurate scoring, especially for aggregated data sources like Performance Analytics.
- Indicators reading static values (e.g., active user count) maintain consistent scoring across frequencies when absolute targets are used.
- Scores and related numeric values are rounded to two decimal places for precision and consistency.
Practical Benefits for ServiceNow Customers
- This normalization process provides a standardized, comparable scoring framework across diverse application metrics.
- It supports data-driven decision-making for application portfolio management by reflecting both quantitative data and strategic priorities through weighting and direction settings.
- Customers can configure indicators and weights to tailor scoring to business objectives and fiscal periods.
- Understanding normalization helps in interpreting scores accurately and ensures appropriate use of target values and indicator frequencies to maintain score integrity.
The indicators and their respective weights are used to calculate application score profiles for each configuration item. Use the score profile to calculate application scores and assess the applications. Apply these scores to compare applications and make strategic decisions about which ones to keep, replace, maintain, or invest more in.
The preconfigured indicators or the indicators that you created retrieve their related data based on the frequency set at the indicator definition stage. This data is captured in the Application weight column of the Application Indicator Score [apm_app_indicator_score] table. The Target maximum and Target minimum that are set while creating an application indicator are for calculating the applications normalized value.
The normalized value of the application score, which is measured on a scale of 1–10, is derived from the following formula:
(Application Weight - Target minimum)/(Target maximum - Target minimum) * 9+1- If the Target maximum and Target minimum are not set, then the maximum value within the range of applications is taken as the target maximum value. Similarly, the minimum value within the range of applications is taken as the target minimum value.
- If the Target maximum and Target minimum are set and the Consider Absolute Values check box is selected, the entered values are considered.
- If the Target maximum and Target minimum
are set and the Consider Absolute Values check box is cleared, the
values are considered based on the following intelligent logic.
Target maximum = Minimum value of (Target maximum value defined in the Indicator [apm_metric] table, Maximum value of Application Weights for the fiscal period)For example, consider a scenario where:- The application weights are 10, 20, 30,.…., and 1000.
- Value entered in the Target maximum field is 100.
With these assumptions, the Target maximum value considered is 100, as the defined Target maximum value (100) is lesser than the maximum application weight (1000).
Target minimum = Maximum value of (Target minimum value defined in the Indicator [apm_metric] table, Minimum value of Application Weights for the fiscal period)For example, consider a scenario where:- The application weights are 10, 20, 30,.…., and 1000.
- Value entered in the Target minimum field is 100.
With these assumptions, the Target minimum value considered is 10, as the defined Target minimum value (100) is greater than the minimum application weight (10).
-
The Target maximum and Target minimum values are applied during normalization only when the indicator frequency matches the fiscal period being scored. If the frequencies don't match, the system uses dynamic normalization and derives the minimum and maximum boundaries from the actual application weights in the current scoring run.
This behavior is intentional for indicators where raw values vary by fiscal period — for example, Performance Analytics indicators and Query Condition indicators that aggregate counts over time. For these indicators, applying a monthly target maximum to a quarterly or yearly aggregated value produces incorrect scores.
For Query Condition indicators that read a static field value from the business application record — such as active user count — the raw value is the same regardless of the fiscal period. For such indicators, using the same absolute target values across all frequencies produces consistent and meaningful scores. However, because the system applies the same frequency-matching rule to all indicator types, absolute target values aren't used when the frequencies don't match.
The Application Weight that is lesser than or equal to the target minimum is given the lower score, which is 1.
The Application Weight that is greater than or equal to the target maximum is given the maximum score, which is 10.
When you set the application indicators, you can also configure the Direction as Maximize or Minimize. The application with the maximum value gets the minimum score when the direction is Minimize. The application with the minimum value gets the maximum score when the direction is Maximize.
If the Direction in the indicator is Minimize:
(10 - above calculated Normalized value) + 1Application profile weightage is then applied on the Normalized value to derive the Indicator Score:
Normalized Value * Weightage as in application score profile %After the indicator score is calculated for each of the indicators, the application score is calculated by summing up all the indicator scores used in the profile.
If the source of the indicator is Indicators in the Data source field, then the application weight is calculated as the sum of the normalized scores of all its dependent indicators.
- The normalized score of the parent indicators is then calculated in a similar manner as it is calculated for all the other indicators.
- The normalized value, indicator score, application weight, target maximum, target minimum, and total weight are all rounded to two decimal places only.
In the figure, since the Cost and Incident indicators are set to minimize, the applications with lower costs and lower number of incidents have higher scores.