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sourceDocument: Australia Governance, Risk, and Compliance
sourceDocumentLink: https://www.servicenow.com/docs/r/australia/governance-risk-compliance

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ft:publication_title :

    - Australia Governance, Risk, and Compliance

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# Normalize scores for metrics

# Normalize the scores for metrics {#ariaid-title1}

Release version: Australia  
Updated September 10, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read
Summarize  
![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI  
This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete.  

## Summary of Normalize the scores for metrics

This feature allows ServiceNow customers to normalize assessment scores for questions (metrics) using the "Maximum normalization input" setting.
It applies when questions are of the Choice or Multiple Selection data types and the "Scored" checkbox is not selected.
Normalization ensures that metric values are unique and comparable on a 0 to 100 scale, improving assessment score consistency and interpretability.
Show full answer Show less  

## Key Features

* **Maximum normalization input field:** Available only for Choice or Multiple Selection questions without the Scored box checked.
* **Choice type questions normalization:**
  * Without Maximum normalization input: Scores are calculated by scaling the response value between the lowest and highest values.
  * With Maximum normalization input: Scores are calculated by dividing the response value by the highest response value, then multiplying by 100.
* **Multiple selection type questions normalization:**
  * Without Maximum normalization input: Scores are the sum of selected normalization input values divided by the total sum of all normalization input values, multiplied by 100.
  * With Maximum normalization input: The system assigns zero to the lowest value response; for each selected response, the score is the highest normalization input value divided by the maximum normalization input value, multiplied by 100. The overall metric score is the highest of these values.

## Key Outcomes

* Normalized metric scores allow for consistent comparison across different question responses.
* Enables flexible scoring methods depending on whether maximum normalization input is used.
* Supports both single-choice and multiple-selection questions with precise, formula-driven normalization logic.
* Customers can tailor scoring to better reflect the importance or weight of each possible answer within assessments.  
You can use the Maximum normalization input setting to use normalized values to calculate assessment scores for questions (metrics).

## When Maximum normalization input applies {#set-max-norm-input__section_pnh_fqg_lzb}

The Maximum normalization input field appears only when:

* The data type of the question is either Choice or Multiple Selection.
* The Scored check box is not selected.
{#set-max-norm-input__ul_v2m_ryg_lzb}

To use normalized scoring, the value assigned to each metric definition (possible answer) for each metric (question) must be unique.

In the following examples, the Scale definition is High (larger numerical values are good).

## Choice type questions {#set-max-norm-input__section_hcc_yvn_cyb}

When Maximum normalization input is not selected

:

    Formula: (\[Value of the response\] -- \[Lowest value\] ) / ( \[Highest value\] -- \[Lowest value\]) \*
    100.
    In this example, the question allows a choice among answers with values of `1`, `2`, and `4`.{#set-max-norm-input__table_bnt_flc_mzb__entry__3}

    | Response | Calculation | Score |
    |-|-|-|
    | Dog | \[(1-1)/(4-1)\] \* 100 | 0 |
    | Cat | \[(2-1)/(4-1)\] \* 100 | 33 |
    | Goldfish | \[(4-1)/(4-1)\] \* 100 | 100 |
    [Table 1. Scores]

    {#set-max-norm-input__table_bnt_flc_mzb}

When Maximum normalization input is selected

:

    Formula: `([Value of the response]/ [Highest value]) * 100`.

    In this example, the question allows a choice among answers with values of `1`, `2`, and `4` and normalization input values of `3`, `5`, and
    `9` respectively.
    {#set-max-norm-input__table_fqp_nlc_mzb__entry__3}

    | Response | Calculation | Score |
    |-|-|-|
    | Dog | (1 / 4) \* 100 | 25 |
    | Cat | (2 / 4) \* 100 | 50 |
    | Goldfish | (4 / 4) \* 100 | 100 |
    [Table 2. Scores]

    {#set-max-norm-input__table_fqp_nlc_mzb}

## Multiple selection type questions {#set-max-norm-input__section_r21_vlh_lzb}

When Maximum normalization input is not selected

:

    Formula: `([Sum of the normalization input values for the selected responses] / [Sum of all the normalization input values]) * 100`.

    In this example, the question allows for multiple selections among answers with values of `1`, `2`, and `4` and normalization input values of `3`,
    `5`, and `9` respectively.
    {#set-max-norm-input__table_bl2_tnc_mzb__entry__3}

    | Response | Calculation | Score |
    |-|-|-|
    | Dog and Cat | (\[3+5\] / 17) \* 100 | 47 |
    | Cat | (5 / 17) \* 100 | 29 |
    | Cat and Goldfish | (\[5+9\] / 17) \* 100 | 82 |
    | Goldfish | (9 / 17) \* 100 | 53 |
    [Table 3. Scores]

    {#set-max-norm-input__table_bl2_tnc_mzb}

When Maximum normalization input is selected

:

    * The system uses the value `0` for the response that has the lowest value. In this example, the Dog response is assigned the value `0`.
    * Formula for each selection: `([Highest normalization input value for the selected responses] / [Maximum of the normalization input values]) * 100`.
    * The score for the metric (question) is the maximum calculated score among all responses.
    {#set-max-norm-input__ul_wmd_3pp_lzb}  
    In this example, the user selects Dog and Cat.

    * The score for the Dog response is `(0 / 9) * 100 = 0`.
    * The score for the Cat response is `(5 / 9) * 100 = 55.5`.
    * The score for the overall metric is `55.5`.
    {#set-max-norm-input__ul_ds1_ypp_lzb}

    Formula: `(Highest of the normalization input values for the selected responses / Highest of all the normalization input values) * 100`.

    In this example, the question allows for multiple selections among answers with values of `1`, `2`, and `4` and normalization input values of `3`,
    `5`, and `9` respectively.
    {#set-max-norm-input__table_zqh_24c_mzb__entry__3}

    | Response | Calculation | Score |
    |-|-|-|
    | Dog and Cat | (5 / 9) \* 100 | 56 |
    | Cat | (5 / 9) \* 100 | 56 |
    | Cat and Goldfish | (9 / 9) \* 100 | 100 |
    | Goldfish | (9 / 9) \* 100 | 100 |
    [Table 4. Scores]

    {#set-max-norm-input__table_zqh_24c_mzb}