---
sourceDocument: Yokohama Governance, Risk, and Compliance
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/yokohama/governance-risk-compliance

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    - yokohama

ft:locale :

    - en-US

ft:publication_title :

    - Yokohama Governance, Risk, and Compliance

ft:clusterId :

    - grc

bundleId :

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workflow :

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---

# Normalize scores for metrics

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

* Release version: Yokohama
* 
* Updated March 12, 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 enables ServiceNow customers to normalize assessment scores for questions (metrics) using the Maximum normalization input setting.
Normalized scoring adjusts raw response values to a consistent scale, facilitating fairer and more meaningful score comparisons across different question types and answer values.
Show full answer Show less  
The Maximum normalization input option is applicable only when the question's data type is **Choice** or **Multiple Selection** , and the **Scored** checkbox is not selected. Each answer option must have a unique value, and normalization uses these values to calculate scores.

## Key Features

* **Choice type questions without Maximum normalization input:** Scores are calculated by scaling the response value between the lowest and highest possible values, using the formula:   
  (\[Value of the response\] -- \[Lowest value\]) / (\[Highest value\] -- \[Lowest value\]) 100.
* **Choice type questions with Maximum normalization input:** Uses the formula:   
  (\[Value of the response\] / \[Highest value\]) 100, where normalization input values are assigned per answer.
* **Multiple selection questions without Maximum normalization input:** Scores are based on the sum of normalization input values for all selected responses divided by the sum of all normalization input values, multiplied by 100. Formula:   
  (Sum of selected normalization input values / Sum of all normalization input values) 100.
* **Multiple selection questions with Maximum normalization input enabled:** The lowest response value is assigned zero. Scores for each selected response are calculated as:   
  (Highest normalization input value for the selected response / Maximum normalization input value) 100.   
  The overall metric score is the maximum among all selected responses.

## Key Outcomes

* Enables consistent scoring across diverse answer values by normalizing raw input, improving assessment accuracy.
* Supports both single-choice and multiple-selection question types with tailored normalization formulas.
* Maximum normalization input allows customization of normalization scales per answer, enhancing flexibility in scoring.
* By applying these normalization methods, customers get standardized percentage-based scores that facilitate better comparison and evaluation of metrics.  
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}