Normalize the scores for metrics

  • Release version: Australia
  • Updated March 12, 2026
  • 2 minutes to read
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    Summary of Normalize the scores for metrics

    This document outlines how to use Maximum normalization input settings in ServiceNow to normalize scores for assessment metrics. This is particularly relevant for Choice and Multiple Selection questions where unique values must be assigned to each metric definition.

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    Key Features

    • Normalization Methods: Two approaches are provided depending on whether Maximum normalization input is selected or not.
    • Choice Type Questions:
      • Without Maximum normalization: Scores are calculated using the formula: ([Value of the response] – [Lowest value]) / ([Highest value] – [Lowest value]) 100.
      • With Maximum normalization: Scores are calculated as: ([Value of the response] / [Highest value]) 100.
    • Multiple Selection Type Questions:
      • Without Maximum normalization: The formula used is ([Sum of the normalization input values for the selected responses] / [Sum of all normalization input values]) 100.
      • With Maximum normalization: The lowest value response is assigned a score of 0, and the score is calculated based on the highest normalization input values.

    Key Outcomes

    Using Maximum normalization input allows for a standardized scoring method that can help assess responses more accurately based on their relative performance. This ensures that scores reflect the significance of each response in the context of all possible answers, providing clearer insights for decision-making.

    You can use the Maximum normalization input setting to use normalized values to calculate assessment scores for questions (metrics).

    When Maximum normalization input applies

    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.

    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

    When Maximum normalization input is not selected

    Option to select maximum normalization input.

    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.
    Table 1. Scores
    Response Calculation Score
    Dog [(1-1)/(4-1)] * 100 0
    Cat [(2-1)/(4-1)] * 100 33
    Goldfish [(4-1)/(4-1)] * 100 100
    When Maximum normalization input is selected

    Option to select maximum normalization input.

    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.

    Table 2. Scores
    Response Calculation Score
    Dog (1 / 4) * 100 25
    Cat (2 / 4) * 100 50
    Goldfish (4 / 4) * 100 100

    Multiple selection type questions

    When Maximum normalization input is not selected

    Option to select maximum normalization input.

    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.

    Table 3. Scores
    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
    When Maximum normalization input is selected

    Option to select maximum normalization input.

    • 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.
    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.

    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.

    Table 4. Scores
    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