Normalize the scores for metrics

  • Release version: Zurich
  • Updated March 12, 2026
  • 2 minutes to read
    • Summarize
    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 a setting called Maximum normalization input. Normalized scoring adjusts raw values into percentages to provide consistent, comparable scores across different questions, especially when answers have different scales or significance.

    Show full answer Show less

    When Maximum normalization input applies

    • The question’s data type must be either Choice or Multiple Selection.
    • The Scored checkbox must not be selected.
    • Each metric definition (possible answer) must have a unique value assigned to enable normalization.

    Normalization methods for Choice type questions

    There are two scenarios:

    • Without Maximum normalization input: Scores are calculated by normalizing the response value within the range of lowest to highest values, using the formula:
      ([Response Value] – [Lowest Value]) / ([Highest Value] – [Lowest Value]) 100.
    • With Maximum normalization input: Scores are computed as the ratio of the response value to the highest response value, multiplied by 100, using the formula:
      ([Response Value] / [Highest Value]) 100.

    Normalization methods for Multiple Selection type questions

    Two scenarios apply here as well:

    • Without Maximum normalization input: The score is based on the sum of normalization input values for selected responses divided by the sum of all normalization input values, multiplied by 100. Formula:
      (Sum of selected normalization values / Sum of all normalization values) 100.
    • With Maximum normalization input: The response with the lowest value is assigned 0. The score for each selected response is calculated as:
      (Highest normalization input value for the selected response / Maximum normalization input value) 100.
      The overall metric score is the maximum score among all selected responses.

    Practical impact for customers

    By enabling Maximum normalization input, customers can ensure that assessment scores accurately reflect the relative importance or weight of different answers, rather than just their raw values. This is useful when answer values are not evenly distributed or when certain answers should carry more weight in the scoring. Customers can expect more precise and meaningful assessment results, especially for complex or multi-select questions.

    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