Normalized value for an assessment

  • Release version: Zurich
  • Updated July 31, 2025
  • 2 minutes to read
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    Summary of Normalized value for an assessment

    The normalized value in ServiceNow assessments is calculated using a linear equation based on the metric's scale definition, enabling consistent risk assessment across various metrics. This value standardizes input values relative to defined minimum and maximum metric values and adjusts for metric weight, bias, and scale factors.

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    Normalized Value Calculation for Metrics

    The normalized value is proportional to the metric’s scale. For metrics where lower values are better, the normalized value is adjusted by subtracting from 1. The formula for a single metric is:

    Normalized value = (Input Value – Min value) / (Max value – Min value) × (current metric weight × bias / sum of all metric weights in the category) × scalefactor

    Here, bias accounts for the ratio of total category metric weight to the sum of valid metric weights, excluding scripted metrics and skipped metrics (which remove their weight from the sum). Certain metric types such as String, Date, Date/Time, Reference, Attachment, and Ranking are excluded from normalized value calculations.

    Example metrics include numeric and yes/no types; string types are invalid for normalization.

    Normalized Value for Multiple Selection Metrics

    For multiple selection metrics, the normalized value sums the scores of selected choices. Each choice’s score is its normalization input divided by the metric’s max value (sum of all choices’ normalization inputs). The formula is:

    Normalized value = (Sum of scores of selected choices) × (current metric weight / sum of valid metric weights in the category) × scalefactor

    The minimum value is always zero for multiple selection metrics.

    Weighted Value for Risk Assessment

    To support risk assessment reporting, the weighted value is calculated from the metric results as:

    weightedvalue = metric.weight × result.actualvalue

    Practical Implications for ServiceNow Customers

    • Normalized values standardize diverse metric inputs, facilitating consistent risk scoring and comparison across assessments.
    • Understanding metric scale and weight, including exclusions, ensures accurate calculation and meaningful reporting.
    • Multiple selection metrics require inputting normalization values for each choice to properly reflect their contribution.
    • The weighted value calculation directly ties normalized results to risk assessment scoring, helping prioritize risks effectively.

    Using the Metric Result [asmtmetricresult] table for reporting allows customers to access calculated normalized and weighted values for comprehensive assessment insights.

    The normalized value is calculated based on a linear equation and the scale definition of the metric. This value can be used for risk assessment.

    Normalized value for any metric

    The normalized value is directly proportional to the scale definition of the metric. If the scale definition is low, that is, the lower scale values are better, then Normalized value = 1.0 – Normalized value.

    For the reporting purpose, use the Metric Result [asmt_metric_result] table.

    Normalized value = (Input Value - Min value defined in metric) / (Max value defined in metric - Min value defined in metric) * (current metric weight * bias / (sum of all metric weight in the metric category)) * scale_factor

    Bias is the ratio of total metric weight in the category and the sum of valid metric weight in the metric category. While calculating bias, the scripted metrics are excluded.
    Note:
    • If a metric is skipped when taking the assessment, its weight is excluded when calculating sum of valid metric weight in the metric category.
    • The following metric types are excluded in the normalized value calculation:
      • String
      • Date
      • Date/Time
      • Reference
      • Attachment
      • Ranking

    For example, consider the following scenario.

    Calculate the normalized value for the Please rate the competency of the technician metric.

    Table 1. Values of the metric
    Input value 3
    Minimum value 1
    Maximum value 6
    Current metric weight 10
    Number of metrics in the metric category 6
    • 4 of type=number
    • 1 of type=yes/no
    • 1 of type=string (invalid data type; value cannot be calculated)
    Valid metric weight of each response 10
    Scale factor 10

    Normalized value = (3 - 1) / (6 - 1) * (10 / (10 + 10 + 10 + 10 + 10)) * 10 = 0.8

    Normalized value for a multiple selection metric

    The normalized value for a multiple selection metric is calculated by using the weight of the metric and the score for each choice of the metric.

    In a multiple selection metric, for each choice that should be used for the normalization calculation, define the normalization input value.

    Normalized value = (Score of all choices) * (current metric weight / (sum of valid metric weight in the metric category)) * scale_factor

    Here, score of all choices of the metric is the sum of individual scores of each choice.
    • Score of each choice in a multiple selection metric= Normalization input of the choice / max value of the metric
    • max value of the metric = Sum of the normalization input for all choices of the metric
    • min value of the metric is always 0

    For example, consider the following scenario.

    Calculate the normalized value for the multiple selection metric, Please rate the competency of the technician, with three choices, A, B, and C.

    Table 2. Values of the metric
    Choice A Normalization input is 1
    Choice B Normalization input is 1
    Choice C Normalization input is 2
    Minimum value 0
    Maximum value 4
    Current metric weight 10
    Number of metrics in the metric category 5
    Valid metric weight of each metric 10
    Scale factor 10

    If Choice A and B are selected, Normalized value = ((1 / 4) + (1 / 4)) * (10 / (10 + 10 + 10 + 10 + 10)) * 10 = 1

    Weighted value for a risk assessment

    For a risk assessment, the weighted value from metric results table is calculated as following.

    weighted_value = metric.weight * result.actual_value