Normalized value for an assessment

  • Release version: Yokohama
  • Updated January 30, 2025
  • 2 minutes to read
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    Summary of Normalized value for an assessment

    The normalized value in assessments is calculated using a linear equation based on the metric’s scale definition. This value is essential for risk assessments and provides a standardized measure of metric results, enabling consistent interpretation and comparison across different metrics.

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    Normalized Value Calculation for Metrics

    The normalized value reflects the position of an input value within the metric’s defined range and adjusts for metric weight and category bias. It is calculated as:

    Normalized value = ((Input Value - Min value) / (Max value - Min value)) × (Current metric weight × Bias / Sum of all metric weights in the category) × Scale factor

    Bias accounts for the ratio between total metric weight and valid metric weight in the category, excluding scripted metrics. If a metric is skipped during assessment, its weight is excluded from valid weights.

    Metrics with data types such as String, Date, Date/Time, Reference, Attachment, and Ranking are excluded from normalized value calculations.

    Example for a Numeric Metric

    • Input value: 3
    • Minimum value: 1
    • Maximum value: 6
    • Current metric weight: 10
    • Number of metrics in category: 6 (only 4 are numeric and valid)
    • Scale factor: 10

    Calculation results in a normalized value of 0.8, demonstrating how input values are scaled and weighted within their category.

    Normalized Value for Multiple Selection Metrics

    For multiple selection metrics, the normalized value sums the scores of selected choices, each normalized by their input values relative to the metric’s maximum value. The formula is:

    Normalized value = (Sum of scores of selected choices) × (Current metric weight / Sum of valid metric weights) × Scale factor

    The minimum value in this case is always zero.

    Example for Multiple Selection Metric

    • Choices: A (input 1), B (input 1), C (input 2)
    • Maximum value: 4 (sum of all choices’ inputs)
    • Current metric weight: 10
    • Number of metrics in category: 5
    • Scale factor: 10

    If choices A and B are selected, the normalized value calculates to 1, illustrating the aggregation of selected choices’ normalized scores.

    Weighted Value for Risk Assessment

    In risk assessments, the weighted value is derived by multiplying the metric weight by the actual metric result value from the Metric Result table. This weighted value supports risk prioritization based on metric significance.

    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