Understanding Normalization
Normalization in mathematics refers to the process of adjusting values measured on different scales to a common scale. This process typically involves scaling the data so that it falls within a specific range, such as 0 to 1, making it easier to compare and analyze.
Example 1 - Security Activity Anomalies per 100m²
If you are comparing the number of security activity anomalies, such as Alarms activated, at different sites or facilities of various sizes, you can normalize these values per 100m² to make the comparison fair and meaningful.
Why Normalize per 100m²?
Comparability: It standardizes the values, making it easier to compare data from areas of different sizes.
Clarity: It provides a clear and understandable metric for interpreting the data.
Consistency: Ensures that measurements are consistent across different regions or scenarios.
Calculation
To normalize a value per 100m², you would use the following formula:
Normalized Value = (Original Value / Area in m²) × 100
Example Calculation
If you have 50 alarms activated over an area of 200m², the normalized value per 100m² would be:
Normalized Alarms = (50 alarms / 200 m²) × 100 = 25 alarms per 100m²
This normalized value allows for direct comparison with other sites or facilities, regardless of their size.
Example 2 - Shrink Security Status per 100m²
If you are comparing the shrink security status, such as the amount of money lost due to Shrink (theft, fraud, etc.), at different sites or facilities of various sizes, you can normalize these values per 100m² to make the comparison fair and meaningful.
Calculation
To normalize a value per 100m², you would use the following formula:
Normalized Value = (Original Value / Area in m²) × 100
Example Calculation
If you have $10,000 lost due to shrink over an area of 400m², the normalized value per 100m² would be:
Normalized Shrink Loss = ($10,000 / 400 m²) × 100 = $2,500 per 100m²