You may have employees with multiple Ethnicity/Race selections which could result in duplicate records for each ethnicity. Learn how One Model can help.
Your employees may identify with multiple ethnicities/races when providing biographical information.
Consider the example where you may have an employee who identifies as Asian and Black or African-American. While some companies may only offer a single option of "Two or More Races" for such employees, others allow multiple selections and enable employees to submit numerous options. In these situations, the effect of multiple selections may be the duplication of records appearing in the data. In the context of One Model, when we pull your workforce data, you may find duplicate records in the Employee table.
The example above where an employee selects both "Asian" and "Black or African-American" as their ethnicity/race, you may expect to find two records in the Employee table for this particular employee: 1) where their ethnicity/race is marked as "Asian," and 2) where their ethnicity/race is marked as "Black or African-American."
While it can be beneficial to capture each selection chosen by an employee, without intervention, duplicate records can lead to incorrect reporting of certain metrics, such as Headcount (EOP). And, if you're a company that needs support in this regard, One Model has a variety of options for working with your data to help you properly report your metrics:
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One Model can concatenate multiple ethnicities into a single value. Using the employee example from above, instead of having two records in the Employee table, you would now have a single record where their ethnicity/race is marked as "Asian / Black or African-American." This could be valuable as concatenated values would then show as a node in your Ethnicity/Race dimension, allowing you to precisely identify and filter them in combination with other nodes.
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One Model can pull the ethnicity/race field out of the Employee table and place it into a model table (a table that isn't designed for metric creation), which would ensure that there wouldn't be any duplicates in the Employee table or a metric like Headcount (EOP). One Model would join the model table to the Employee table, allowing you to view a metric like Headcount (EOP) by Ethnicity/Race. However, viewing by Ethnicity/Race would then cause duplicates to appear as employees would show under each selection they've made. Depending on how you'd like to analyze your data, this can still be valuable.
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One Model can apply logic to ensure that any employee with multiple selections is collated into a single record in the Employee table with their ethnicity/race marked as "Two or More Races."
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One Model can do a combination, such as applying both options #3 and #4, where we still pull the true ethnicity/race selections into a model table but then collate the multiple selections into a "Two or More Races" value under a new, different column in the Employee table. In this example, One Model would work with you to ensure the Ethnicity/Race dimension is working how you'd expect, considering there'd be two different ethnicity fields on the site.
To begin working through an option that best fits your needs, or if you have any questions, please contact your Customer Success Lead.
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