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Employee Selection and Workforce Diversity: Are Current Tools Up To The Task?

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Guest Author:  Stephen B. Jeong, Ph.D.

Hispanics, African Americans, Asians and Native Americans now constitute more than one-third of the U.S. population. By 2042, they are projected to make up nearly one-half of all Americans.  Given these rapidly changing demographics—and consequently, the rapidly changing U.S. marketplace—many organizations are recognizing that workplace diversity is a business necessity. Creating and promoting a diverse workforce is particularly essential for industries where a significant number of employees deal face-to-face with prospective customers, because the latter are more likely to buy from people like themselves. So retail, financial, legal, insurance, hospitality and consumer goods businesses may want and need staff diversity. Yet existing selection tools may not be up to the task. Here’s why:

1. Job tests based on outdated material

In the context of legal defensibility and employee selection tools, the concept of “validation” simply refers to accumulated “evidence” showing that a given selection is, indeed, a good (or valid) predictor of job performance.  Selection specialists (or those who design selection tests) typically gather validation evidence by correlating job applicants’ scores on a given selection test (e.g., on intelligence, job knowledge, values, personality) with their future job performance (predictive validation) or using incumbents (concurrent validation).  If the resulting correlation is relatively high, the test is considered to be a valid predictor of job performance.  Employment tests and other employee selection tools are judged on their “validation” strength, or the degree to which they can accurately predict future job performance. If there is a high correlation between an applicant’s score on a given selection test (e.g., testing intelligence, job knowledge, values or personality) and his/her future performance, the test is considered to be a good predictor.

One critical issue with the above approach is that the majority of the tests used in the U.S. today were validated primarily on a Caucasian pool. This means that while a given test may work well in predicting job performance for Caucasian job applicants, it may be biased, at a minimum, and in the worst case, invalid, when used with non-Caucasian applicants.  There are proven differences between Caucasians and non-Caucasians in terms of values, management and leadership styles, and general work-related preferences, and selection tests that fail to recognize them may be unhelpful for predicting job performance, retention, and engagement of non-Caucasians.

2. Differences between Western and non-Western cultures

Intercultural academics have been able to label what many of us have already known; that there are cultural variations that can differentially impact one’s thoughts, emotions, and behaviors in the workplace.  In addition to the more commonly known “individualistic” and “collectivistic” cultural differences, employees in Western countries (e.g., U.S., Europe, Australia, New Zealand) generally prefer a more equal power distribution in the workplace, while employees from Asian countries (e.g., South Korea, Japan, China, Taiwan) tend to be more accustomed to autocratic or paternalistic power relationships – or top-down authority.  They also differ in assertiveness, preferred levels of uncertainty and short-term vs. long-term orientations, all of which may impact one’s job performance, satisfaction, and promotion opportunities. For example, while assertiveness is generally a desired trait in Western societies, it is much less so and even frowned upon in countries such as Japan, Korea, and Taiwan. If a selection test assumes assertiveness as a desirable trait, a Taiwan-born applicant, who may have been a top salesman in his country, may be knocked out of the selection process here.

3. Difference Among Non-Caucasians And Acculturation

In addition to the Western vs. non-Western distinction, selection tools should further take into account differences among non-Western cultures – e.g., Hispanics, African-Americans, Asian-Americans and Native Americans, differences between foreign- and US-born, and differences among nationalities within a racial or ethnic group – which include customs, values, work ethics, body language, and communication styles. Ethiopians are very different from South Africans; Costa Ricans from Bolivians; Japanese from Koreans. The point here is that these sub-groups vary greatly with respect to normative values that guide their behavior in the workplace.

People also vary with respect to their degree of acculturation and assimilation to the mainstream. Naturally, attitudes and values of those individuals who have resided in the U.S. for longer periods of time are likely to be more similar to the general American population. However, more recent immigrants are less likely to be so. Hence, if an organization’s business and diversity strategy dictates the inclusion of more recent immigrants, it is critical to understand that current selection tools used in the U.S. would be least applicable to recent immigrants from non-Western countries.

It is important to make one thing clear:  I’m not suggesting that all selection tests must identify and include all unique cultural attributes in order to be useful – that would be impractical. Rather, one should simply consider the fact that the majority of the selection tests in use today are likely to hold less value when used on non-Western and non-Caucasian applicants.

So, what’s the answer?  There is no one simple solution. It depends on an organization’s industry, strategy, mission and priorities as well as its customer demographics.  If the goal is to sell to new immigrants, one should select applicants whose views closely mirror that of one’s prospective customers. If the future American market place—in which the current minorities add up to almost a majority—is at all a consideration, our current employment selection tools need to be revised to reflect both the common as well as those unique cultural attributes that can play out in the work setting.  For current and future generations of immigrant workers—whose primary identification is with a non-Western culture—a new measurement approach should lead to a more meaningful (and valid) performance prediction—one that addresses those attributes valued by their culture.

Stephen B. Jeong, is currently the Managing Director of Waypoint People Solutions –, a human capital consulting firm that focuses on high precision employee diagnostic surveys using cutting-edge measurement technology and methodologies. He holds Ph.D. in Industrial-Organizational psychology from the Ohio State University and has been advising private, public, and government organizations since 2000.  He can be reached at

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6 responses to “Employee Selection and Workforce Diversity: Are Current Tools Up To The Task?”

  1. Alana Fares Avatar

    Dr. Jeong has raised several excellent points on the use of selection tools and the impacts on Diversity. We support his view that careful examination of the data behind any assessment is critical to determine the potential impacts it can have on workforce diversity. We also strongly believe that there are assessments available today that are certainly up to the task.

    For example, SHL has published findings on the differences (or similarities) between countries and groups for many SHL assessments. SHL has a global norm available for the Occupational Personality Questionnaire (the OPQ32) that consists of 337,646 individuals from 19 different countries and a wide variety of roles. Countries in the study include South Africa and China, for example. Careful and expert consideration was given to sample weightings, which may be employed in a variety of ways such as by Gross Domestic Product (GDP), total population, and working population or language.

    Our research also supports that in some instances, it may be better to use an international/national norm than an unrepresentative or too narrow national norm. Small numbers within local population norm groups can be subject to some sampling biases in terms of demographics in the population sampled. The diversity of the samples contained within norms should be carefully considered when determining if a local or a larger scope (e.g. international) norm is appropriate.

    Dr. Jeong also highlights that it is important to understand what factors are being measured by an assessment. For example, different populations may show differences in terms of values, leadership styles, personality, etc. Well researched work-related assessments such as the SHL OPQ32 measure against a framework that can be consistently (measurably) tied to behaviors that impact performance in the workplace. Since the OPQ32 does not attempt to measure factors outside this defined framework, the influences of values, motivators, or other group or culture-sensitive factors can be substantially removed from the measure. This reduces the risks of “unintended consequences” when using the assessment for selection.

    Finally, when choosing an assessment vendor, it is critical that buyers examine carefully the published data available on group differences and demographics for the assessment. SHL publishes data of known differences that exist between groups, allowing for informed decisions to be made about the appropriateness of the OPQ32 in specific contexts or with specific groups.

  2. Patti Hammerbacher Avatar
    Patti Hammerbacher

    I hired people for data-entry positions. I was able to devise a data-entry test for each applicant. The data must be accurate regardless of your background. After a while, I made the applicants write a few sentences about their last position. This was just to make sure they could construct a complete sentence. But I wish I had gone further with my criteria even if it eliminated some groups of people. I wish I had also relied on whether or not people had hobbies or had done any sort of independent research on a topic that they found interesting. I’m amazed at the number of people who don’t seek out info – no initiative – no inquiring minds. Maybe this would eliminate people from a very poor background, but I don’t think so. I’m not sure if I feel that the internet is a blessing for such people or if it makes it too easy.

  3. Stephen Avatar

    If I may make a suggestion, for your data entry position, in addition to work background (e.g., similar types of position and length), you may also think about employing measure or measures that tap their enjoyment or tolerance for highly detail-oriented and perhaps, somewhat mundane tasks (conscientiousness). These are important to the extent that not everyone has the propensity to endure through an 8-hour workday involving data entry.

    A low budget option to select conscientious individuals is to ask (on a scale of 1 to 5) whether they enjoy putting together 1000-piece (or more) gig-saw puzzles. People who enjoy these tend to exhibit higher than average levels of conscientiousness.

    Another question is to ask (again, on a scale of 1 to 5) whether they tend to read instructions when they buy new products. You would need to frame these questions in a way that does not make the too obvious, of course.

    Hope that helps!

  4. Karen U. Avatar
    Karen U.


    Great website! I think there are many valuable information and advices here. Along the same line, I came across the following website which I found interesting. Traditionally, personality tests such as MBTI have been used as career aptitude test. However, these tests have a very limited scope as they ignore many important factors such as person’s skills, values, and interests.

    There have been many advancements in the area of career aptitude testing. Usage of artificial intelligence to evaluate suitability of a job for a person is one of the these techniques. You can take a complete version of the MBTI personality test plus many others such as memory, IQ, problem solving, and patience tests in OptYourLife. This website’s expert system tries to find the most suitable career path for you using neural network. Moreover, salary of different careers will be considered in the final analysis to provide a more insightful advice for you:

    http://www.optyourlife [dot] com/


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