
Do you also want to increase the diversity of your workforce and attract the best talent? Read here what diversity-appropriate personnel selection can look like packaged in psychometric mini-games!
More and more companies are setting themselves the goal of increasing the diversity of their workforce, particularly at senior management levels. The consistent focus of all recruiting measures on increasing diversity is thus becoming one of the most important strategic approaches in small, large and medium-sized companies. There are many reasons why diversity is so important. Diversity therefore plays an important role not only from a social perspective but also from an economic perspective.
Increasing diversity — What's the point?
Increased diversity = One of the most important weapons in the War for Talents.
Probably the most important argument for taking diverse target groups more into account when making hiring decisions is the shortage of skilled workers. Because with the shift away from an employer market (number of vacancies, < Zahl geeignete Bewerber:innen) zu einem Arbeitnehmermarkt (Zahl offene Stellen > number of suitable applicants), companies continue to struggle with the challenge of finding qualified specialists.
In this competition for the best young talent, so-called High Potentials, it therefore simply makes no sense from an economic perspective to overlook talents with diverse backgrounds or not to address them directly and consistently. For example, talented women in today's working world are often just as well or even better trained than their male fellow students (Hobler et al. 2020). By not actively addressing female talent in terms of their individual needs, companies risk losing the best talent for open positions.
Increased diversity = increased profitability
Companies with a workforce that is characterized by diverse personal (e.g. gender, sexual orientation, culture) and professional backgrounds (e.g. degrees, professional experience) are more innovative, successful and profitable. Studies impressively show how strong the connection between diversity and profitability is: Companies with a high degree of diversity are, for example, with a probability of up to 36% above average profitable (McKinsey, 2015). One important reason: diverse, heterogeneous teams work more productively, creatively and efficiently as purely homogeneous teams (Homann & Greer, 2013).
Increased diversity = increased employer attractiveness
However, the positive effects of higher diversity not only radiate internally (e.g. company figures, team effectiveness), but also externally (e.g. Employer brand). Companies that focus on diversity are not only more profitable, but are also perceived more attractively by potential applicants (Daugherty & Chowdhury, 2019). For example, for the large number of employees, it is even It is more important to work in a diverse environment than to receive a higher salary (Stepstone, 2020). Other benefits of higher diversity include a higher retention (employee retention) and lower fluctuation (job change) (Chamberlain, 2016).
Increasing diversity — but how?
A fair and non-discriminatory Staff selection is the most important lever for greater diversity in the company. Because this is how recruiting lays the foundation for more diversity in teams and thus sustainable corporate success through the selection of talent. But what levers must companies use to make their personnel selection non-discriminatory and fair and thus attract talent from different backgrounds?
Screw 1: Standardization of the recruiting process
The most common reason for (often unintentional) discrimination against applicants with diverse backgrounds is a lack of standardization of the selection process. Because without realizing it, HR managers are often influenced by irrelevant aspects in less standardized selection processes (this is also referred to as Unconscious Biases), which lead to incorrect personnel decisions.
Unconscious bias: “unconscious cognitive distortions and other faulty tendencies in perception, memory, and judgment” (Wondrak, 2014)
Two examples of unconscious biases in a job interview:
- Applicants with dialect or foreign accents are seen as less competent (Rakić, Steffens, & Mummendey, 2011)
- Technical requirements (e.g. programming skills, Excel skills)
In order to ensure validity and fairness in recruiting, it is therefore necessary to standardize the personnel selection process and design it according to scientific findings. As a result, the highest possible standardization and scientific basis for each individual should Staff selection criterion are respected, which are used to make the hiring decision. In particular, this includes the standardization of job interviews, the use of scientific aptitude diagnostic test methods and an empirical, data-driven Requirements analysis). For example, job interviews are valid (i.e. they reliably predict career success) in particular if they are based on a well-founded analysis of requirements, follow structured guidelines and decisions are made by consensus through trained interviews (>2 interviews, see also our guidelines for designing job interviews)
Adjusting screw 2: Neutral, inclusive language
It starts with the job title and ends with the description of the tasks: language and images in job advertisements should appeal equally to applicants from various backgrounds.
In practice, however, this is rarely the case. For example, the language in job advertisements is traditionally geared primarily to the needs of white, male applicants, and the images used rarely show the faces of women or people with different ethnic backgrounds.
The episode: An important potential to appeal to individuals with diverse backgrounds and experiences is being squandered. For example, research shows that women are less likely to apply for a job if it lists a variety of requirements (Mohr 2014) or uses stereotypically masculine adjectives (e.g. assertive, combative). Companies should therefore continuously update their job advertisements and corporate communications to possible Hiring Biases and check inclusivity. An important step here is, for example, to review the requirements for their actual connection with professional success and to remove criteria for which no verifiable connection can be found. Further potential lies in the continuous review of the impact of adjectives and descriptions in different target groups and the selection of images that represent an inclusive corporate culture (see also our guidelines for designing job advertisements).
Adjusting screw 3: Diversity-appropriate aptitude diagnostics
One of the most important secrets of success for greater diversity in companies is the use of scientifically based Aptitude diagnostics in the personnel selection process. This is because the strong orientation of aptitude diagnostic methods to the quality criteria of classical test theory generally ensures a high level of objectivity, reliability and validity of the selection process.
Another important quality criterion in scientific aptitude diagnostics is Test fairness. Test fairness describes that no group is systematically disadvantaged in a testing process (e.g. based on gender or ethnic background). But care must be taken. This is because although the use of aptitude diagnostic methods and the standardization of selection tools contribute significantly to a higher level of fairness, this is not always the case. For example, questions and test content (often unintentionally) are aimed at Western cultures (Camilli, 2006) and a lack of standardization of test results in various, current samples leads to distortions in test evaluation.
There is therefore great potential in the use of largely language-free test methods, for example in the form of psychometric mini-games. After all, gender, ethnic origin and skin color play no role in the test results of the largely language-free but psychologically and metrologically based mini-games. Assist in analyzing test results intelligent algorithms, which are constantly evolving and incorporate the results of large-scale, diverse samples.
Screw 4: Unconcious Bias Trainings and Workshops
Greater diversity always means continuous learning and reflection on one's own prejudices. Because even though HR managers and employees can rely on current research results, aptitude diagnostics and intelligent algorithms for job advertisements and the selection of talent, we are never protected from unconscious prejudices that can distort evaluations.
An important lever for diversity-appropriate personnel selection is therefore continuous training and training, which constant reflection and active change of one's own behavior and thought patterns stimulate. In order to anchor diversity not only in personnel selection but also in corporate culture, such training is central not only for recruiting employees, but also across divisions. Because only when all employees become aware of their own biases can a culture be established in which everyone understands that everyone ultimately benefits from more diversity.
A first step is to become aware of these hiring biases. You can then be supported by intelligent algorithms!
Sources
- Chamberlain, R.P. (2016), “Five steps toward recognizing and mitigating bias in the interview and hiring process,” Strategic HR Review, Vol. 15 No. 5, pp. 199-203. https://doi.org/10.1108/SHR-07-2016-0064 .
- Daugherty, P.R., Wilson, H.J., & Chowdhury, R. (2019). Using artificial intelligence to promote diversity. MIT Sloan Management Review, 60(2), 1. Retrieved from https://search.proquest.com/docview/2161594133?accountid=14570
- Homan, A.C., & Greer, L.L. (2013). Considering diversity: The positive effects of considerate leadership in diverse teams. Group Processes & Intergroup Relations, 16 (1), 105—125. https://doi.org/10.1177/1368430212437798
- Heilman, M.E., Okimoto, T.G. (2007). Why are women penalized for success at male-typed tasks? The implied communality deficit. Journal of Applied Psychology, 92, 81—92. doi:10.1037/0021-9010.92.1.81
- Hobler, D., Lott, Y., Pfahl, S. & Buschoff K.S. (2020). Status of equality between women and men in Germany WSI Report. Institute of Economics and Social Sciences (WSI). dusseldorf
- Huffcutt, A.I., & Roth, P.L. (1998). Racial Group Differences in Employment Interview Evaluations. Journal of Applied Psychology, 83 (2), 179—189.
- McKinsey (2015). “Diversity Wins: How Inclusion Matters.” https://www.mckinsey.com/featured-insights/diversity-and-inclusion/diversity-wins-how-inclusion-matters
- Mohr T.S. (2014). Why Women Don't Apply for Jobs Unless They're 100% Qualified. Harvard Business Review. https://hbr.org/2014/08/why-women-dont-apply-for-jobs-unless-theyre-100-qualified
- Kersting M., & Ott, M. (2016) Diversity-appropriate personnel selection. In: Genkova P., Ringeisen T. (eds) Diversity Competence Handbook. Springer Reference Psychology. Springer, Wiesbaden. https://doi.org/10.1007/978-3-658-08594-0_8
- Posthuma, R.A., & Campion, M.A. (2009). Age stereotypes in the workplace: Common stereotypes, moderators, and future research directions. Journal of Management, 35, 158—188.
- Savage, D., & Bales, R.A., Video Games in Job Interviews: Using Algorithms to Minimize Discrimination and Unconscious Bias (December 19, 2016). ABA Journal of Labor & Employment Law, Vol. 32 (2017). https://ssrn.com/abstract=2887757.
- Tolstoy-Miller, G. (2017). Unconscious Bias: Stereotypical Hiring Practices. TEDxLincolnSquare. https://www.youtube.com/watch?v=QCFb4BiDDcE.
- Vollmer, L. (2015). Unconscious discrimination — socio-psychological effects and possible solutions. In M. Klemisch, A. Spitzley, & J. Wilke (eds.), Gender and Diversity Management in Research (pp. 52-59). Stuttgart: Fraunhofer Verl. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-430199
- Voss, E. (2014). Diversity Charter. Recognize diversity — identify strategies for dealing sensitively with unconscious prejudices. https://www.charta-der-vielfalt.de/fileadmin/user_upload/Studien_Publikationen_Charta/Vielfalt_erkennen_BF.pdf#page=35.
- Wondrak, M. (2014): The power of pigeonholed thinking — unconscious bias. In: the standard. Issue 7/8/9 June 2014, p.K12. DerStandard publishing company: Vienna.
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