Lack of inclusiveness puts 40 percent of companies at a disadvantage in labor market

Companies are crucial in creating an inclusive society. The Social and Economic Council (SER) in 2019 pointed out the role that businesses play in creating more diversity within companies and in reducing inequality in society. Yet we know very little about inclusiveness within businesses. (Business) cultures and labor markets differ between countries and hence also (large) differences exist with regard to the inclusiveness of firms within these countries. But every country has firms that behave less inclusive in comparison to their competitors. This Dutch case study provides these less inclusive firms interesting insights on the consequences of their choices. Not only do we describe to what extent Dutch companies make inclusive choices when recruiting, we also show the effects of inclusiveness on business performance. We also share some insights on how to increase inclusiveness within businesses

To measure the level of inclusiveness among companies, we conducted a survey of 1,500 Dutch companies. Respondents may be inclined to give socially desirable answers in this type of survey. To overcome this problem, we used a method known as the Bayesian truth serum (Prelec, 2004; see appendix for an explanation). The idea behind this method is that individuals' actual views are usually related to their expectations about others' views. We therefore presented respondents with two questions.

We asked respondents whether they would choose a majority candidate for vacancies and we asked for their estimate of the percentage of companies that would choose the majority candidate for vacancies (see box 1 for survey questions). By analyzing the correlation between responses to these questions and the extent to which respondents deviated from this correlation in their answers, we recognized whether respondents may or may not be likely to give socially desirable answers. This allowed us to distinguish between socially desirable answers and actual opinions. This gave us a clean view of the extent to which companies are actually inclusive when selecting job candidates.[1]

[1] All results and charts in this article are based on the data from the companies that did not provide socially desirable answers.

Of the respondents, 35 percent unequivocally state that they would choose a majority candidate for vacancies. Moreover, 5 percent of the respondents are prone to giving socially desirable answers. They say they do not choose the majority candidate for vacancies, but deviate from their expectations about other companies' choices in their answer to such an extent that it is suspected that in practice they do choose a majority candidate. Combined, these percentages indicate that 40 percent of companies in the Netherlands are not inclusive: this group chooses majority candidates to fill vacancies.

It is striking that much of the Dutch business community does not operate in an inclusive manner. Especially since companies that do so also generally show better outcomes; in the labor market, in their revenue growth and in the extent to which they experience uncertainty about their revenue expectations.

Less labor market tightness

To assess the extent to which inclusive companies experience more or less labor market tightness, we asked survey respondents two questions that they could answer on a scale of 1 to 7. First, we asked to what extent their own company experiences labor market tightness. In addition, we asked to what extent other companies in their own sector experience that tightness. By subtracting the answers to these questions from each other, we gained insight into the companies that experience more, less or the same amount of labor market tightness compared to other companies in the sector.

Among firms that typically choose a majority candidate, 19 percent experience more labor market tightness than competitors in the same sector, while among firms that do not, the percentage is only 9 percent (see Figure 1). In contrast, 36 percent of firms that do not typically choose a majority candidate in advance, experience less labor market tightness than competitors in the sector, while this percentage for less inclusive firms is 31 percent. Companies that make inclusive choices can fish from a broader pool of candidates in the labor market and therefore also experience less labor market tightness.

The positive association between majority candidate preference and perceived labor market tightness persists even when we control for differences across sectors, firm size and specific respondent and firm characteristics (see Appendix). There are significant inclusion differences across sectors. For example, executives in sectors such as construction, and information and communications are more inclusive than their counterparts in energy, water supply and manufacturing.

Smaller chance of sales decline

Not only do inclusive firms experience less labor market tightness than non-inclusive firms, their turnover is also less likely to have declined over the past three years. At 32.2 percent, the percentage of firms that experienced a drop in sales in the past year is significantly higher among non-inclusive firms than among inclusive firms. There, the percentage is only 23.6 percent (see Figure 2). Moreover, the percentage of companies that actually saw an increase in sales is larger among inclusive companies than among non-inclusive companies: 48.5 percent versus 38.6 percent. It is possible that inclusive firms can also claim a more diverse and therefore larger buyer market from their employee base than non-inclusive firms and, as a result, their sales grow more than those of non-inclusive firms. Another possible explanation is that non-inclusive companies cannot adequately serve their buyers due to a shortage of personnel and therefore see their sales stagnate.

Less uncertainty about future revenue trends

Finally, we see that in recent years, inclusive firms not only had a lower probability of revenue decline, but also experienced less uncertainty about their future revenue (see Figure 3). While about 37 percent of non-inclusive firms experience a lot of uncertainty, at 28 percent this percentage is significantly lower among inclusive firms. Also, the percentage of firms experiencing little uncertainty is significantly higher among inclusive firms (27 percent) than among non-inclusive firms (21 percent). It is possible that more inclusive companies can draw from more diverse sources of information and thus make a more informed estimate of future revenue trends. But directors of non-inclusive companies may also be more risk-averse, which may manifest itself not only in hiring policies but also in perceived uncertainty about revenue.

It may seem logical to require companies to work on their diversity policies now, but that is too easy. In fact, we see that companies that say they strive to have an employee base that reflects society and those that say diversity is an integral part of their strategy do not actually operate more inclusively in the labor market. On the contrary, the extent to which companies embrace such diversity policies makes no difference to the inclusive choices they make in the labor market (see Figure 4). This has also been described in the literature by Dobbin and Kalev (2016). They analyze which diversity policies have a positive effect on a company's diversity and which do not. The policies that are often unsuccessful have in common that they are mandatory and therefore antagonize decision makers or managers (Dobbin and Kalev, 2016). In our study, while larger companies appear to be more committed to diversity policies than smaller companies, they are ultimately less likely to make inclusive choices when job openings occur (see Box 2). This result could be interpreted in line with Dobbin and Kalev (2016): mandatory diversity policies within large companies are counterproductive, creating less inclusive behavior and not more.

See footnote here [2].

[2] This relationship is significant even when we control for industry effects, person and firm characteristics (see Appendix).

So just having a diversity policy does not work; it does not yet lead to different behavior when companies actually have to make choices when hiring new employees. Nevertheless, there are definitely starting points for companies to work with inclusion.[3] First, consider initiatives that increase contact between different groups[4], such as mentoring programs. These have a positive impact on the promotion opportunities of mentees, but just as important is the positive effect they have on the commitment and conviction of the mentor. Involvement from the top of the company is also crucial (SER, 2019). In that respect, the inclusion figures of this survey are unfortunately not very encouraging: of the respondents surveyed, the vast majority, are in an executive or board position at the company they represent.[5] It is especially worrisome that 38 percent of this group indicate that when vacancies arise, they prefer a majority candidate. Without the commitment and conviction of these directors, it is very difficult to make progress on diversity and inclusion.

[3] Dobbin and Kalev (2016) cite several measures that show positive results in this context, including working in horizontal, diverse teams and manager recruitment activities for specific minority groups (e.g., in schools). Diversity taskforces and diversity managers play an important role within companies in holding them accountable for malpractise regarding hiring and promotion standards.

[4] Pettigrew and Tropp (2000) show in a meta-study that contact between majority and minority groups can reduce prejudice by 94 percent.

[5] About 38 percent of respondents are owners, 26 percent are directors or executives and 29 percent of the respondents are in a managing position.

The pace of business diversity and inclusion in the Netherlands is low, the SER concluded back in 2019. The government therefore introduced a growth quota for women, and urged companies to set targets and communicate the results. Quotas are a proven tool also used by Norway and Italy, for example, for women at the top of the corporate sector. Despite the fact that quotas for minority groups often do not fare well in public opinion, research shows that they do not detract from the qualifications of individuals in quota positions.[6] On the contrary, quotas often have the effect of altering the selection process for candidates for open director positions (Bijkerk et al., 2021) and that often candidates with even better qualifications are hired (Bertrand et al., 2019). The percentage of firms indicating a preference for majority candidates in hiring policies is high. This high percentage should encourage companies to look at where they can improve their selection procedures. Quotas and transparent targets could make procedures more inclusive.[7]

It is costly to be non-inclusive

By 2050, it is estimated that 30 to 40 percent of the Dutch population has a migrant background. And of the generation aged between 25 and 35 in 2018, 52 percent of women have a college or university degree. For men from the same generation, the figure is 42 percent. And, for now, labor market tightness is also increasing due to an aging population. For the UK and other countries these numbers are comparable: by 2041 about 26% of the population in the UK will be 65 years or older, climate change is expected to result in 1.2bn migrants worldwide by 2050 and 57% of young women in comparison to 44% of young men participated in 2020 in higher education in the UK. Systematically having a preference for certain groups of workers in a labor market is therefore very costly for companies. Lack of inclusiveness is also costly for society, as limited diversity and inclusion in business creates unused labor potential and inequality. Without additional measures, the costs of a non-inclusive labor market will only increase in the near future for society and for the firms themselves.

[6] See Bertrand et al., 2019

[7] Quotas provide role models for minority groups that should have a positive long-term effect on minority groups' ambition and investment in education (Coate and Loury, 1993). However, quotas can also create negative spillovers for minority group employees when quotas are too ambitious (Coate and Loury, 1993) or if they lead to compensatory behavior by executives (Zinovyeva and Bagues, 2011 and Bagues et al. 2014).

Abolmagd, M. (2016). Tell Me the Unverifiable Truth-Bayesian Truth Serum and Social Desirability Bias, MSc. Thesis Erasmus School of Economics, 1-77.

Bagues, M., Sylos-Labini, M., and Zinovyeva, N. (2014). Do gender quotas pass the test? Evidence from academic evaluations in Italy. Scuola Superiore Sant'Anna, LEM Working Paper Series, 14, 1-28.

Bertrand, M., Black, S. E., Jensen, S., and Lleras-Muney, A. (2019). Breaking the glass ceiling? The effect of board quotas on female labor market outcomes in Norway. The Review of Economic Studies, 86(1), 191-239.

Bijkerk, S. H., Dominguez-Martinez, S., Kamphorst, J., and Swank, O. H. (2021). Labor market quotas when promotions are signals. Journal of Labor Economics, 39(2), 437-460.

Coate, S., and Loury, G. (1993). Antidiscrimination enforcement and the problem of patronization. The American Economic Review, 83(2), 92-98.

Dobbin, F., and Kalev, A. (2016). Why diversity programs fail. Harvard Business Review, 94(7), 52-60.

Pettigrew, T. F., and Tropp, L. R. (2013). Does intergroup contact reduce prejudice? Recent meta-analytic findings. In Reducing prejudice and discrimination. Psychology Press, 103-124.

Prelec, D. (2004). A Bayesian truth serum for subjective data. Science, 306(5695), 462-466.

Socio-Economic Council (2019). Diversity at the top, time for acceleration, 1-237.

Zinovyeva, N., and Bagues, M. (2010). Does gender matter for academic promotion? Evidence from a randomized natural experiment, SSRN working paper, 1-53.

A. Bayesian truth serum (Prelec, 2004)

Prelec (2004) developed the Bayesian truth serum to recognize (consciously or unconsciously) socially desirable answers from respondents in surveys. The survey then asks the respondent not only about their own opinion on, say, a preference for a majority group, but also about an estimate of others' opinions on the subject. There is often a positive correlation between a respondent's own opinion and his or her prediction of others' opinions (see also Figure 6). This positive correlation has two causes. First, there is the false consensus effect, in which respondents overestimate the relative prevalence of their own opinions. In addition, there is the selective exposure effect, in which other individuals with the same opinion are more salient. See also Abolmagd (2016) for further specifications. Figure 6 shows that in our survey, firms that indicate a preference for a majority candidate (the blue distribution) also have a higher estimate of firms in the industry that have the same preference compared to those without that preference (the orange distribution): the blue distribution is located more to the right than the orange distribution.

Prelec’s (2004) method assigns a positive information score to the answer most common in the survey (which therefore includes socially desirable answers). It then evaluates each respondent's prediction as to whether it differs from the predictions of respondents with the same opinion. This prediction score, together with the information score, provides an indication of whether the respondent's opinion is a socially desirable answer.

B. Regression analyses preference and firm characteristics

Figure 7 contains the regression table (ordinary least squares) for firms' diversity strategy and majority candidate preference. The regressions all check for possible sector effects on preference (sector fixed effects). In addition, they check for the respondent’s personal characteristics (gender, age and whether they are a director or not) and certain company characteristics (percentage of foreign sales, innovation sales and investment and age of the company).

Large firms are significantly more likely to have a diversity strategy. Firms with a preference for a majority candidate experience significantly more labor market tightness, higher uncertainty regarding revenue over the next 12 months, and lower revenue growth over the past three years.