Gender Disparities in the Workplace Begin With Unequal Levels of Inclusion
International Women’s Day is a great opportunity to celebrate and support all the amazing women in our personal and professional lives. But in spite of continued efforts, gender disparities are still rampant in many sectors of our economy, and across society as a whole: women are still underrepresented in the workplace, especially in leadership roles, and they often are the first to be impacted by societal problems, as evidenced by the disproportionate impact that the COVID-19 pandemic has wreaked on women.
In our research on workplace inclusion we have found a strong correlation between inclusion, satisfaction, and representation: both at the aggregate level, and for virtually every company with which we have worked, women and other underrepresented groups are much more likely to report experiences of workplace exclusion than those who are members of the “normative majority,” which in most corporate contexts means white, cisgender, heterosexual men with no disabilities.
On the occasion of this year’s International Women’s Day, we wanted to dig into the data we have collected from several US-based and global companies, to see what patterns our analysis may reveal about the disparities in how women and men experience exclusion in the workplace. To this end, my colleague Chibin Zhang compiled and analyzed data from 1,635 corporate employees (999 women and 636 men) representing 10 companies with locations across 37 countries.
The data was collected as part of our Inclusion Assessment, during which individual employees from participating organizations use our online platform to describe specific Experiences of Exclusion, and indicating (1) in which of nine Categories of Inclusion the exclusion belongs and (2) what was the Source of the exclusion. Because we also collect (anonymous) identity data from each participant, we are able to compare the experiences of different groups based on a variety of demographic and other personal characteristics.
We use the data collected to calculate three metrics:
The Prevalence Score indicates what proportion of the individuals within a group shared at least one Experience of Exclusion “card.” The Prevalence Score thus measures how widespread exclusion is within the group.
The Severity Score reflects the average number of Experience of Exclusion cards submitted by those individuals in the group who submitted at least one card. The Severity Score thus gives a sense of how acutely exclusion impacts those who are experiencing exclusion.
The Exclusion Score combines Prevalence and Severity to create a single numerical score that captures both dimensions of the problem.
Each of these metrics is designed to work at any level of analysis, starting from the overall exclusion score for an entire population, all the way down to, let’s say, comparing the metric for the Compensation & Benefits category between Black women and white men within a specific division of a company (assuming there is enough data to do so).
Using the global data set mentioned above, we wanted to explore the differences between the experience of women and men at multiple levels of analysis. We started by calculating the overall Exclusion Score for everyone in our sample, which comes to a value of 2.01 based on the fact that, across the entire pool of 1,635 employees, we collected 3,300 cards describing experiences of exclusion (3,300 cards by 1,635 people = 2.01 cards per person).
Next we wanted to see, at the most aggregate level, what differences may exist between men and women. When we calculated the exclusion scores separately for the 636 men and the 999 women in our sample, as shown in Figure 1, we found that the aggregate exclusion score for men is only 1.46, while for women it is 2.37.
In other words, our data shows that, in the aggregate, women are 1.6 times more likely than men to experience exclusion in the workplace.
Next, we wanted to see whether and how these gender disparities manifest themselves across individual Categories of Inclusion. First, we calculated the Exclusion Score for three common categories: Compensation & Benefits, which is linked to issues of pay gaps; Career Opportunities, which is linked with issues of representation; and Respect, which is linked to everyday workplace experiences that can make people excluded by not being respected through the words and actions of their colleagues.
When across the entire population, we found that Respect has by far the largest Exclusion Score (0.70), followed by Career Opportunities (0.42) and Compensation & Benefits (0.29). This is a fairly universal finding across virtually every organization we have worked with, and it reflects our observation that although being excluded with respect to compensation and promotion clearly has a significant impact, the day-to-day experiences that result from interacting with colleagues are most likely to lead to stronger feelings of exclusion and lower satisfaction.
Our next question was whether and how much of a disparity exists, for each of these categories, between men and women. To explore this, we did a more nuanced analysis by calculating all three scores (Prevalence, Severity and Exclusion) separately for men and for women across these three categories. The results are shown in Figure 2.
Each circle in Figure 2 corresponds to one Category of Inclusion either for men or for women. The size of each circle is proportional to the Exclusion Score. The horizontal (X axis) position of each circle reflects the Prevalence, while the vertical (Y axis) position reflects the Severity. Hence any circle that appears toward the right has higher Prevalence (meaning that a greater proportion of the group has shared at least one experience in that category), while any circle toward the top has higher Severity (meaning that those who experience that category, do so more acutely). Lastly, to facilitate the gender comparison, the circles for the men and women in each category have the same color and are connected by a gray band.
The fact that each pair of circles shows a pattern going from lower left (for men) to upper right (for women) means that, in each of these categories, a larger proportion of the women in a company are likely to experience exclusion, and that when they do experience it, it is more severe.
The pair of circles toward the lower left of the figure show that issues of Compensation & Benefits impact a much larger proportion of women (29% of all women) than men (19% of all men), and that women’s exclusion in this category (1.33) is significantly more severe than it is for men (1.12). In fact, the overall exclusion score for women, at 0.38, is 1.8 times larger than the exclusion score for men of 0.21.
The pair of circles near the center of the figure show that the overall Prevalence and Severity for the Career Opportunity category are both higher for women than for men, and overall higher than the scores for Compensation & Benefits. In this case, the exclusion score for women (0.54) is 1.4 times larger than it is for men (0.38).
Last but certainly not least, the pair of circles toward the upper right show that, indeed, the Respect category is linked to much greater exclusion than the other categories, but it also shows that this category shows the greater gender disparity: nearly 46% of all women reported at least one experience in this category, with a Severity Score of 1.98 and an overall Exclusion Score of 0.90. In contrast, only 32% of all men report a Severity Score of 1.43 and an overall Exclusion Score of 0.45 — exactly half of the Exclusion Score for women.
These findings align with the disparities that have long been observed at the macroscopic level: relative to men, women in the workplace tend to have lower representation and tend to be under-compensated. However, our results are much more telling than the typical macroscopic statistics about gender disparities for two reasons.
First, our results can pinpoint the root causes of the observed disparities; for instance, the scores in the Compensation & Benefits reflect how often women find themselves in specific situations in which they realize that their compensation is inadequate. When we couple these findings with the detailed descriptions that participants provide, we can get a very clear understanding of what specific processes or people within each organization are creating these experiences.
Second, because we measure exclusion across several categories representing a wide range of workplace experiences, our results can help to identify all of the factors that lead women to feel more excluded. And because feelings of inclusion are tightly linked to overall job satisfaction, and because job satisfaction is clearly linked to performance and to retention rates, our analysis can shine a bright light on the specific trouble areas that are having a negative impact on the experiences of women and other underrepresented groups, and on the overall performance and diversity of entire organizations.
We hope our findings will guide an increasing number of organizations to become more inclusive, and that, as a result, we will see significant progress across all aspects of the participation of women and other underrepresented groups in the workplace.
